Integrated AutoML-based framework for optimizing shale gas production: A case study of the Fuling shale gas field

Integrated AutoML-based framework for optimizing shale gas production: A case study of the Fuling shale gas field

This study introduces a comprehensive and automated framework that leverages data-driven methodologies to address various challenges in shale gas development and production. Specifically, it harnesses the power of Automated Machine Learning (AutoML) to construct an ensemble model to predict the esti...

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Bibliographic Details
Main Authors: Tianrui Ye, Jin Meng, Yitian Xiao, Yaqiu Lu, Aiwei Zheng, Bang Liang
Format: Article
Language:English
Published: KeAi Communications Co., Ltd. 2025-03-01
Series:Energy Geoscience
Subjects:
Machine learning
Model interpretation
Bi-objective optimization
Shale gas
Key factor analysis
Fracturing optimization
Online Access:http://www.sciencedirect.com/science/article/pii/S2666759224000805

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http://www.sciencedirect.com/science/article/pii/S2666759224000805

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