Prediction of Coal Seam Permeability by Hybrid Neural Network Prediction Model
Publication: Journal of Energy Engineering
Volume 150, Issue 4
Abstract
Coalbed methane (CBM) productive efficiency and coal mine disasters such as gas outbursts and water inrush are closely correlated with coal seam permeability. Effective prediction of coal seam permeability can provide guidance for CBM production and prevention of coal mine disasters. In this research, a hybrid neural network prediction model integrating a genetic algorithm, an adaptive boosting algorithm, and a back propagation neural network was developed to predict coal seam permeability. Additional momentum and variable learning rate algorithms were used to improve the learning rate and accuracy of the model, and the model structure was optimized, including the number of hidden layer nodes and the transfer function. The input parameters of the prediction model included gas pressure, compressive strength, reservoir temperature, and effective stress. The corresponding output parameter was coal seam permeability. The correlation between the parameters was calculated. Additionally, a comparative analysis between the proposed prediction model and four other prediction models was carried out to demonstrate the advantages of the proposed model. The results indicated that the correlations between compressive strength, gas pressure, reserve temperature, effective stress, and coal seam permeability were 0.334, , , and , respectively. The proposed prediction model had high accuracy compared with the other prediction models, and its coefficient of determination and root mean squared error were 0.999 and 0.021. Thus, the model can predict coal seam permeability more accurately.
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Data Availability Statement
All data, models, or codes that support the findings of this study are available from the corresponding author upon reasonable request.
Acknowledgments
This research was sponsored by the key technical project CNPC (2022ZG06) and the Evaluation of Reservoir Sensitivity Characteristics of Special Development of Large Oil and Gas Fields and Coalbed Methane of the National Science and Technology Major Project (2016ZX05044-003).
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Published In
Journal of Energy Engineering
Volume 150 • Issue 4 • August 2024
Copyright
© 2024 American Society of Civil Engineers.
History
Received: Oct 26, 2023
Accepted: Mar 20, 2024
Published online: Jun 13, 2024
Published in print: Aug 1, 2024
Discussion open until: Nov 13, 2024
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