In this paper, we introduce fast marching-succession of steady-states (FM-SSS) method to predict gas production from shale gas formations. The solutions of fast marching method (FMM) will describe the dynamic drainage boundary, and the succession of steady-state (SSS) method is applied to predict the gas production within the drainage boundary. As only the grids within drainage need to be taken into calculation at each time-step, this approach works much more efficiently than the implicit finite difference method, especially, at the early stage of production when the drainage is relatively small.We combine FMM with SSS to conduct reservoir simulation and predict gas production in shale gas reservoirs. The pressure profiles of transient flow are approximated with the pressure profiles of steady-state flow in our approach. The difference between the proposed method and the conventional SSS method is that we provide an efficient method to characterize the boundary conditions. In the conventional SSS method, the boundary pressure has to be measured, which is inconvenient for simulation purposes, whereas FM-SSS method takes the dynamic drainage as a changing boundary and approximates the drainage boundary pressure with initial reservoir pressure, such that the boundary condition can be numerically characterized. A major advantage of our approach is that it is unconditionally stable and more efficient than the implicit finite difference method because much smaller-scale linear equations need to be solved at each time-step.
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March 2018
Research-Article
Production Forecasting for Shale Gas Reservoirs With Fast Marching-Succession of Steady States Method
Bailu Teng,
Bailu Teng
School of Mining and Petroleum Engineering,
Faculty of Engineering,
University of Alberta,
Edmonton, AB T6G 1H9, Canada
e-mail: bailu@ualberta.ca
Faculty of Engineering,
University of Alberta,
Edmonton, AB T6G 1H9, Canada
e-mail: bailu@ualberta.ca
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Linsong Cheng,
Linsong Cheng
School of Petroleum Engineering,
China University of Petroleum (Beijing),
Beijing 102249, China
e-mail: lscheng@cup.edu.cn
China University of Petroleum (Beijing),
Beijing 102249, China
e-mail: lscheng@cup.edu.cn
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Shijun Huang,
Shijun Huang
School of Petroleum Engineering,
China University of Petroleum (Beijing),
Beijing 102249, China
e-mail: fengyun7407@163.com
China University of Petroleum (Beijing),
Beijing 102249, China
e-mail: fengyun7407@163.com
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Huazhou Andy Li
Huazhou Andy Li
School of Mining and Petroleum Engineering,
Faculty of Engineering,
University of Alberta,
Edmonton, AB T6G 1H9, Canada
e-mail: huazhou@ualberta.ca
Faculty of Engineering,
University of Alberta,
Edmonton, AB T6G 1H9, Canada
e-mail: huazhou@ualberta.ca
Search for other works by this author on:
Bailu Teng
School of Mining and Petroleum Engineering,
Faculty of Engineering,
University of Alberta,
Edmonton, AB T6G 1H9, Canada
e-mail: bailu@ualberta.ca
Faculty of Engineering,
University of Alberta,
Edmonton, AB T6G 1H9, Canada
e-mail: bailu@ualberta.ca
Linsong Cheng
School of Petroleum Engineering,
China University of Petroleum (Beijing),
Beijing 102249, China
e-mail: lscheng@cup.edu.cn
China University of Petroleum (Beijing),
Beijing 102249, China
e-mail: lscheng@cup.edu.cn
Shijun Huang
School of Petroleum Engineering,
China University of Petroleum (Beijing),
Beijing 102249, China
e-mail: fengyun7407@163.com
China University of Petroleum (Beijing),
Beijing 102249, China
e-mail: fengyun7407@163.com
Huazhou Andy Li
School of Mining and Petroleum Engineering,
Faculty of Engineering,
University of Alberta,
Edmonton, AB T6G 1H9, Canada
e-mail: huazhou@ualberta.ca
Faculty of Engineering,
University of Alberta,
Edmonton, AB T6G 1H9, Canada
e-mail: huazhou@ualberta.ca
1Corresponding author.
Contributed by the Petroleum Division of ASME for publication in the JOURNAL OF ENERGY RESOURCES TECHNOLOGY. Manuscript received November 28, 2016; final manuscript received October 9, 2017; published online January 22, 2018. Assoc. Editor: Daoyong (Tony) Yang.
J. Energy Resour. Technol. Mar 2018, 140(3): 032913 (14 pages)
Published Online: January 22, 2018
Article history
Received:
November 28, 2016
Revised:
October 9, 2017
Citation
Teng, B., Cheng, L., Huang, S., and Andy Li, H. (January 22, 2018). "Production Forecasting for Shale Gas Reservoirs With Fast Marching-Succession of Steady States Method." ASME. J. Energy Resour. Technol. March 2018; 140(3): 032913. https://doi.org/10.1115/1.4038781
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