Prediction of Coalbed Methane Production Using a Modified Machine Learning Methodology
Prediction of Coalbed Methane Production Using a Modified Machine Learning Methodology
About this item
Full title
Author / Creator
Publisher
Basel: MDPI AG
Journal title
Language
English
Formats
Publication information
Publisher
Basel: MDPI AG
Subjects
More information
Scope and Contents
Contents
Compared to natural and shale gas, studies on predicting production specific to coalbed methane (CBM) are still relatively limited, and mainly use decline curve methods such as Arps, Stretched Exponential Decline Model, and Duong’s model. In recent years, machine learning (ML) methods applied to CBM production prediction have focused on the signifi...
Alternative Titles
Full title
Prediction of Coalbed Methane Production Using a Modified Machine Learning Methodology
Authors, Artists and Contributors
Author / Creator
Identifiers
Primary Identifiers
Record Identifier
TN_cdi_doaj_primary_oai_doaj_org_article_62c2f0e337d648a29fa851bac92fceed
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_62c2f0e337d648a29fa851bac92fceed
Other Identifiers
ISSN
1996-1073
E-ISSN
1996-1073
DOI
10.3390/en18061341
