A systematic review of data science and machine learning applications to the oil and gas industry

Z Tariq, MS Aljawad, A Hasan, M Murtaza… - Journal of Petroleum …, 2021 - Springer
This study offered a detailed review of data sciences and machine learning (ML) roles in
different petroleum engineering and geosciences segments such as petroleum exploration …

[HTML][HTML] A survey on the application of machine learning and metaheuristic algorithms for intelligent proxy modeling in reservoir simulation

CSW Ng, MN Amar, AJ Ghahfarokhi… - Computers & Chemical …, 2023 - Elsevier
Abstract Machine Learning (ML) has demonstrated its immense contribution to reservoir
engineering, particularly reservoir simulation. The coupling of ML and metaheuristic …

Application of artificial neural network for predicting the performance of CO2 enhanced oil recovery and storage in residual oil zones

H Vo Thanh, Y Sugai, K Sasaki - Scientific reports, 2020 - nature.com
Abstract Residual Oil Zones (ROZs) become potential formations for Carbon Capture,
Utilization, and Storage (CCUS). Although the growing attention in ROZs, there is a lack of …

A recurrent neural network–based proxy model for well-control optimization with nonlinear output constraints

YD Kim, LJ Durlofsky - SPE Journal, 2021 - onepetro.org
In well-control optimization problems, the goal is to determine the time-varying well settings
that maximize an objective function, which is often the net present value (NPV). Various …

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 …

Impact of newly implemented enhanced oil and gas recovery screening policy on current oil production and future energy supply in India

A Bera, RK Vij, S Shah - Journal of Petroleum Science and Engineering, 2021 - Elsevier
A significant amount of current oil production in India comes from the matured fields.
Insufficient discovery of new oil and gas fields raises a momentous issue for the demand of …

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 …

Artificial-neural-network (ANN) based proxy model for performances forecast and inverse project design of water huff-n-puff technology

X Rao, H Zhao, Q Deng - Journal of Petroleum Science and Engineering, 2020 - Elsevier
Water huff-n-puff is an effective improved oil recovery (IOR) technology for tight or low-
permeability reservoirs which are developed by fractured horizontal wells. This paper trains …

A machine learning‐based approach to the multiobjective optimization of CO2 injection and water production during CCS in a saline aquifer based on field data

P Vaziri, B Sedaee - Energy Science & Engineering, 2023 - Wiley Online Library
The presence of carbon capture and storage (CCS) projects is important due to the growing
production of greenhouse gases, especially carbon dioxide (CO2). Our target functions have …

A review of tracer testing techniques in porous media specially attributed to the oil and gas industry

AK Patidar, D Joshi, U Dristant, T Choudhury - Journal of Petroleum …, 2022 - Springer
The significance of the tracer testing technique is widely accepted in reservoir performance
analysis in hydrology as well as in hydrocarbon exploration and production. The subsurface …