Parallel and distributed chimp-optimized LSTM for oil well-log reconstruction in China

Well-log analysis contributes significantly to effective oil and gas extraction, but inconsistent logs may render subsequent geological analyses useless. This study tackles this problem by devising a deep Long Short-Term Memory (LSTM) model that uses the new Parallel and Distributed Chimp Optimizati...

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Veröffentlicht in:	Scientific reports Jg. 15; H. 1; S. 25950 - 21
Hauptverfasser:	Wang, Zisong, Cheng, Zhiliang, Wang, Wenxiang, Ding, Xiujian, Xia, Lu
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	London Nature Publishing Group UK 17.07.2025 Nature Publishing Group Nature Portfolio
Schlagworte:	639/166 639/4077 Chimp optimization algorithm Computers Datasets Distributed processing Drilling Efficiency Geology Humanities and Social Sciences Long short-term memory Machine learning Missing data multidisciplinary Neural networks Oil and gas extraction Optimization algorithms Parallel computing Real time Science Science (multidisciplinary) Well log analysis Long short-term memory Parallel computing Chimp optimization algorithm Oil and gas extraction Well log analysis
ISSN:	2045-2322, 2045-2322
Online-Zugang:	Volltext
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