A comprehensive review of computer vision for reservoir modelling and data assimilation

The integration of computer vision (CV) techniques into reservoir modeling and data assimilation is reshaping petroleum engineering, driven by advances in machine learning and the growing availability of high-resolution imaging data. Traditional reservoir characterization is challenged by uncertaint...

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Vydáno v:	Discover applied sciences Ročník 7; číslo 12; s. 1399 - 24
Hlavní autor:	Kazemi, Alireza
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Cham Springer International Publishing 01.12.2025 Springer Nature B.V Springer
Témata:	Accuracy Applied and Technical Physics Artificial intelligence Chemistry/Food Science Computed tomography Computer vision Data assimilation Data augmentation Data collection Decision making Deep learning Diffusion rate Digital rock physics Earth science Earth Sciences Engineering Environment Fault detection Fluid flow Geology Image resolution Image segmentation Kalman filters Machine learning Management systems Materials Science Medical imaging Permeability Petroleum engineering Physics Porosity Pressure distribution Real time Regression analysis Regression models Reservoir management Reservoir modelling Reservoirs Review Seismic interpretation Simulation Subjectivity Surrogate modelling Synthesis Uncertainty Well logs Computer vision Seismic interpretation Digital rock physics Reservoir modelling Surrogate modelling Data assimilation
ISSN:	3004-9261, 2523-3963, 3004-9261, 2523-3971
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