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A critical review on intelligent optimization algorithms and surrogate models for conventional and unconventional reservoir production optimization
Aiming to find the most suitable development schemes of conventional and unconventional
reservoirs for maximum energy supply or economic benefits, reservoir production …
reservoirs for maximum energy supply or economic benefits, reservoir production …
[HTML][HTML] A survey on the application of machine learning and metaheuristic algorithms for intelligent proxy modeling in reservoir simulation
Abstract Machine Learning (ML) has demonstrated its immense contribution to reservoir
engineering, particularly reservoir simulation. The coupling of ML and metaheuristic …
engineering, particularly reservoir simulation. The coupling of ML and metaheuristic …
Robust optimization of the locations and types of multiple wells using CNN based proxy models
For the cost-effective optimization of well locations and types under geologic uncertainty,
proxy modeling or surrogate modeling of reservoir simulation is required. Recently, a …
proxy modeling or surrogate modeling of reservoir simulation is required. Recently, a …
A holistic review on artificial intelligence techniques for well placement optimization problem
Well placement optimization is one of the major challenging factors in the field development
process of oil and gas industry. The objective function of well placement optimization is …
process of oil and gas industry. The objective function of well placement optimization is …
Interpretable knowledge-guided framework for modeling reservoir water-sensitivity damage based on Light Gradient Boosting Machine using Bayesian optimization …
K Sheng, G Jiang, M Du, Y He, T Dong… - Engineering Applications of …, 2024 - Elsevier
Reservoir water sensitivity damage significantly contributes to production declines in low-
permeability oil and gas fields. An accurate and rapid assessment of water sensitivity is …
permeability oil and gas fields. An accurate and rapid assessment of water sensitivity is …
Multi-objective optimization of water-alternating flue gas process using machine learning and nature-inspired algorithms in a real geological field
A Naghizadeh, S Jafari, S Norouzi-Apourvari… - Energy, 2024 - Elsevier
Flue gas water-alternating gas (flue gas-WAG) is a promising technique for enhancing oil
production and reducing greenhouse gas emissions. The effective utilization of this …
production and reducing greenhouse gas emissions. The effective utilization of this …
A novel multi-objective optimization method for well control parameters based on PSO-LSSVR proxy model and NSGA-II algorithm
Single-objective well control problems have been studied for many years as one of the most
typical optimization problems by researchers worldwide. However, single-objective …
typical optimization problems by researchers worldwide. However, single-objective …
A hybrid surrogate-assisted integrated optimization of horizontal well spacing and hydraulic fracture stage placement in naturally fractured shale gas reservoir
Horizontal well drilling and hydraulic fracturing are the most frequently adopted technologies
for the commercial development of shale reservoirs. However, expensive production …
for the commercial development of shale reservoirs. However, expensive production …
Fast marching method assisted permeability upscaling using a hybrid deep learning method coupled with particle swarm optimization
Geo-cellar models contain millions of gridblocks and are very time-consuming to simulate.
This challenge necessitates upscaling geo-cellular models to obtain fit-for-purpose models …
This challenge necessitates upscaling geo-cellular models to obtain fit-for-purpose models …
Efficient well placement optimization coupling hybrid objective function with particle swarm optimization algorithm
Well placement optimization is a critical part of the oil field development planning which
aims to find the optimal locations of wells to maximize a traditional objective function (TOF) …
aims to find the optimal locations of wells to maximize a traditional objective function (TOF) …