A critical review on intelligent optimization algorithms and surrogate models for conventional and unconventional reservoir production optimization

L Wang, Y Yao, X Luo, CD Adenutsi, G Zhao, F Lai - Fuel, 2023 - Elsevier
Aiming to find the most suitable development schemes of conventional and unconventional
reservoirs for maximum energy supply or economic benefits, reservoir production …

Leveraging machine learning in porous media

M Delpisheh, B Ebrahimpour, A Fattahi… - Journal of Materials …, 2024 - pubs.rsc.org
The emergence of artificial intelligence (AI) and, more particularly, machine learning (ML),
has had a significant impact on engineering and the fundamental sciences, resulting in …

Shale oil production prediction and fracturing optimization based on machine learning

C Lu, H Jiang, J Yang, Z Wang, M Zhang, J Li - Journal of Petroleum …, 2022 - Elsevier
With the advancement of horizontal well and hydraulic fracturing technology, the
development of unconventional reservoirs such as shale oil has become a hot issue in the …

Multi-solution well placement optimization using ensemble learning of surrogate models

M Salehian, MH Sefat, K Muradov - Journal of Petroleum Science and …, 2022 - Elsevier
Well location optimization aims to maximize the economic profit of oil and gas field
development while respecting various constraints. The limitations of the currently available …

Analysis of different objective functions in petroleum field development optimization

A Rostamian, MV de Sousa Miranda… - Journal of Petroleum …, 2024 - Springer
Oilfield development optimization plays a vital role in maximizing the potential of
hydrocarbon reservoirs. Decision-making in this complex domain can rely on various …

Machine-Learned Surrogate Models for Efficient Oil Well Placement Under Operational Reservoir Constraints

SM Mousavi, P Bakhtiarimanesh, F Enzmann… - SPE Journal, 2024 - onepetro.org
Recent predictive analytics and soft computing methods enhanced the exploration of new
hydrocarbon reserves. Machine learning (ML) has showed a promising role in oil and gas …

Iterative sequential robust optimization of quantity and location of wells in field development under subsurface, operational and economic uncertainty

A Mirzaei-Paiaman, SMG Santos… - Journal of Petroleum …, 2022 - Elsevier
Determination of optimal quantity and location of wells is a crucial step in any field
development project. Multiple challenges exist in the real-world projects, such as gigantic …

A transfer learning framework for well placement optimization based on denoising autoencoder

J Qi, Y Liu, Y Ju, K Zhang, L Liu, Y Liu, X Xue… - Geoenergy Science and …, 2023 - Elsevier
Well placement optimization is directly related to the recovery factor of reservoir
development, and at present, the mainstream solution is an evolutionary algorithm …

Application of machine learning algorithms in classification the flow units of the Kazhdumi reservoir in one of the oil fields in southwest of Iran

F Mohammadinia, A Ranjbar, M Kafi… - Journal of Petroleum …, 2023 - Springer
By determining the hydraulic flow units (HFUs) in the reservoir rock and examining the
distribution of porosity and permeability variables, it is possible to identify areas with suitable …

A random forest-assisted decomposition-based evolutionary algorithm for multi-objective combinatorial optimization problems

MB De Moraes, GP Coelho - 2022 IEEE congress on …, 2022 - ieeexplore.ieee.org
Many real-world optimization problems involve time-consuming fitness evaluation. To
reduce the computational cost of expensive evaluations, researchers have been developing …