Kim

IMPERIAL COLLEGE LONDON

Department of Earth Science and Engineering

Centre for Petroleum Studies

Shallow Seismic Analysis

in Pagosa Springs, Colorado, USA

by Junghee Kim

A report submitted in partial fulfilment of the requirements for the MSc

September 2012

DECLARATION OF OWN WORK I declare that this thesis is entirely my own work and that where any material could be construed as the work of others, this has been fully cited and referenced, and/or with appropriate acknowledgement given. Signature

Name of student Junghee Kim

Name of supervisor Dr. Adam Booth

Word Count 14744 words

Junghee Kim 1

ABSTRACT

In the Pagosa Springs, Colorado USA, students of Imperial College London and Colorado School of Mines Geophysics Camp 2012 have performed geophysical analyses. Seismic data, comprising P-wave and S-wave data acquired along two lines (North Line and Zen Garden), were interpreted to analyse near surface geology for geotechnical and groundwater purposes.

Refraction analyses were performed using gradient-intercept, reciprocal, time term inversion and tomographic inversion methods to calculate the velocity and thickness of each subsurface layer. The presence of significant refractor overlaps favoured reciprocal and time term inversion methods as it allowed enough room for delay time window analysis to be performed.

Results of each of these methods show a strong correlation in velocity and thickness values. Output of the time term inversion was fed into the tomographic inversion as a starting model. Convergence to a local minimum was reached after about 10 iterations, with an RMS error of less than 10% in most cases.

Analyses of the results in the North Line and Zen Garden area show a slightly undulating three layer near surface geology with a dip. Unconsolidated sediments with depth of about 2 m and properties that are consistent with shale were interpreted. The layer occupying a depth between 2 m to around 15 m was interpreted to be water saturated sandstone. The depth over 15 m seems like sandstone. However because the depth over 15 m is not reachable with ray tracing path, it is not possible to sample beyond ~15 m with the hammer seismic data.

By using the velocities acquired from tomographic inversion, datum static correction (including refraction static correction) has been performed to the reflection data, after stack and show improvement in terms of continuity of reflectivity. However, it suffers from insensitivity due to its very shallow features.

Junghee Kim 2

Table of Contents ABSTRACT ............................................................................................................................................ 1

ACKNOWLEDGEMENT ...................................................................................................................... 9

CHAPTER ONE ................................................................................................................................... 10

1.0 Introduction ............................................................................................................................... 10

1.1 Objectives ....................................................................................................................................... 11

CHAPTER TWO .................................................................................................................................. 12

2.0 Geological setting of Pagosa Springs, Colorado USA .............................................................. 12

CHAPTER THREE .............................................................................................................................. 15

3.0 Theory and Literature review .................................................................................................... 15

3.1 Refraction Seismic Method ....................................................................................................... 15

3.2 Time-Distance curves for layered media .................................................................................. 16

3.3 Hidden Layers, Velocity Inversions, and Blind Zones ............................................................. 20

3.4 Refraction Arrival picking and time adjustments ..................................................................... 22

3.5 Manual picking and automatic picking of traveltimes .............................................................. 22

3.6 Reciprocal Time Correlation ..................................................................................................... 23

3.7 Refraction Interpretation ........................................................................................................... 24

3.8 Gradient-Intercept method ........................................................................................................ 24

3.9 Delay-Time Concept ................................................................................................................. 24

3.10 Reciprocal Method ........................................................................................................................ 26

3.11 Term-time inversion .................................................................................................................. 31

3.12 Tomographic inversion method .................................................................................................... 35

CHAPTER FOUR ................................................................................................................................. 39

4.0 METHODOLOGY ................................................................................................................... 39

4.1 Data acquisition ........................................................................................................................ 40

4.3 Refraction Data Analysis .......................................................................................................... 46

4.3.1 Basic refraction analysis in North Line .................................................................................... 46

4.3.1.1 Promax .................................................................................................................................. 46

4.3.1.2 Geometry assignment ............................................................................................................ 46

4.3.1.3 Initial data analysis and quality control ................................................................................ 47

4.3.1.4 First Break Picking in Promax .............................................................................................. 47

4.3.1.5 Extraction to Matlab ............................................................................................................. 48

4.3.1.6 Gradient intercept method ..................................................................................................... 49

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4.3.2 Advanced refraction analysis (North Line) ............................................................................ 50

4.4.2.1 Seisimager ............................................................................................................................. 50

4.4.2.2 Initial data analysis and quality control ................................................................................ 50

4.4.2.3 Data Processing ..................................................................................................................... 50

4.4.2.4 Elevation importing. ............................................................................................................. 50

4.4.2.5 Amplitude Recovery ............................................................................................................. 51

4.4.2.6 Travel Time Pick and QC ..................................................................................................... 52

4.4.2.7 Reciprocal Time Check ......................................................................................................... 52

4.4.2.8 First break picks of P-wave in North Line ............................................................................ 53

4.4.2.9 Advanced Seismic Refraction Analysis using Seisimager .................................................... 53

4.4.2.10 Layer assignment ................................................................................................................ 53

4.4.2.11 Reciprocal method .............................................................................................................. 54

4.4.2.12 Time term inversion ............................................................................................................ 55

4.4.2.13 Tomographic inversion ....................................................................................................... 56

4.3.3 Seismic Reflection Data Processing and Analysis in North Line ............................................ 60

4.3.3.1 Refraction Muting ................................................................................................................. 60

4.3.3.2 Bandpass Filtering ................................................................................................................ 62

4.3.3.3 Static Correction ................................................................................................................... 64

4.3.3.3.1 Elevation Statics Analysis in North line. ........................................................................... 65

4.3.3.3.2 Datum static correction from tomographic inversion of Seisimager in Promax: ............... 66

4.3.3.4 Stacking................................................................................................................................. 68

4.3.4 Comparison with the other methods (DC-resistivity) .............................................................. 71

4.3.4.1 DC Resistivity Survey ........................................................................................................... 71

4.3.5 Advanced refraction analysis (Zen Garden ) ........................................................................... 73

4.3.5.1 First break picks of P-wave in Zen Garden ........................................................................... 73

4.3.5.2 S-wave first break picking .................................................................................................... 74

4.3.5.3 Time-term inversion and Tomographic inversion in Zen Garden ......................................... 76

4.3.6 Comparison with Ground Penetration Radar (GPR) ............................................................... 77

4.3.6.1 GPR (Ground Penetration Radar) ......................................................................................... 77

CHAPTER FIVE. ................................................................................................................................. 82

5.0 RESULTS AND DISCUSSION ............................................................................................... 82

5.1 Basic refraction analysis in North Line ........................................................................................... 82

5.1.1Results from Gradient-Intercept method on the North line ...................................................... 82

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5.2 Advanced seismic refraction analysis in North Line ...................................................................... 86

5.2.1. Time Term Inversion .............................................................................................................. 86

5.2.2 Tomographic Inversion ............................................................................................................ 89

5.2.3 Reciprocal Method ................................................................................................................... 99

5.3 Statics analysis of P-wave data in North Line .............................................................................. 103

5.5.1 Elevation static correction from first break picks picked in Promax: .................................... 103

5.5.2 Datum statics from tomographic inversion . .......................................................................... 104

5.5.3 Application of static correction to the stack ........................................................................... 106

5.5.4 Comparison of the stack with results from refraction analysis. ............................................. 109

........................................................................................................................................................ 111

5.5.5 Comparison with the result of DC-resistivity survey in North line area. ............................... 112

5.4 Advanced refraction analysis in Zen Garden ................................................................................ 114

5.4.1 P-wave velocity model analysis in Zen Garden ..................................................................... 114

5.4.2 S-wave Velocity model from tomographic inversion in Zen Garden .................................... 119

5.4.3 Poison’s ratio analysis ............................................................................................................ 121

5.4.4 Vp/Vs analysis ....................................................................................................................... 123

CHAPTER SIX. .................................................................................................................................. 125

6.0 Conclusions and Recommendations ....................................................................................... 125

References ........................................................................................................................................... 127

Appendix ............................................................................................................................................. 130

List of tables

Table 4-1 Summary of data acquisition in Pagosa Springs Colorado USA ........................................................... 42

Table 5-1 Depth model from basic refraction analysis ........................................................................................ 85

Table 5-2 Velocity model from basic refraction analysis ..................................................................................... 85

Table 5-3 Seismic Velocities of Earth Materials (Gary Mavko, 2005) .................................................................. 99

Table 5-4 P- to S-wave velocity and Poisson’s ratios calculated from P- and S-wave in Zen Garden ................ 121

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List of figures

Figure 1-1Seismic waves and the behaviour at interfaces .................................................................................... 10

Figure 2-1 Location of Pagosa Springs in entire map of United States of America. (Map is copyright Google

Earth) .................................................................................................................................................................... 13

Figure 2-2 Areal Map of the Structures in the San Juan Basin with the area of Pagosa Springs outlined in red (

Imperial College London and Colorado School of Mines Students of the geophysics field camp, 2012) .............. 13

Figure 2-3 Areal map with the Archuleta anticlinorium showing relations with the San Juan Basin and other

basin. ( Imperial College London and Colorado School of Mines Students of the geophysics field camp, 2012) .. 14

Figure 3-1 Relationship between the angles of incidence and refraction ............................................................. 15

Figure 3-2 Source-to-receiver raypath of a refracted ray in a two-layer case. ..................................................... 16

Figure 3-3 Traveltime-offset curve for a horizontal interface two-layer case ...................................................... 17

Figure 3-4 Source-to-receiver raypath of a refracted ray in a three-layer horizontal case ................................... 18

Figure 3-5 Traveltime-offset curve for a horizontal interface three-layer case .................................................... 20

Figure 3-6 Hidden layer problem in refraction caused by a layer having insufficient thickness and velocity

contrast ................................................................................................................................................................. 21

Figure 3-7 Blind layer problem in refraction caused mainly by a velocity inversion. ............................................ 22

Figure 3-8 Refraction picking options: t0 is the first break (first kick) time, t1 is the first arrival time through the

first inflection time, and t2 to t7 are the trough, zero crossing, and peak times (Cox, 1999) .............................. 23

Figure 3-9 Principle of the delay-time method ..................................................................................................... 25

Figure 3-10 Principle of reciprocal method ........................................................................................................... 26

Figure 3-11 Principle of reduced traveltimes ........................................................................................................ 28

Figure 3-12 Principle of time-term inversion (in case that the refractor is parallel to the ground surface) ......... 31

Figure 3-13 Principle of time-term inversion (in case that the refractor is non-parallel to the ground surface) .. 33

Figure 3-14 Process of depth calculation in time-term inversion.......................................................................... 34

Figure 3-15 Principle of tomographic inversion .................................................................................................... 35

Figure 4-1 Project work-flow ................................................................................................................................ 39

Figure 4-2 Data Acquisition work-flow ................................................................................................................. 40

Figure 4-3 hammer seismic showing different p-wave ray paths ......................................................................... 41

Figure 4-4 Data acquisitions of P-wave and S-wave ............................................................................................. 41

Figure 4-5 Elevation profile of survey area (North line) (information from GPS in Colorado field camp) ............. 43

Figure 4-6 Data conversion work-flow .................................................................................................................. 43

Figure 4-7 General Cross-section of Pagosa Springs showing location of North line and Zen Garden with

exaggerated vertical scale in larger detail. ........................................................................................................... 44

Figure 4-8 map of survey area (Map is copyright Google Earth) ......................................................................... 45

Figure 4-9 work-flow of basic refraction analysis in North Line........................................................................... 46

Figure 4-10 Geometry assignment screen of Common Depth Point (CDP) and Fold in Promax ........................... 47

Figure 4-11 Deciding what pick to make for the first arrivals, First Kick, Trough or Peak. ................................... 48

Figure 4-12 First break picking on first-kick in Promax ......................................................................................... 48

Figure 4-13 Gradient-intercept method graph ..................................................................................................... 49

Figure 4-14 work-flow of advanced refraction analysis in North Line .................................................................. 50

Figure 4-15 Original data before applying any form of gain. ............................................................................... 51

Figure 4-16 Data in figure 4-15 after amplitude correction, stretching. .............................................................. 51

Figure 4-17 Reciprocal test for two shots with significant refractor overlap. ....................................................... 52

Figure 4-18 Example of P-wave first break picking on first-kick ........................................................................... 53

Figure 4-19 Example of layer assignment ............................................................................................................. 54

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Figure 4-20 Example of reverse line forming with delay time line for reciprocal method .................................... 55

Figure 4-21 Example of Layered model from time-term inversion ....................................................................... 56

Figure 4-22 Process of Tomographic inversion ..................................................................................................... 57

Figure 4-23 Design of the number of layers for initial model ............................................................................... 58

Figure 4-24 Ray tracing path in tomographic inversion ....................................................................................... 59

Figure 4-25 work-flow of seismic reflection data processing and analysis in North Line ..................................... 60

Figure 4-26 Refraction muting in Promax. (left: before refraction muting, middle: applying refraction muting,

right : after refraction muting ) ............................................................................................................................ 61

Figure 4-27 Aliased reflectors of data in FK spectrum analysis ............................................................................ 62

Figure 4-28 Schematic drawing on cut range of Bandpass (frequency: 50 – 100 - 200 - 400 Hz)......................... 63

Figure 4-29 Bandpass filter application ( left: gather before applying bandpass, right: gather after applying

bandpass ............................................................................................................................................................... 64

Figure 4-30 schematic geometry for elevation statics with data from first break picks on first-kick of Promax .. 65

Figure 4-31 schematic geometry for datum statics using data from tomographic inversion of Seisimager ........ 66

Figure 4-32 Screen showing difficulties on velocity picking in Promax ................................................................. 68

Figure 4-33 Schematic drawing showing possibility of use of constant velocity for Normal Move Out in short

offset ..................................................................................................................................................................... 69

Figure 4-34 Expected reflector through a look into gather in Promax ................................................................. 70

Figure 4-35 Reflector shown in Brute stack in Promax ......................................................................................... 70

Figure 4-36 work-flow of comparison of North Line with DC-resistivity ............................................................... 71

Figure 4-37 SP and inverted resistivity profiles of PAGO 02 (Imperial College London and Colorado School of

Mines Geophysics Field Camp, 2012).................................................................................................................... 72

Figure 4-38 North line area where North line hammer seismic survey line crossing with PAGO 02 DC resistivity

survey line (Map is copyright Google Earth) ......................................................................................................... 72

Figure 4-39 Work-flow of advanced refraction analysis in Zen Garden ................................................................ 73

Figure 4-40 Example of P-wave firstbreak picking on first-kick in Zen Garden ..................................................... 74

Figure 4-41 Example of the raw data of S-wave in Zen Garden ........................................................................... 75

Figure 4-42 Example of choosing bad trace of S-wave in Zen Garden .................................................................. 75

Figure 4-43 Example of S-wave firstbreak picking on first-kick in Zen Garden ..................................................... 76

Figure 4-44 Work-flow of comparison of Zen Garden with GPR ........................................................................... 77

Figure 4-45 GPR acquisition comprising of the radar components and the analogue interpretation of a radar

time section. Tx: Transmitter, Rx: Receiver (Redrawn from Imperial College London and Colorado School of


Figure 4-46 Barn 3 survey line ( red line: SW- NE ) cited from Google Map ........................................................ 79

Figure 4-47 General cross-section of Pagosa Springs showing the location of Barn 3 and Zen Garden. Vertical

scale has been exaggerated to show features in larger detail. (Imperial College London and Colorado School of


Figure 4-48 General cross-section of the location of GPR acquisition in data acquisition line of Barn 3. Vertical

scale has been exaggerated to show features in larger detail. (Imperial College London and Colorado School of


Figure 5-1 Depth model generated from picking firstbreak on the first pick in Promax ...................................... 82

Figure 5-2 Depth model generated from picking firstbreak on first kick in Promax ............................................ 83

Figure 5-3 Depth model generated from picking firstbreak on first trough in Promax ....................................... 83

Figure 5-4 Velocity model generated from picking firstbreak on the first pick in Promax ................................... 84

Figure 5-5 Velocity model generated from picking firstbreak on first kick in Promax .......................................... 84

Figure 5-6 Velocity model generated from picking firstbreak on the first trough in Promax ............................... 85

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Figure 5-7Connected Layer assignment of whole North line in Plotrefa TM of Seisimage ................................... 87

Figure 5-8 Layered model from time-term inversion of North line with smoothing effect (Smoothing passes: 3)

added in Plotrefa TM of Seisimager...................................................................................................................... 88

Figure 5-9 Principle of designing the number of layers for the initial model ........................................................ 89

Figure 5-10 the image of one move-up time term inversion result chosen for parameter tests for initial model in

North line in comparison with the whole North line time term inversion image in Plotrefa TM of Seisimager ... 91

Figure 5-11 images of one pattern time term inversion result chosen for parameter tests for initial model in

North line in Plotrefa TM of Seisimager ( (a) P-wave velocity 30 m/s – 3000 m/s, the number of layers 10 (b)

P-wave velocity 30 m/s – 3000 m/s, the number of layers 15 (c) P-wave velocity 30 m/s – 3000 m/s, the

number of layers 18 ............................................................................................................................................. 92

Figure 5-12 images of time term inversion result chosen for parameter tests for initial model in North line in

Plotrefa TM of Seisimager ((a) P-wave velocity 30 m/s – 1000 m/s, the number of layers 15 (b) P-wave

velocity 30 m/s – 3000 m/s, the number of layers 15 (c) P-wave velocity 30 m/s – 10000 m/s, the number of

layers 15 ) ............................................................................................................................................................. 93

Figure 5-13 The image of initial model in whole North line in Plotrefa TM of Seisimager ( calculated with

parameters of P-wave velocity 30 m/s – 3000 m/s, the number of layers 15 ...................................................... 95

Figure 5-14 Misfit between synthetic and observed travel time as a function of the iteration number. Observe

the lack of significant reduction in the travel time misfit after about 10 iterations. ............................................ 96

Figure 5-15 the image of P-wave velocity model from tomographic inversion in whole North line in Plotrefa TM

of Seisimager (value 10 was chosen for the number of iteration ) ....................................................................... 97

Figure 5-16 the image of Ray tracing path of P-wave velocity model from tomographic inversion in whole North

line in Plotrefa TM of Seisimager .......................................................................................................................... 98

Figure 5-17 an image of reciprocal method showing delay time line and reverse time line in one move-up of

North line in Plotrefa TM of Seisimager (delay times in both sides are calculated and averaged ) ................... 100

Figure 5-18 the image of P-wave velocity model generated by reciprocal method in one move-up of North line

in Plotrefa TM of Seisimager ( delay times in both sides are calculated and averaged ) ................................... 101

Figure 5-19 Comparison between images of P-wave velocity models generated by reciprocal method and time-

term inversion in one move-up of North line in Plotrefa TM of Seisimager (Note that both methods are

conducted in same position) ............................................................................................................................... 102

Figure 5-20 plots of Elevation static correction on P-wave obtained from first break pick on first kick in

Northline of receiver shown in Promax . ............................................................................................................. 103

Figure 5-21 plots of Elevation static correction on P-wave obtained from first break pick on first kick in Northline

of source shown in Promax . ............................................................................................................................... 103

Figure 5-22 Values of LVL Static ( refraction static), Elevation static correction of receiver and total datum static

correction shown in Promax . The values of elevation static correction and LVL static correction are added up to

find datum static correction. .............................................................................................................................. 104

Figure 5-23 plots of Datum static correction on P-wave obtained from tomographic inversion in North line of

receiver shown in Promax . ................................................................................................................................. 105

Figure 5-24 plots of Datum static correction on P-wave obtained from tomographic inversion in North line of

source shown in Promax . ................................................................................................................................... 105

Figure 5-25 the image of stack not applied with static correction (only bandpass applied : Bandpass frequency

range : 50 – 100 -200 -400 hz . ........................................................................................................................... 106

Figure 5-26 the image of stack applied with elevation static correction ( bandpass and elevation static

correction applied : Bandpass frequency range : 50 – 100 -200 -400 hz .) ......................................................... 107

Figure 5-27 the image of stack applied with Datum static correction ( bandpass and datum static correction

applied applied : Bandpass frequency range : 50 – 100 -200 -400 hz Here Datum static correction = LVL static

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correction ( Refraction static correction (LVL) .................................................................................................... 107

Figure 5-28 the image of stack ( only bandpass applied : Bandpass frequency range : 50 – 100 -200 -400 hz . 108

Figure 5-29 the image of stack applied with elevation static correction ( bandpass and elevation static

correction applied : Bandpass frequency range : 50 – 100 -200 -400 hz .) ......................................................... 108

Figure 5-30 the image of stack applied with datum static correction ( bandpass and datum static correction

applied applied : Bandpass frequency range : 50 – 100 -200 -400 hz Here datum static correction = LVL static

correction ( Refraction static correction )+ elevation static correction............................................................... 108

Figure 5-31 A possible fault by comparison between refraction processed image and reflection processed image

in North line. (a) image from time-term inversion (b) image from tomographic inversion (c) image from brute

stack applied with datum statics correction. ...................................................................................................... 110

Figure 5-32 A possible fault (F1) by comparison of the stack with superimposed and flattened refraction

processed image( from tomographic inversion) in North line ............................................................................ 111

Figure 5-33 A possible fault expected by result from DC-resistivity survey and Hammer seismic survey in North

Line area (The DC-resistivity model is fit to the PAGO02 pararelly, and the tomographic inversion image is fit to

the North line in parallel) DC-resistivity image is cited from Imperial College London and Colorado School of

Mines Geophysics Camp 2012. ........................................................................................................................... 113

Figure 5-34 the image of P-wave velocity model generated by time term inversion in Zen Garden in Plotrefa TM

of Seisimager ...................................................................................................................................................... 114

Figure 5-35 the image of P-wave velocity model from tomographic inversion in Zen Garden in Plotrefa TM of

Seisimager (value 10 was chosen for the number of iteration ) ......................................................................... 115

Figure 5-36 the image of Ray tracing path of P-wave velocity model from tomographic inversion in Zen Garden

in Plotrefa TM of Seisimager .............................................................................................................................. 116

Figure 5-37 Comparison of P-wave velocity model from tomographic inversion and subsurface model from basic

gradient intercept method done by Imperial College London and Colorado School of Mines Geophysics Field

Camp, 2012 ( right Figure.- cited from Imperial College London and Colorado School of Mines Geophysics Camp,

2012 (right Figure cited from Imperial College London and Colorado School of Mines Geophysics Camp, 2012).

............................................................................................................................................................................ 117

Figure 5-38 the image of S-wave velocity model generated by time term inversion in Zen Garden in Plotrefa TM

of Seisimager ...................................................................................................................................................... 118

Figure 5-39 the image of S-wave velocity model from tomographic inversion in Zen Garden in Plotrefa TM of

Seisimager (value 10 was chosen for the number of iteration) .......................................................................... 118

Figure 5-40 the image of Ray tracing path of S-wave velocity model from tomographic inversion in Zen Garden

in Plotrefa TM of Seisimager .............................................................................................................................. 119

Figure 5-41 Comparison of shapes of P-wave data and S-wave data ................................................................ 120

Figure 5-42 Chart of Poisson’s ratio, Vp/Vs ratio and P-wave velocity (Redrawn from Thomas M. Brocher, 2005)

............................................................................................................................................................................ 122

Figure 5-43 Chart of Vp, Vp/Vs ratio and Porosity in Zen Garden ( Redrawn from E.R.(Ross) Grain, 2000) .... 123

Figure 5-44 (a) Seismic section at Barn 3 and (b) its interpretation related to the Dakota Sandstone. (Imperial

College London and Colorado School of Mines Geophysics Field Camp, 2012) .................................................. 124

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ACKNOWLEDGEMENT

Dr. Adam Booth. I would like to express my special appreciation to him. He is my supervisor. Without his guidance and supervision, the completion of this project would not be possible.

In addition, I would like to express special gratitude to Professor Helmut for his kind supports and guidance throughout this entire course.

I also appreciate Faculty of Colorado School of Mines for the efforts that are made to acquire these data from Pagosa Springs, Colorado, USA.

Sincere thanks to Mr Seth who was in charge of data acquisition in Pagosa Springs for his kind support and guidance.

Special thanks to My sister, Mrs. In-hee Kim and his husband Mr. Isaac Choi, my parent, Mrs. Sun-hee Kim, Mr. Hyun-dong Kim.

And I also thank Kenneth for his spiritual supports.

Junghee Kim 10

CHAPTER ONE

1.0 Introduction

Seismic surveys measure the earth’s elastic properties using seismic waves (Sheriff 2002). The source of these disturbances can be controlled as in the case of exploration and engineering seismology, or it can be uncontrolled as in the case of earthquake seismology. (Dobrin 1976) The propagation is described by the elastic wave equation, which is derived from two laws of physics, Hooke’s law and Newton’s second law of motion. (Dobrin 1976) When an elastic wave propagates through a medium in the earth is reflected, refracted and transmitted at an interface (Figure 1-1) (Dobrin 1976). The wave can also be diffracted around discontinuities. (Dobrin 1976)

Figure 1-1 Seismic waves and the behaviour at interfaces (Dobrin 1976; Waters 1997)

There are two forms of seismology, reflection and refraction seismology (Jakubowicz 2012). Refraction seismology involves the recording, processing and analysis of refracted seismic energy and is mainly used for near surface studies. Reflection seismology involves processing and analysing seismic reflected energy. Reflection surveys are mainly applied in exploration for mining and hydrocarbon exploration (Dobrin 1976), and crustal studies (Reading et al, 2011). Seismic experiments performed for near surface investigations are referred as shallow seismic surveys. (Karastathis et al. 2007)

Shallow seismic studies are often applied to detect geologic structures in fault zones and to find shallow, soft layers of underground earth materials especially in area of rapid

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urbanisation and heavy agriculture. (Karastathis et al. 2007)

Seismic refraction survey using a Hammer source was conducted along selected line across Pagosa Springs, Colorado in June 2012. The aim was to perform near surface study and characterisation of the hydrothermal activities in the area. Although Pagosa Springs in Colorado is famous for the hydrothermal activities, these are still not well understood. (Imperial College London and Colorado School of Mines Geophysics Field Camp 2012)

In this project, near surface study and characterisation using refraction analysis of data acquired at Pagosa Springs will be performed with a view to determining the depth of the bedrock and the ground water, the lateral and vertical changes in lithology, the lithology type and investigating the structural features such as micro faults.

1.1 Objectives

The aims of the near surface study in Pagosa Springs are as follows:

To use P-wave and S-wave refraction methods to obtain velocity-depth models for near-surface layering at Pagosa Springs.

To combine P- and S-wave observations to quantify physical properties of near-surface layering, and to propose lithology.

To investigate the interpretation of P-wave refraction data as a reflection profile, including a near-surface

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CHAPTER TWO

2.0 Geological setting of Pagosa Springs, Colorado USA

Pagosa Springs is located on the northeast edge of the San Juan Basin as seen in Figure 2-2. ( Imperial College London and Colorado School of Mines, geophysics filed camp 2012) This is a large depositional basin concentrated in western New Mexico and Four Corners region of the western United States (Fred 1982).The basin is bordered in the north by the San Juan Mountains of southern Colorado, in the northeast by the Chama Basin, in the east by the Nacimiento and San Pedro Uplifts, in the south by the Zuni Uplift and the Zuni Mountains of New Mexico and in the west by the Defiance Uplift of eastern Arizona and western New Mexico. The central basin with deepest sedimentary units is mainly located in north western New Mexico and a small part of southern Colorado. (Fred 1982) Uplift of mountain ranges almost prior to the Cambrian age and the transgression of multiple seaways beginning in the late Cambrian age caused this basin to form. This is the reason why the basin includes almost continuous column of sedimentary units beginning in the late Cambrian and continuing until the glaciations and orogenies of the late Cenezoic. (Fred 1982). On the Archuleta anticlinorium, Pagosa Springs is located in the northeast edge of this basin. (Fred 1982) The Archuleta anticlinorium is located in the edge of the San Juan Basin starting from southern Colorado with a north- northwest trend, continuing into north central Arizona. (Fred 1982) The region is located 15 miles west of the continental divide with the San Juan River serving as the primary stream system because it flows from the Divide to the Pacific Ocean to the Southwest. Its allochthonous folding over the underlying basement is the most significant characteristics of this structure. (Fred 1982) A shallow north-north western trending anticline through Pagosa Springs is produced by this. This gives the 12000 ft of sedimentary units in the area, a dip of about 5-10˚ towards the San Juan Mountains in the north eastern half of the anticlinorium and a similar dip towards the basin on the south western half. (Fred 1982) To the north, the units merge with the surrounding basins beneath the San Juan Mountains. (Fred 1982) However, to the south, the units increase in dip when they move towards the main basin. (Fred 1982)

In the Pagosa Springs, Colorado USA, geophysical analyses have been performed by students of Imperial College London and Colorado School of Mines during the geophysical summer camp 2012. Different geophysical experiments were performed in this area. One of such was the refraction seismic method which is to analyse near surface geology of the area for geotechnical and groundwater purposes.

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Figure 2-1 Location of Pagosa Springs in entire map of United States of America. (Map is copyright Google Earth)

Figure 2-2 Areal Map of the Structures in the San Juan Basin with the area of Pagosa Springs outlined in red (

Imperial College London and Colorado School of Mines geophysics field camp 2012)

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Figure 2-3Areal map with the Archuleta anticlinorium showing relations with the San Juan Basin and other basin. (

Imperial College London and Colorado School of Mines, geophysics field camp 2012)

Junghee Kim 15

CHAPTER THREE

3.0 Theory and Literature review

3.1 Refraction Seismic Method

Refraction can be defined in terms of the change in direction of a seismic ray or wavefront at an interface between layers of different velocities (Cox 1999). The relationship between the angles of incidence and refraction at the interface (Figure 3-1) is governed by Snell’s law, which is given as (Craig Lippus 2007):

(2.1)

Where , represent the angles of incidence and refraction and , represent the velocities in the first and second layer respectively. (Craig Lippus 2007)

Figure 3-1Relationship between the angles of incidence and refraction (Jacob Fokkema and Nafi Toksoz 2012)

When the angle of incidence is such that the refracted wavefront is perpendicular to the

interface ( ), it is referred to as critical angle of incidence ( ) and the refracted ray travels along the interface between the two layers. Equation (2.1) is the then adjusted to the form (Craig Lippus 2007)::

(2.2)

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The waves that travel to and along the interface between the two layers and return to the surface through the upper layer are referred to as refraction waves, head waves, Mintrop waves, or bow waves (Cox 1999).

3.2 Time-Distance curves for layered media

Figure 2.5 shows the raypath of a refracted ray from a source location at S to a receiver

location at R for a two-layer horizontal interface case. The total traveltime ( ) for this raypath, having a source-to-receiver separation of x is given as the sum of the traveltime on each of the three sections making up the path. (Jacob Fokkema and Nafi Toksoz 2012) i.e:

(2.3)

This implies that:

Rearranging the equation:

(2.4)

Figure 3-2 Source-to-receiver raypath of a refracted ray in a two-layer case (Jacob Fokkema and Nafi Toksoz 2012).

Using Snell’s law (Jacob Fokkema and Nafi Toksoz 2012)

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(2.5)

Finally we have:

(2.6)

Equation (2.5) represents a straight line with a slope of

and an intercept of given by:

(2.7)

Figure 2.5 shows the traveltime graph representing the propagation of the refracted ray for a two-layer horizontal case. From the graph we can calculate and use it to estimate to the refractor z. (Jacob Fokkema and Nafi Toksoz 2012)

Figure 3-3Traveltime-offset curve for a horizontal interface two-layer case (Jacob Fokkema and Nafi Toksoz 2012)

From Equation (2.7), we have that (Jacob Fokkema and Nafi Toksoz 2012):

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(2.8)

Using equation 2.2 and some trigonometric properties, we have that (Jacob Fokkema and Nafi Toksoz 2012) :

(2.9)

Figure 3-4 Source-to-receiver raypath of a refracted ray in a three-layer horizontal case (Jacob Fokkema and Nafi

Toksoz 2012)

For a three-layer case having a raypath diagram shown in figure 3-4, Equations (2.5 – 2.7) can be extended following the same processes as above to yield the total traveltime as

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(Jacob Fokkema and Nafi Toksoz 2012),

(2.10)

This again is a straight line equation with a slope of

and an intercept of given as:

(2.11)

The depth of the first layer is calculated as before, while the thickness of the second layer is given as:

(2.12)

Therefore,

(2.13)

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Figure 3-5 Traveltime-offset curve for a horizontal interface three-layer case (Jacob Fokkema and Nafi Toksoz 2012)

Figure 3-5 shows the traveltime curve for the three layer case from which we read the intercept times and calculate the thicknesses of the various interfaces.

For a multilayer problem, Equation (2.14) is given by (Cox 2009)

(2.14)

Where

(2.15)

3.3 Hidden Layers, Velocity Inversions, and Blind Zones

In order to be detected in a first arrival refraction survey, a layer must satisfy two conditions: (a) be underlain by a layer of higher velocity so that head waves are produced, and (b) have a thickness and velocity such that the head waves become first arrivals at some range (Kearey and Brooks, 2002). It is possible for layers to exist in the Earth, yet not produce any refracted first-arrival waves, and a simple first arrival refraction survey will not be able to

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detect these layers if these conditions are not met. The possibility of undetected layers should therefore be considered when interpreting refraction data. (Philip Kearey et al. 2002)

Figure 3-6 Hidden layer problem in refraction caused by a layer having insufficient thickness and velocity contrast

(Philip Kearey et al. 2002).

In practice, two different types of problem are shown: (1) Hidden layer, and (2) Blind zone.

A hidden layer, from its name, is one that cannot be detected by first arrival seismic refraction method, and may be caused by insufficient thickness and velocity contrast of the layer (Cox, 1999). The layer produces head waves, but does not give rise to first arrivals (Kearey and Brooks, 2002). Rays travelling to deeper levels arrive before those critically refracted at the top of the layer in question (Figure 3-6). In such a case, a method of survey involving recognition of only first arrivals will fail to detect the layer. It is good practice to examine the seismic traces for possible arrivals occurring behind the first arrivals. (Philip Kearey et al. 2002)

A blind layer violates the first condition necessary for first arrival refraction experiment detection by resulting from a low-velocity layer, as illustrated in Figure 3-7 (Kearey and Brooks 2002). Rays are critically refracted at the top of such a layer and the layer will therefore not give rise to head waves. The interpretation of travel-time curves, in the presence of a low-velocity layer, leads to an overestimation of the depth to underlying interfaces. (Philip Kearey et al. 2002)

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Figure 3-7 Blind layer problem in refraction caused mainly by a velocity inversion (Philip Kearey et al. 2002).

3.4 Refraction Arrival picking and time adjustments

The first step in the interpretation of a refraction experiment data is to review and pick the arrival times (Cox 1999). While the review phase involves the initially analysis of the data to be picked, the picking phase is concerned with the actual picking of traveltimes, which is usually done either manually or automatically. Certain adjustments of reciprocal time are also performed on the picked traveltimes before any form of interpretation is then carried out. (Cox 1999)

3.5 Manual picking and automatic picking of traveltimes

Figure 2.10 shows a refraction arrival in which the various forms of picks (from first kick, peak, trough) has been shown. Picking requires that we have a broadband signal, minimal filtering of data, a good signal-to-noise ratio, and a high gain display (Cox 1999). First break or kick (represented by t0 in Figure 3-8 ) is usually picked because a change in frequency with offsets, receiver and source locations (usually common with land surveys) may cause a shift relative to the first break. (Cox 1999)

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Figure 3-8 Refraction picking options: t0 is the first break (first kick) time, t1 is the first arrival time through the first

inflection time, and t2 to t7 are the trough, zero crossing, and peak times (Cox 1999)

In most settings, it is desirable in manual picking of travels times that the accuracy stays within 1 or 2 ms for individual picks (Cox 1999).

In the presence of a large dataset the picking is usually automated. Automated picking works well in a good signal-to-noise dataset, and the first arrivals are well defined. (Cox 1999)

3.6 Reciprocal Time Correlation

Regardless of the subsurface structure, seismic reciprocity condition between any two points must be satisfied for the surface-consistent refracted travel times,(Hagedoorn 2006) i.e.:

(2.16)

This condition should be tested and corrected prior to performing any form of interpretation.

It is usually done by calculating the reciprocal time misfits between all pairs of shot locations

(Si and Sj) with reciprocal (reversed) recording (Hagedoorn 2006):

(2.17)

When the misfit ( ) is large, corrections are then applied to traveltime picks, though it is

advised that the picking be redone when possible (Hagedoorn 2006).

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3.7 Refraction Interpretation

In an area with simple planar refractors and the velocities in the overlying layers are laterally invariant, any of Equations (2.4) to (2.17) can be used to determine the layer velocities and their corresponding depths. However, in practice the geology is usually very complex and special efforts are therefore required in refining these equations and in applying them subsequently (Jacob Fokkema and Nafi Toksoz 2012).

Refraction interpretation methods are broadly divided into two approaches (Cox 1999): Those in which the data are analysed at a common surface location and those in which the data are analysed at a common subsurface location.

Inversion can also be used to interpret refraction data. Tomographic and time-term inversions are the most common applied in practice.

3.8 Gradient-Intercept method

The gradient-intercept method (also called intercept method) is used as an interpretation method when the geology is simple and planar. It uses the Equations derived above ((2.4) ~ 2.17)), where the intercept time (zero offset time) is used to determine the refractor depth at the source location (Jacob Fokkema and Nafi Toksoz 2012). (Figure 3-2).

3.9 Delay-Time Concept

In a complex subsurface where the interfaces are undulating and multi-layered, most of the refraction-statics methods, such as the Plus-Minus and the Generalized Reciprocal methods are based on the delay-time approximation of refracted travel times (Hagedoorn 2006) to solve for the refraction statics. Consider a source located at point S and a receiver at point R at the surface (Figure 2.4). In the delay-time approximation, the refractor is considered as near-horizontal between the two points, and the distance between them is much greater than the critical distance. (here, critical distance means the minimum distance from the energy source at which the first critical refraction can be received (Jacob T. Fokkema and M.Nafi Toksoz 2012). Generally, this implies that the velocity of the refractor (bedrock) is much larger than that of the overburden.

Under these approximations, the travel-time from S to R can then be separated to the source-side and receiver-side times (Jacob Fokkema and Nafi Toksoz 2012).:

(2.18)

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Figure 3-9 Principle of the delay-time method (Jacob Fokkema and Nafi Toksoz 2012).

Time can be represented as a sum of the travel time along the reflector and the “source delay” time (Jacob Fokkema and Nafi Toksoz 2012).:

(2.19)

For source delay, , we therefore have (Jacob Fokkema and Nafi Toksoz 2012):

(2.20)

In a similar way, the receiver delay time is defined, and the total time from the source to the receiver is (Jacob Fokkema and Nafi Toksoz 2012) :

(2.21)

This equation relates the velocity of the bedrock and the depth of the weathering layer to the first-arrival travel times. This equation is further inverted to solve for the depths of the weathering layer near the sources and receivers, and the velocity of the refractor (Jacob Fokkema and Nafi Toksoz 2012).

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3.10 Reciprocal Method

Concept of Delay time in Reciprocal Method is as Figure 3-10.

Figure 3-10 Principle of reciprocal method (Jacob Fokkema and Nafi Toksoz 2012).

Referring Equation (2.19) and Equation (2.20), if AC = BD, in this case, × 2 (because

in both sides) +

(here x = ) (Jacob Fokkema and Nafi Toksoz 2012; Seisimager/2D

Manual 2005)..

(2.22)

But if it is different values,

Then,

(2.23)

Similarly,

(2.24)

And

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(2.25)

Delay time to in Reciprocal method

(2.26)

If substituting,

(2.27)

This is equal to,

(2.28)

In the Figure 3-10,

(2.29)

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Therefore,

(2.30)

Here, to is twice the time required for the seismic energy to travel from P to P’.

Delay time DT at point P is defined as below (Jacob Fokkema and Nafi Toksoz 2012; Seisimager/2D Manual 2005).. .

(2.31)

Computation of reduced traveltime allows us to remove the effect of changing layer thickness on the traveltim curve and give a better measurement of velocity. The delay time and refractor depth are calculated (Jacob Fokkema and Nafi Toksoz 2012; Seisimager/2D Manual 2005).. .

Figure 3-11 Principle of reduced traveltime (Jacob Fokkema and Nafi Toksoz 2012; Seisimager/2D Manual 2005)

The reduced traveltime at point P for a source at A T’AP (Jacob Fokkema and Nafi Toksoz

2012; Seisimager/2D Manual 2005)..

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(2.32)

This is same as

(2.33)

By rearranging,

(2.34)

Because

(2.35)

(2.36)

Therefore,

(2.37)

Assuming that the AC = BD,

(2.38)

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(2.39)

Because

(2.40)

Therefore,

(2.41)

(2.42)

Therefore, the depth in P point is decided as following (Jacob Fokkema and Nafi Toksoz

2012; Seisimager/2D Manual 2005)..

(2.43)

Note that Equation (2.43) is same as (Jacob Fokkema and Nafi Toksoz 2012;

Seisimager/2D Manual 2005).

(2.44)

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3.11 Term-time inversion

A linear Least-Squares approach is used to define the time-term method. This is to

determine the best discrete-layer solution to the data (Takaya Iwasaki 2002; Seisimager/2D

Manual 2005).

Figure 3-12 Principle of time-term inversion (in case that the refractor is parallel to the ground surface) (Takaya

Iwasaki, 2002; Seisimager/2D Manual 2005). .

Slowness is defined as S which is inverse velocity (Takaya Iwasaki 2002; Seisimager/2D

Manual 2005). .

(2.45)

(2.46)

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From Snell’s Law,

(2.47)

Travel time definition in reciprocal method (in the assumption that the depths in both sides

are same)

(2.48)

If the total travel time = t from source to receiver, h = z, S1 = 1/V1, S2 = 1/V2

(2.49)

C is defined as follows,

(2.50)

Then

(2.51)

Z and S2 are not known

The example above has assumption that the refractor is parallel to the ground surface

If these are non-parallel, curved surfaces, there are three un-knowns Z1, Z3 and S2. (Takaya

Iwasaki 2002; Seisimager/2D Manual 2005). .

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Figure 3-13 Principle of time-term inversion (in case that the refractor is non-parallel to the ground surface) (Takaya

Iwasaki 2002; Seisimager/2D Manual 2005). .

Now,

(2.52)

Generalisation,

(2.53)

In matrix form,

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(2.54)

Where m = number of traveltimes, and n = number of receivers (Depths to be calculated).

So, Z1, Z2, ••• Zn and S2 are solved.

Figure 3-14 Process of depth calculation in time-term inversion

To make it clear, in Figure 3-14, the first source can have many cases of x values with different t values. When the seismic ray is passing P1, many receivers can receive this ray. By the travel times and x values, z1 is decided. The second source does same thing again calculating z2 and it is repeated up to the last source calculating z3, z4, ·····, zn. This is expressed as Equation (2.54).

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3.12 Tomographic inversion method

Jacob R. Sheehan et al. (2000) stated that tomographic inversion method is able to resolve velocity gradients and lateral velocity changes and can be applied in settings where conventional refraction techniques don’t work. For example, the method can be applied in areas of compaction, karst, and fault zones.

Tomographic inversion requires an initial model because this inversion is non-linear problem.

Iteratively tracing rays through the model compares the calculated traveltimes to the

measured traveltimes. And it modifies the model and repeats the process until the misfit

between calculated and measured times is minimised. Therefore, the ultimate goal is to find

the minimum traveltime source and receiver for each source-receiver pair. By solving l

(raypath) and s (slowness: inverse velocity). Because both are unknowns, the problem is

under-constrained and an iterative, least-squares approach. (Non-linear problem) (Jacob R.

Sheehan et al. 2000 ; Seisimager/2D Manual 2005).

Figure 3-15 Principle of tomographic inversion (Jacob R. Sheehan et al. 2000 ; Seisimager/2D Manual 2005).

(2.55)

S= slowness

= velocity

lij = raypath

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(2.56)

Therefore,

(2.57)

Or

(2.58)

Following can be said.

●

●

(2.59)

This can be expressed as

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(2.60)

This is the Least squares method. Generally, M > N

The conditions are required in the tomographic inversion.

First, Jacobian matrix requires ray-path.

Second, Ray-path cannot be calculated without a velocity model.

Third, cannot solve at once.

Fourth, must use non-linear Least Square method.

Iterative solution of a non-linear Least Squares matrix is as follows.

1) Theoretical value Yo (travel time) for initial value Xo (Slowness) is calculated.

(2.61)

2) Calculate residuals (∆Y) between theoretical value Yo and observed value Y.

(2.62)

3) Calculate correction value for X(∆Y) by the least squares method (Here, A = raypath)

(2.63)

4) Calculate new estimate for X1 ( there X1 = Xo + ∆X ) 5) Put the X1 value back to the model.

(2.64)

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This process is repeated until the misfit is close to the minimum.

And with the X values (Slowness) and Y values (travel time), the depths of each point are decided. (Jacob R. Sheehan et al. 2000; Seisimager/2D Manual 2005)

In the time-inversion and tomographic inversion, RMS error checking was performed for data quality purpose.

Here Root-mean-square error

(2.65)

Here n is the number of layer, and Ei is the difference between the inverted and actual velocities for the ith layer. (Khaled Al Dulaijan 2008)

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CHAPTER FOUR

4.0 METHODOLOGY

This section introduces the source of data acquisition, its preparation technique, data processing and methods of analyses. Procedure of this project is as follows in Figure 4-1.

Figure 4-1Project work-flow

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4.1 Data acquisition

Figure 4-2 Data Acquisition work-flow

The location of the North line in the Pagosa Springs, 2012 firstly was chosen for survey is because according to geological study, this area is assumed to have anomalous features such as fault, and dipping interfaces.(Imperial College London and Colorado School of Mines Geophysics Field Camp 2012) On the location map of the North Line, P-wave seismic refraction acquisition was performed. Secondly, the location of the Zen Garden was chosen for survey because this area is very close to North line, the geological feature in this area is assumed to be similar to the North line area. In addition, in the Zen Garden area, S-wave seismic refraction acquisition, as well as P-wave seismic refraction acquisition has been performed. The availability of S-wave and P-wave information allow us to calculate Poisson’s ratio and Vp/Vs through which the rock properties, lithology, porosity and water spreading in the area could be analysed. In North Line, shot and receiver spacing were each 3 m, while the shot point was in same position of receiver point. In Zen Garden, shot and receiver spacing were each 3m, while the shot point was midway between two adjacent receivers and 24 geophones were deployed at a time in each line making the maximum offset 70.5m. In Gen Garden the shot moves in between the geophone spread, down to the end of the line resulting in a total of 24 shots. In North Line, the shot moves in same position of geophone spread, down to the end of the line resulting in a total of 24 shots. Then the setup is rolled along the line until the end of the survey line is reached. The experiment was rolled seven times on the North Line, but done just once on the Zen garden line. P-waves were recorded in both the North line and the Zen garden using vertical geophones, while an addition S-wave survey was carried out in the Zen garden, using horizontal geophones (Figure 4-4).

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Figure 4-3 hammer seismic showing different p-wave ray paths

Figure 4-4 Data acquisitions of P-wave and S-wave

A summary of the acquisition set is shown in table 4-1.

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Table 4-1 Summary of data acquisition in Pagosa Springs Colorado USA(Imperial College London and Colorado

School of Mines Geophysics Field Camp 2012)

Zen Garden area is almost flat (elevation: about 2141 m) and the North line area has topography as shown in Figure 4.5. (Imperial College London and Colorado School of Mines Geophysics Field Camp 2012) (Appendix. 6)

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Figure 4-5 Elevation profile of survey area (North line) (information from GPS in Colorado field camp)

4.2 Data conversion

Figure 4-6 Data conversion work-flow

When the data were acquired, the file format was SU file. To process the data, the SU format file had to be converted to SEG-Y file and SEG-2 file.

Matlab was used to convert SU format files to SEG-Y for application in Promax for basic analysis and reflection processing and SEG-2 format files for application in Seisimager for advanced analysis. ( Mathworks 2012)

Promax and Seisimager will be explained later.

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Figure 4-7 General Cross-section of Pagosa Springs showing location of North line and Zen Garden with exaggerated vertical scale in larger detail. ( Imperial College London and

Colorado School of Mines Geophysics Field Camp 2012 )

In Figure 4-7, the blue arrow is directing the locations of North line and Zen Garden. (Imperial College London and Colorado School of Mines

Geophysics Field Camp 2012)

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Figure 4-8 map of survey area (Map is copyright Google Earth)

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4.3 Refraction Data Analysis

Refraction analysis basically involves the processing and interpretation of first for various near surface parameter estimation.

4.3.1 Basic refraction analysis in North Line

Figure 4-9 work-flow of basic refraction analysis in North Line

4.3.1.1 Promax

SEG-Y format file is used for this process. With the hammer seismic data in Promax, process of the first break picking is conducted.(Promax 1998) Based on the data obtained from this process, Seismic refraction analysis has been performed further in matlab for the basic analysis.

4.3.1.2 Geometry assignment

In this process, geometry information of shot spacing (3 m), receiver spacing (3 m) and move-ups (patterns)(1 – 24, 25-48, 49 -72, 73 -96, 97 -120, 121 – 144, 145 -168)) have been assigned.

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Figure 4-10 Geometry assignment screen of Common Depth Point (CDP) and Fold in Promax

The acquisition was done every move-up (pattern) separately. Once it was done, the line was rolled up and spread out another line of another pattern. We repeated the process 7 times. That is why the fold versus CDP graph looks as 7 peaks.

Maximum fold of coverage in Land data (North Line) = The number of channels / (shot interval/group interval) = 24 / (3/3) = 24 (Jakubowicz 2012)

4.3.1.3 Initial data analysis and quality control

The original seismic data are initially subjected to quality in other to look for bad shot gathers. The following shot gather were discovered to be really and as such not suitable for analysis and interpretation. In the initial stage, data were quality controlled for repeated shots. They were subsequently removed from the dataset. (Appendix 5)

4.3.1.4 First Break Picking in Promax

First break picking is to detect or pick the onset arrivals of refracted signals from all the signals received by the receiver and produced by a source generated. This is sometimes called first break detection or first arrival picking. (Chugn-Kuang and Chu and Jerry Mendel 1994) In this project, first break picking has been done using Promax in each shot.

Picking first arrival is faced with the decision of what to pick, First Kick, Peak, or Trough (Figure 3-9).

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Figure 4-11 Deciding what pick to make for the first arrivals, First Kick, Trough or Peak.

Picks were made in this project by selecting first kicks first, peak and later trough.

In this project, to see the sensitivity by first break picking, first-kick, peak and trough of the seismic have been picked and the results (Depth models and Velocity models) from the different first-break picks have been compared.

Figure 4-12 First break picking on first-kick in Promax

4.3.1.5 Extraction to Matlab

The data of first break picks were extracted and loaded to Matlab for refraction analyses (basic analysis: gradient -intercept method).

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4.3.1.6 Gradient intercept method

The gradient intercept method discussed in chapter was first used to interpret the picked travel times. Because the travel time picks do not fall on a straight line, a line of best fit so-called polyfit was used to approximate a straight line representing the picks in MATLAB (Figure 4-13). The test of error between actual data and data from polyfit are measured in Appendix 7.

Figure 4-13 Gradient-intercept method graph

The velocities of the first and second layers (and third layers in some case) are estimated from the slopes of each segment of the plot. The thickness of each layer is also estimated using the intercept formulae derived in chapter 3. These velocity and thickness values are placed at the source position and interpolated with the other values at every source position. The results will be in Chapter 5.

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4.3.2 Advanced refraction analysis (North Line)

Figure 4-14 work-flow of advanced refraction analysis in North Line

4.4.2.1 Seisimager

SEG-2 format file is used for this process. Seisimager has two main modules. PickwinTM and PlotrefaTM. PickwinTM helps to conduct first break picking and PlotrefaTM helps to analyse the data. Seisimager is a tool for refraction analysis. (Seisimager Manual, 2005). In this project, the Seisimager has been used.

4.4.2.2 Initial data analysis and quality control

The data loaded in Seisimager are checked and bad data are removed. The removed data were equal to the data removed in Promax. Some data in Zen Garden especially S-wave data had a lot of noise. Some trace did not have any information. Some traces were killed in some cases and some traces were not applied with first break picks by skipping picking in the trace. Bandpass was considered. However, by concluding the data given are ok with first break picking because it can still showing the first break picks even though it is a lot noisy deep down.

4.4.2.3 Data Processing

The data are uploaded to computer and Seisimager processes the seismic data. Using function of PickwinTM, the first arrival times are picked. (Seisimager 2005)

Complete analysis process is as following steps. (Anne Obermann 2000)

4.4.2.4 Elevation importing.

The elevation data were imported to the Seisimager before processing for the North line while for the Zen Garden, the area is regarded as flat area. The elevation was set as 2141 m in Zen Garden. .

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4.4.2.5 Amplitude Recovery

The refraction data may have suffered from amplitude decay due to spherical divergence and other factors. It is also possible that there have one or two dispersion phenomena in the data. It is therefore, necessary that before making any pick on the data, some form of conditioning (which includes amplitude recovery) should be made on the refraction data.

Figure 4-15 Original data before applying any form of gain.

Figure 4-15 shows the original data as acquired, without any kind of processing applied to it. Obviously, picking on a dataset as this is not practical. The dataset is therefore corrected for amplitude decay, stretched so as to display a few initial times, as we have no need for late arrivals, and finally the amplitudes are clipped to avoid errors in the auto-picker. Figure 4-16 shows the corrected form of the same data as figure 4-15. First arrivals picking can now be done on some data as Figure 4-16.

Figure 4-16 Data in figure 4-15 after amplitude correction, stretching.

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4.4.2.6 Travel Time Pick and QC

Having corrected for amplitude, first arrivals are then picked and interpreted.

4.4.2.7 Reciprocal Time Check

A basic principle of refraction seismic method is that time reciprocity is valid, i.e. interchanging the source and the receiver positions does not change the arrival time of the refraction events (Phillip Kearey et al. 2002).

The error in the reciprocal time is therefore used a QC test for the quality of picks made. Errors greater than 5% of the traveltime suggests that the pick was bad and as such should be repeated. Figure 4-17 shows a sample of a reciprocal time test made in this project. Clearly the error is minimal and hence suggests that this pick is very good. The test is performed for the entire line using sets of shots having significant refractor overlap.(Appendix 8.)

Figure 4-17 Reciprocal test for two shots with significant refractor overlap.

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4.4.2.8 First break picks of P-wave in North Line

Figure 4-1 Example of P-wave first break picking on first-kick

The whole 7 move-ups have been first break picked and each move-up has been first break picked individually. The first break picks of whole 7 move-ups are to show the whole seismic refraction map and the individual first break picks are for showing individual seismic refraction image of interesting area. At this time, the first break picks were picked at first kick points (Note that the hammer seismic source is impulsive energy which is minimum phase. So, first break picks would be the first energy that is detected.). The first break picks have been picked every 3 shot.

4.4.2.9 Advanced Seismic Refraction Analysis using Seisimager

The travel times picked are interpreted using gradient, reciprocal method (a better interpretation method with no assumption of plane interface), Inversions techniques (Time term and tomographic).

4.4.2.10 Layer assignment

The seismic refraction methods such as reciprocal method, time-term inversion are using the concept of delay time as discussed in chapter two. The processing software used (Seisimager PlotRefra) relies on the user to assign layers on the travel time picks. Figure 4-19 shows the layer assignment done for one example. It is worth noting that great care had been taken in picking the travel times as the affect the results of any interpretation algorithm strongly.

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Figure 4-19 Example of layer assignment

4.4.2.11 Reciprocal method

According to Jocelyn Dufour and Darren Foltinek (2000), the reciprocal method (in other words, delay time method) is developed to solve the time delays of reflection seismic data. Based on the determination of the crossover point and reciprocity, the method is performed.

In this project, area of West to East distance 85 m to 144 m in North Line has been chosen for this analysis since this method can analyse only reciprocal time window area which should be chosen. The result is compared with result from the other methods in the North Line.

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Figure 4-2 Example of reverse line forming with delay time line for reciprocal method

The pink line in Figure 4-20 is showing the reduced travel time line generated in Seisimager. It calculates delay time. And optionally, the reverse delay time line is created and does same process and averages the delay time values. With calculated V1 and V2 (when assigned), It calculates depth in the each points (P1, P2, … Pn) within reciprocal window according to Equation (2.44) and interpolates those.

The result will be shown in Chapter 5.

4.4.2.12 Time term inversion

Time-term inversion assumes that the subsurface is vertically stratified and does not consider the lateral changes during inversion. The depth to the top of the underlying layers is calculated based on points of first break picking. On the basis of the points assigned for different layers, a layered model is generated. The depth is calculated and interpolated and the layered model from the time term inversion is generated (Takaya Iwasaki 2002; Seisimager/2D Manual 2005)..

In this project, with the values V1 and V2 calculated in Seisimager, depths of every point (P1, P2,.., Pn) in Figure 4-20 are calculated by principle of Equation (2.54) and interpolated. Same process is performed between 2nd layer and 3rd layer if there is 3rd layer.

Figure 4-21 shows one example of result of time-term inversion.

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Figure 4-3 Example of Layered model from time-term inversion (from one move-up data of North Line)

4.4.2.13 Tomographic inversion

The tomographic inversion as discussed in chapter three, tries to match the acquired data by iteratively adjusting a model until the misfit between the data created from this model and the real data is below some acceptable level. The tomographic inversion performed in this project uses an initial model generated from time term inversion (Jacob R. Sheehan et al. 2000 ; Seisimager/2D Manual 2005)..

Tomographic inversion method is fairly sensitive to the initial model. It was therefore necessary that out results of time term inversion was good enough to start the tomographic inversion. (Jacob R. Sheehan et al. 2000 ; Seisimager/2D Manual 2005).

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Figure 4-4 Process of Tomographic inversion (from one move-up data of North Line)

Actual values of matrix To are calculated with layers designed for tomographic inversion. The values of layer lengths get divided and become corresponding to the number of layers designed manually to make initial model. To make it clear, let’s assume the number of layers in time-term inversion was 3 and 6 layers are designed for tomographic inversion.

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Figure 4-23 Design of the number of layers for initial model

As seen Figure 4-23, number of elements in matrix of To became same number as T1 (From 3 layers to 6 layers) and it is applied to find ∆S. The number of elements in matrix of ∆S, S1, S2, ….,Sn becomes same number as the number of layers manually designed for tomographic inversion. In this project, to find sensitivity of initial model by parameter (the number of layers, minimum velocity and maximum velocity) set up was tested before tomographic inversion. And at the point when ∆Y is almost “0” when RMS values do not decrease much anymore, the number of iterations was checked. (note that RMS values are inversely proportional to the number of iterations ) The chosen value of number of iterations is n for the tomographic inversion. Setting range of Minimum and maximum velocities were tested. After tomographic inversion, ray tracing was performed to show the penetration of the rays used in estimating the synthetic travel time data employed in the tomographic inversion algorithm.

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Figure 4-24 Ray tracing path in tomographic inversion

Through ray tracing path, the reliability of the data with depth was checked. (note that it is not possible to sample beyond depth not reachable with ray tracing path with the hammer seismic data. (Jacob R. Sheehan et al. 2000 ; Seisimager/2D Manual 2005)

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4.3.3 Seismic Reflection Data Processing and Analysis in North Line

Figure 4-25 work-flow of seismic reflection data processing and analysis in North Line

To generate stack that can be compared with image from refraction processing, basic seismic reflection data processing has been performed in Promax.

SEG-Y file is used for this process. With the hammer seismic data in Promax, the seismic reflection data processing is performed. Even though the seismic reaches very shallow, it would be enough to prove the effect of static correction derived from refraction data in the stack.

4.3.3.1 Refraction Muting

The direct arrival waves and refracted waves dominate data. The amplitudes related to those events are high because they travel closely and are not attenuated. (Jakubowicz 2012)

In seismic reflection data processing, refraction and direct arrival are considered as a coherent noise and removed. The refraction muting is applied to these data.

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Figure 4-26 Refraction muting in Promax. (left: before refraction muting, middle: applying refraction muting, right : after refraction muting )

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4.3.3.2 Bandpass Filtering

Bandpass Filter is applied. Here bandpass filter(s) is a frequency filter(s) to each input trace operated by the filter algorithm in the frequency domain (Steve H. Danbom, Ph.D., P.G. Rice University ESCI 444). To find out the range of frequency of bandpass, the bandpass parameter tests have been conducted.(note that the attempt to find out the range of frequency of bandpass using the function of FK Spectrum Analysis did not work because in the analysis window, the signal was highly aliased. This is assumed because the sampling rate is too big. The reason of this assumption is because if KMax of data acquired with hammer are not satisfied with Equation (3.1), the data are aliased.

(3.1)

Here KMax = Maximum frequency (hz)

∆x = sampling rate (s)

(Jakubowicz 2012)

The sampling rate was checked in Promax. It was 2.5 ms. The Nyquist Frequency is 1/ 2.5 ×1000 = 400 hz. The data acquired with hammer must have higher maximum frequency than this.

Figure 4-27 Aliased reflectors of data in FK spectrum analysis

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Figure 4-5 Schematic drawing on cut range of Bandpass (frequency: 50 – 100 - 200 - 400 Hz)

The parameter test was performed. The ranges of frequencies are illustrated in Appendix 9.

The bandpass range of 50-100-200-400 was giving the best result keeping reflector the most and removing the ground roll the most. So this value was chosen.

By applying bandpass with frequency range 50-100-200-400, the ground roll was successfully removed and reflector existing in the data seems to reveal.

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Figure 4-6 Bandpass filter application ( left: gather before applying bandpass, right: gather after applying bandpass

4.3.3.3 Static Correction

In this project, the final datum was set as 2259 m and replacement velocity was set at 1700 m/s in this project. The final datum 2259 m was chosen with the height around 10 m higher than the highest elevation. The replacement velocity 1700 m/s was chosen with the average velocity value of weathering layer.

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4.3.3.3.1 Elevation Statics Analysis in North line.

Figure 4-70 schematic geometry for elevation statics with data from first break picks on first-kick of Promax

Elevation static correction is calculated as:

(3.2)

(Khaled Al Dulaijan 2008)

In this project, the base of weathering was calculated in Promax with the first break picks on first-kick. And the elevation statics have been calculated based on the value, final datum value and replacement velocity.

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4.3.3.3.2 Datum static correction from tomographic inversion of Seisimager in Promax:

Figure 4-8 schematic geometry for datum statics using data from tomographic inversion of Seisimager

tLVL is calculated as:

(3.3)


The elevation static correction is calculated as:

(3.4)


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The Datum static correction tDatum = tLVL + tE

Therefore,

(3.5)


In tomographic inversion’s case, h = h0 + h1 + h2 + h3 + • • • • + hn

1, 2, 3, 4 • • • • • n

The h and a values were at different every each shot because those have different number of layers. The data calculated from tomographic inversion are in Appendix 10 and 11.

With the data from tomographic inversion, the LVL statics (refraction statics), elevation statics and Datum statics has been calculated.

Datum statics correction (Elevation statics + refraction statics) is performed in Promax. The values of the number of layers, thickness and velocity were extracted from results of tomographic inversion in Seisimager. Through the values, the LVL (refraction statics) and elevation statics were calculated and datum statics have been calculated. By inputting and applying the datum statics values in Promax, the datum statics correction has been done.

The result applied with this datum statics correction was compared with the result not applied with the statics correction and applied with the elevation statics correction by a model from first break picks in Promax. The results will be shown in Chapter 5.

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4.3.3.4 Stacking

Figure 4-32 Screen showing difficulties on velocity picking in Promax

Red image (high amplitude) was spreading out in the velocity picking window in Figure 4.32. This made velocity picking very difficult. The reason why the amplitude (red) is spread out seems because offset is very short. The difference of velocities between offsets creates the red image which implies high amplitude. However, due to short offset, the difference between offsets is almost none. So, it detects all area within offset as high amplitudes of velocities. For this reason, NMO by velocity picking was not chosen. Instead, constant velocity was assumed and based on this, NMO corrections were applied.

To make it clearer, in Figure 4-33, range A is assumed to be distance of North Line (504 m). Within this offset, the hyperbolic line of seismic reflection looks almost straight line within range of short offset (504 m) in the beginning of the line. The straight line can be explained as constant velocity. After tests changing the constant velocities, 2500 m/s of constant velocity has been chosen for Stacking.

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Figure 4-33 Schematic drawing showing possibility of use of constant velocity for Normal Move Out in short offset

Using the constant velocity tested (2500 m/s), normal move out is done and the data are then stacked.

Because the reflectivity range is very shallow in the data, the expected reflector is also very shallow as well. As seen in Figure 4-34 in the gather, only the travel time 0 to 150 ms is expected to have reflector.

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Figure 4-34 Expected reflector through a look into gather in Promax

After stacking the gathers, reflectors are shown clearly within 50 ms only in Figure 4-35.

Figure 4-35 Reflector shown in Brute stack in Promax

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FK-filtering and deconvolution were not working well in the processing. The reasons are assumed as follows. (David Forel et al. 2005)

Effective deconvolution operators can be difficult to design because of variable source signatures, short trace lengths, and high attenuation in the shallow subsurface. (David Forel et al., 2005) Deconvolution can be more destructive than constructive in many cases of shallow seismic. FK filter could not be done on the data because the amount of aliasing observed in the frequency spectrum of the data made it impractical.

Post stack bandpass seems to cut too much seismic image including reflector. So, the post-stack bandpass was not applied at this time. The image was clearer to distinguish when without post-stack bandpass

4.3.4 Comparison with the other methods (DC-resistivity)

Figure 4-36 work-flow of comparison of North Line with DC-resistivity

While electrical resistivity methods are not the key focus of this project, observations from the refraction seismic are compared to resistivity data during interpretation. The fundamental theory of electrical resistivity is therefore reviewed in this project.

4.3.4.1 DC Resistivity Survey

Corresponding internal physical rock properties can characterise materials in the subsurface (Torleif Dahlin, 2001). In imaging the distribution in the subsurface, the differences of the properties between materials play a very important role (Torleif Dahlin 2001). Resistivity can describe a material’s resistance to the flow of electricity as one property (Torleif Dahlin 2001). By the DC resistivity method, current is injected into the ground along a specified array, while electrical potential measurements along the array are performed to characterise how the resistivity of the subsurface changes laterally and with depth (Torleif Dahlin 2001). By the resistivity values obtained from the geology of the PAGO2 DC-resistivity line, the data were inverted into a resistivity model. The model mapped potential structures and fluid distribution in relation to geothermal effect the area (Imperial College London and Colorado School of Mines Geophysics Field Camp 2012).

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Figure 4-37 SP and inverted resistivity profiles of PAGO 02 (Imperial College London and Colorado School of Mines

Geophysics Field Camp, 2012)

In this DC resistivity model, the red colour implies high resistivity and blue colour implies low resistivity which can possibly include a lot of water because water is very highly conductive. ( Imperial College London and Colorado School of Mines Geophysics Field Camp 2012) According to the DC resistivity model, the fault is expected. (Imperial College London and Colorado School of Mines Geophysics Field Camp 2012) If this assumption is correct, there would be some similar indication in result from the refraction data because the area where fault is expected is sharing the area of North Line.

As seen in Figure 4-38, the refraction seismic line in North line is not exactly matched with DC resistivity line but they were crossing. By comparing these two, in this project, the attempt to see the similarity and difference between these two was conducted.

Figure 4-9 North line area where North line hammer seismic survey line crossing with PAGO 02 DC resistivity

survey line (Map is copyright Google Earth)

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4.3.5 Advanced refraction analysis (Zen Garden )

Figure 4-10 Work-flow of advanced refraction analysis in Zen Garden

In Zen Garden, the processing is same as in North Line. The description of same processes was omitted in this thesis and some additional processes are described in this thesis.

4.3.5.1 First break picks of P-wave in Zen Garden

At this time, the first break picks were only picked at first kick points (Note that the hammer seismic source is impulsive energy which is minimum phase. So, first break picks would be the first energy that is detected.) The first break picks have been picked every 3 shot.

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Figure 4-11 Example of P-wave first break picking on first-kick in Zen Garden

4.3.5.2 S-wave first break picking

At this time also, the first break picks were picked at first kick points (Note that the hammer seismic source is impulsive energy which is minimum phase. So, first break picks would be the first energy that is detected.) In this case, the horizontal geophone received mostly S-waves and the source was applied to semi-horizontal plate which generated mostly S-wave. The first break picks have been picked every 3 shot.

So in Figure 4-43, the first break picks of S-wave were same way as previous. However, because the S-wave data were a lot noisier than P-wave data, more QCs were performed. There were some traces which did not include any information. (note trace offset 33) in Figure 4.41. These kinds of traces were killed for first break picks as seen Figure 4-42 and Figure 4-43 show the process of killing a bad trace and picking first break.

Note that the location of acquisition of P-wave and S-wave is same.

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Figure 4-41 Example of the raw data of S-wave in Zen Garden

Figure 4-42 Example of choosing bad trace of S-wave in Zen Garden

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Figure 4-43 Example of S-wave first break picking on first-kick in Zen Garden

Zen Garden survey line is only 74 m (only one channel) which does not require connecting the patterns to show whole seismic refraction map.

4.3.5.3 Time-term inversion and Tomographic inversion in Zen Garden

In Zen Garden, the time-term inversion and tomographic inversion with P-wave data and S-wave data were performed. The processes are same as those in North Line.

The P-wave result was compared with basic analysis result available from Imperial College London and Colorado School of Mines Geophysics Field Camp 2012.

When elevations are 2141 m, 2131 m and 2121 m in Zen Garden, the P-wave and S-wave velocities from tomographic inversion have been checked and recorded. Using the values, Vp/Vs values and Poisson’s ratios were calculated. Using the values, lithology including porosity with different depth (0 m, 10 m, 20 m deep) were anticipated.

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4.3.6 Comparison with Ground Penetration Radar (GPR)

Figure 4-44 Work-flow of comparison of Zen Garden with GPR

The data acquired in these areas have been compared with the data processed with seismic refraction data in these areas.

4.3.6.1 GPR (Ground Penetration Radar)

GPR (Ground Penetration Radar) - Non-invasive geophysical method. This is using the propagation of electromagnetic (EM) waves and makes the image of the subsurface. In Barn 3 area, the GPR was pulled along the ground. A transmitting antenna emitted a short, high frequency EM pulse into the ground every 0.05 m. The EM wave was diffracted, reflected and refracted when a contrast in the dielectric permittivity within the subsurface exists. Reflected waves at the ground surface were continuously recorded by the receiver in Figure 4-45. (Marcin Słowik 2012)

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Figure 4-45 GPR acquisition comprising of the radar components and the analogue interpretation of a radar time

section. Tx: Transmitter, Rx: Receiver (Redrawn from Imperial College London and Colorado School of Mines

Geophysics Field Camp 2012)

The result of GPR acquired in Barn 3 have been compared with the results of porosity difference from Vp/Vs and Vp in Zen Garden to find out the reason why the porosity is different with different depth. The Barn 3 area is on similar geology with the Zen Garden according to geological map. So, it can give a good comparison with the Zen Garden area. (Imperial College London and Colorado School of Mines Geophysics Field Camp 2012)

In Figure 4-46, the red circle is showing Barn 3 area with comparison of Zen Garden (Blue circle). Red line is showing data acquisition line in Barn 3.

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Figure 4-46 Barn 3 survey line (red line: SW- NE) cited from Google Map

As seen in Figure 4-47, the Barn 3 area has very thin Mancos Shale layer (some area in that has no Mancos Shale layer). And so does Zen Garden area. And Dakota Sandstone layer underlies the Mancos Shale layer. (Imperial College London and Colorado School of Mines Geophysics Field Camp 2012)

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Figure 4-47 General cross-section of Pagosa Springs showing the location of Barn 3 and Zen Garden. Vertical scale has been exaggerated to show features in larger detail. (Imperial

College London and Colorado School of Mines Geophysics Field Camp 2012)

The schematic map in Figure 4-47 shows the location of Barn 3 (red arrow) and that of Zen Garden (blue arrow).

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Figure 4-12 General cross-section of the location of GPR acquisition in data acquisition line of Barn 3. Vertical scale has been exaggerated to show features in larger detail. (Imperial

College London and Colorado School of Mines Geophysics Field Camp 2012)

As seen in Figure 4-48, some areas of data acquisition line of the Barn 3 has no Mancos Shale covered and Dakota Sandstone is revealed on surface. To find out the property (especially porosity) of the Dakota Sandstone, the revealed point is used as GPR analysis. The red circle in the Figure 4-48 is showing the GPR acquisition point.

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CHAPTER FIVE.

5.0 RESULTS AND DISCUSSION

5.1 Basic refraction analysis in North Line

5.1.1Results from Gradient-Intercept method on the North line

Figures 5-1 to 5-6 show the gradient intercept results from first kick, trough and peak. From these results the sensitivity of the travel time sensitivities are seen to be negligible, i.e. any form of picking used would still give consistent results.

Results of Depth models are as follows.

Figure 5-1 Depth model generated from picking first break on Peak in Promax

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Figure 5-2 Depth model generated from picking first break on First Kick in Promax

Figure 5-3 Depth model generated from picking first break on Trough in Promax

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The results of Velocity models are as follows.

Figure 5-4 Velocity model generated from picking first break on Peak in Promax

Figure 5-5 Velocity model generated from picking first break on First Kick in Promax

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Figure 5-6 Velocity model generated from picking first break on Trough in Promax

Average depth values of picks made on peak in general were the biggest and average depth values of picks made on first kick in general were the smallest as seen Table 5-1.

Similarly, the values of velocities were a bit different. The average velocity values of first break picks made on peak were generally biggest and those made on first kick were smallest as seen in Table 5-2.

Table 5-1 Depth model from basic refraction analysis

Table 5-2 Velocity model from basic refraction analysis

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The shapes of the models (depth model and velocity model respectively) generated from different first break picking were similar (Figures 5-1 ~ 5-3 and Figure 5-4 ~ 5-6). The fact that similar models are created explains that the position where the first breaks are picked does not affect the results that much. The most important thing on first break picking is consistency of the first break picks in both cases of depth model and velocity model according to this test.

Error analysis (difference between value applied with polyfit) and has been performed (Appendix 7). The results were 3.2 m/s average. This is inaccuracy rate of about 8%. This seems because the polyfit function is very sensitive to the range of polyfit that is made manually. More accurate analyses are required.

However, at least, this method gave some information. The findings through results from depth models and velocity models were this area (North Line) is undulated and made of three layers.

5.2 Advanced seismic refraction analysis in North Line

As seen in Figure 5-7, this area is shown as 3 layers. In every 3 shot, the travel time has been assigned with 2nd layer and 3rd layer. The first layers were assigned with red colour, the 2nd layers were assigned with green colour and 3rd layers were assigned with blue colour.

5.2.1. Time Term Inversion

The time-term inversion method generated a model with about 30 m depth to the bedrock refractor. The RMS error were less than 2 ms. To make comparison with reciprocal method easier, (vertical) smoothing effect of the layers was added to the time-term inversion. Note that this is still layered model having constant velocities in each layer. By giving smoothing effect, possible change of velocities with tomographic inversion (but just image function of prediction) is shown on the time-term inversion. To do this, parameter of number of smoothing passes has been set up as 3. Here, the bigger is number, the smoother is image.

The image of the result of the time-term inversion is shown in Figure 5-8.

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Figure 5-7 Connected Layer assignment of whole North line in Plotrefa TM of Seisimage

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Figure 5-8 Layered model from time-term inversion of North line with smoothing effect (Smoothing passes: 3) added in Plotrefa TM of Seisimager

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5.2.2 Tomographic Inversion

The tomographic method needs the input of an initial velocity model. In this project, the initial model was used with the velocity model from time term inversion.

Here the reason designing the number of layers for the initial model is because Length of ray path gets different depends on this value as seen Figure.

Figure 5-9 Principle of designing the number of layers for the initial model

The difference between S0 values (Slowness: 1/V1, 1/V2, 1/V3) from time-term inversion and new S1 values (calculated) is calculated. At this time, the number of elements of matrix S1 becomes same number of layers designed for tomographic inversion. Please refer to Figure 5-9.

(4.1)

(Here, L = matrix of lij and T1 = calculated travel time, To= observed travel time)

(4.2)

Because it is non-linear problem, Lt L × ∆S = Lt × ∆T So, ∆S is found. And initial model is decided as So + ∆S

Therefore,

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(4.3)

One part of move-ups in North Line in Figure 5-10 was used to test the parameters for generating an initial model.

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Figure 5-10 the image of one move-up time term inversion result chosen for parameter tests for initial model in North line in comparison with the whole North line time term

inversion image in Plotrefa TM of Seisimager

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Figure 5-11 images of one pattern time term inversion result chosen for parameter tests for initial model in North line

in Plotrefa TM of Seisimager ((a) P-wave velocity 30 m/s – 3000 m/s, the number of layers 10 (b) P-wave velocity 30 m/s – 3000 m/s, the number of layers 15 (c) P-wave velocity 30 m/s – 3000 m/s, the number of layers 18)

First, as seen in Figure 5-11, with a constant P-wave velocity of minimum 30 m/s and maximum 3000 m/s, the number of layers was changed. 10, 15, 18 layers were applied to generate starting models with P-wave velocity (30 m/s ~ 3000 m/s). A bit slightly coarser velocity grids have been shown in the initial model of fewer layers (10) as seen (a) in Figure 5-11. But (b) in Figure 5-11 is almost same as (c) in Figure 5-11.

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Figure 5-12 images of time term inversion result chosen for parameter tests for initial model in North line in Plotrefa

TM of Seisimager ((a) P-wave velocity 30 m/s – 1000 m/s, the number of layers 15 (b) P-wave velocity 30 m/s – 3000 m/s, the number of layers 15 (c) P-wave velocity 30 m/s – 10000 m/s, the number of layers 15)

For 15 layer starting model fixed, the maximum velocity has been changed to 1000 m/s, 3000 m/s and 10000 m/s.

1000 m/s maximum velocity setting caused error as seen (a) in Figure 5-12. It seems because the maximum velocity setting value is lower than actual maximum value (around 2800 m/s).

Note that setting minimum velocities higher than 300 m/s brought error as well. This seems because the minimum velocity setting value is bigger than actual minimum velocity value. (b) and (c) do not have a big difference. Through this test, it is found that setting the maximum velocity should be higher than actual maximum value and the minimum velocity setting should be lower than actual minimum value.

Therefore, since sufficient flexibility in the number of model layers ( around 15 ) allows the velocity estimate to be fairly stable, the 15 was chosen for the number of layers, 3000 m/s for maximum velocity and 30 m/s for minimum velocity were chosen as parameters to generate the initial model.

The Figure 5-13 shows the initial model generated from time-term inversion with parameter of 15 in the number of layers and 3000 m/s in maximum velocity chosen as parameters set

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in this project.

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Figure 5-13 The image of initial model in whole North line in Plotrefa TM of Seisimager ( calculated with parameters of P-wave velocity 30 m/s – 3000 m/s, the number of layers 15

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Figure 5-14 Misfit between synthetic and observed travel time as a function of the iteration number. Observe the lack

of significant reduction in the travel time misfit after about 10 iterations.

Several tests were performed to decide the number of iterations used in the tomographic inversion. Initial tests show little of no improvement in the velocity model after 10 iterations (Figure 5-14), suggesting possible convergence of the inversion to the true model. The number of iteration was therefore fixed at 10 for application to the entire North line.

In this project, number 10 is chosen for the number of iteration in tomographic inversion because this number is enough to make misfit between calculated values and observed values almost minimum.

This image from tomographic inversion in Figure 5-15 is showing more specific and precise geological feature than time-term inversion providing smooth velocity changes with depth.

From this ray tracing path in Figure 5-16, the data up to about 20 m deep would be reliable since the ray path is going through by the depth. However, after the depth, the ray path does not reach which means the data deeper than about 20 m cannot be reliable.

Tomographic inversion allowed to confirm the results of the time term inversion and made the velocities of the sediments and bedrock constrained. But it is allowed to show some interesting look at possible drainages and shallow low velocity layers. The P-wave velocity of the middle layer in North line area is matched with water saturated sandstone. However, to make sure it is really water saturated sandstone, further investigation is required.

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Figure 5-15 the image of P-wave velocity model from tomographic inversion in whole North line in Plotrefa TM of Seisimager (value 10 was chosen for the number of iteration )

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Figure 5-1 the image of Ray tracing path of P-wave velocity model from tomographic inversion in whole North line in Plotrefa TM of Seisimager

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Table 5-3 Seismic Velocities of Earth Materials (Gary Mavko 2005)

5.2.3 Reciprocal Method

The reciprocal method generated better image than the time-term inversion data yielding a depth closer to 25 m. Not all the shots were useful in producing the model because this method can be applied in the condition that the reciprocal time is same as original time which is not easy to be in real data. For this method, manual adjustment of the travel time was inevitable. And this method was able to calculate delay time only within reciprocal time window area and generated the image of velocity model only this area. It is very tedious and redundant job to apply this method in whole survey area while this only shows similar result to time term inversion data. In other words, application of the reciprocal method is not easy in terms of the process and time required. The reciprocal method slightly improved than the model by time term inversion. Notice that the reciprocal method generated two layered model (even if it has smooth effect shown in the image) while time-term inversion generated three-layered model. This is because the delay time for calculation of depth is only calculated with V1 and V2 according to Equation (2.44). In Figure 4-20, The V1 = 300 m/s, V2 = 2833 m/s are calculated.

After checking this method generates similar result to time-term inversion data and it is not proper for situation of more than three layers, this method is not chosen for further investigation.

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Figure 5-2 the image of reciprocal method showing delay time line and reverse time line in one move-up of North line

in Plotrefa TM of Seisimager (delay times in both sides are calculated and averaged )

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Figure 5-3 the image of P-wave velocity model generated by reciprocal method in one move-up of North line in

Plotrefa TM of Seisimager ( delay times in both sides are calculated and averaged )

The delay times calculated in both sides and averaged. The values averaged with both directions helps buffering the error that can be caused in one side with the other side’s result in some cases.

Note that even if the result of reciprocal method looks several colour gradients, this is basically two layered model. The gradients were generated by Smoothing function of Seisimager to predict real velocity model.

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Figure 5-4 Comparison between images of P-wave velocity models generated by reciprocal method and time-term

inversion in one move-up of North line in Plotrefa TM of Seisimager (Note that both methods are conducted in same

position)

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5.3 Statics analysis of P-wave data in North Line

5.5.1 Elevation static correction from first break picks picked in Promax:

The graphs in Figure 5-20 and Figure 5-21 show the elevation statics calculated from first break picks on first kick picked in Promax.

Figure 5-20 plots of Elevation static correction on P-wave obtained from first break pick on first kick in North Line

of receiver shown in Promax.

Figure 5-11 plots of Elevation static correction on P-wave obtained from first break pick on first kick in North Line

of source shown in Promax .

Because the location of source and receiver in North Line is shared, the shapes of elevation statics are identical.

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5.5.2 Datum statics from tomographic inversion .

On the other hand, datum statics has been calculated with data from tomographic inversion derived in Seisimager. The data are available in Appendix 10 and 11. To calculate the Datum statics, the LVL statics (refraction statics) and elevation statics are also calculated from the data from tomographic inversion. The results are shown in Figure 5-22.

Figure 5-22 Values of LVL Static ( refraction static), Elevation static correction of receiver and total datum static

correction shown in Promax. The values of elevation static correction and LVL static correction are added up to find

datum static correction.

The datum statics inputted in Promax are shown as shown in Figure 5-23 and Figure 5-24. The Figure 5-23 is showing receiver datum static correction.

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Figure 5-23 plots of Datum static correction on P-wave obtained from tomographic inversion in North Line of

receiver shown in Promax.

Source datum static correction is shown in Figure 5-24.

Figure 5-24 plots of Datum static correction on P-wave obtained from tomographic inversion in North Line of source

shown in Promax.

Because the location of source and receiver in North Line is shared, the shape of datum statics is identical.

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5.5.3 Application of static correction to the stack

After applying statics, there was slight change. Since the reflector is not deep enough, it was not easy to distinguish the change. However there were very small changes after applying static corrections. Static corrections helped the reflectors not cut by bringing the reflector down from upper top window. And datum static correction gave the best image helping continuity of the seismic.

Stack not applied with any static correction (but bandpass applied) in North line area is shown in Figure 5-25.

Figure 5-25 the image of stack not applied with static correction (only bandpass applied : Bandpass frequency range :

50 – 100 -200 -400 hz).

With elevation statics and the datum statics respectively were applied in gathers of seismic data of North line in Promax and stacked and compared with brute stack which is not applied to any statics.

Stack applied with Elevation static correction calculated with first break picked in Promax is shown in Figure 5-26.

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Figure 5-26 the image of stack applied with elevation static correction ( bandpass and elevation static correction

applied : Bandpass frequency range : 50 – 100 -200 -400 hz).

Stack applied with datum static correction (Datum statics (refraction (LVL) statics + elevation statics) and Bandpass) is shown in Figure 5-27.

Figure 5-27 the image of stack applied with Datum static correction ( bandpass and datum static correction applied

applied : Bandpass frequency range : 50 – 100 -200 -400 hz Here Datum static correction = LVL static correction (

Refraction static correction(LVL))

The Images of Figure 5-26 and Figure 5-27 compared to Figure 5-25 were improved in terms of continuity of the data. The datum statics (Figure 5-27) seems to show the best image. Elevation statics (Figure 5-26) seems to be showing second best image.

The following Figure 5-28, Figure 5-29 and Figure 5-30 are showing magnified stacks which are applied with elevation static correction and datum static correction. And the first stack is not applied with any static correction.

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Figure 5-28 the image of stack ( only bandpass applied : Bandpass frequency range : 50 – 100 -200 -400 hz .

Figure 5-29 the image of stack applied with elevation static correction (bandpass and elevation static correction applied : Bandpass frequency range : 50 – 100 -200 -400 hz .)

Figure 5-30 the image of stack applied with datum static correction (bandpass and datum static correction applied: Bandpass frequency range : 50 – 100 -200 -400 hz Here datum

static correction = LVL static correction ( Refraction static correction ) + elevation static correction.

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The reason why these are magnified is to see the difference closer because the change by static correction was very small. As seen in Figure 5-28, the stack that is not applied with static correction was the roughest. However elevation static correction and datum static correction made the stack in the window adjusting the continuity in window. The elevation static correction drew the image down the most and the datum static correction drew the image down but less than elevation statics. In terms of continuity, the datum static correction seems to make the stack the best image even if the change is very slight. This seems that refraction static correction played a role of correction of brute stack.

For datum statics, the velocity model created from tomographic inversion was used. It gave an improvement in the image. But still it is not clear even if it gives some indication on geology. The biggest reason of this seems because the reflector depth is not that deep enough to show geological feature.

5.5.4 Comparison of the stack with results from refraction analysis.

As seen in Figure 5-31, the time term inversion and tomographic inversion result and the stack result from reflection processing indicate a possible fault line. However, the F1 is just guess based on the results. More certain indication is required to certify this. Later, DC-resistivity survey result will be shown to support this finding.

Figure 5-32 is showing the stack applied with datum static correction and depth converted. The stack is superimposed with refraction line (image of tomographic inversion). In this case, the refraction line is assumed to be flat to compare with brute stack.

Through this comparison, the depth of the weathering layer of the tomographic inversion can be compared with reflection image. The weathering layer is just up to around 15 m deep as seen in Figure 5-32. The possible fault (F1) can be indicated. However because the stack is showing brief geological feature, it needs more investigation.

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Figure 5-31 A possible fault by comparison between refraction processed image and reflection processed image in

North Line. (a) the image from time-term inversion (b) the image from tomographic inversion (c) the image from the

stack applied with datum statics correction.

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Figure 5-32 A possible fault (F1) by comparison of the stack with superimposed and flattened refraction processed image ( from tomographic inversion) in North

Line

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5.5.5 Comparison with the result of DC-resistivity survey in North line area.

One DC-resistivity survey line crossing North line of seismic refraction line was considered to be compared with North line to make sure on the fault. Because in distance 1050 m W-E of DC-resistivity survey line, a possible fault was interpreted, in North line, around the area, there should be some indication of fault in North line hammer seismic survey line as well because DC-resistivity survey line and hammer seismic survey line is closely located and crossing in some point..

As seen in Figure 5-33, similarity of the location of a possible fault was detected in between DC survey line and seismic refraction survey line. The location of fault is matched. The fault is very likely to be there based on results of the refraction analysis, stack analysis and DC-resistivity model analysis.

..

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Figure 5-33 A possible fault expected by result from DC-resistivity survey and Hammer seismic survey in North Line area (The DC-resistivity model is fit to the PAGO02 pararelly,

and the tomographic inversion image is fit to the North line in parallel) DC-resistivity image is cited from Imperial College London and Colorado School of Mines Geophysics Camp

2012.

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5.4 Advanced refraction analysis in Zen Garden

For this, Zen Garden near North line has been investigated with S-wave and P-wave acquisition data. It could help to understand the possible presence of groundwater and more accurate information through Poisson’s ratio and Vp/Vs in this area.

5.4.1 P-wave velocity model analysis in Zen Garden

P-wave velocity model result of Time-term inversion in Zen Garden is shown in Figure 5-34. RMS error was 2.20 msec (These data are reliable since the RMS error are less than 5 msec). Just like North line, the layers were shown as three layers and middle layer seems similar to velocity of water-saturated sandstone (about 1500 m/s) please refer to the chart..

Just like North line, tomographic inversion has performed using the result from time term inversion for an initial model. Before performing the tomographic inversion, RMS value changes by change of the number of iteration have been checked. After 10 iterations, the RMS value has been stabilised.

Figure 5-34 the image of P-wave velocity model generated by time term inversion in Zen Garden in Plotrefa TM of

Seisimager

For this reason, value of 10 is chosen as a parameter for the number of iteration in tomographic inversion. This number is enough to make misfit almost minimum

The image of the result from tomographic inversion is shown in Figure 5-35. The result from tomographic inversion shows more smoothed velocities while results from time-term inversion show only constant velocities in each layer.

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Figure 5-35 the image of P-wave velocity model from tomographic inversion in Zen Garden in Plotrefa TM of

Seisimager (value 10 was chosen for the number of iteration)

At this time RMS error was 2.3 ms. In P-wave analysis, there seem to have water saturated sandstone showing layer around 1500 m/s according to Table 5-3.

Bottom layer in these images seems like sandstone because the velocity is matched with velocity of the sandstone around 2400 m/s in Table 5-3. However, the data are not reliable to make sure this is sandstone because this depth is not reachable for ray tracing path as seen in Figure 5-36.

Area deeper than 15 m should needs further investigation for this reason. To investigate the deeper area, the other method such as DC-resistivity survey would be helpful. In fact, processing of deep seismic data at a nearby site suggests that the velocity of the underlying Dakota Sandstone is 2400 m/s (Karalis 2012)

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Figure 5-16 the image of Ray tracing path of P-wave velocity model from tomographic inversion in Zen Garden in

Plotrefa TM of Seisimager

RMS = 3.82 ms (the value is less than 5, these data are reliable enough )

In brief, P-wave analysis showed there would be water saturated sandstones range between depth 2 m and depth 13 m according to Table 5-3.

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Figure 5-37 Comparison of P-wave velocity model from tomographic inversion and subsurface model from basic gradient intercept method done by Imperial College London and

Colorado School of Mines Geophysics Field Camp, 2012 (right Figure - ( Imperial College London and Colorado School of Mines Geophysics 2012 )

When comparing the P-wave velocity model result of tomographic inversion with the basic hammer seismic analysis which is done in Colorado field camp 2012 in the Zen Garden, there were some similarities on approximate. One of differences was in the basic hammer seismic analysis, the water saturated sandstone. (Depth 2 m – 13 m) is interpreted as saturated sediment. According to the results from S-wave, Vp/Vs analysis and Poisson’s ratio analysis (this will be shown soon), the middle part (depth 2 m - 13 m) seems to be water saturated sandstone.

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In Zen Garden area, S-wave data have been acquired. The S-wave velocity model showed the S-wave was slower than P-wave. However, the shape of the S-wave velocity model was very similar to P-wave velocity model. The information of S-wave with that of P-wave in same location was very useful to find out information of lithology and porosity.

Just like P-wave, Time term inversion has been performed with S-wave. The result is shown in Figure 5-38.

Figure 5-38 the image of S-wave velocity model generated by time term inversion in Zen Garden in Plotrefa TM of

Seisimager

The image of result from tomographic inversion of S-wave data using the initial model derived from the time-term inversion is shown in Figure 5-39.

S-wave did not detect the top layer in the time inversion. However, the velocity 780 m/s of S-wave in the middle layer is matched with water saturated sandstone and the velocity 1100 m/s of S-wave in bottom layer is matched with sandstone according to the Table 5-3. .

Figure 5-39 the image of S-wave velocity model from tomographic inversion in Zen Garden in Plotrefa TM of

Seisimager (value 10 was chosen for the number of iteration)

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5.4.2 S-wave Velocity model from tomographic inversion in Zen Garden

After tomographic inversion, the top layer seems to appear. The lower velocity (about 400 m/s) in depth 0 m to 2 m suggests shale and the higher velocity (about 700 m/s ) in depth 2 m to 12 m suggests sandstone according to Table 5.3, which is consistent with the geological model of the area.

Figure 5-40 the image of Ray tracing path of S-wave velocity model from tomographic inversion in Zen Garden in

Plotrefa TM of Seisimager

Similarly, the range of depth between 0 m and 10 m in S-wave result can be reliable. However, when deeper than that range and the ray tracing path did not reach, the data is not reliable. The further investigation is required in the deeper area.

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Figure 5-41 Comparison of shapes of P-wave data and S-wave data

As seen in Figure 5-41, the shapes between image from P-wave and image from S-wave are very similar. Just the velocities are different. This can be interpreted as the water existing in Zen Garden is saturated in the pores of rocks through which S-wave can still go through even if the S-wave is blocked by water. Note S-wave cannot go through water or air.

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5.4.3 Poison’s ratio analysis

Table 5-4 P- to S-wave velocity and Poisson’s ratios calculated from P- and S-wave in Zen Garden

The Table 5-4 is calculated by the Equation (4.4). The Poisson’s ratio can be expressed in terms of properties measured in the field including P-wave velocity and S-wave velocity (Thomas Brocher 2005)

Here, Ơ = Poisson’s ratio

Vp = P-wave velocity

Vs = S-wave velocity

Note that if Vs = 0, Poisson’s ratio becomes 1/2. This is indicating either a fluid because shear waves do not pass through the fluids or a material that maintains constant volume regardless of stress. This is known as an ideal incompressible material. Vs approaching 0 is characteristic of a gas reservoir. The Poisson’s ratio for Carbonate rocks is ~ 0.3, for sandstones is ~ 0.2, and above 0.3 for shale. The Poisson’s ratio of coal is ~ 0.4. (cited from G. N. Greaves et al. Poisson’s ratio and modern materials; Nature material.)

In this case of Zen Garden as you can see in Table 4.2, in the top area of elevation 2141, Ơ = 0.43 which is bigger than 0.3. Therefore, it indicates this part can be made of shale. This is matched with information of geology in this area. The top part is covered with Mancos Shale according to geophysics summer camp report (Imperial College London and Colorado School of Mines geophysics field camp 2012). However, there are still possibilities the top of Zen Garden can be made of different materials. Further investigation on this part is required to make sure this is Mancos Shale layer.

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Figure 5-42 Chart of Poisson’s ratio, Vp/Vs ratio and P-wave velocity (Redrawn from Thomas Brocher 2005)

This chart is showing the lithology based on the Poisson’s ratio, P-wave velocity and Vp/Vs ratio. As seen figure 4-32, the red dot is when elevation is 2131 m, Vp = 1500 m/s Vs = 900 m/s and Vp/Vs is around 1.67. As seen in Fig 1, the location of red dot is very close to the Sandstond (fluid). This means this might be water saturated sandstone which is matched with result of P-wave analysis in the elevation area (1500 m/s P-wave velocity).

The black dot is when elevation is Vp = 1800 m/s, V= 1222 m/s, Vp/Vs = 1.47 and Poisson’s ratio = 0.073. This is very closely located near Sandstone (gas). That is matched with geology reported by Imperial College London and Colorado school of mines in the summer field trip as Dakota Sandstone.

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5.4.4 Vp/Vs analysis

Figure 5-43 Chart of Vp, Vp/Vs ratio and Porosity in Zen Garden ( Redrawn from Ross Crain 2000)

As seen in Figure 5-43, the red dot is showing when elevation is 2131 m, Vp = 1500 m/s Vs = 900 m/s. The value of the Vp/Vs is around 1.67. The porosity in this case is very high. This can imply that the water is saturated in the big porosities. In the other hand, the black dot is showing when elevation is 2121 m, Vp = 1800 m/s, V= 1222 m/s, Vp/Vs = 1.47 and Poisson’s ratio = 0.073. This case, the porosity is lower than the case of red dot. That means this does not include water as much as the case of red dot. So, this can indicate that the deeper the less porosity ( where water can be saturated ) exist.

GPR result in Barn 3 area which is assumed to be similar geological structure with Zen Garden from Colorado field camp has been analysed. The result of GPR is shown in Figure 4-81.

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Figure 5-2 (a) Seismic section at Barn 3 and (b) its interpretation related to the Dakota Sandstone. (Imperial College

London and Colorado School of Mines Geophysics 2012)

In the Figure 5-44, the irregularity in the reflectors is shown because of the presence of void spaces (porosity) that allow radar waves to pass through. In depth 1 m, fractured Dakota sandstone has been detected by the GPR. As seen in Figure 5-35. the irregularity of the reflectors is suddenly getting a lot after 1 m, and gets less and less. That means porosity is getting smaller and smaller as it gets deep.

Interpretation on this is as follows. As seen in Figure 4-34, in image from GPR weathered sandstone was detected on top of unweathered sandstone. It tells the weathered sandstone would have more porosity and possibly water saturated. And as the depth is more deeper, more unweathered sandstones are gradually more dominating the part. So, it would be less porosity and less water saturated. This can explain about reason of porosity result from Vp/Vs and Poisson’s ratio

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CHAPTER SIX.

6.0 Conclusions and Recommendations

Gradient-intercept, reciprocal, time-term inversion and tomographic inversion have been used to interpret first arrival travel time picks of refractions data from the Pagosa Springs, Colorado, USA. The various results show a strong correlation to the advanced seismic refraction data even if the time-intercept method is just an approximation. The time term inversion gave more specific and precise information on the area. And the tomographic inversion used the result from time term inversion and reduced the misfit between observed data and calculated data and gave more realistic information on the area.

Reciprocal method uses the so-called delay time method and was used on certain part of the North Line. Results show that it was sensitive to the presence of significance refractor over-lapping the reciprocal time window. Moreover, it was computationally expensive as repeated experiments needed to be done. However, the result was a bit better than time term inversion as it should a gradation in the velocity values with depth. The reciprocal method produced only 2 layered models while time-term inversion produced 3 layered models even though it has showed smoothed effect in one of the function of Seisimager with which real velocity model can be predicted.

In general, the results of modelling in both Zen Garden area and North Line area seem to be agreeing with existing information from Colorado Geophysics Camp. However, the results from tomographic inversion gave better insight on North Line and Zen Garden. Since in many cases, the real earth does not change the layers directly from one constant velocity to different constant velocity directly, the tomographic inversion image gave more realistic and gradually changing velocity model. According to the P-wave & S-wave analysis in Zen Garden, and P-wave velocity analysis in North Line and Zen Garden, a layer of water saturated sandstone was interpreted. According to Poisson’s ratio, Vp/Vs and P-wave values, the lithology of top layer is possibly shale. This is matched with Mancos Shale in geology information provided in geological map. The middle part is matched with water saturated sandstone which was same result from previously processed seismic refraction data. This part was all same results in North Line and Zen Garden. (Appendix 1, 2, 3, 4)

As for porosity, based on Poisson’s ratio and P wave velocity values, after passing unconsolidated sediment (which is very thin), the porosity was high but shows a decrease with depth. This is corresponding to result of GPR that was done previously in Imperial College London and Colorado School of Mines geophysics field camp 2012. This porosity theory supports the water saturated zone in shallow area of Sandstone. (Dakota sandstone according to geological information provided in geological map)

In general, the P-wave velocities found in Pagosa Springs area range from 400 m/s to approximately 2500 m/s with a calculated depth of average 15 m. This was similar values in both Zen Garden and North Line. These areas share the same geology structure because they are geographically very close according to the provided geological map from Imperial College London and Colorado School of Mines Geophysics Field Camp 2012. This explains why the P-wave velocity models are so similar.

Bedrock velocities of P-wave in this area range from 2000 m/s to 2700 m/s in both the North line and Zen Garden. However, the information of Bedrock is found difficult to trust because the ray tracing path did not reach the depth. For investigation of the depth of the depth

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further investigation is required, perhaps this time with a longer survey spread and a stronger energy source.

Both model of North Line and model of Zen Garden suggest a maximum possible shale layer thickness of 1 m to 2 m. Irregularities and dipping interface in the bedrock surface were slightly shown in the both models.

The north Line shows a consistent sediment thickness with a bit of thickening around a distance of 170 m to 220 m implying there might be a possible fault in around distance 220 m area matching with location of fault interpreted by DC-resistivity survey. In Zen Garden, the weathering layer was gradually deepening from South to North and the bottom interface was showing as dipping and slightly undulated.

The datum statics correction and elevation statics correction both gave slight improvement to the reflection image after brute stack. Even if it is very small difference, the datum statics correction using data obtained from tomographic inversion gave a little improvement to the stack than elevation statics obtained from data of first break picks on first-kick. However, because reflector in the stack was too shallow, significant difference by the statics correction was not shown much.

Through the comparison between results from time-term inversion, tomographic inversion and stack, similar feature of possible fault was found. This fault line is matched with existing result from previously conducted DC resistivity survey. Therefore, there is a possible fault in North Line.

If the deep seismic was done in the same line, the datum statics calculated would give significant improvement of the deep seismic data. And through the deep seismic survey, the investigation under the depth limit of refraction survey would be done. More data such as density, log data and etc would give more advanced investigations. The different inversion such as wave-form inversion would be worth trying to have better and more precise images of the interest area.

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Torleif Dahlin, 2001. The development of DC resistivity imaging techniques, Volume 27, Issue 9, Pages 1019-1029, Geological Applications of Digital Imaging, Department of Geotechnology, Lund University, Lund, Sweden.

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Appendix

1. Results of time-term inversion in North Line and Zen Garden

2. Results of reciprocal method in North Line and Zen Garden

3. Values Vp and Vs and lithology depending on the different depth in North

Line and Zen Garden

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4. Results of tomographic inversion in North Line and Zen Garden

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5. Data QC in North Line.

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6. Elevation data in North Line.

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7. Error analysis between values of actual plots and values derived from polifit

(one example of SIN 4 ) - A

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7. Error analysis between values of actual plots and values

derived from polifit (one example of SIN 4 ) - B

7. Error analysis between values of actual plots and values derived from polifit

(one example of SIN 4 ) - C

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8. Reciprocal time check -A

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8. Reciprocal time check -B

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8. Reciprocal time check -C

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9. Parameter test for bandpass

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10. Statics data obtained from tomographic inversion in Seisimager (Calculation)

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11. Statics data obtained from tomographic inversion in Seisimager. ( Sorted )

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Kim

Education

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