An efficient data-driven global sensitivity analysis method of shale gas production through convolutional neural network-Reference-Cited by-同舟云学术

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An efficient data-driven global sensitivity analysis method of shale gas production through convolutional neural network

Published:2024-08 Issue:4 Volume:21 Page:2475-2484
ISSN:1995-8226
Container-title:Petroleum Science
language:en
Short-container-title:Petroleum Science

Author:

Xue Liang^ORCID,Xu Shuai,Nie Jie,Qin Ji,Han Jiang-Xia^ORCID,Liu Yue-Tian,Liao Qin-Zhuo

Publisher

Elsevier BV

Reference44 articles.

1. Channel hydraulic fracturing and its applicability in the marcellus shale;Ajayi,2011

2. A semianalytical model for pressure-transient analysis of fractured wells in unconventional plays with arbitrarily distributed discrete fractures;Chen;SPE J.,2018

3. Transient pressure analysis for fractured wells;Cinco-Ley;J. Petrol. Technol.,2007

4. Efficient and accurate global sensitivity analysis for reservoir simulations by use of the probabilistic collocation method;Dai;SPE J.,2014

5. A simulation approach for shale gas development in China with embedded discrete fracture modeling;Dai;Mar. Petrol. Geol.,2019

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