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A supervised machine learning approach to discriminate reservoir fluid presence and saturation in the Gulf of Mexico using frequency and spectral shape attributes
(2023-05-13)
The first chapter in this research aims to define reliable attributes to differentiate subsurface
fluids and measure their attenuation to provide insights into reservoir properties. The study
investigates the effects ...
Machine learning for the subsurface characterization at core, well, and reservoir scales
(2020-05-08)
The development of machine learning techniques and the digitization of the subsurface geophysical/petrophysical measurements provides a new opportunity for the industries focusing on exploration and extraction of subsurface ...
Seismic attribute optimization with unsupervised machine learning techniques for deepwater seismic facies interpretation: users vs machines
(2020-07)
Machine learning (ML) has many applications within the geosciences, from predicting seismic facies, to automatic fault detection. A variety of machine learning algorithms are commonly employed, among these principal component ...
Statistical and deep learning methods for geoscience problems
(2021-12-15)
Machine learning is the new frontier for technology development in geosciences and has developed extremely fast in the past decade. With the increased compute power provided by distributed computing and Graphics Processing ...