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Harnessing the power of machine learning for carbon capture, utilisation, and storage (CCUS)–a state-of-the-art review
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 …
decarbonisation efforts to meet the Paris Agreement targets and mitigate the worst effects of …
A review of proxy modeling highlighting applications for reservoir engineering
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 …
production optimization and forecasting, uncertainty analysis, history matching, and risk …
Predicting field production rates for waterflooding using a machine learning-based proxy model
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 …
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
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 …
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
Develo** a model that can accurately predict the hydrocarbon production by only
employing the conventional mathematical approaches can be very challenging. This is …
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 …
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 …
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
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 …
driven by the incorporation of massive amounts of data, either in textual or graphical form …
[HTML][HTML] Magnetized and quadratic convection based thermal transport in ternary radiative bio-nanofluid via intelligent neural networks: Two hidden layers mechanism
Significance The thermal analysis of nanofluid in a vertical cylinder (artery) in a magnetized
environment holds significant implications in physiological and thermal regulation networks …
environment holds significant implications in physiological and thermal regulation networks …
Application of nature-inspired algorithms and artificial neural network in waterflooding well control optimization
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 …
data-driven proxy models that could be utilized to maximize the net present value of a …