AI Chat Paper
Note: Please note that the following content is generated by AMiner AI. SciOpen does not take any responsibility related to this content.
{{lang === 'zh_CN' ? '文章概述' : 'Summary'}}
{{lang === 'en_US' ? '中' : 'Eng'}}
Chat more with AI
PDF (649.9 KB)
Collect
Submit Manuscript AI Chat Paper
Show Outline
Outline
Show full outline
Hide outline
Outline
Show full outline
Hide outline
Original Article | Open Access

Automatic fracture optimization for shale gas reservoirs based on gradient descent method and reservoir simulation

Research Institute of Petroleum Exploration & Development, Beijing 100089, P. R. China
Department of Petroleum Engineering, Colorado School of Mines, Golden, CO 80401, USA
College of Energy, State Key Laboratory of Oil and Gas Reservoir Geology and Exploitation, Chengdu University of Technology, Chengdu 610059, P. R. China
School of Petroleum Engineering, Southwest Petroleum University, Chengdu 610500, P. R. China
Show Author Information

Abstract

In shale gas reservoir development, determination of hydraulic fracture geometry for horizontal wells is a demanding yet challenging task. One type of approach for hydraulic fracture optimization is based on reservoir simulation. To improve optimization efficiency and accuracy, an automatic and robust procedure integrating the gradient descent method with gas reservoir simulation has been developed. Fractured reservoir models were constructed using the "Multiple INteracting Continua" method, whereby an in-house shale gas reservoir simulator was implemented to model multiple gas transport mechanisms including non-Darcy flow, gas desorption, Klinkenberg effect, and geomechanical effect. The optimization procedure was first validated against two ideal cases and then applied to two realistic cases to optimize fracture spacing, half-length, and dimensionless fracture conductivity. It showed that the optimization results depend on optimization objective, reservoir property, natural fractures, economics and termination criteria. This gradient descent assisted fracture optimization procedure can achieve significant computational reduction and high prediction accuracy for various shale gas reservoir cases.

References

 
Asadollahi, M., Naevdal, G. Waterflooding optimization using gradient based methods. Paper SPE 125331 Presented at SPE/EAGE Reservoir Characterization & Simulation Conference, Abu Dhabi, UAE, 19-21 October, 2009.
 
Bangerth, W., Klie, H., Wheeler, M., et al. On optimization algorithm for the reservoir oil well placement problem. Computational Geosciences, 2006, 10: 303-319.
 
Bellout, M. C., Echeverría Ciaurri, D., Durlofsky, L. J., et al. Joint optimization of oil well placement and controls. Computational Geosciences, 2012, 16: 1061.
 
Brake, A. C. Fracture optimization in a giant gas field. Paper SPE 164029 Presented at SPE Unconventional Gas Conference and Exhibition, Muscat, Oman, 28-30 January, 2013.
 
Chen, C., Jin, L., Gao, G., et al. Assisted history matching using three derivative-free optimization algorithms. Paper SPE 154112 Presented at Spe Europec/eage Conference, Copenhagen, Denmark, 4-7 June, 2012.
 
Cui, X. Poststack impedance inversion using improved particle swarm optimization. Paper Presented at Society of Exploration Geophysicists SEG Technical Program Expanded Abstracts 2016, Dallas, Texas, 16 October-21 October, 2016.
 
Goodfellow, I., Bengio, Y., Courville, A. Deep Learning: Adaptive Computation and Machine Learning Series, 2016 Edition. Massachusetts, USA, The MIT Press, 2016.
 
Hajizadeh, Y., Christie, M. A., Demyanov, V. Ant colony optimization algorithm for history matching. Paper SPE 121193 Presented at Society of Petroleum Engineers EUROPEC/EAGE Conference and Exhibition, Amsterdam, Netherlands, 8-11 June, 2009.
 
Hefley, B., Seydor, S. The economic impact of the value chain of a Marcellus shale well. Social Science Electronic Publishing, 2011.
 
Ma, X., Gildin, E., Plaksina, T. Efficient optimization framework for integrated placement of horizontal wells and hydraulic fracture stages in unconventional gas reservoirs. Journal of Unconventional Oil and Gas Resources, 2015, 9: 1-17.10.1016/j.juogr.2014.09.001
 
Moridis, G. J., Blasingame, T. A., Freeman, C. M. Analysis of mechanisms of flow in fractured tight-gas and shale-gas reservoirs. Paper SPE 139250 Presented at SPE Latin American and Caribbean Petroleum Engineering Conference, Lima, Peru, 1-3 December, 2010.
 
Pereira, C. A., Kazemi, H., Ozkan, E. Combined effect of non-Darcy flow and formation damage on gas well performance of dual-porosity and dual-permeability reservoirs. SPE Reservoir Evaluation & Engineering, 2006, 9(5): 543-552.10.2118/90623-PA
 
Perrin, J., Cook, T. Hydraulically fractured wells provide two-thirds of U.S. natural gas production. 2016. (accessed 6 April, 2021)
 
Pruess, K. GMINC-A Mesh Generator for Flow Simulations in Fractured Reservoirs. Berkeley, USA, Lawrence Berkeley National Laboratory, 1983.
 
Pruess, K. TOUGH2-A General-Purpose Numerical Simulator for Multiphase Fluid and Heat Flow. Berkeley, USA, Lawrence Berkeley Laboratory, 1991.
 
Rammay, M. H., Awotunde, A. A. Stochastic optimization of hydraulic fracture and horizontal well parameters in shale gas reservoirs. Journal of Natural Gas Science and Engineering, 2016, 36: 71-78.
 
Saldungaray, P. M., Palisch, T. T. Hydraulic fracture optimization in unconventional reservoirs. Paper SPE 96812 Presented at SPE Middle East Unconventional Gas Conference and Exhibition, Abu Dhabi, UAE, 23-25 January, 2012.
 
Thompson, R., Wright, J. Oil and Gas Property Evaluation, 2015 Edition. Colorado, USA, Thompson-Wright Associates, 2015.
 
U.S. Energy Information Administration. March 2016. Trends in U.S. Oil and Natural Gas Upstream Costs.
 
Wang, L., Wang, S., Zhang, R., et al. Review of multi-scale and multi-physical simulation technologies for shale and tight gas reservoirs. Journal of Natural Gas Science and Engineering, 2017, 37: 560-578.
 
Warren, J. E., Root, P. J. The behavior of naturally fractured reservoirs. Society of Petroleum Engineers Journal, 1963, 228: 245-255.
 
Wu, Y. S. Multiphase Fluid Flow in Porous and Fractured Reservoirs, First Edition. Amsterdam, Netherlands, Gulf Professional Publishing, 2015.
 
Wu, Y. S., Pruess, K. A numerical method for simulating non-Newtonian fluid flow and displacement in porous media. Advances in Water Resources, 1998, 21: 351-362.
 
Young, T., Mohlenkamp, M. J. Introduction to numerical methods and Matlab Programming for Engineers. Lecture 27: 101-103, Ohio University Department of Mathematics, OH, 2009.
 
Yu, W., Sepehrnoori, K. Optimization of multiple hydraulically fractured horizontal wells in unconventional gas reservoirs. Journal of Petroleum Engineering, 2013, 2013: 1-16.
 
Zhang, H., Sheng, J. Optimization of horizontal well fracturing in shale gas reservoir based on stimulated reservoir volume. Journal of Petroleum Science and Engineering, 2020, 190: 107059.
Advances in Geo-Energy Research
Pages 191-201
Cite this article:
Chen J, Wang L, Wang C, et al. Automatic fracture optimization for shale gas reservoirs based on gradient descent method and reservoir simulation. Advances in Geo-Energy Research, 2021, 5(2): 191-201. https://doi.org/10.46690/ager.2021.02.08

933

Views

167

Downloads

26

Crossref

24

Web of Science

30

Scopus

Altmetrics

Received: 06 April 2021
Revised: 20 April 2021
Accepted: 20 April 2021
Published: 24 April 2021
© The Author(s) 2021

This article is distributed under the terms and conditions of the Creative Commons Attribution (CC BY-NC-ND) license, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Return