Knowledge-based rigorous machine learning techniques to predict the deliverability of underground natural gas storage sites for contributing to sustainable development goals
This study presents a method to develop a series of unique deliverability smart models for underground natural gas storage (UNGS) in different types of target formations. The natural gas supply loop is defined by periodic mismatches between demand and supply. Efficient and faster approaches for fore...
Main Authors: | , , , , |
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Format: | Article |
Language: | English |
Published: |
Elsevier
2022-11-01
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Series: | Energy Reports |
Subjects: | |
Online Access: | http://www.sciencedirect.com/science/article/pii/S235248472201143X |