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SPWLA 53 rd Annual Logging Symposium, June 16-20, 2012

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FRACTURE HEIGHT DETERMINATIONWITH TIME-LAPSE BOREHOLE ACOUSTICS ATTRIBUTES

E. Velez, L. Rodriguez, J. Zambrano, Schlumberger; E. Rodriguez, I. Bahamon, and C. Becerra, Ecopetrol

Society of Petrophysicists and Well Log Analysts

Copyright 2012, held jointly by the Society of Petr ophysicists and Well Log Analysts (SPWLA) and the submitting authors

This paper was prepared for presentation at the SPWLA 53rd Annual Logging Symposium held in C artagena, Colombia, June 16-20, 2012.

ABSTRACT

As high-permeability reservoirs approach their last years of productivity, the oil and gas production will likely comefrom low-permeability formations that require hydraulic fracture stimulation to be economically feasible. Theintroduction of hydraulic fracturing as part of the normal completion procedure in fields located in the Upper Valleyof the Magdalena basin in Colombia has achieved a twofold increase in the oilfield production.

Companies need tools that help them determine how successfully the hydraulic fractures have optimized well production and field development. These tools should provide information about hydraulic fracture conductivity,geometry, complexity, and orientation.

A new workflow for a time-lapse anisotropy analysis using data from an acoustic scanning platform is used toestimate the fracture height growth from the hydraulic fractures created in a typical well.

The application of the acoustic scanning platform technology as a fracture optimization tool allows a comprehensiveevaluation of the post stimulation production results. This provides precise information for calibration of the existinggeomechanical model, which will result in an optimized fracture design and corresponding positive effect in well

production and field development.

INTRODUCTION

Understanding the mechanics and geometry of hydraulic fractures has been a challenge since the first hydraulicfracture jobs were performed.

The first aspect considered when designing a hydraulic fracture job is the reservoir characteristics. In low- permeability reservoirs, which are the most common reservoirs stimulated, industry experts have established that thefracture length is the overriding factor for increased productivity and recovery (Ali et al. 2002).

From a reservoir-development point of view, a practical understanding of the hydraulic fracture geometry andorientation will enable engineers to determine the well spacing and hence the field development strategy to extract

more hydrocarbons.

Simulation engineers use hydraulic fracture simulators to design and predict optimal treatments. Basic inputs to thismodel include fluid and proppant properties and volumes, closure stress, pore pressure, and mechanical rock

properties, such as Poisson s ratio and Y oungs modulus .

The risk of an inadequate treatment is increased by estimating these inputs. To reduce this risk, mechanical earthmodels (MEMs) can be used as an input in the stimulation modeling (Fig. 1). Part of this step requires theacquisition of logs to obtain petrophysical and mechanical properties. In this study, the acoustic scanning platformlog was used to acquire
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compressional and shear velocities maximum horizontal stress direction and magnitude (if anisotropy mechanism is stress induced, identified

by the dispersion analysis). pore pressure estimation, etc.

The minimum horizontal stress can be calibrated by the direct measurement from a fracture data determinationservice.

Fracture modeling is a necessary part of the stimulation design and improvement process. However, even the mostcomplex model falls short in predicting reality (Barre et al. 2002).

Fig. 1 Hydraulic fracturing optimization feedback loop.

EVALUATE HYDRAULIC FRACTURE GEOMETRY

There are several methods to confirm hydraulic fracture geometry before, during, and after fracture creation (Fig. 2).The most common way to evaluate the treatment and the resulting geometry is with a net pressure fracture analysisshortly after, or even during, the fracture treatment.

Two other methods are post-treatment production analysis and well testing (buildup and drawdown). These two better define the effective production geometry than what has been done hydraulically.

Near-wellbore methods are used to investigate the geometry of hydraulic fractures. These include radioactivetracers, temperature, and production logs and are widely used to detect the hydraulic fracture height. Their limitationis that their measurement in a region at or near the wellbore may not represent what is happening away from the

borehole. They are time-dependent, meaning logging must be done almost immediately after the hydraulic fracturewas created.

Production logs are used to identify perforation intervals that are open and contributing to flowback or production. A positive flow response compared with a no-flow response from a pretreatment logging pass may imply that the zonehas been stimulated, but flow from a perforated interval may not mean the interval has been stimulated effectively:the fluids could be flowing through communicating hydraulic fractures from one zone to the next.

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The far-field methods for hydraulic fracture monitoring, such as surface and downhole tilt meters and microseismicmonitoring, have proved successful for characterizing hydraulic fracture behavior and geometry.

These methods are the best for determining the hydraulic fracture geometry but still have limitations: distance

between the monitor well and the treated well, the velocity model, the reservoir fluid type, etc. The limitationssometimes constrain their use; another factor to consider is the cost of these services.

In this paper we illustrate a technique using time-lapse acoustic anisotropy acquisition to evaluate hydraulic fracturegeometry (mainly height); it can be classified between the near-wellbore methods and the far-field methods.

THEORY AND METHODOLOGY

Shear Anisotropy and Cross-Dipole LoggingShear waves propagate through rocks with different velocities in different directions. This phenomenon is calledacoustic anisotropy, and it is caused by the anisotropic nature of the rocks elastic properties. All sedimentary rocksexhibit some degree of acoustic anisotropy related to aligned fractures, layering, or stress imbalance.

A cross-dipole log is acquired using a sonic tool with orthogonal dipole transmitters. Each transmitter firesindependently and the information is acquired in the same reference line of the transmitters (inline) and at 90degrees (cross-line).

Processing of the four-component acquired waveforms consists of Alford rotation at a given depth to identify thefast- and slow-shear directions (Alford, 1986). The resulting waveforms corresponding to the fast- and slow-shearorientations are then subjected to semblance processing to obtain the fast- and slow-shear slownesses, as described

by Kimball and Marzetta (1986) and Esmersoy et al. (1994). Table 1 gives a summary of the various techniques.

Table 1: Methods to evaluate hydraulic fracture geometry. The color scale denotes the reliability of the method(Adapted from Cipolla and Wright 2000).

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Sonic Waveform Dispersion AnalysisThe past generations of cross-dipole tools were able to detect and quantify the amount of anisotropy but could notidentify the driving mechanism (anisotropy type), such as intrinsic or stress-induced anisotropy.

The ability to analyze the dipole flexural dispersive curve (where the low-frequency limit of the curves asymptotesto the formation are the shear values) and model the tool acoustic behavior inside the well (not possible with dipolesonic tools) has enabled new evaluation methods to identify the dominant mechanism causing anisotropy purelyfrom sonic measurements (Plona et al. 2000).

To identify the anisotropy mechanism using dispersion analysis (Fig. 3), we can divide the formation into four types: Homogeneous isotropic: The dipole dispersion curves of cross-dipole data should fit to a model dispersion

curve calculated from the isotropic properties of the formation and borehole parameters in an isotropicformation (Fig. 3a).

Heterogeneous isotropic: This indicates formation alteration (Fig. 3b). Homogenous anisotropic: This indicates intrinsic anisotropy and can be related to layering (TIV) or fractures

(TIH) (Fig. 3c). Heterogeneous anisotropic: This indicates stress-induced anisotropy around the borehole wall (Fig. 3d).

Fig. 3 Dispersion analysis for fracture anisotropy characterization: a) homogeneous isotropic, b) heterogeneous

isotropic, c) homogenous anisotropic, d) heterogeneous anisotropic

Differential Cased Hole Sonic AnisotropyDifferential cased hole sonic anisotropy (DCHSA) is a time-lapse technique using acoustic scanning platform data tocompare the anisotropy results before and after the hydraulic fracture job (Nikitin et al. 2006).

The objective is to determine the hydraulic fracture height using the better of the following two indicators:1) differential energy (minimum-maximum energy) and slowness anisotropy (Sloani) where the fracture height isthe observed increase in anisotropy, and 2) shear slowness comparison (fast and slow) where the fracture height isthe difference between shears greater than 1% (empirical cutoff).

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Traditionally, only the anisotropy difference analysis is analyzed and used when evaluating hydraulic fracture heightfrom time-lapse sonic analysis; there are some situations where the cross-energy difference and the Sloani differenceare not good indicators of the fracture height:

No anisotropy increment: This can be due to the effect of perforations not aligned with the preferred fracture plane (PFP), creating nonaligned paths around the borehole at the depth of investigation of the acousticscanning platform (4 to 5 ft) (Fig. 4).

High anisotropy before the hydraulic fracture: This can be explained if the reservoir is in a highly tectonic area(stress-induced anisotropy) or is too laminated (transverse intrinsic anisotropy). In any of these cases theanisotropy increment created by the hydraulic fracture job could be difficult to detect.

Only if the data analysis covers the two points of the DCSHA technique can we obtain the hydraulic fracture height.

Fig. 4 Effect of perforations not aligned with the direction of maximum horizontal stress (PFP).

CASE OF STUDIES

We present studies of datasets acquired from two Colombia wells; each had different initial and final anisotropyconditions.

Case Study 1

The first study is of a well in the Llanos basin of Colombia, where wells are historically difficult to fracture. In thiscase, a hydraulic fracture stimulation model was built for three intervals (Fig. 5) that were to be perforated andfractured. A stimulation model was built with calibrated mechanical properties from a 1D MEM created for the wellusing acoustic scanning platform and openhole density data and calibrated minimum closure stress.The prefracture anisotropy analysis shows no anisotropy along the logged interval, and based on dispersion analysisthe formation was classified as homogeneous isotropic. The postfracture anisotropy analysis showed no anisotropyincrement in the stimulated zones; however, from a comparison of the fast and slow shears before and aftertreatment and calculation of the HF factor, the hydraulic fracture height was obtained.

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Fig. 7 Hydraulic fracture height obtained vs. modeled height, Stage 2.

Fig. 8 Hydraulic fracture height obtained vs. modeled height, Stage 3.

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Case Study 2This well is located in the Putumayo basin in southern Colombia, where hydraulic fracturing is the established

primary stimulation method for production optimization. The porosity of the sands range from 15% to 18%, and permeability is between 5 to 50 mD. Sand U3, highlighted in pink on Fig. 9, is a fracture treatment candidate. The

objective of the hydraulic fracture is to bypass the formation skin damage and create a conductive channel toincrease production.

Fig. 9 Petrophysical analysis for Case Study 2: The pink zone is the candidate for hydraulic fracture treatment.

In this case the stimulation model uses as input the formation petrophysical lithology and correspondent mechanical

properties values. The geomechanical model evolved based on sonic logs from several wells in the field and wascalibrated by using diagnostic pumping data, but it was never compared to any information after treatment. Theresults of the stimulation model are shown in Fig. 10, where the model fracture height is shown as 60 ft.

Fig. 10 Stimulation model for the U3 sand; fracture height modeled is 60.3 ft .

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The prefracture analysis shows small amounts of anisotropy on the bottom of the logged interval; the anisotropy wasclassified as stress induced. The U3 sand shows no anisotropy.

The postfracture analysis shows no increment in energy difference on the U3 sand, a very small shear velocitydifference, and about a 2% increment in slowness anisotropy. The fracture height obtained is 48 ft.

The results obtained with the DCHSA technique are only 12 ft less than that predicted with the stimulation model.This result shows that the small shale at the bottom of the sand contains the fracture; the model predicts the fracturegrows 12 ft below this. Fig. 11 shows a comparison of the actual results versus the modeled fracture.

Fig. 11 Case Study 2: Comparison of fracture heights obtained with the DCHSA technique and the stimulationmodel.

The information provided by the DCHSA analysis was critical not only for the well but for the whole field. Thewells w ater cut after treatment was higher than expected, and by initial analysis this was attributed to a possiblefracture contact with a water zone located just below the interval. Confirmation that the fracture was contained wasmade by the post-treatment analysis and resulted in a calibration of the saturation model to match the water

production obtained after fracturing the interval.

CONCLUSIONS

The fracture height enables a comprehensive evaluation of the post-stimulation production results.Precise information is available for calibration of the existing geomechanical model, which results in an optimizedfracture design (fracture geometry and conductivity).

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Fracture height also results allows a better prediction of the well productivity.

The DCSHA technique expands the use of acoustic anisotropy with dispersion analysis into the stimulation production domain.

ACKNOWLEDGMENTS

We thank Ecopetrol for permission to publish this work, Marcelo Frydman for his valuable help on this paper, andthe Colombia geomechanics team for their contribution to the work presented.

REFERENCESAlford, R.M., 1986, Shear data in the presence of azimuthal anisotropy: 56th SEG Ann. Internat. Mtg.,ExpandedAbstracts, 476 479.

Ali, S., Norman, D., Wagner, D., Ayoub, J. et al., 2002, Combined stimulation and sand control: Oilfield Review14(2), 30 47.

Barre, R.D., Fisher, M.K., and Woodrof, R.A., 2002, A practical guide to hydraulic fracture diagnostic technologies:Paper SPE 77442 presented at the SPE Annual Technical Conference and Exhibition, San Antonio, Texas, 29September 2 October.

Cipolla, C.L. and Wright, C.A., 2002, Diagnostic techniques to understand hydraulic fracturing: What? Why? AndHow?: Paper SPE 59735 presented at the SPE/CERI Gas Technology Symposium, Calgary, 3 5 April.

Esmersoy, C., Boyd, A., Kane, M., and Denoo, S., 1995, Fracture and stress evaluation using dipole-shearanisotropy logs: Paper J presented at the 36 th SPWLA Annual Logging Symposium. Paris, 26-29, June

Kimball, C.V., and Marzetta, T.L., 1986, Semblance processing of borehole acoustic array data: Geophysics, 49,no. 3, 274 281.

Mueller, M., Boyd, A., and Esmersoy, C., 1994, Case studies of the dipole shear anisotropy log: SEG AnnualInternational Meeting, Expanded Abstracts, 1143 1146.

Nikitin, A., Maniere, J. et al., 2006, Differential cased hole sonic anisotropy for evaluation of propped fracturegeometry in western Siberia, Russia: Paper SPE 102405 presented at the SPE Russian Oil and Gas TechnicalConference and Exhibition, Moscow, Russia, 3 6 October.

Plona, T.J., Sinha, B.K., Kane, M.R., and Viloria, O., 2000, Using acoustic anisotropy: Paper H presented at the 41 th SPWLA Annual Logging Symposium, Dallas, Texas, 4 -7, June

Saldungaray P., Barrienos P., Wielemaker E., Plona T., Haldorsen J.B.U., 2006, Anisotropy evaluation in theCuitlahuac field Mexico, from cross-dipole sonics and borehole seismics generated by two orthogonal shearvibrators: Paper presented at the 47 th SPWLA Annual Logging Symposium, Veracruz, Mexico, 4 7 June.

Tang, X.M. and Chunduru, R.K., 1997, Inversion of shear wave anisotropy from cross-dipole logging data: SEGAnnual International Meeting, Expanded Abstracts, 274.

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ABOUT THE AUTHORS

Edgar Velez is a senior petrophysics engineer working in the area of sonic waveform processing an interpretationwith wireline supporting the implementation and application of advance acoustics answers for Latin America, Edgarstarted as a junior log analyst in 2003, in Villahermosa Mexico after graduating with a bachelors degree inGeophysical engineering from the Universidad Nacional Autonoma de Mexico. He has been in different positions inSchlumberger as Petrophysicist, Data Services leader in Mexico North and Acoustic Domain Champion. He ismember of the SPWLA and SPE.

Lucia Rodriguez is a Civil Engineer from Universidad Nacional de Colombia with a Master in Geomechanics fromthe same university and Specialized in Project Management from Universidad del Rosario in Colombia. Luca

joined Schlumberger since 2005 and currently is in charge of geomechanics activity for Colombia, Per, Ecuador,Venezuela, Trinidad and Tobago with Data and Consulting Services, the geosciences segment of Schlumberger.She has developed several geomechanics projects for different applications such as wellbore stability, sanding,fracturing and reservoirs from 1D, 2D, 3D and 4D perspectives.

Jose Rafael Zambrano is a Petrophysicist Log Analyst working in the areas of sonic waveform processing andothers petrophysical log data processing and interpretation with Schlumberger Data & Consulting Services in

Bogota, Colombia. Rafael started with Schlumberger as Borehole Geologist in 2009, after graduating withBachelors degree in Geological Engineering from Peoples Friendship University of Russia, Moscow, Russia.

Eusebio Rodriguez is a Senior Stimulation Engineer working for ECOPETROL S.A., with experience in matrixacidizing, hydraulic and acid fracturing, water and sand control. Graduated as Petroleum Engineer from ZuliaUniversity (LUZ) in Venezuela in 1994. Eusebio has worked in west and east Venezuela, Mexico, Colombia,Ecuador and Argentina as field engineer, technical advisor and developing technical solutions for specificapplications.

Jorge Italo Bahamon is a Senior Stimulation Engineer in charge of the Stimulation Program for ECOPETROLS.A. (NOC in Colombia). Jorge Italo started as a field engineer for Stimulation, Coiled Tubing and cementingservices in 2,002 in Permian Basin (New Mexico, USA) after graduating with a Bachelors degree in PetroleumEngineering from the Universidad de America, Bogota, Colombia. Since that time he has been involved in differentareas regarding stimulation such us global coach for matrix stimulation and hydraulic fracturing, and sales leader forstimulation services in different areas such as United States, Mexico and Colombia in America; and Egypt andMalaysia Overseas. He is a registered professional Engineer in Colombia (ACIPET) and a member of SPE

Carlos Becerra is a petroleum engineer from the University of America (Bogota, Colombia) with specialization infinance of Unillanos in Villavicencio Meta, started his work experience in the area of drilling fluids in the Cusianaand Cupiagua fields of the BP company in Colombia, in 2006 started work on the Colombian state companyEcopetrol, ini tially as a production engineer and treatment wells of Apiay field, then in 2007 joined the group

professional of Subsurface operations for Castilla field in the llanos orientales basin, he planning and designingWorkover operations to the wells of these field. Since 2009 and to date is coordinating operations of Fracture andStimulation in Apiay and Suria, fields of the Superintendent of operations Apiay Ecopetrol also is part ofcommunities of practice of well stimulation and Workover of Ecopetrol.

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