Blar i NTNU Open på forfatter "Nait Amar, Menad"
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Application of Low-Salinity Waterflooding in Carbonate Cores: A Geochemical Modeling Study
Jahanbani Ghahfarokhi, Ashkan; Egbe, Daniel Isong Otu; Nait Amar, Menad; Torsæter, Ole (Peer reviewed; Journal article, 2020)Waterflooding is the most widely applied improved oil recovery technique. Recently, there has been growing interest in the chemistry and ionic composition of the injected water. Low-salinity waterflooding (LSWF) is a ... -
Application of nature-inspired algorithms and artificial neural network in waterflooding well control optimization
Ng, Cuthbert Shang Wui; Jahanbani Ghahfarokhi, Ashkan; Nait Amar, Menad (Peer reviewed; Journal article, 2021)With the aid of machine learning method, namely artificial neural networks, we established data-driven proxy models that could be utilized to maximize the net present value of a waterflooding process by adjusting the well ... -
Applying hybrid support vector regression and genetic algorithm to water alternating CO2 gas EOR
Nait Amar, Menad; Zeraibi, Noureddine; Jahanbani Ghahfarokhi, Ashkan (Peer reviewed; Journal article, 2020)Water alternating CO2 gas injection (WAG CO2) is one of the most promising enhanced oil recovery techniques. The optimization of this process requires performing many time‐consuming simulations. In this paper, an intelligent ... -
Modeling interfacial tension of the hydrogen-brine system using robust machine learning techniques: Implication for underground hydrogen storage
Ng, Cuthbert Shang Wui; Djema, Hakim; Nait Amar, Menad; Jahanbani Ghahfarokhi, Ashkan (Peer reviewed; Journal article, 2022)During the last years, there has been a surge of interest in cleaner ways for producing energy in order to successfully handle the climate issues caused by the consumption of fossil fuels. The production of hydrogen (H2) ... -
Optimization of WAG in real geological field using rigorous soft computing techniques and nature-inspired algorithms
Nait Amar, Menad; Jahanbani Ghahfarokhi, Ashkan; Ng, Cuthbert Shang Wui; Zeraibi, Noureddine (Peer reviewed; Journal article, 2021)To meet the ever-increasing global energy demands, it is more necessary than ever to ensure increments in the recovery factors (RF) associated with oil reservoirs. Owing to this challenge, enhanced oil recovery (EOR) ... -
Predicting thermal conductivity of carbon dioxide using group of data-driven models
Nait Amar, Menad; Jahanbani Ghahfarokhi, Ashkan; Zeraibi, Noureddine (Peer reviewed; Journal article, 2020)Thermal conductivity of carbon dioxide (CO2) is a vital thermophysical parameter that significantly affects the heat transfer modeling related to CO2 transportation, pipelines design and associated process industries. The ... -
Predicting wax deposition using robust machine learning techniques
Nait Amar, Menad; Jahanbani Ghahfarokhi, Ashkan; Ng, Cuthbert Shang Wui (Journal article; Peer reviewed, 2021)Accurate prediction of wax deposition is of vital interest in digitalized systems to avoid many issues that interrupt the flow assurance during production of hydrocarbon fluids. The present investigation aims at establishing ... -
Prediction of CO2 diffusivity in brine using white-box machine learning
Nait Amar, Menad; Jahanbani Ghahfarokhi, Ashkan (Peer reviewed; Journal article, 2020)Accurate knowledge of the diffusivity coefficient of CO2 in brine has a significant effect on the design success and monitoring of CO2 storage in saline aquifers, which is a part of carbon capture and sequestration (CCS). ... -
Production optimization under waterflooding with Long Short-Term Memory and metaheuristic algorithm
Ng, Cuthbert Shang Wui; Jahanbani Ghahfarokhi, Ashkan; Nait Amar, Menad (Peer reviewed; Journal article, 2022)In petroleum domain, optimizing hydrocarbon production is essential because it does not only ensure the economic prospects of the petroleum companies, but also fulfills the increasing global demand of energy. However, ... -
Proxy Model Development for the Optimization of Water Alternating CO2 Gas for Enhanced Oil Recovery
Matthew, D Aqnan Marusaha; Jahanbani Ghahfarokhi, Ashkan; Ng, Cuthbert Shang Wui; Nait Amar, Menad (Peer reviewed; Journal article, 2023)Optimization studies are an important task in reservoir engineering practices such as production optimization and EOR (Enhanced Oil Recovery) assessments. However, they are extensive studies with many simulations that ... -
Smart Proxy Modeling of a Fractured Reservoir Model for Production Optimization: Implementation of Metaheuristic Algorithm and Probabilistic Application
Ng, Cuthbert Shang Wui; Jahanbani Ghahfarokhi, Ashkan; Nait Amar, Menad; Torsæter, Ole (Journal article; Peer reviewed, 2021)Numerical reservoir simulation has been recognized as one of the most frequently used aids in reservoir management. Despite having high calculability performance, it presents an acute shortcoming, namely the long computational ... -
A Survey on the Application of Machine Learning and Metaheuristic Algorithms for Intelligent Proxy Modeling in Reservoir Simulation
Ng, Cuthbert Shang Wui; Nait Amar, Menad; Jahanbani Ghahfarokhi, Ashkan; Imsland, Lars Struen (Peer reviewed; Journal article, 2022)Machine Learning (ML) has demonstrated its immense contribution to reservoir engineering, particularly reservoir simulation. The coupling of ML and metaheuristic algorithms illustrates huge potential for application in ... -
Well production forecast in Volve field: Application of rigorous machine learning techniques and metaheuristic algorithm
Ng, Cuthbert Shang Wui; Jahanbani Ghahfarokhi, Ashkan; Nait Amar, Menad (Peer reviewed; Journal article, 2021)Developing a model that can accurately predict the hydrocarbon production by only employing the conventional mathematical approaches can be very challenging. This is because these methods require some underlying assumptions ...