Hybrid machine learning framework for multi-well trajectory optimization in an unconventional field-Reference-Cited by-同舟云学术

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Hybrid machine learning framework for multi-well trajectory optimization in an unconventional field

Published:2024-11 Issue: Volume:131 Page:205443
ISSN:2949-9089
Container-title:Gas Science and Engineering
language:en
Short-container-title:Gas Science and Engineering

Author:

Davudov D.,Odi U.^ORCID,Gupta A.^ORCID,Singh G.,Dindoruk B.^ORCID,Venkatraman A.,Osei K.

Publisher

Elsevier BV

Reference30 articles.

1. Optimization of well placement geothermal reservoirs using artificial intelligence;Akin;Comput. Geosci.,2010

2. Opportunities in Utilization of Digital Twins in Unconventional Gas Fields: Enhancing Efficiency and Performance through Virtual Replication;Alsulaiman,2024

3. A well placement optimization constrained to regional pressure balance;Al-Ismael,2018

4. Reservoir opportunity index-advance in well and subsurface design for cost effective field development;Ataei,2014

5. Hands-on Machine Learning with R;Boehmke,2019

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