Reservoir Characterization for Shales: a Barnett Shale Case Study
|
|
- Damian Barber
- 6 years ago
- Views:
Transcription
1 GUSS14-24 Reservoir Characterization for Shales: a Barnett Shale Case Study JOHN PENDREL CGG GeoSoftware ALFONSO IUNIO MARINI Eni E&P This paper has been selected for presentation for the 2014 Gussow Geosciences Conference. The authors of this material have been cleared by all interested companies/employers/clients to authorize the Canadian Society of Petroleum Geologists (CSPG), to make this material available to the attendees of Gussow 2014 and online. ABSTRACT This paper describes the integration of disparate reservoir measures and analyses toward an improved reservoir description and the facilitation of more efficient exploration and production programs. We use the elastic inversion of pre-stack seismic reflection data to compute key reservoir properties such as volume of quartz and brittleness. Bayesian inference is then used to define and map relevant litho-facies. Geometric analysis of the seismic stack data is completed to identify lineaments describing faults and collapse events. All these are then combined with information form logs to design optimum well paths and fracking programs. This paper is a continuation of our previous work (Varga et al., 2012). INTRODUCTION Designing optimum drilling programs for shale plays requires a multi-faceted reservoir characterization scheme which can simultaneously address several issues. These include: Drilling through rocks with optimum brittleness Drilling normal to the direction of maximum present local stress Determining the proximity of natural fractures, their nature and chances of reactivation Drilling to avoid water infiltration, i.e. avoiding collapse features (examples from Barnett) Drilling through regions of enhanced quartz content Drilling through regions of enhanced porosity Drilling through regions of optimal TOC The key tools of the explorationist are elastic reservoir property estimates from seismic inversions, geometric attributes and discrete fracture networks (DFNs) from seismic and relative inversions. We follow others in using an indexed scaled average of Poisson s Ratio and Young s Modulus as a proxy for brittleness. We use observed relations in logs to estimate Vquartz and porosity from the native outcomes of inversions: P Impedance, Vp/Vs, and Density. From these we also use Bayesian analysis to identify and map key facies 1
2 defined in Vquartz Brittleness TOC space. We estimate the direction of maximum stress from geometric attributes and DFN analysis of both seismic and relative inversions. These allow us to also map pre-existing fractures. Geometric attributes can also be used to highlight Barnett collapse features, and correlate water encroachment events to this paleomorphological evidence. Optimizing recoverable reserves from shales requires proper alignment of horizontal well paths and placement of the lateral portions within the optimum layers and optimal sweet facies. According to published statistics, the well mis-positioning account for a 50% failure ratio in a development campaign. The effect of adding also EOR (fracking) failures generates a failure number close to 70%. If causes are examined, the scarcity of subsurface data collected in order to describe and model the key reservoir properties is the major problem. A method is presented here to identify these optimum regions in a petro-elastic space, characterizing shales in a way useful to help building static models for simulation. The first stage of the process uses well data. Generally, logs from a very dedicated petrophysical model integrated with core data analyses are needed to understand the relationships between petrophysical vs. mechanical (elastic) rock properties. These latter are then used to reach a segmentation of the involved lithologies via the important petrophysical and mechanical shale reservoirs properties. As well, properties will allow us to predict how the rocks will respond to hydraulic fracturing. Next, a simultaneous AVO seismic inversion is performed to determine primary elastic properties from seismic (moduli) indicative of the rock stress state, and also derivative descriptive attributes. For instance, rock frackability is estimated from Poisson s Ratio and Young s Modulus, from a weighted average relationship. The final stage is an integration of the inverted properties, possibly interpreted in terms of a number of significant and reservoir quality-related facies, particularly designed to recognize the most suitable one for fracturing and the optimization of production. This is often obtained through a Bayesian probabilistic procedure of classification, using well data-based facies petro-elastic model, describing the a priori information concerning the facies probability density functions (pdf s) distributions in the petro-elastic space. These models are typically used in well planning to identify optimum area, proper lateral directions and vertical depth variances required to drill and complete successful production wells. The Barnett Shale is one of the most important hydrocarbon-bearing geologic formations in North America. (Loucks and Ruppel, 2007). The structurally deepest part of the Fort Worth Basin lies to the northeast where the Barnett Shale formation is more than 1000 ft. thick and interbedded with limestone units. Multiple tectonic events have structurally deformed the Barnett so that it is a naturally fractured heterogeneous reservoir. The collapse of the Barnett Shale into karst features in the underlying Ellenburger Group carbonates is a common feature, easily revealed by seismic geomorphological analyses. Yucatan Cenotes -like, circular and depressed structures are generated by the corrosive actions of the flushing water in the karst reservoir resulting in massive collapses of significant carbonatic rock volumes underlying the Barnett formation. The collapsed Barnett retains some of the structure induced by the underlying rock collapse, resulting in a connection to the aquifer zone. Therefore, the presence of sub-circular rim faults in the Barnett is strongly suggestive of water encroachment. The Barnett is an organically rich, thermally mature, and vertically variable formation, in its lithological and geomechanical properties. The formation permeability is in the micro to nano-darcy range and porosity varies between 0.5 and 10%. From the reconstructed subsurface images it is clear that the range of the optimum reservoir has a maximum elongated axis of 1-2 km. Within this environment, we have very discontinuous spatial variability of the optimal sweet spots geo-bodies. Shale play sweet spots are typically characterized by mid to high kerogen content (not very high, since high kerogen values induce an excess of ductility), lower clay volumes, higher effective porosity and low water saturation. From a petro-elastic point of view, this corresponds to high Young s Modulus and low Poisson s Ratio. The mineralogy of the Barnett Shale is comprehensive of clays, quartz, calcite, kerogen and other minerals. Shales may also be described in terms of mechanical properties, using measures such as silica content, fracture content, brittleness and pressure gradient. Natural fractures are present and re-activated during stimulation and increase production efficiency by widening the treatment zone. Our test area is in Figure 1 showing the 2
3 time structure of the Barnett along with the location of the seven vertical wells. Figure 1. The study area showing the TWT structure of the Barnett and the location of the seven vertical wells. RESULTS The native properties derivable from AVO inversions of pre-stack seismic data are P Impedance, Vp/Vs and Density (Figure 2). An important quality control of the reservoir properties from inversion is a check for bias. For accurate QI work, we require that the outcomes of inversion be unbiased. This is determined by cross-plots of high-cut filtered logs vs inversion properties at the log locations. This check is done not only for the native results of inversion but also for all of the derivative properties. These derivatives are other properties of interest, such as brittleness, Vquartz and porosity. Density is usually not fully determined for conventional seismic data due to the limited extent of the incident angle range and the small number of partial stacks available. Anyway, we used incident angle components higher than 50, in order to obtain an independent contribution to the results. Other information comes from the observed relations between density, P Impedance and Vp/Vs observed in the recorded logs. We quantified the Barnett Shale s brittleness factor by averaging Young s Modulus and Poisson s Ratio. Averaging these two disparate properties was made possible by first indexing them on a scale of The volume of quartz (Vqtz) was determined by levering on relations between Vqtz and Vp/Vs, LambdaRho and Density, again observed in the log data via cross-plot and discriminant analyses. A neural net application was then used to compute the final Vqtz volume. Next a set of lithological/geomechanical facies were defined based on Vqtz and brittleness. The design template is shown in Figure 3 where the concentric ellipses represent pdf s corresponding to the facies. It is believed that the best reservoir is the high quartz zone with medium brittleness, so avoiding the poorly-fracable ductile high TOC shale, and the too brittle low-toc more-quartzy layers. The design template facilitates the computation of the probability of occurrence of each of the facies In addition, a most-probable facies is determined. Applying the same analysis to high-cut filtered logs and overlaying them is a powerful QC. The results are shown in Figure 4. Overlain are high-cut filtered logs. The matches to the logs are good but not perfect since the high frequency information of the logs was not exposed to the inversion algorithm and the relation between Vqtz and other combinations of logs is itself probabilistic and uncertain within a tolerable error level. Ductile shales at the Barnett Fm. base (blue in Figure 4, lower panel) act as seals at the base of the reservoir and can isolate the productive sequence above from the waterbearing Ellenburger formation below. The type 3 (high quartz - medium brittleness) facies is colored in orange and represents the zone of greatest exploration potential as the kerogen content is relatively high. Figure 2. The native outcomes of elastic inversion are shown along an arbitrary line through the seven vertical wells. The flattened top of Barnett is indicated by the white arrow on the left hand sides of each panel. In each panel, high-cut filtered logs are overlain. The reservoir extends to the black area (Viola) in each panel. 3
4 Figure 3. Facies template for Bayesian analysis. The facies are described by Vqtz and Brittleness Index. The ellipses are 2D PDFs for each facies (two standard deviations shown). This is illustrated in the log cross-plot in Figure 5 where Kerogen content is plotted vs. brittleness and coloured by facies type. Figure 6 is a time slice through the mostprobable facies volume shown in 3D perspective. The facies volumes were next transformed from time to depth, enabling the construction of probablistic net pay maps. Also estimated, were effective porosity and kerogen content. Porosity was computed from the observed linear relation to P Impedance. Kerogen was found to be related to density although different linear relations were observed and utilized for each facies type. Major natural fractures in the eastern portion of the survey area were identified from seismic structural attribute analyses. Figure 7 shows the discrete fracture network (DFN) which was created from one such analysis. We experimented with different inputs to the DFN process and found that the Figure 4. Quartz % (Vqtz in the upper panel) and Brittleness Index (middle) derived from AVO Inversion. High-cut logs are overlain. The lowest panel shows the most-probable facies from Bayesian analysis. Green represents the most brittle rocks with high quartz content. Medium brittleness and high Vqtz are in orange. The lower blue facies are compliant, shale-rich rocks. Figure 6. Time slice through the most-probable facies volume Figure 5. The Type 3 facies with high Vqtz and medium brittleness exhibit the best kerogen content in the reservoir interval. Figure 7. Discrete fracture network from FractureSpark TM 4
5 outputs from relative inversions were particularly useful. Coherency and most-negative or most-positive curvatures were also found to be useful. The goal was to fully characterize structural and stratigraphic complexities in the sequence of interest, to identify intervals with favorable characteristics for drilling horizontal wells, possible fracture barriers, and potential hazards such as water conduits. This is illustrated in Figure 8 where a brittleness section, well trajectory, curvature depth slice and structural map of the carbonate substratum, revealing highs and lows, are corendered. Plots such as these, facilitate the optimum design of fracking stages. Another such example is shown in Figure 9. The termination point of the well occurs where a fracture event connects the reservoir to the water-bearing Viola below. In addition, the fault is coincident with a karst collapse feature. The combination of these provided easy access for the water, which made further drilling impossible. Figure 9. The well was terminated when significant amounts of water were encountered. This location is coincident with both an Ellenburger-penetrating fault and a collapse feature. A structural sag in the sequence of interest already revealed a possible lowered area. The colours in the superimposed section indicate the best (green) and poorer reservoir facies (red). The B&W background section is a Continuity display showing the main and detailed structural lineaments. The facies quality is also poor at the end of the well path, a fact which is confirmed by the gamma ray log (high values are red along the well track). CONCLUSION Figure 8. A brittleness section, well trajectory, curvature slice and structural maps of the carbonate substratum highs are co-rendered in depth. The red lines highlight the main fault systems affecting the well bore. Fracking programs can be optimally designed when these disparate pieces of information are brought together and integrated in a model frame. In this paper we have discussed a reservoir characterization workflow for the Barnett shale which has proved to result in drilling successes and better understanding of several geological observations. Data from a few vertical pilot wells (seven), seismic inversion and its derivatives and geometric attributes were integrated to create a 3-D solid model allowing better delineation and management of subsurface heterogeneities for the drilling of and production from, some 200 horizontal wells. The generated products were checked along hundreds of horizontal production wells, to verify matches, identify reasons for failures and to indicate the best productive areas, their associated local risks and benefits. The result was a greater understanding of gas vs water production and their relations to aquifer encroachment. Given this very positive experience, the generated datasets were included in the reservoir model for use in simulation experiments. The discussed workflow offers economic potential for both this and other types of unconventional reservoirs, LTO first of all. 5
6 ACKNOWLEDGMENT The authors gratefully acknowledge Eni E&P for permission to show the results of this study. Assistance and advice from our CGG colleagues at Jason, TerraSpark and Hampson- Russell was very much appreciated. REFERENCES Loucks, R.G., and Ruppel, S.C., 2007, Mississippian Barnett Shale: Lithofacies and depositional setting of a deepwater shale-gas succession in the Fort Worth Basin, Texas, American Association of Petroleum Geologists Bulletin, v. 91, #4, p Varga, R., Lotti, R., Pachos, A., Holden, T., Marini, I. Spadafora, E., Pendrel, J., 2012, Seismic inversion in the Barnett Shale successfully pinpoints sweet spots to optimize well-bore placement and reduce drilling risks, Society of Exploration Geophysicists International Annual Meeting, Technical Program Expanded Abstracts 2012:
Maximize the potential of seismic data in shale exploration and production Examples from the Barnett shale and the Eagle Ford shale
Maximize the potential of seismic data in shale exploration and production Examples from the Barnett shale and the Eagle Ford shale Joanne Wang, Paradigm Duane Dopkin, Paradigm Summary To improve the success
More informationURTeC: Summary
URTeC: 2665754 Using Seismic Inversion to Predict Geomechanical Well Behavior: a Case Study From the Permian Basin Simon S. Payne*, Ikon Science; Jeremy Meyer*, Ikon Science Copyright 2017, Unconventional
More informationCorrelation of brittleness index with fractures and microstructure in the Barnett Shale
Correlation of brittleness index with fractures and microstructure in the Barnett Shale Z. Guo (British Geological Survey), M. Chapman (University of Edinburgh), X.Y. Li (British Geological Survey) SUMMARY
More informationNORTH AMERICAN ANALOGUES AND STRATEGIES FOR SUCCESS IN DEVELOPING SHALE GAS PLAYS IN EUROPE Unconventional Gas Shale in Poland: A Look at the Science
NORTH AMERICAN ANALOGUES AND STRATEGIES FOR SUCCESS IN DEVELOPING SHALE GAS PLAYS IN EUROPE Unconventional Gas Shale in Poland: A Look at the Science Presented by Adam Collamore Co-authors: Martha Guidry,
More informationGeophysical and geomechanical rock property templates for source rocks Malleswar Yenugu, Ikon Science Americas, USA
Geophysical and geomechanical rock property templates for source rocks Malleswar Yenugu, Ikon Science Americas, USA Summary Sweet spot identification for source rocks involve detection of organic rich,
More informationUnconventional reservoir characterization using conventional tools
Ritesh K. Sharma* and Satinder Chopra Arcis Seismic Solutions, TGS, Calgary, Canada Summary Shale resources characterization has gained attention in the last decade or so, after the Mississippian Barnett
More informationPorosity. Downloaded 09/22/16 to Redistribution subject to SEG license or copyright; see Terms of Use at
Geostatistical Reservoir Characterization of Deepwater Channel, Offshore Malaysia Trisakti Kurniawan* and Jahan Zeb, Petronas Carigali Sdn Bhd, Jimmy Ting and Lee Chung Shen, CGG Summary A quantitative
More informationGeophysical and geomechanical rock property templates for source rocks Malleswar Yenugu, Ikon Science Americas, USA
Malleswar Yenugu, Ikon Science Americas, USA Summary Sweet spot identification for source rocks involve detection of organic rich, high porous facies combined with brittleness, which is prone for hydraulic
More informationInvestigating the Barnett Shale
Investigating the Barnett Shale An Integrated Workflow from Petrophysics to Visualisation and Seismic Decomposition Vision for Energy The Barnett Shale 1981: Barnett Shale discovery 8,000+ wells to date
More informationMaximizing Recoverable Reserves in Tight Reservoirs Using Geostatistical Inversion from 3 D Seismic: A Case Study rom The Powder River Basin, USA
URTeC: 2153909 Maximizing Recoverable Reserves in Tight Reservoirs Using Geostatistical Inversion from 3 D Seismic: A Case Study rom The Powder River Basin, USA Haihong Wang*, CGG GeoConsulting; Howard
More informationInduced microseismic fracture prediction
Predicting hydraulically-induced microseismic fractures from seismic inversion volumes: A North Texas Barnett Shale case study Xavier E. Refunjol*, University of Oklahoma, Joël Le Calvez, Schlumberger,
More informationstress direction are less stable during both drilling and production stages (Zhang et al., 2006). Summary
Inversion and attribute-assisted hydraulically-induced microseismic fracture prediction: A North Texas Barnett Shale case study Xavier E. Refunjol *, Katie M. Keranen, and Kurt J. Marfurt, The University
More informationSeismic characterization of Montney shale formation using Passey s approach
Seismic characterization of Montney shale formation using Passey s approach Ritesh Kumar Sharma*, Satinder Chopra and Amit Kumar Ray Arcis Seismic Solutions, Calgary Summary Seismic characterization of
More informationOptimising Resource Plays An integrated GeoPrediction Approach
Optimising Resource Plays An integrated GeoPrediction Approach Edward Hoskin, Stephen O Connor, Scott Mildren, Michel Kemper, Cristian Malaver, Jeremy Gallop and Sam Green Ikon Science Ltd. Summary A mechanical
More informationDownloaded 01/29/13 to Redistribution subject to SEG license or copyright; see Terms of Use at
The value of production logging combined with 3D surface seismic in unconventional plays characterization John Henry Alzate*, Roderick Perez, Deepak Devegowda, Kurt J. Marfurt, The University of Oklahoma
More informationWorkflows for Sweet Spots Identification in Shale Plays Using Seismic Inversion and Well Logs
Workflows for Sweet Spots Identification in Shale Plays Using Seismic Inversion and Well Logs Yexin Liu*, SoftMirrors Ltd., Calgary, Alberta, Canada yexinliu@softmirrors.com Summary Worldwide interest
More informationRecap and Integrated Rock Mechanics and Natural Fracture Study on the Bakken Formation, Williston Basin Abstract Figure 1:
Recap and Integrated Rock Mechanics and Natural Fracture Study on the Bakken Formation, Williston Basin Cosima Theloy, Department of Geology & Geological Engineering Abstract The late Devonian to early
More informationMultifocusing 3D diffraction imaging for dectection of fractured zones in mudstone reservoirs
Multifocusing 3D diffraction imaging for dectection of fractured zones in mudstone reservoirs Alana Schoepp, Evgeny Landa, Stephane Labonte Shell Canada Ltd., Geomage, Shell CanadaLtd Summary Unconventional
More informationStochastic Modeling & Petrophysical Analysis of Unconventional Shales: Spraberry-Wolfcamp Example
Stochastic Modeling & Petrophysical Analysis of Unconventional Shales: Spraberry-Wolfcamp Example Fred Jenson and Howard Rael, Fugro-Jason Introduction Recent advances in fracture stimulation techniques
More informationDownloaded 10/25/16 to Redistribution subject to SEG license or copyright; see Terms of Use at
Facies modeling in unconventional reservoirs using seismic derived facies probabilities Reinaldo J. Michelena*, Omar G. Angola, and Kevin S. Godbey, ireservoir.com, Inc. Summary We present in this paper
More informationTowards Interactive QI Workflows Laurie Weston Bellman*
Laurie Weston Bellman* Summary Quantitative interpretation (QI) is an analysis approach that is widely applied (Aki and Richards, 1980, Verm and Hilterman, 1995, Avseth et al., 2005, Weston Bellman and
More informationLithology prediction and fluid discrimination in Block A6 offshore Myanmar
10 th Biennial International Conference & Exposition P 141 Lithology prediction and fluid discrimination in Block A6 offshore Myanmar Hanumantha Rao. Y *, Loic Michel, Hampson-Russell, Kyaw Myint, Ko Ko,
More informationMITIGATE RISK, ENHANCE RECOVERY Seismically-Constrained Multivariate Analysis Optimizes Development, Increases EUR in Unconventional Plays
White Paper MITIGATE RISK, ENHANCE RECOVERY Seismically-Constrained Multivariate Analysis Optimizes Development, Increases EUR in Unconventional Plays SM Seismically-Constrained Multivariate Analysis Optimizes
More informationShale gas reservoir characterization workflows
Shale gas reservoir characterization workflows Satinder Chopra + *, Ritesh K. Sharma +, James Keay + and Kurt J. Marfurt + Arcis Seismic Solutions, Calgary; The University of Oklahoma, Norman Downloaded
More informationFull-Azimuth 3-D Characterizes Shales
JULY 2013 The Better Business Publication Serving the Exploration / Drilling / Production Industry Full-Azimuth 3-D Characterizes Shales By Duane Dopkin, Joanne Wang and Shiv Pujan Singh HOUSTON Shale
More informationQUANTITATIVE ANALYSIS OF SEISMIC RESPONSE TO TOTAL-ORGANIC-CONTENT AND THERMAL MATURITY IN SHALE GAS PLAYS
E: infoikonscience.com W: www.ikonscience.com QUANTITATIVE ANALYSIS OF SEISMIC RESPONSE TO TOTAL-ORGANIC-CONTENT AND THERMAL MATURITY IN SHALE GAS PLAYS Ebrahim Zadeh 12, Reza Rezaee 1, Michel Kemper 2
More informationBest practices predicting unconventional reservoir quality
Introduction Best practices predicting unconventional reservoir quality Cristian Malaver, Michel Kemper, and Jorg Herwanger 1 Unconventional reservoirs have proven challenging for quantitative interpretation
More informationSurface seismic data have proven to be an invaluable
SPECIAL Practical SECTION: applications Practical of applications anisotropy of anisotropy ARCANGELO SENA, GABINO CASTILLO, KEVIN CHESSER, SIMON VOISEY, JORGE ESTRADA, JUAN CARCUZ, EMILIO CARMONA, and
More informationPROSPECT EVALUATION OF UNCONVENTIONAL PLAYS IN RUSSIA EPUG 2014
PROSPECT EVALUATION OF UNCONVENTIONAL PLAYS IN RUSSIA EPUG 2014 Main definitions AGENDA Shale/shale play definition - Organic matter content - Thermal maturity Potential for unconventionals development
More informationQUANTITATIVE INTERPRETATION
QUANTITATIVE INTERPRETATION THE AIM OF QUANTITATIVE INTERPRETATION (QI) IS, THROUGH THE USE OF AMPLITUDE ANALYSIS, TO PREDICT LITHOLOGY AND FLUID CONTENT AWAY FROM THE WELL BORE This process should make
More informationModeling Optimizes Asset Performance By Chad Baillie
MARCH 2016 The Better Business Publication Serving the Exploration / Drilling / Production Industry Modeling Optimizes Asset Performance By Chad Baillie MISSOURI CITY, TX. As more well and completion data
More informationSummary. Simple model for kerogen maturity (Carcione, 2000)
Malleswar Yenugu* and De-hua Han, University of Houston, USA Summary The conversion of kerogen to oil/gas will build up overpressure. Overpressure is caused by conversion of solid kerogen to fluid hydrocarbons
More informationGeophysical model response in a shale gas
Geophysical model response in a shale gas Dhananjay Kumar and G. Michael Hoversten Chevron USA Inc. Abstract Shale gas is an important asset now. The production from unconventional reservoir like shale
More informationDownloaded 01/06/15 to Redistribution subject to SEG license or copyright; see Terms of Use at
Application of wide-azimuth 3D seismic attributes to predict the microfractures in Block MA area for shale gas exploration in South China Yusheng Zhang* 1, Gang Yu 1, Ximing Wang 1, Xing Liang 2, and Li
More informationDownloaded 01/29/13 to Redistribution subject to SEG license or copyright; see Terms of Use at
An integrated study of a Mississippian tripolitic chert reservoir Osage County, Oklahoma, USA Benjamin L. Dowdell*, Atish Roy, and Kurt J. Marfurt, The University of Oklahoma Summary With the advent of
More informationDrill Cuttings Analysis: How to Determine the Geology of a Formation and Reservoir
Drill Cuttings Analysis: How to Determine the Geology of a Formation and Reservoir Chuck Stringer ASA Manager Southern Region 2015 TECH MKT_2014-BD-REG-1673 1 The one item that has lacked serious consideration
More informationOptimizing Vaca Muerta Development
Optimizing Vaca Muerta Development What can be applied from seismic experiences in the Eagle Ford and other unconventional plays? Wednesday, September 19, 2012 4:50 PM Murray Roth, President Transform
More informationNumerical Simulation and Multiple Realizations for Sensitivity Study of Shale Gas Reservoir
SPE 141058 Numerical Simulation and Multiple Realizations for Sensitivity Study of Shale Gas Reservoir A.Kalantari-Dahaghi, S.D.Mohaghegh,SPE, Petroleum Engineering and Analytic Research Laboratory(PEARL)
More informationSeismic modeling evaluation of fault illumination in the Woodford Shale Sumit Verma*, Onur Mutlu, Kurt J. Marfurt, The University of Oklahoma
Seismic modeling evaluation of fault illumination in the Woodford Shale Sumit Verma*, Onur Mutlu, Kurt J. Marfurt, The University of Oklahoma Summary The Woodford Shale is one of the more important resource
More informationP314 Anisotropic Elastic Modelling for Organic Shales
P314 Anisotropic Elastic Modelling for Organic Shales X. Wu* (British Geological Survey), M. Chapman (British Geological Survey), X.Y. Li (British Geological Survey) & H. Dai (British Geological Survey)
More informationEstimation of shale reservoir properties based on anisotropic rock physics modelling
Estimation of shale reservoir properties based on anisotropic rock physics modelling K. Qian* (China University of Petroleum,Beijing), F. Zhang (China University of Petroleum,Beijing), X.Y. Li (British
More informationHampsonRussell. A comprehensive suite of reservoir characterization tools. cgg.com/geosoftware
HampsonRussell A comprehensive suite of reservoir characterization tools cgg.com/geosoftware HampsonRussell Software World-class geophysical interpretation HampsonRussell Software is a comprehensive suite
More informationFrom Micro to Macro: Application of a Geomechanically Calibrated, Seismically Constrained Reservoir Model to Unconventional Resource Development
13-14 June 2017 The Woodlands, Texas, USA The Woodlands Resort From Micro to Macro: Application of a Geomechanically Calibrated, Seismically Constrained Reservoir Model to Unconventional Resource Development
More informationShale Capacity Key In Shale Modeling
SEPTEMBER 213 The Better Business Publication Serving the Exploration / Drilling / Production Industry Shale Capacity Key In Shale Modeling By Ahmed Ouenes HOUSTON After more than a decade of successful
More informationQuantitative Interpretation
Quantitative Interpretation The aim of quantitative interpretation (QI) is, through the use of amplitude analysis, to predict lithology and fluid content away from the well bore. This process should make
More informationSCOOP Woodford. Regional Field Study
SCOOP Woodford Regional Field Study OVERVIEW The Woodford shale is an organic rich siliceous shale formation of late Devonian and early Mississippian age deposited throughout most of the Anadarko basin
More informationOptimizing the reservoir model of delta front sandstone using Seismic to Simulation workflow: A case study in the South China Sea
Optimizing the reservoir model of delta front sandstone using Seismic to Simulation workflow: Lin Li and Bin Tao, CNOOC (China) Panyu Operating Company; Haihong Wang*, Shulin Sun, Fengping Mu, Wanlong
More informationBrittleness analysis study of shale by analyzing rock properties
Brittleness analysis study of shale by analyzing rock properties *Ju Hyeon Yu, Sung Kyung Hong, Joo Yong Lee 1) and Dae Sung Lee 2) 1) Petroleum and Marine Resources Division, Korea Institute of Geoscience
More informationNet-to-gross from Seismic P and S Impedances: Estimation and Uncertainty Analysis using Bayesian Statistics
Net-to-gross from Seismic P and S Impedances: Estimation and Uncertainty Analysis using Bayesian Statistics Summary Madhumita Sengupta*, Ran Bachrach, Niranjan Banik, esterngeco. Net-to-gross (N/G ) is
More informationAn Integrated Petrophysical Approach for Shale Gas Reservoirs
An Integrated Petrophysical Approach for Shale Gas Reservoirs Richard Arnold & Matt Bratovich Baker Hughes Reservoir Development Services 1 2014 B A K E R H U G H E S I N C O R P O R A TED. A LL R I G
More informationRock Physics of Organic Shale and Its Implication
Rock Physics of Organic Shale and Its Implication Lev Vernik, Marathon Oil Corporation, Houston, USA lvernik@marathonoil.com Yulia Khadeeva, Marathon Oil Corporation, Houston, USA Cris Tuttle, Marathon
More informationAn Analytic Approach to Sweetspot Mapping in the Eagle Ford Unconventional Play
An Analytic Approach to Sweetspot Mapping in the Eagle Ford Unconventional Play Murray Roth*, Transform Software and Services, Denver, Colorado, Murray@transformsw.com Michael Roth, Transform Software
More informationURTeC: Abstract
URTeC: 2902950 Can Seismic Inversion Be Used for Geomechanics? A Casing Deformation Example Jeremy J. Meyer 1*, Jeremy Gallop 1, Alvin Chen 1, Scott Reynolds 1, Scott Mildren 1 ; 1. Ikon Science Copyright
More informationDetermine the azimuths of conjugate fracture trends in the subsurface
Reconnaissance of geological prospectivity and reservoir characterization using multiple seismic attributes on 3-D surveys: an example from hydrothermal dolomite, Devonian Slave Point Formation, northeast
More informationIntegrating rock physics modeling, prestack inversion and Bayesian classification. Brian Russell
Integrating rock physics modeling, prestack inversion and Bayesian classification Brian Russell Introduction Today, most geoscientists have an array of tools available to perform seismic reservoir characterization.
More informationSPE MS. Abstract. Introduction
SPE-176931-MS Sweet Spot Identification and Prediction of Frac Stage Performance Using Geology, Geophysics, and Geomechanics - Application to the Longmaxi Formation, China Yang, X., Wang, X., SCGC, Aoues,
More informationDETECTION AND QUANTIFICATION OF ROCK PHYSICS PROPERTIES FOR IMPROVED HYDRAULIC FRACTURING IN HYDROCARBON-BEARING SHALE
DETECTION AND QUANTIFICATION OF ROCK PHYSICS PROPERTIES FOR IMPROVED HYDRAULIC FRACTURING IN HYDROCARBON-BEARING SHALE Antoine Montaut, Paul Sayar, and Carlos Torres-Verdín The University of Texas at Austin
More informationSeismic reservoir characterisation
Seismic reservoir characterisation Unconventional reservoir (shale gas) Robert Porjesz 1 2014 B A K E R H U G H E S I N C O R P O R A TED. A LL R I G H TS R E S E R V E D. TERMS A N D C O N D I TI O N
More informationDownloaded 12/02/14 to Redistribution subject to SEG license or copyright; see Terms of Use at
Hydrocarbon-bearing dolomite reservoir characterization: A case study from eastern Canada Amit Kumar Ray, Ritesh Kumar Sharma* and Satinder Chopra, Arcis Seismic Solutions, TGS, Calgary, Canada. Summary
More informationGeological Classification of Seismic-Inversion Data in the Doba Basin of Chad*
Geological Classification of Seismic-Inversion Data in the Doba Basin of Chad* Carl Reine 1, Chris Szelewski 2, and Chaminda Sandanayake 3 Search and Discovery Article #41899 (2016)** Posted September
More informationGas Shale Hydraulic Fracturing, Enhancement. Ahmad Ghassemi
Gas Shale Hydraulic Fracturing, Stimulated Volume and Permeability Enhancement Ahmad Ghassemi Tight Gas A reservoir that cannot produce gas in economic quantities without massive fracture stimulation treatments
More informationDownloaded 09/16/16 to Redistribution subject to SEG license or copyright; see Terms of Use at
Ehsan Zabihi Naeini*, Ikon Science & Russell Exley, Summit Exploration & Production Ltd Summary Quantitative interpretation (QI) is an important part of successful Central North Sea exploration, appraisal
More informationDownloaded 11/02/16 to Redistribution subject to SEG license or copyright; see Terms of Use at Summary.
in thin sand reservoirs William Marin* and Paola Vera de Newton, Rock Solid Images, and Mario Di Luca, Pacific Exploración y Producción. Summary Rock Physics Templates (RPTs) are useful tools for well
More informationInterpretation. Vector correlation of AVAz and curvature in a post hydraulically fracture Barnett Shale survey
Vector correlation of AVAz and curvature in a post hydraulically fracture Barnett Shale survey Journal: Manuscript ID: INT--0 Manuscript Type: -0 Seismic attributes Date Submitted by the Author: -Jun-
More informationThis paper was prepared for presentation at the Unconventional Resources Technology Conference held in Denver, Colorado, USA, August 2013.
URTeC Control ID Number: 1581818 Correlation of Azimuthal AVO Gradient Anisotropic Analysis and Curvature on Prediction of Fractures on Barnett Shale Shiguang Guo*, Bo Zhang, Tengfei Lin, Kurt J. Marfurt
More informationOsareni C. Ogiesoba 1. Search and Discovery Article #10601 (2014)** Posted May 31, 2014
Seismic Multiattribute Analysis for Shale Gas/Oil within the Austin Chalk and Eagle Ford Shale in a Submarine Volcanic Terrain, Maverick Basin, South Texas* Osareni C. Ogiesoba 1 Search and Discovery Article
More informationRock Physics of Shales and Source Rocks. Gary Mavko Professor of Geophysics Director, Stanford Rock Physics Project
Rock Physics of Shales and Source Rocks Gary Mavko Professor of Geophysics Director, Stanford Rock Physics Project 1 First Question: What is Shale? Shale -- a rock composed of mud-sized particles, such
More informationThin Sweet Spots Identification in the Duvernay Formation of North Central Alberta*
Thin Sweet Spots Identification in the Duvernay Formation of North Central Alberta* Ritesh K. Sharma 1 and Satinder Chopra 1 Search and Discovery Article #10902 (2017)** Posted January 16, 2017 *Adapted
More informationA Review of Three North American Shale Plays: Learnings from Shale Gas Exploration in the Americas*
A Review of Three North American Shale Plays: Learnings from Shale Gas Exploration in the Americas* David Waldo 1 Search and Discovery Article #80214 (2012)** Posted May 28, 2012 *Adapted from oral presentation
More informationKeywords. PMR, Reservoir Characterization, EEI, LR
Enhancing the Reservoir Characterization Experience through Post Migration Reprocessed (PMR) Data A case study Indrajit Das*, Ashish Kumar Singh, Shakuntala Mangal, Reliance Industries Limited, Mumbai
More informationHalliburton Engineering for Success in Developing Shale Assets
Halliburton Engineering for Success in Developing Shale Assets Nov 30, 2010 Shale is a Very Broad Name Used to Describe a Large Category of Rock In conventional petroleum geology shale is thought of as
More informationExploration / Appraisal of Shales. Petrophysics Technical Manager Unconventional Resources
Exploration / Appraisal of Shales Rick Lewis Petrophysics Technical Manager Unconventional Resources Organic Shale Factors Controlling Gas Reservoir Quality Conventional sandstone Mineral framework Gas
More informationDownloaded 09/09/15 to Redistribution subject to SEG license or copyright; see Terms of Use at
Reservoir properties estimation from marine broadband seismic without a-priori well information: A powerful de-risking workflow Cyrille Reiser*, Matt Whaley and Tim Bird, PGS Reservoir Limited Summary
More informationKurt Marfurt Arnaud Huck THE ADVANCED SEISMIC ATTRIBUTES ANALYSIS
The Society of Exploration Geophysicists and GeoNeurale announce Kurt Marfurt Arnaud Huck THE ADVANCED SEISMIC ATTRIBUTES ANALYSIS 3D Seismic Attributes for Prospect Identification and Reservoir Characterization
More informationSTACK/STACK EXTENSION MERAMEC /OSAGE/ WOODFORD STUDY
STACK/STACK EXTENSION MERAMEC /OSAGE/ WOODFORD STUDY FIELD STUDIES OVERVIEW NUTECH has combined its expertise with the emerging interest in North American shale plays in order to develop the most detailed
More informationKurt Marfurt Arnaud Huck THE ADVANCED SEISMIC ATTRIBUTES ANALYSIS
The Society of Exploration Geophysicists and GeoNeurale announce Kurt Marfurt Arnaud Huck THE ADVANCED SEISMIC ATTRIBUTES ANALYSIS 3D Seismic Attributes for Prospect Identification and Reservoir Characterization
More informationThe SPE Foundation through member donations and a contribution from Offshore Europe
Primary funding is provided by The SPE Foundation through member donations and a contribution from Offshore Europe The Society is grateful to those companies that allow their professionals to serve as
More informationRESERVOIR CHARACTERIZATION FOR UNCONVENTIONAL RESOURCE POTENTIAL, PITSANULOK BASIN, ONSHORE THAILAND. Prat Boonyasatphan
RESERVOIR CHARACTERIZATION FOR UNCONVENTIONAL RESOURCE POTENTIAL, PITSANULOK BASIN, ONSHORE THAILAND by Prat Boonyasatphan Copyright by Prat Boonyasatphan, 2017 All Rights Reserved A thesis submitted to
More informationDetermination of Duvernay Formation Reservoir Properties through Probabilistic Petrophysical Analysis calibrated to Core Studies.
Determination of Duvernay Formation Reservoir Properties through Probabilistic Petrophysical Analysis calibrated to Core Studies. Nasir Rahim, Neil Watson Canadian Discovery Ltd. Summary The petrophysical
More informationThis paper was prepared for presentation at the Unconventional Resources Technology Conference held in Denver, Colorado, USA, August 2013.
URTeC Control ID 1619856 1 URTeC Control ID Number: 1619856 Distance Metric Based Multi-Attribute Seismic Facies Classification to Identify Sweet Spots within the Barnett shale: A Case Study from the Fort
More informationStatistical Rock Physics
Statistical - Introduction Book review 3.1-3.3 Min Sun March. 13, 2009 Outline. What is Statistical. Why we need Statistical. How Statistical works Statistical Rock physics Information theory Statistics
More informationA Case Study into the Successful Evaluation and Completion Nonconventional. Jorge Viamontes, PhD VP Reservoir Intelligence, NUTECH
A Case Study into the Successful Evaluation and Completion Nonconventional Wells in Mexico Jorge Viamontes, PhD VP Reservoir Intelligence, Presentation Outline - experience in the Eagle Ford and Burgos
More informationTechnology of Production from Shale
Technology of Production from Shale Doug Bentley, European Unconventional, Schlumberger May 29 th, 2012 Johannesburg, South Africa What are Unconventional Reservoirs Shale both Gas & Oil Coal Bed Methane
More informationISSN Online: X ISSN Print: Shale Gas Potential in Pakistan: By comparison of Sembar formation and Barnett Shale Texas
Journal of Electrical Power & Energy Systems, 2018, 2(9), 19-25 http://www.hillpublisher.com/journals/jepes/ ISSN Online: 2576-053X ISSN Print: 2576-0521 Shale Gas Potential in Pakistan: By comparison
More informationThe Marrying of Petrophysics with Geophysics Results in a Powerful Tool for Independents Roger A. Young, eseis, Inc.
The Marrying of Petrophysics with Geophysics Results in a Powerful Tool for Independents Roger A. Young, eseis, Inc. While the application of new geophysical and petrophysical technology separately can
More informationReservoir connectivity uncertainty from stochastic seismic inversion Rémi Moyen* and Philippe M. Doyen (CGGVeritas)
Rémi Moyen* and Philippe M. Doyen (CGGVeritas) Summary Static reservoir connectivity analysis is sometimes based on 3D facies or geobody models defined by combining well data and inverted seismic impedances.
More informationCHARACTERIZING RESERVOIR PROPERTIES OF THE HAYNESVILLE SHALE USING THE SELF-CONSISTENT MODEL AND A GRID SEARCH METHOD.
CHARACTERIZING RESERVOIR PROPERTIES OF THE HAYNESVILLE SHALE USING THE SELF-CONSISTENT MODEL AND A GRID SEARCH METHOD Meijuan Jiang Department of Geological Sciences The University of Texas at Austin ABSTRACT
More informationComparative Study of AVO attributes for Reservoir Facies Discrimination and Porosity Prediction
5th Conference & Exposition on Petroleum Geophysics, Hyderabad-004, India PP 498-50 Comparative Study of AVO attributes for Reservoir Facies Discrimination and Porosity Prediction Y. Hanumantha Rao & A.K.
More informationFifteenth International Congress of the Brazilian Geophysical Society. Copyright 2017, SBGf - Sociedade Brasileira de Geofísica
Geostatistical Reservoir Characterization in Barracuda Field, Campos Basin: A case study Frank Pereira (CGG)*, Ted Holden (CGG), Mohammed Ibrahim (CGG) and Eduardo Porto (CGG). Copyright 2017, SBGf - Sociedade
More informationAn overview of AVO and inversion
P-486 An overview of AVO and inversion Brian Russell, Hampson-Russell, CGGVeritas Company Summary The Amplitude Variations with Offset (AVO) technique has grown to include a multitude of sub-techniques,
More informationGeosciences Career Pathways (Including Alternative Energy)
Geosciences Career Pathways (Including Alternative Energy) Shale Carbonates Clastics Unconventionals Geology Characterization and Production Properties of Gas Shales Geomechanics in International Shale
More informationSearch and Discovery Article # (2015) Posted April 20, 2015
Considering the Vertical Variation in Rock Mechanical Properties of a Lithologic Zone Using Laboratory Derived Data Is it Time for Geomechanical Stratigraphy?* Douglas E. Wyatt 1, Jesse Hampton 1, Dandan
More informationComparison of Reservoir Quality from La Luna, Gacheta and US Shale Formations*
Comparison of Reservoir Quality from La Luna, Gacheta and US Shale Formations* Joel Walls 1 and Elizabeth Diaz 2 Search and Discovery Article #41396 (2014) Posted July 24, 2014 *Adapted from oral presentation
More informationUsing multicomponent seismic for reservoir characterization in Venezuela
Using multicomponent seismic for reservoir characterization in Venezuela REINALDO J. MICHELENA, MARÍA S. DONATI, ALEJANDRO A. VALENCIANO, and CLAUDIO D AGOSTO, Petróleos de Venezuela (Pdvsa) Intevep, Caracas,
More informationSpecial section: Interpretation for unconventional resources
t Special section: Interpretation for unconventional resources Downloaded 03/04/14 to 129.15.127.245. Redistribution subject to SEG license or copyright; see Terms of Use at http://library.seg.org/ Integration
More information4D stress sensitivity of dry rock frame moduli: constraints from geomechanical integration
Title 4D stress sensitivity of dry rock frame moduli: constraints from geomechanical integration Authors Bloomer, D., Ikon Science Asia Pacific Reynolds, S., Ikon Science Asia Pacific Pavlova, M., Origin
More informationConstraining seismic rock-property logs in organic shale reservoirs
Constraining seismic rock-property logs in organic shale reservoirs Malleswar Yenugu 1 and Lev Vernik 2 Abstract One of the major challenges of unconventional shale reservoirs is to understand the effects
More informationInterpretation and Reservoir Properties Estimation Using Dual-Sensor Streamer Seismic Without the Use of Well
Interpretation and Reservoir Properties Estimation Using Dual-Sensor Streamer Seismic Without the Use of Well C. Reiser (Petroleum Geo-Services), T. Bird* (Petroleum Geo-Services) & M. Whaley (Petroleum
More informationStochastic vs Deterministic Pre-stack Inversion Methods. Brian Russell
Stochastic vs Deterministic Pre-stack Inversion Methods Brian Russell Introduction Seismic reservoir analysis techniques utilize the fact that seismic amplitudes contain information about the geological
More informationPETROLEUM GEOSCIENCES GEOLOGY OR GEOPHYSICS MAJOR
PETROLEUM GEOSCIENCES GEOLOGY OR GEOPHYSICS MAJOR APPLIED GRADUATE STUDIES Geology Geophysics GEO1 Introduction to the petroleum geosciences GEO2 Seismic methods GEO3 Multi-scale geological analysis GEO4
More information