Applications of hybrid models in chemical, petroleum, and energy systems: A systematic review

S Zendehboudi, N Rezaei, A Lohi - Applied energy, 2018 - Elsevier
Mathematical modeling and simulation methods are important tools in studying various
processes in science and engineering. In the current review, we focus on the applications of …

Applications of Machine Learning in Subsurface Reservoir Simulation—A Review—Part II

A Samnioti, V Gaganis - Energies, 2023 - mdpi.com
In recent years, Machine Learning (ML) has become a buzzword in the petroleum industry,
with numerous applications which guide engineers in better decision making. The most …

Experimental investigation, binary modelling and artificial neural network prediction of surfactant adsorption for enhanced oil recovery application

AF Belhaj, KA Elraies, MS Alnarabiji… - Chemical Engineering …, 2021 - Elsevier
Throughout the application of enhanced oil recovery (EOR), surfactant adsorption is
considered the leading constraint on both the successful implementation and economic …

EOR screening using optimized artificial neural network by sparrow search algorithm

SM Tabatabaei, N Attari, SA Panahi… - Geoenergy Science and …, 2023 - Elsevier
Enhanced oil recovery (EOR) is a crucial aspect of reservoir engineering, and the use of
machine-learning algorithms in the initial stages of screening has been widely accepted as …

Reconstruction of 3D porous media using multiple-point statistics based on a 3D training image

Y Wu, C Lin, L Ren, W Yan, S An, B Chen… - Journal of Natural Gas …, 2018 - Elsevier
To date many methods of constructing porous media have been proposed. Among them, the
multiple-point statistics (MPS) method has a unique advantage in reconstructing 3D pore …

Impact of SnO2 nanoparticles on enhanced oil recovery from carbonate media

M Jafarnezhad, MS Giri, M Alizadeh - Energy Sources, Part A …, 2017 - Taylor & Francis
As many oil fields go into their final stage of production, new technologies are necessary in
order to maintain the production and increase the recovery of hydrocarbons. In recent years …

Performance prediction model of miscible surfactant-CO2 displacement in porous media using support vector machine regression with parameters selected by ant …

AH Helaleh, M Alizadeh - Journal of Natural Gas Science and Engineering, 2016 - Elsevier
Hybrid system is a potential tool to deal with nonlinear regression problems. This paper
presents an efficient prediction model for Surfactant-Water Solution Alternating CO 2 …

Exergy prediction model of a double pipe heat exchanger using metal oxide nanofluids and twisted tape based on the artificial neural network approach and …

M Mmohammadiun… - Journal of Heat …, 2016 - asmedigitalcollection.asme.org
In heat transfer area, researches have been carried out over several years for the
development of convective heat transfer enhancement (HTE) techniques. For proper …

Deep Learning-Based Surrogate-Assisted Intelligent Optimization Framework for Reservoir Production Schemes

L Wang, H Wang, L Zhang, L Zhang, R Deng… - Natural Resources …, 2025 - Springer
Determination of reservoir production schemes has always been a difficult problem during
the close-loop management of waterflooding reservoir. Different well control results in …

Artificial neural network model for alkali-surfactant-polymer flooding in viscous oil reservoirs: Generation and application

S Le Van, BH Chon - Energies, 2016 - mdpi.com
Chemical flooding has been widely utilized to recover a large portion of the oil remaining in
light and viscous oil reservoirs after the primary and secondary production processes. As …