Application of statistical machine learning clustering algorithms to improve EUR predictions using decline curve analysis in shale-gas reservoirs-Reference-Cited by-同舟云学术

Application of statistical machine learning clustering algorithms to improve EUR predictions using decline curve analysis in shale-gas reservoirs

Published:2022-01 Issue: Volume:208 Page:109216
ISSN:0920-4105
Container-title:Journal of Petroleum Science and Engineering
language:en
Short-container-title:Journal of Petroleum Science and Engineering

Author:

Chen Zijuan^ORCID,Yu Wei^ORCID,Liang Jenn-Tai^ORCID,Wang Suojin,Liang Hwa-chi^ORCID

Funder

Texas A and M Engineering Experiment Station, Texas A and M University

Publisher

Elsevier BV

Subject

Geotechnical Engineering and Engineering Geology,Fuel Technology

Reference49 articles.

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2. A new approach to estimating ultimate recovery for multistage hydraulically fractured horizontal wells by utilizing completion parameters using machine learning;Alarifi;SPE Production & Operation,2021

3. An efficient K-means clustering algorithm;Alsabti;Electrical Engineering and Computer Science,1997

4. An introduction to kernel and nearest-heighbor monparametric regression;Altman;Am. Statistician,1992

5. Analysis of Decline Curves;Arps,1945

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