A novel surrogate model with deep learning for predicting spacial-temporal pressure in coalbed methane reservoirs

A novel surrogate model with deep learning for predicting spacial-temporal pressure in coalbed methane reservoirs

Coalbed methane (CBM) is a vital unconventional energy resource, and predicting its spatiotemporal pressure dynamics is crucial for efficient development strategies. This paper proposes a novel deep learning–based data-driven surrogate model, AxialViT-ConvLSTM, which integrates AxialAttention Vision...

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Bibliographic Details
Main Authors: Yukun Dong, Xiaodong Zhang, Jiyuan Zhang, Kuankuan Wu, Shuaiwei Liu
Format: Article
Language:English
Published: KeAi Communications Co., Ltd. 2025-04-01
Series:Natural Gas Industry B
Subjects:
Coalbed methane
Spatial-temporal pressure prediction
Deep learning
Surrogate models
AxialAttention Vision Transformer
ConvLSTM
Online Access:http://www.sciencedirect.com/science/article/pii/S2352854025000233
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