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Uncertainty reduction in reservoir parameters prediction from multiscale data using machine learning in deep offshore reservoirs. (2020)
Thesis
ARIGBE, O.D. 2020. Uncertainty reduction in reservoir parameters prediction from multiscale data using machine learning in deep offshore reservoirs. Robert Gordon University [online], PhD thesis. Available from: https://openair.rgu.ac.uk

Developing a complete characterization of reservoir properties involved in subsurface multiphase flow is a very challenging task. In most cases, these properties - such as porosity, water saturation, permeability (and their variants), pressure, wetta... Read More about Uncertainty reduction in reservoir parameters prediction from multiscale data using machine learning in deep offshore reservoirs..

Real-time relative permeability prediction using deep learning. (2018)
Journal Article
ARIGBE, O.D., OYENEYIN, M.B., ARANA, I. and GHAZI, M.D. 2019. Real-time relative permeability prediction using deep learning. Journal of petroleum exploration and production technologies [online], 9(2), pages 1271-1284. Available from: https://doi.org/10.1007/s13202-018-0578-5

A review of the existing two and three phase relative permeability correlations shows a lot of pitfalls and restrictions imposed by (a) their assumptions (b) generalization ability and (c) difficulty with updating in real time for different reservoir... Read More about Real-time relative permeability prediction using deep learning..