Application of GA/PSO Metaheuristic Algorithms Coupled with Deep Neural Networks for Predicting the Fracability Index of Shale Gas Formations

Shale gas reserves represent a significant source of natural gas, but unlocking their full potential depends on effective hydraulic fracturing. This research investigates the application of machine learning (ML) techniques to predict fracability index (FI), offering a faster and more cost-effective...

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Veröffentlicht in:	Natural resources research (New York, N.Y.) Jg. 34; H. 4; S. 2117 - 2142
Hauptverfasser:	Nadege, Mbula Ngoy, Shu, Biao, Ngungu, Meshac B., Arthur, Mutangala Emmanuel, Dominique, Kouassi Verena
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York Springer Nature B.V 01.08.2025
Schlagworte:	Accuracy Algorithms Artificial intelligence Artificial neural networks Automation Back propagation Back propagation networks Brittleness Experimental methods Fractals Genetic algorithms Heuristic methods Hydraulic fracturing Hydrocarbons Machine learning Minerals Natural gas Neural networks Oil and gas fields Optimization Ordovician Particle swarm optimization Predictions Propagation Reservoirs Shale Shale gas Shales Silurian
ISSN:	1520-7439, 1573-8981
Online-Zugang:	Volltext
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