Prediction of gas production potential based on machine learning in shale gas field: a case study
Author:
Affiliation:
1. Energy College, Chengdu University of Technology, Chengdu, China
2. State Key Laboratory of Oil and Gas Reservoir Geology and Exploitation, Chengdu, China
3. Second Gas Production Plant, Southwest Oil & Gas Branch, Sinopec, China
Funder
National Natural Science Foundation of China
Publisher
Informa UK Limited
Subject
Energy Engineering and Power Technology,Fuel Technology,Nuclear Energy and Engineering,Renewable Energy, Sustainability and the Environment
Link
https://www.tandfonline.com/doi/pdf/10.1080/15567036.2022.2100521
Reference29 articles.
1. Feature Selection-Based ANN for Improved Characterization of Carbonate Reservoir
2. Support vector regression for porosity prediction in a heterogeneous reservoir: A comparative study
3. A Single Artificial Neural Network Model Predicts Bubble Point Physical Properties of Crude Oils
4. A Large-Scale Study for a Multi-Basin Machine Learning Model Predicting Horizontal Well Production
5. Comparative Analysis of Machine Learning Based Feature Selection Approach for Carbonate Reservoir Cementation Factor Prediction
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2. CLAP: Gas Saturation Prediction in Shale Gas Reservoir Using a Cascaded Convolutional Neural Network–Long Short-Term Memory Model with Attention Mechanism;Processes;2023-09-04
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