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The Use of Advanced Well Logging Tools and Techniques Towards Improved Reservoir
Characterization And Their Value To Reservoir Engineering
A Critical Analysis
The oil and gas industry has been known for a long time to exhibit great prowessin creating innovative solutions towards problems encountered in the searching,
exploiting and developing of petroleum resources for the use of mankind. Within the
discipline of well logging, such innovations have been placed at the forefront for
improving reservoir characterization and generating data for reservoir engineers and
reserves evaluators.
A well log can be considered a record of one or more physical measurements as a
function of depth in a borehole. Since the advent of well logging in the 1920s, its
subsequent development into a sophisticated technology revolutionized the oil and gas
exploration and production industry. The ability to look and measure such things as
formation type, formation dip, porosity, fluid type and other important factors
transformed the drilling and completion of oil and gas wells from an ill-defined art into a
refined science. Well logging has come a very long way since with logging while
drilling[LWD] being the most significant step in the past 30 years.
New tools and evaluation techniques are constantly being developed and
evaluated for their use and this paper shall outline the use of three such innovations and
their current status.
1. Magnetic resonance, specifically using MR to distinguish oil, water, gas and oil basedmud-filtrate [MRF]
2. Simulating resistivity profiles of Mud-filtrate invasion to obtain suitable representativewaterflood data
3. Resistivity anisotropy - its effect on reserves and tools to resolve vertical and
horizontal components of resistivity
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1. Magnetic resonance, specifically using MR to distinguish oil, water, gas and oil based
mud-filtrate [MRF]
Introduction
In nature, atoms do not stay stationary but move about rotating in particular
orientations [hence possessing angular momenta]. Certain elements also seem to exhibit
properties as though they were magnets spinning about an axis. H1 and C13 nuclei both
exhibit this property. [Peter Atkins- Physical Chemistry] These magnets can now be
aligned, if placed in an induced magnetic field and will resonate at a particular
electromagnetic frequency, dependant on the properties of the molecules and the induced
field. This gives rise to the magnetic resonance of the nuclei of the molecules. The
concept of nuclear magnetic resonance [NMR] has long been a highly valuable technique
to chemists for elucidating molecular structures of molecules as the technique is
noninvasive and can be quite sensitive. Medical professionals have used Magnetic
Resonance Imaging [MRI] to image hydrogen protons in water molecules in cells to look
noninvasively at organs and their current medical state.
Well loggers and formation evaluation specialists have previously found
applications of magnetic resonance theory in determining hydrocarbon viscosity and total
porosity. The most recent innovations, however, have been in the field of Magnetic
Resonance Fluid [MRF] characterization. NMR becomes a very powerful technique as its
measurement is independent of current formation evaluation measures such as porosity
and density. This means that answers to reservoir characterization problems solved with
NMR information can be quite conclusive and can be combined with current formation
evaluation techniques to give great insight into interpretation problems. The following
chapter shall describe the technological innovations of Schlumbergers MR Scanner*,
the challenges faced by magnetic resonance techniques and the most current NMR fluid
characterization method. [Freedman et al SPE 71713]
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Schlumberger MR Scanner
Schlumbergers MR Scanner is currently one of the most advanced logging
tools within the field of magnetic resonance. It boast numerous features which will be
outlined further, inclusive of irreducible fluid storage volume determination based on
lithology-independent porosity, high vertical resolution, advanced fluid characterization
independent of lithology and multiple depths of investigation with measurements in
transverse [T2] and longitudinal [T1] relaxation time.
In NMR logging, a magnetic field is emitted and experienced by Hydrogen atoms
and they begin to align themselves in this magnetic field. Then, another magnetic is
applied perpendicular to the first field which causes the atoms to precess at an angle 90
0
to the first field. When the second field is removed, these atoms begin to realign
themselves into their original orientation and begin to emit electromagnetic radiation at
radio-wave frequency [RF]. At first, all molecules precess at the same speed but as time
goes on, the atoms begin to precess at different speeds because of the non-homogeneity
of the magnetic field and the signal RF decays. This is picked up by antennae and when
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further pulses of perpendicular magnetic fields are applied, the signal decays even
further. The signals are then received as echoes. The time for the process of precessing to
realign after the pulse gives rise to T2 or Transverse relaxation.
T2 relaxation can also happen because of molecular processes which are related to
petrophysical properties which cannot be compensated for and these correspond to
factors such as fluid porosity and pore size distribution. These processes are grain surface
relaxation, relaxation by molecular diffusion in magnetic field gradients and relaxation by
bulk fluid processes.
Grain surface relaxation is dependent upon the surface to volume ratio of the pore
spaces and hence when this factor is accounted for in the signal received an idea of pore
size distribution can be attained as it is proportional to the signal received by the
antennae. Because of the MR Scanners multiple antennae receive signals at different
frequencies, different depths of investigation [DOI] are possible thereby easily
identifying mud-filtrate characteristics and native formation fluids. The highest resolution
antenna corresponds to a shallowest depth of investigation of 1.25 inches. The DOI
possible occur from 1.5, 2.3, 2.7 and 4 inches dependant on the modes set on the MR
Scanner. This gives a view of the formation beyond filtrate invasion and formation
damage in many cases.
Molecular diffusion relaxation is dependent on amount of H 1 atoms that collide
with each other and lose energy thermally rather than by precessing. This affects the echo
train spacings, decay rates and amplitudes of the RF signals. This enables measurement
of molecular diffusion rates and this is dependant on the volume of fluid present in the
formation and hence the total fluid porosity.
Bulk fluid processes are important when the bulk fluid phase comes in contact
with another phase and is prevented from contacting the pore walls or when large vuggy
pores are present and the bulk fluid does not come in contact with the pore walls. These
effects affect the T2 relaxation and hence can be evaluated for the purposes of reservoir
characterization.
The length of time is takes for T2 signals to show decay that shows the H1 atoms
no longer come back in alignment with the initial magnetic field is called T1 or
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longitudinal relaxation time. All molecules give a particular T1 signature and this is used
to identify light hydrocarbons via a quick look T1 contrast interpretation that is also
possible with this tool.
With this information, the MR Scanner can perform fluid saturation depth logging
showing off which sections of the formation may contain movable water rather than just
simply filtrate invasion. Low oil saturation estimates from resistivity measurement can be
rechecked with depth logging to determine if the lower resistivity reading is due to
invasion of water based mud or low in-situ hydrocarbon saturation.
Advanced diffusion editing acquisition methods combined with multi-frequency
capability of the MR Scanner provide robust fluid saturation and hydrocarbon viscosity
answers. Guru, U et al 2008 mentions the latest methods in use with the MR Scanner
inclusive of the density magnetic resonance porosity [DMRP] technique [elaborated in
Freedman et al, 1998] for improved estimation of porosity and hydrocarbon saturation in
pay, the use of high resolution dual DOI with different polarization times on both
antennae to evaluate thin beds and assist in detecting very light hydrocarbons and finally
the measurement of diffusion rates and comparison to T1 and T2 relaxation times for
MRF.[elaborated in DePavia, et al SPE 84482]
[Source: Schlumberger MR Scanner Catalogue]
Nuclear Magnetic Fluid Characterization [MRF]
Several methods have been developed in the literature for in-situ fluid
characterization. Formerly, methods involving MRF involved the calibration of tool
response to various mixtures of hydrocarbon and water to evaluate comparative readings
from the well logs. This method shows many short comings in that the molecular
diffusion coefficients may not be single valued in reservoirs with multiple molecular
species present [Bloembergen et al 1948]. It has been shown that viscosity is inversely
proportional to proton relaxation times but this is applicable to each constituent species in
the crude oil. General information on rough classes of hydrocarbons relative to gas/oil
ratios and empirical NMR viscosity correlations for crude oils are available. Data of
mixtures of hydrocarbon and water [SPE 49010] and the constituency viscosity model
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[CVM] link to multi-fluid relaxation times has been discussed by Freedman, R et al 2001
[SPE 71713]
Now, multi-frequency capabilities of NMR devices allow a variety of new
measurement parameters with which to determine fluid types. Plots of molecular
diffusion coefficients and T2 relaxation times are now possible at any depth and inversion
of this data allows for accurate fluid typing giving relative volumes of bound water, free
water, oil and gas.[SPE 84482]
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Recent papers on 4D NMR [Heaton et al 2008] have made attempts to improve
the inversion of well log data for fluid typing by considering 4 signal dimensions of
molecular diffusion rate, T2, T1 and radial variation of the signal at different DOI. The
inclusion of radial variation to the data analysis shows the change in fluid properties and
concentrations through depth much in the same way multiple resistivity measurements
measure at water saturation at different DOI. This 4D inversion of data assumes that
bound fluid volume is constant at all DOI being observed.
Short Comings
As with all NMR logging tools, the time needed to recover a suitable signal
distribution for T2 relaxation times competes with the overall speed of logging the well.
The MR Scanner boasts of capability to log at speeds up to 900 ft/hr for T2 radial
profiling but up to 3, 600 ft/hr for bound fluid logging.
A minimum vertical resolution of 7.5 inches is achieved by the tools superior
technical design elements that incorporate the distance from the RF signal to antennae
with the strength of the magnetic field applied and the frequency of the pulsed magnetic
field.
Choosing data acquisition parameters for determining petrophysical cutoffs for
bound fluid and distributions for magnetic resonance fluid characterization are very
important and have been covered in other papers. [Flaum et al 1998] If chosen
inappropriately, it may be impossible to properly interpret the data. It is highly
recommended that a job planner be use before data acquisition to ensure the parameters
used are appropriate. This isnt so much an issue when comparing T 2 relaxation with
diffusion rates for MRF however, but the quality of data can still be compromised.
Things such as no. of echoes, no. of repeats, wait time and echo spacing acquisition
parameters that are not properly set could potentially miss signals from formation fluids
that maybe present.
The position in the T2distribution where a particular fluid appears is dependent on
the fluids location with respect to the rock surface within a pore space. If it is in large
pores (greater than 200 microns) then it will exhibit bulk properties, generally long T1and
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T2times. Examples of large pores are vugs and coarse grained sands. If the fluids cannot
come in contact with the rock surface they will also exhibit bulk properties. The other
extreme is when fluids are in close contact with the rock surface then the T1and T2times
will be very short, tens of milliseconds versus seconds. Examples of early time fluids are
irreducible water and clay water. Heavy oils can also appear at an early time in the T2
distribution. Interpretation models can accommodate any of these fluids. It is the
responsibility of the petrophysicist analyzing the data to decide which is most appropriate
for his project.
Early T2 relaxation times usually correspond to bound water and hence a T 2 cutoff
is usually applied to the data when collected to separate signals from irreducible water
from producible free water. NMR tools respond to the H 1 density, which is directly
proportional to porosity in fresh-water filled rocks. When the fluids are different from
this, the porosity needs to be adjusted for the differences in H1. Porosity is computed by
integrating the area under the T2 distribution. The area under the T2 distribution is a
function of the initial polarization, T1. If the hydrogen nuclei are not fully polarized (WT
not several times T1) then the T2 signal will under-represent the porosity. This is what
gives rise to the relatively slow logging speeds of MR logging tools as the tool must wait
for a complete response of T2 signal so that the entire distribution is captured.
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2. Simulating resistivity profiles of Mud-filtrate invasion to obtain suitable representativewaterflood data [Predicting waterflood performance data through numerical simulation of
mud-filtrate invasion.]
Figure 1. Resistivity Profiles of Mud-Filtrate Invaded Formation
Scientific papers on the simulation of mud-filtrate invasion have been a very
recent topic in the area of formation evaluation. The profiles of mud-filtrate invasion can
help identify a lot of different formation factors, notably porosity, water saturation and
permeability and this is usually evident in resistivity readings with different depths of
investigation. The flowing of mud-filtrate into a sand is, however, very similar to the
process of water flooding or even chemical flooding where one phase of fluid is pumped
into the formation at a particular pressure to displace or move the in situ fluid through the
sand. The following shall briefly outline the most recent advancements in modeling
filtrate invasion over time and how this modeling of invasion can be applied to the field
of enhanced recovery.
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Modeling Filtrate Invasion
Wu et al 2005 adequately describes a method for simulating the behaviour and
physics of mudcake growth and filtrate invasion. The model couples mudcake growth
and immiscible multiphase filtrate invasion. George, B et al 2004 also constructively
assesses in situ hydrocarbon saturation [S0] in the presence of deep invasion and highly
saline connate water by considering the mixing of fresh water mud and saline connate
water at the water concentration front of the invading mud-filtrate. Both papers rely on
the input of petrophysical parameters either measured or derived from mostly core data or
synthesized to resemble typical data variations.
The general approach considers a static filtration where by the mudcake growth
occurs at a constant rate and then reaches a limiting point of growth because of dynamic
parameters. The model used mostly is derived from Dewan and Chenevert, 2001 WBM
or Semmelbeck et al 1995. The flow rate function is usually described by Darcys law
while general assumptions are similar to those undergone in reservoir simulation.
Numerical simulation of the phenomena seems to be based largely on the physics of
water injection into a well. Initially, the filtrate invasion model assumed for interpretation
defines rough boundaries for extent of invasion with piston like displacement but the use
of numerical simulation techniques helps us eliminate this idealistic picture to obtain a
better picture of the invasion profile in a sand formation for better interpretation of
resistivity measurements.
Malik, M et al 2008 quantifies the effects of petrophysical properties on AIT
measurements acquired in the presence of Oil Based Mud [OBM] -Filtrate invasion.
Sensitivity analyzes from these papers helps quantify the importance of variation of
petrophysical parameters to the process of mudcake build up and mud-filtrate invasion
using OBM. Wu et al 2005 also covers the influence of WBM properties and
petrophysical parameters on filtrate invasion but only does a time lapse curve of
resistivity and does not attempt to reconstruct resistivity profiles from either induction or
laterolog measurements although such an extension is not far fetched as it is done in
Salazar, J et al 2005 and George et al 2004.
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All the above papers seem to take similar steps in performing the simulation and
reproduce resistivity measurements even given the use of induction and/or laterolog tools.
[The use of both tools and the effect on the measurement is discussed at the end of
George, B et al 2004 but for fresh water mud on a highly saline connate water formation]
Salazar, J et al 2006 and 2005 use similar methods for permeability elucidation
but extrapolates from core data in a key well for use in uncored wells. This method
shows great promise as parameters can now be derived from the logged wells that can be
influential in understanding the effectiveness of water flooding in uncored wells. The
method discussed below is taken from Salazar, J et al 2005 and is applicable to
multiphase, immiscible filtrate invasion.
Figure adapted From M. Malik et al 2008
Simulating Mud-filtrate invasion in uncored wells
The first stage of the study consists of a full petrophysical analysis using both
core and log data from the key well. Rock types are identified and porosity,
permeability, capillary pressure and water saturation are related to the geological
framework and lithofacies present. Basically this stage sets up physical properties that
exist in the near wellbore region.
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The ultimate aim of the second stage is to derive reservoir compartments and flow
units by integrating log and core data with rock-type models and storage and flow
capacity plots. Flow units are taken as horizontal layers to simulate the invasion process
in a two dimensional chemical flood simulator. [Previously, the simulator used was
developed at University of Texas and is commercially called UTCHEM. (Delshad et al
1996) but this has now been modified and is now referred to as INVADE. Results from
INVADE have been proven to be numerically comparable to other commercial
simulators (SPE 71739)] This stage sets up the complete physical framework in the
simulator that the mud-filtrate will invade inclusive of the macro and micro scale
properties as they vary in the actual physical environment.
The third stage of quantifies the influence of mud-filtrate invasion on spatial
distribution of fluids in the permeable rocks of the formation by doing sensitivity analysis
of the time evolution of the mud-filtrate. Basically the resistivity values are computed
from water saturations and salt concentrations and history matched with actual measured
values from well logs.
Lastly, based on the analysis for the key well, a petrophysical analysis is
performed in any additional wells without core data for the physical structure elucidation
and mud-filtrate invasion is carried out in the wells with the only free parameter beign the
average absolute permeability per flow unit. All other remaining petrophysical
parameters are either estimated from well logs or extrapolated from the key well core
data. In this method, a modified Winland permeability equation [Pittman, 1992] is used to
compute the initial value of absolute permeability and this value is progressively adjusted
until calculated shallow resistivity and measured shallow array induction log show a
reasonable match. Time lapsed resistivity log data between LWD and wireline logs can
be used also to calibrate this data. This new methodology estimates in-situ absolute
permeability and is consistent with radial length [depth] of investigation and vertical
resolution of induction logs.
Advantages of simulating mud-filtrate invasion
Because the process of filtrate invasion in overbalanced drilling basically consists
of the mud-filtrate sweeping away in-situ oil, data gained from simulation may be
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comparable to data from water flooded core data in terms of quantifying displacement
efficiency, profiles of in-situ hydrocarbon saturation, endpoint relative water
permeability, irreducible hydrocarbon saturation and near wellbore behaviour of injected
water. In theory, the time lapsed resistivity profiles are history matched given the
conditions of the filtrate invasion and the simulation generated gives an idea of the water
saturation profiles, the permeability of the formation to filtrate and the pressure drop
across the mudcake.
If the pore volume and the volume of filtrate lost known, then water saturation
profiles will give the displacement efficiency of the filtrate at a given distance away from
the wellbore. Although there is a maximum length of invasion of filtrate, the area up to
the end of the flushed zone corresponds to the irreducible hydrocarbon saturation. Total
pore volume up to this point minus volume of invaded fluid will give the movable
volume of hydrocarbon displaced and this gives an indication of displacement efficiency
which is essential information for the reservoir engineer planning a water flood.
Of course, relative permeability of the formation to water is important for the
calculating of fractional flow in the reservoir. But more importantly, the behavior of the
invaded fluid in the near well bore region is significant as we may be able to observe
several phenomena such as streaking from low permeability sands to higher permeability
sand units and channeling of filtrate past the hydrocarbon. Such behaviour is extremely
beneficial as core measurements in the laboratory can not see this behaviour in profile.
Saturation profiles seen on this scale may also give the true shape of the saturation profile
on the reservoir scale.
Also, with the advent of simulation of OBM filtrate invasion, an obvious
application can be the obtaining of data for a chemical flood. Although data from this
may not be as readily justifiable against actual core data, the fact exist that research into
the area may lead quite interesting results.
Value to Reservoir engineer
It is said that data only adds value if that data creates opportunities to improve
decisions. The reservoir engineer is usually concerned with how much hydrocarbon will
be recovered and at what rate the recovery will take place. As such, the uncertainty in
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acquiring information in both aspects should be quantified in order to have an
understanding of the risk you are being exposed to versus the potential reward of a
successful decision.
In the following diagram, the decision faced by the reservoir engineer is modeled
and we see that there is a chance that even if the correct decision is made, the information
gathered may still be insufficient. Hence, from the diagram one can see that it is very
important to understand and [to some extent] quantify the risk associated with the
decision options to obtain information. In many cases, the option of carrying out a
simulation and taking a core may be exposed to the same uncertainties such as
uncertainties on the reservoir scale involving thief zones, faults, baffles and other
heterogeneities. However, because of the differences in the relative cost of doing a core
operation and simulation, the engineer must evaluate the expected value of each decision,
take into account the risk profile of the company and make a decision as to which option
exposes the company to least risk with the most potential [expected value] profit.
However, given that simulation takes information that is commonly acquired from the
time a well is drilled, the cost of simulating filtrate invasion becomes quite low when
compared to the cost of doing even a wireline core operation. This may lead to deceiving
results when comparing expected values of both options. Hence it is also within the
prevue of engineer to reasonably asses the correctness of the expected value calculation.
It is, by no means, an easy decision between both options as the uncertainties of
all measured parameters must now be quantified and applied to mathematical evaluation
of the water flood and the range of possible answers be quantified in terms of their
probability for each decision.
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Figure 2. Modeling A Decision to Perform a Water Flood
Coreinformatio
n
Coreinformatio
n
Coreinformatio
n
Simulation
Coreinformatio
n
Neither
DECISION
OPTIONS
YES
NO
Simulation
Neither
Simulatio
nNeither
Simulation
Neither
[Chance ofobtaining sufficient
data]
SufficientData
SufficientData
InsufficientData
InsufficientData
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3. Resistivity anisotropy - its effect on reserves and tools to resolve vertical and
horizontal components of resistivity
The word anisotropy is derived from a Greek root word that means unequal of
turning. In the oil industry, it is used to describe the character of formations whose
physical properties are significantly different in tow or three orthogonal directions.
Anisotropy can occur at various scales that are not always resolvable via traditional well
logging tools. These scales are; at the pore scale [micro-scale], at the laminations or thin
clay layer scale [meso-scale] and at the log resolvable bedding scale [macro-scale]. In an
effort to measure meso-scale anisotropy with a logging tool, measurements made by that
tool must be made in multiple directions. This is the case with tri-axial induction tools
although they are not made for higher spatial resolution but rather to measure vertical
[Rv] and horizontal Rh resistivity and sense changes in anisotropy axially over length of
resolution.
The triaxial resistivity tool described here is an experimental prototype described by
Rosthal et al (2003) and now called the Rt Scanner. This prototype, using co-located
sensor technology, had a triaxial transmitter and two triaxial receiver arrays. The long
array had a main coil placed 39" from the transmitter and a bucking coil placed 27" from
the transmitter. The short array had spacings of 27" and 21". Thus the sensor array
located at 27" consisted of six collocated coils, the main coils for the 27" array as well as
bucking coils for the 39" array. The tool also included a conventional short 9" array. Rt
Scanner tool has six triaxial arrays for Rvand Rh to be calculated at
each of the six triaxial spacings. Three single-axis receivers are used to
fully characterize the borehole signal to remove it from the triaxial
measurements. The Rt Scanner tool delivers standard AIT* Array Induction Imager
Tool measurements for correlation with existing field logs along with formation dip and
azimuth calculation for structural interpretation.
This tool helps resolve readings in horizontal resistivity [Rh] measurements especially in
thin bedded pay or low resistivity pay. In this case, the resistivity anisotropy data is best
interpreted using the laminated sand-shale model introduced by Clavaud et al(2003 &
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2005). This model considers alternating layers of high resistivity isotropic sands,
separated by low resistivity anisotropic shales. To solve the underdetermined horizontal
and vertical resistivity equations, a volume fraction of shale must be entered as well as a
shale anisotropy ratio.
The Clavaud Sand-Shale model further constrains the shale anisotropy ratio according to
whether the sand fraction is more or less resistive than the shale fraction at a given level.
A saturation equation, in this case the dual water model, is applied to both the computed
resistivity of the sand and of the shale fractions. Total water saturation is then calculated
by taking a volumetric average of the volume of fluids in each component, sand and
shale. This value can then be compared to a similar total saturation estimate computed
from a conventional petrophysical model. [Calvert, S et al, 2006 SPWLA]
Laminated sand-shale models with anisotropic shales have been discussed
extensively in literature but the interpretation methods usually are written in often
elaborate mathematical equations which, often, make the interpretation of data difficult as
a particular solutions sensitivity to errors can be a tedious process analytically. Also, no
clear procedure to determine key parameters such as shale anisotropy or guide to the
choice of solution really exist.
A Graphical crossplot can give a better insight into petrophysical changes than a
set of equations by using the interactivity of instant visualization of solutions within the
analysis.
Objectives of graphical analysis are:
- To determine the shale anisotropy parameters and whether it is necessary to create
multiple zones
- To define the region where each analytical solution is applicable
- To illustrate the effect of data outliers on the results
- To quickly perform sensitivity analysis
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The precise methodology for the interpretation of anisotropic shales is covered in several
literature sources and the above graphical method is covered in World Oil, September
2007 in the article titled Graphical Analysis of Laminated Sand-Shale Formations In the
Presence of Anisotropic Shales by Cao Minh et al. Its use in formation evaluation is
quite obvious with the resolving of resistivity measurements given the horizontal
resistivity.
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Reference:
Magnetic Resonance Fluid Characterization
Freedman, R. et al; Field Applications of a New Nuclear Magnetic Resonance Fluid
Characterization Method; SPE 71713, 2001 SPE
Cannon, D.E., Cao Minh, C. et al; Quantitative NMR Interpretation; SPE 49010, 1998 SPE
Schlumberger MR Scanner catalogue , Produced by Schlumberger Marketing Communications,
November 2005, Schlumberger
Anand, V. et al; NMR Diffusional Coupling: Effects of Temperature and Clay Distribution;
PETROPHYSICS Vol. 49, No. 4, August 2008, Pgs 362-372; 2008 SPWLA
Guru, U. et al; Low-Resistivity Pay Evaluation using Multidimensional and High-Resolution
Magnetic Resonance Profiling; PETROPHYSICS Vol. 49, No. 4 August 2008, Pgs 342-350; 2008 SPWLA
Heaton, N., Bachman, H. N., Cao Minh, C. et al; 4D NMR- Applications of the Radial
Dimension in Magnetic Resonance Logging; SPWLA 48th Annual Logging Symposium, 2007,Paper P
Flaum, C., Kleinberg, R.L., Bedford, J.; Bound Water Volume, Permeability and Residual Oil
Saturation from Incomplete Magnetic Resonance Logging Data; SPWLA 39th Annual Logging
Symposium, 1998, Paper UU
Tri-axial Resistivity Measurements
Calvert, S. and Pritchard, T.; Triaxial Array Induction Tool Aids Field Development For The
North Coast Marine Area, Trinidad W.I.; SPWLA 47th Annual Logging Symposium, 2006,Paper N
Clavaud, J., Cao Minh, C.; Graphical Analysis of Laminated Sand-Shale Formations in the
Presence of Anisotropic Shales; September 2007 Pgs 37-44 World Oil, 2007
Schlumberger Rt Scanner catalogue, Produced by Schlumberger Marketing Communications,
January 2006, Schlumberger 2006
Clavaud, J.; Intrinsic Electrical Anisotropy of Shale: The Effect Of Compaction;
PETROPHYSICS Vol. 49 No. 3 June 2008, Pgs 243-260; 2008 SPWLA
Simulation of Mud-filtrate invasion
Salazar, J.M., Torres-Verdin, C.; Assessment of Permeability from Well Logs Based on Core
Calibration and Simulation of Mud-Filtrate Invasion; PETROPHYSICS Vol. 46, No. 6
December 2005, Pgs 434-451; 2006 SPWLA
George, B., Torres-Verdin, C.; Assessment of In-Situ Hydrocarbon Saturation in the Presence
of Deep Invasion and Highly Saline Connate Water; PETROPHYSICS Vol. 45, No. 2 March-
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Appendix