Use of a New Analytical Model To Match Production Data and Identify Opportunities To Maximize Well Productivity in the Tuscaloosa Marine Shale Reservoir
- Boyun Guo (University of Louisiana, Lafayette) | Xu Yang (University of Louisiana, Lafayette)
- Document ID
- Society of Petroleum Engineers
- SPE Production & Operations
- Publication Date
- November 2019
- Document Type
- Journal Paper
- 770 - 780
- 2019.Society of Petroleum Engineers
- production, oil, shale, TMS, fracturing
- 6 in the last 30 days
- 122 since 2007
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The low productivity of the oil wells in the Tuscaloosa Marine Shale (TMS) Trend, located in Louisiana and Mississippi, is a mystery. Production data from 55 wells in the TMS Trend were analyzed to identify possible means of enhancing well productivity. The -1/2 slope in a log-log plot for reservoir linear flow (RLF) was observed for some wells, but not all, and the -1 slope for boundarydominated flow (BDF) has not been seen in the past 5 years of production. The behavior of the TMS wells is attributed to the ultralow permeability of the TMS matrix and the decline of fracture conductivity, both of which delay the BDF. On the basis of the concept of the distance of investigation, derived from the radius-of-investigation concept, the matrix permeability of the seven TMS wells was estimated to be between 34 and 65 nd, with an average of 51 nd. A new mathematical model for production decline of multifractured horizontal wells was developed taking into consideration the time-dependent fracture conductivity during the BDF period. This model fits TMS-well production data, with an average error of 6.12% and an R2 value of 0.96. Assuming constant matrix permeability, fitting the new model to the production data in the BDF period gives a rate of fracture-conductivity decline of between 0.20 and 0.74% per month. The new mathematical model reveals opportunities to optimize well completion to enhance well productivity in the TMS Trend. For a given amount of fracture proppant allocated to a well, the shortest possible fracture spacing should be used to maximize well productivity. If the number of fractures is fixed as a constraint of well completion design, well productivity is inversely proportional to the square root of fracture spacing (i.e., if the fracture spacing is shortened by fourfold, well productivity is expected to double). If the horizontal wellbore length is fixed as a constraint of well completion, well productivity is inversely proportional to fracture spacing (i.e., if the fracture spacing is shortened by 50%, well productivity is expected to double).
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Ambrose, R. J., Clarkson, C. R., Youngblood, J. E. et al. 2011. Life-Cycle Decline Curve Estimation for Tight/Shale Reservoirs. Presented at the SPE Hydraulic Fracturing Technology Conference, The Woodlands, Texas, 24–26 January. SPE-140519-MS. https://doi.org/10.2118/140519-MS.
Attanasi, E. D., Coburn, T. C., and Ran-McDonald, B. 2019. Statistical Detection of Flow Regime Changes in Horizontal Hydraulically Fractured Bakken Oil Wells. Nat Resour Res 28 (1): 259–272. https://doi.org/10.1007/s11053-018-9389-0.
Besov, A., Tinni, A., Sondergeld, C. et al. 2017. Application of Laboratory and Field NMR To Characterize the Tuscaloosa Marine Shale. Petrophysics 58 (3): 221–231. SPWLA-2017-v58n3a1.
Chaudhary, A. S., Ehlig-Economides, C., and Wattenbarger, R. 2011. Shale Oil Production Performance From a Stimulated Reservoir Volume. Presented at the SPE Annual Technical Conference and Exhibition, Denver, Colorado, 30 October–2 November. SPE-147596-MS. https://doi.org/10.2118/ 147596-MS.
Cheng, Y. 2011. Pressure Transient Characteristics of Hydraulically Fractured Horizontal Shale Gas Wells. Presented at the SPE Eastern Regional Meeting, Columbus, Ohio, 17–19 August. SPE-149311-MS. https://doi.org/10.2118/149311-MS.
Dake, L. P. 1978. Fundamentals of Reservoir Engineering, first edition. Amsterdam: Elsevier.
Evans, S., Siddiqui, S., and Magness, J. 2018. Impact of Cluster Spacing on Infill Completions in the Eagle Ford. Presented at the SPE/AAPG/SEG Unconventional Resources Technology Conference, Houston, Texas, 23–25 July. URTEC-2899323-MS. https://doi.org/10.15530/URTEC-2018- 2899323.
Gong, X., Tian, Y., McVay, D. A. et al. 2013. Assessment of Eagle Ford Shale Oil and Gas Resources. Presented at the SPE Unconventional Resources Conference Canada, Calgary, Alberta, Canada, 5–7 November. SPE-167241-MS. https://doi.org/10.2118/167241-MS.
Guo, B., Yu, X., and Khoshgahdam, M. 2009. A Simple Analytical Model for Predicting Productivity of Multifractured Horizontal Wells. SPE Res Eval & Eng 12 (6): 879-885. SPE-114452-PA. https://doi.org/10.2118/114452-PA.
John, C. J., Jones B. L., Moncrief J. E. et al. 1997. An Unproven Unconventional Seven Billion Barrel Oil Resource: The Tuscaloosa Marine Shale, Basin Res Instit Bull, Louisiana State University, 1–22.
Li, G., Guo, B., Li, J. et al. 2019. A Mathematical Model for Predicting Long-Term Productivity of Modern Multifractured Shale Gas/Oil Wells. SPE Drill & Compl 34 (2): 114–127. SPE-194495-PA. https://doi.org/10.2118/194495-PA.
Li, J., Guo, B., and Ling, K. 2012. Case Studies Suggest Heterogeneity is a Favorable Characteristic of Shale Gas Reservoirs. Presented at the SPE Canadian Unconventional Resources Conference, Calgary, Alberta, Canada, 30 October–1 November. SPE-162702-MS. https://doi.org/10.2118/162702-MS.
Lohr, C. D., Hackley, P. C., Valentine, B. J. et al. 2017. Thermal Gradient Trends in the Tuscaloosa Marine Shale Play Area: Preliminary Results from Studies To Support Oil and Natural Gas Resources Assessments. In GCAGS Trans 66: 1099–1108.
Makinde, I. and Lee, J. 2016. Forecasting Production of Shale Volatile Oil Reservoirs Using Simple Models. Presented at the SPE/IAEE Hydrocarbon Economics and Evaluation Symposium, Houston, Texas, 17–18 May. SPE-179964-MS. https://doi.org/10.2118/179964-MS.
Marsden, J., Kostyleva, M. R., and Gringarten, A. C. 2018. A Conceptual Model for Predicting Production from the Haynesville Shale. Hydraulic Fract J 5 (2): 17–24.
Miller, C. and Bolton, J. 2016. Economic Development Strategies for Fracking: The Case of the Tuscaloosa Marine Shale Play. J Energy Dev 41 (1): 201–222. https://www.jstor.org/stable/90005937.
Mississippi State Oil and Gas Board. 2017. http://www.ogb.state.ms.us/TMSDevelopment.php (accessed 29 August 2018).
Nobakht, M. and Mattar, L. 2012. Analyzing Production Data from Unconventional Gas Reservoirs with Linear Flow and Apparent Skin. J Can Pet Technol 51 (1): 52–59. SPE-137454-PA. https://doi.org/10.2118/137454-PA.
Orangi, A., Nagarajan, N. R., Honarpour, M. M. et al. 2011. Unconventional Shale Oil and Gas-Condensate Reservoir Production, Impact of Rock, Fluid, and Hydraulic Fractures. Presented at the SPE Hydraulic Fracturing Technology Conference and Exhibition, The Woodlands, Texas, 24–26 January. SPE-140536-MS. https://doi.org/10.2118/140536-MS.
Rincones, M. D., Lee, W. J., and Rutledge, J. M. 2015. Production Forecasting for Shale Oil: Workflow. Presented at the SPE Asian Pacific Unconventional Resources Conference and Exhibition, Brisbane, Australia, 9–11 November. SPE-177018-MS. https://doi.org/10.2118/177018-MS.
Shi, X., Yang, X., Meng, Y. et al. 2016. An Anisotropic Strength Model for Layered Rocks Considering Planes of Weakness. Rock Mech Rock Eng 49 (9): 3783–3792. https://doi.org/10.1007/s00603-016-0985-1.
Singh, M., Samadhiya, N. K., Kumar, A. et al. 2015. A Nonlinear Criterion for Triaxial Strength of Inherently Anisotropic Rocks. Rock Mech Rock Eng 48 (4): 1387–1405. https://doi.org/10.1007/s00603-015-0708-z.
Stewart, G. 2014. Integrated Analysis of Shale Gas Well Production Data. Presented at the SPE Asia Pacific Oil & Gas Conference and Exhibition, Adelaide, Australia, 14–16 October. SPE-171420-MS. https://doi.org/10.2118/171420-MS.
Sun, H., Ouyang, W., Zhang, M. et al. 2018. Advanced Production Decline Analysis of Tight Gas Wells with Variable Fracture Conductivity. Petrol Explor Dev 45 (3): 472–480. https://doi.org/10.1016/S1876-3804(18)30052-1.
Sun, H., Zhou, D., Chawathé, A. et al. 2016. Quantifying Shale Oil Production Mechanisms by Integrating a Delaware Basin Well Data from Fracturing to Production. Presented at the SPE/AAPG/SEG Unconventional Resources Technology Conference, San Antonio, Texas, 1–3 August. URTEC-2425721-MS. https://doi.org/10.15530/URTEC-2016-2425721.
Teng, W., Qiao, X., Teng, L. et al. 2016. Production Performance Analysis of Multiple Fractured Horizontal Wells with Finite-Conductivity Fractures in Shale Gas Reservoirs. J Nat Gas Sci Eng 36: 747–759. https://doi.org/10.1016/j.jngse.2016.10.030.
Tran, T., Sinurat, P., and Wattenbarger, B. A. 2011. Production Characteristics of the Bakken Shale Oil. Presented at the SPE Annual Technical Conference and Exhibition, Denver, Colorado, 30 October–2 November. SPE-145684-MS. https://doi.org/10.2118/145684-MS.
Vicente, R. and Ertekin, T. 2006. Modeling of Coupled Reservoir and Multifractured Horizontal Well Flow Dynamics. Presented at the SPE Annual Technical Conference and Exhibition, San Antonio, Texas, 24–27 September. SPE-101929-MS. https://doi.org/10.2118/101929-MS.
Wan, J. and Aziz, K. 2002. Semi-Analytical Well Model of Horizontal Wells with Multiple Hydraulic Fractures. SPE J. 7 (4): 437–445. SPE-81190-PA. https://doi.org/10.2118/81190-PA.
Wang, J., Elsworth, D., and Ma, T. 2018. Conductivity Evolution of Proppant-Filled Hydraulic Fractures. Presented at the 52nd U.S. Rock Mechanics/Geomechanics Symposium, Seattle, Washington, 17–20 June. ARMA-2018-111.
Wang, J. and Liu, Y. 2011. Well Performance Modelling of Eagle Ford Shale Oil Reservoirs. Presented at the SPE North American Unconventional Gas Conference and Exhibition, The Woodlands, Texas, 14–16 June. SPE-144427-MS. https://doi.org/10.2118/144427-MS.
Wen, Q., Zhang, S., and Wang, L. 2005. Influence of Proppant Embedment on Fracture Long Term Flow Conductivity. Natural Gas Industry 25 (5): 65–68.
Yang, C., Sharma, V. K., Datta-Gupta, A. et al. 2015. A Novel Approach for Production Transient Analysis of Shale Gas/Oil Reservoirs. Presented at the SPE/AAPG/SEG Unconventional Resources Technology Conference, San Antonio, Texas, 20–22 July. URTEC-2176280-MS. https://doi.org/10.15530/URTEC-2015-2176280.
Yu, S. 1987. Evaluation of Long Term Fracture Conductivity of Ceramsite Proppant and Lanzhou Fracturing Sand. Oil Drill & Product Techn 9 (5): 93–100.
Yu, W., Xu, Y., Weijermars, R. et al. 2017. Impact of Well Interference on Shale Oil Production Performance: A Numerical Model for Analyzing Pressure Response of Fracture Hits with Complex Geometries. Presented at the SPE Hydraulic Fracturing Technology Conference and Exhibition, The Woodlands, Texas, 24–26 January. SPE-184825-MS. https://doi.org/10.2118/184825-MS.
Yuan, H., Soar, L., Packer, R. et al. 2013. A Case Study To Evaluate Shale Oil Production Performance Models with Actual Well Production Data. Presented at the SPE/AAPG/SEG Unconventional Resources Technology Conference, Denver, Colorado, 12–14 August. URTEC-1582234-MS. https://doi.org/10.15530/URTEC-1582234-MS.
Zerzar, A. and Bettam, Y. 2003. Interpretation of Multiple Hydraulically Fractured Horizontal Wells in Closed Systems. Presented at the SPE International Improved Oil Recovery Conference in Asia Pacific, Kuala Lumpur, 20–21 October. SPE-84888-MS. https://doi.org/10.2118/ 84888-MS.
Zhang, J., Ouyang, L., Zhu, D. et al. 2015. Experimental and Numerical Studies of Reduced Fracture Conductivity due to Proppant Embedment in the Shale Reservoir. J Petrol Sci Eng 130 (June): 37–45. https://doi.org/10.1016/j.petrol.2015.04.004.
Zhang, Z. and Wang, B. 2017. A Simple Analytical Model for Estimating Long-Term Productivity of Multi-Fractured Shale Gas Wells. Int J Engin Res App 7 (7): 6–15. https://doi.org/10.9790/9622-0707040615.
Zhou, P., Pan, Y., Sang, H. et al. 2018. Criteria for Proper Production Decline Models and Algorithm for Decline Curve Parameter Inference. Presented at the SPE/AAPG/SEG Unconventional Resources Technology Conference, Houston, Texas, 23–25 July. URTEC-2903078-MS. https://doi.org/10.15530/URTEC-2018-2903078.