Analyzing the Well-Interference Phenomenon in the Eagle Ford Shale/Austin Chalk Production System With a Comprehensive Compositional Reservoir Model
- Hewei Tang (Texas A&M University) | Bicheng Yan (Texas A&M University (now with Sanchez Oil and Gas)) | Zhi Chai (Texas A&M University) | Lihua Zuo (Texas A&M University) | John Killough (Texas A&M University) | Zhuang Sun (University of Texas at Austin)
- Document ID
- Society of Petroleum Engineers
- SPE Reservoir Evaluation & Engineering
- Publication Date
- September 2018
- Document Type
- Journal Paper
- 2018.Society of Petroleum Engineers
- embedded discrete fracture model, well interference, multi-segment well model, compositional reservoir model, nanopore confinement effect
- 16 in the last 30 days
- 361 since 2007
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Well interference is a common phenomenon in unconventional-reservoir development. The completion and production of infill wells can lead to either positive or negative well-interference impacts on the existing producers. Many researchers have investigated the well-interference phenomenon; however, few of them attempted to apply rigorous simulation methods to analyze both positive and negative well-interference effects, especially in two different formations. In this work, we develop a comprehensive compositional reservoir model to study the well-interference phenomena in the Eagle Ford Shale/Austin Chalk production system. The reservoir model considers capillary pressure in the vapor/liquid-equilibrium (VLE) equation (nanopore-confinement effect), and applies the embedded discrete-fracture model (EDFM) for dynamic fracture modeling. We also include a multisegment-well model to characterize the wellbore-crossflow effect introduced by fracture hits. The simulation results indicate that negative well-interference impact is much more common in the production system. With a smaller permeability difference, the hydraulic-fracturing effect can lead to a positive well-interference period of several hundred days. The nanopore-confinement effect in the Eagle Ford Shale can contribute to the negative well-interference effect. We also analyze the impact of other factors such as initial reservoir pressure, matrix porosity, initial water saturation, and the natural-fracture system on the well performance. Our work provides valuable insights into dynamic well performance under the impact of well interference.
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Agboada, D. K. and Ahmadi, M. 2013. Production Decline and Numerical Simulation Model Analysis of the Eagle Ford Shale Play. Presented at the SPE Western Regional and AAPG Pacific Section Meeting 2013 Joint Technical Conference, Monterey, California, 19–25 April. SPE-165315-MS. https://doi.org/10.2118/165315-MS.
Ajani, A. A. and Kelkar, M. G. 2012. Interference Study in Shale Plays. Presented at the SPE Hydraulic Fracturing Technology Conference, The Woodlands, Texas, 6–8 February. SPE-151045-MS. https://doi.org/10.2118/151045-MS.
Awada, A., Santo, M., Lougheed, D. et al. 2016. Is That Interference? A Work Flow for Identifying and Analyzing Communication Through Hydraulic Fractures in a Multiwell Pad. SPE J. 21 (5): 1554–1566. SPE-178509-PA. https://doi.org/10.2118/178509-PA.
Cao, H. 2002. Development of Techniques for General Purpose Simulators. PhD dissertation, Stanford University, Stanford, California.
Chai, Z., Yan, B., Killough, J. E. et al. 2018. An Efficient Method for Fractured Shale Reservoir History Matching: The Embedded Discrete Fracture Multi-Continuum Approach. J. Pet. Sci. Eng. 160: 170–181. https://doi.org/10.1016/j.petrol.2017.10.055.
Energy Information Agency. 2010. Eagle Ford Shale Play, Western Gulf Basin, South Texas. URL http://www.eia.gov/oil_gas/rpd/shaleusa9.pdf. (accessed September 21, 2017).
Fjar, E., Holt, R. M., Raaen, A. M. et al. 2008. Petroleum-Related Rock Mechanics. Elsevier.
He, Y., Cheng, S., Li, S. et al. 2017. A Semianalytical Methodology To Diagnose the Locations of Underperforming Hydraulic Fractures Through Pressure-Transient Analysis in Tight Gas Reservoir. SPE J. 22 (3): 924–939. SPE-185166-PA. https://doi.org/10.2118/185166-PA.
Hentz, T. F. and Ruppel, S. C. 2010. Regional Lithostratigraphy of the Eagle Ford Shale: Maverick Basin to East Texas Basin. Gulf Coast Assoc. Geol. Soc. Trans. 60: 325–337.
Holmes, J. 1983. Enhancements to the Strongly Coupled, Fully Implicit Well Model: Wellbore Crossflow Modeling and Collective Well Control. Presented at the SPE Symposium on Reservoir Simulation, San Francisco, 15–18 November. SPE-12259-MS. https://doi.org/10.2118/12259-MS.
Hovorka, S. D. 1998. Facies and Diagenesis of the Austin Chalk and Controls on Fracture Intensity—A Case Study From North Central Texas. The University of Texas at Austin, Bureau of Economic Geology, Geological Circular 98-2, 47 p.
Jia, P., Cheng, L., Clarkson, C. R. et al. 2017. A Laplace-Domain Hybrid Model for Representing Flow Behavior of Multifractured Horizontal Wells Communicating Through Secondary Fractures in Unconventional Reservoirs. SPE J. 22 (6): 1856–1876. SPE-186109-PA. https://doi.org/10.2118/186109-PA.
Jiang, J. and Younis, R. M. 2017. An Improved Projection-Based Embedded Discrete Fracture Model (Pedfm) for Multiphase Flow in Fractured Reservoirs. Adv. Water Resour. 109: 267–289. https://doi.org/10.1016/j.advwatres.2017.09.017.
Kou, R., Alafnan, S. F. K., and Akkutlu, I. Y. 2017. Multi-Scale Analysis of Gas Transport Mechanisms in Kerogen. Transport in Porous Media 116 (2): 493–519.
Kurtoglu, B. and Salman, A. 2015. How To Utilize Hydraulic-Fracture Interference to Improve Unconventional Development. Presented at the Abu Dhabi International Petroleum Exhibition and Conference, Abu Dhabi, 9–12 November. SPE-177953-MS. https://doi.org/10.2118/177953-MS.
Liu, Q., Tian, S., Li, G. et al. 2018. An Analytical Model for Fracture Initiation From Radial Lateral Borehole. Journal of Petroleum Science and Engineering 164 (May): 206–218. https://doi.org/10.1016/j.petrol.2018.01.056.
Marongiu-Porcu, M., Lee, D., Shan, D. et al. 2016. Advanced Modeling of Interwell-Fracturing Interference: An Eagle Ford Shale-Oil Study. SPE J. 21 (5): 1567–1582. SPE-174902-PA. https://doi.org/10.2118/174902-PA.
Martin, R., Baihly, J. D., Malpani, R. et al. 2011. Understanding Production From Eagle Ford-Austin Chalk System. Presented at the SPE Annual Technical Conference and Exhibition, Denver, 30 October–2 November. SPE-145117-MS. https://doi.org/10.2118/145117-MS.
Moinfar, A. 2013. Development of an Efficient Embedded Discrete Fracture Model for 3D Compositional Reservoir Simulation in Fractured Reservoirs. PhD dissertation, The University of Texas at Austin.
Nojabaei, B., Johns, R. T., Chu, L. et al. 2013. Effect of Capillary Pressure on Phase Behavior in Tight Rocks and Shales. SPE Res Eval & Eng 16 (3): 281–289. SPE-159258-PA. https://doi.org/10.2118/159258-PA.
Okeahialam, I., Yang, M., Shinde, D. B. et al. 2017. Completion Optimization Under Constraints: An Eagle Ford Shale Case Study. SPE Prod. & Oper 32 (2): 128–136. SPE-174057-PA. https://doi.org/10.2118/174057-PA.
Pearson, K. 2010. Geologic Controls on Austin Chalk Oil and Gas Production: Understanding a Dual Conventional-Continuous Accumulation. Gulf Coast Assoc. Geol. Soc. Trans. 60: 557–570.
Peng, D.-Y. and Robinson, D. B. 1976. A New Two-Constant Equation of State. Ind. Eng. Chem. Fundam. 15 (1): 59–64. https://doi.org/10.1021/i160057a011.
Sahai, V., Jackson, G., Lawal, H. et al. 2015. A Quantitative Approach To Analyze Fracture-Area Loss in Shale Gas Wells During Field Development and Restimulation. SPE Res Eval & Eng 18 (3): 346–355. SPE-169406-PA. https://doi.org/10.2118/169406-PA.
Siripatrachai, N., Ertekin, T., and Johns, R. T. 2017. Compositional Simulation of Hydraulically Fractured Tight Formation Considering the Effect of Capillary Pressure on Phase Behavior. SPE J. 22 (4): 1046–1063. SPE-179660-PA. https://doi.org/10.2118/179660-PA.
Stone, H. L. 1973. Estimation of Three-Phase Relative Permeability and Residual Oil Data. J Can Pet Technol 12 (4): 53–61. PETSOC-73-04-06. https://doi.org/10.2118/73-04-06.
Stone, T., Edmunds, N., and Kristoff, B. 1989. A Comprehensive Wellbore/Reservoir Simulator. Presented at the SPE Symposium on Reservoir Simulation, Houston, 6–8 February. SPE-18419-MS. https://doi.org/10.2118/18419-MS.
Tang, H., Chai, Z., Yan, B. et al. 2017a. Application of Multi-Segment Well Modeling To Simulate Well Interference. Presented at the SPE/AAPG/SEG Unconventional Resources Technology Conference, Austin, Texas, 24–26 July. URTEC-2668100-MS.
Tang, H., Killough, J. E., Heidari, Z. et al. 2017b. A New Technique To Characterize Fracture Density by Use of Neutron Porosity Logs Enhanced by Electrically Transported Contrast Agents. SPE J. 22 (4): 1034–1045. SPE-181509-PA. https://doi.org/10.2118/181509-PA.
Tunstall, T. 2015. Iterative Bass Model Forecasts for Unconventional Oil Production in the Eagle Ford Shale. Energy 93: 580–588. https://doi.org/10.1016/j.energy.2015.09.072.
Valbuena Olivares, E. 2015. Production Performance Modeling Through Integration of Reservoir and Production Network With Asphaltene Deposition. PhD dissertation, Texas A&M University, College Station, Texas.
Walls, J. D. and Sinclair, S. W. 2011. Eagle Ford Shale Reservoir Properties From Digital Rock Physics. First Break 29 (6): 97–101.
Xu, Y., Cavalcante Filho, J. S. A., Yu, W. et al. 2017. Discrete-Fracture Modeling of Complex Hydraulic-Fracture Geometries in Reservoir Simulators. SPE Res Eval & Eng 20 (2): 403–422. SPE-183647-PA. https://doi.org/10.2118/183647-PA.
Yan, B. 2017. Development of General Unstructured Reservoir Utility and Fracture Reservoir Modeling. PhD dissertation, Texas A&M University, College Station, Texas.
Yan, B., Wang, Y., and Killough, J. E. 2017. A Fully Compositional Model Considering the Effect of Nanopores in Tight Oil Reservoirs. J. Pet. Sci. Eng. 152: 675–682. https://doi.org/10.1016/j.petrol.2017.01.005.
Yu, W., Xu, Y., Weijermars, R. et al. 2018. A Numerical Model for Simulating Pressure Response of Well Interference and Well Performance in Tight Oil Reservoirs With Complex-Fracture Geometries Using the Fast Embedded-Discrete-Fracture-Model Method. SPE Res Eval & Eng 21 (2): 489–502. SPE-184825-PA. https://doi.org/10.2118/184825-PA.
Zhang, Y., Lashgari, H. R., Di, Y. et al. 2017a. Capillary Pressure Effect on Phase Behavior of CO2/Hydrocarbons in Unconventional Reservoirs. Fuel 197: 575–582. https://doi.org/10.1016/j.fuel.2017.02.021.
Zhang, Y., Yu, W., Sepehrnoori, K. et al. 2017b. A Comprehensive Numerical Model for Simulating Fluid Transport in Nanopores. Scientific Reports 7. https://doi.org/10.1038/srep40507.