Harnessing the power of machine learning for carbon capture, utilisation, and storage (CCUS)–a state-of-the-art review

Y Yan, TN Borhani, SG Subraveti, KN Pai… - Energy & …, 2021 - pubs.rsc.org
Carbon capture, utilisation and storage (CCUS) will play a critical role in future
decarbonisation efforts to meet the Paris Agreement targets and mitigate the worst effects of …

A review of proxy modeling highlighting applications for reservoir engineering

P Bahrami, F Sahari Moghaddam, LA James - Energies, 2022 - mdpi.com
Numerical models can be used for many purposes in oil and gas engineering, such as
production optimization and forecasting, uncertainty analysis, history matching, and risk …

Predicting field production rates for waterflooding using a machine learning-based proxy model

Z Zhong, AY Sun, Y Wang, B Ren - Journal of Petroleum Science and …, 2020 - Elsevier
Waterflooding, during which water is injected in the reservoir to increase pressure and
therefore boost oil production, is extensively used as a secondary oil recovery technology …

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 …

[HTML][HTML] Well production forecast in Volve field: Application of rigorous machine learning techniques and metaheuristic algorithm

CSW Ng, AJ Ghahfarokhi, MN Amar - Journal of petroleum science and …, 2022 - Elsevier
Develo** a model that can accurately predict the hydrocarbon production by only
employing the conventional mathematical approaches can be very challenging. This is …

[HTML][HTML] 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 …

[HTML][HTML] Review of application of artificial intelligence techniques in petroleum operations

S Bahaloo, M Mehrizadeh, A Najafi-Marghmaleki - Petroleum Research, 2023 - Elsevier
In the last few years, the use of artificial intelligence (AI) and machine learning (ML)
techniques have received considerable notice as trending technologies in the petroleum …

[HTML][HTML] Current trends in fluid research in the era of artificial intelligence: A review

F Sofos, C Stavrogiannis, KK Exarchou-Kouveli… - Fluids, 2022 - mdpi.com
Computational methods in fluid research have been progressing during the past few years,
driven by the incorporation of massive amounts of data, either in textual or graphical form …

Application of nature-inspired algorithms and artificial neural network in waterflooding well control optimization

CSW Ng, A Jahanbani Ghahfarokhi… - Journal of Petroleum …, 2021 - Springer
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 …