Integrating Machine Learning Workflow into Numerical Simulation for Optimizing Oil Recovery in Sand-Shale Sequences and Highly Heterogeneous Reservoir

Integrating Machine Learning Workflow into Numerical Simulation for Optimizing Oil Recovery in Sand-Shale Sequences and Highly Heterogeneous Reservoir

This paper aims to evaluate the efficiency of various machine learning algorithms integrating with numerical simulations in optimizing oil production for a highly heterogeneous reservoir. An approach leveraging a machine learning workflow for reservoir characterization, history matching, sensitivity...

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Bibliographic Details
Main Authors: Dung Bui, Abdul-Muaizz Koray, Emmanuel Appiah Kubi, Adewale Amosu, William Ampomah
Format: Article
Language:English
Published: MDPI AG 2024-10-01
Series:Geotechnics
Subjects:
machine learning
reservoir simulation
history matching
proxy model
water flooding
production optimization
Online Access:https://www.mdpi.com/2673-7094/4/4/55
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