Abstract
With continuous optimization of reservoir performance in the oil and gas industry globally, there are outstanding technical challenges that require development and implementation of technologies and methodologies. One of the main challenges is how to build a static reservoir model that integrates rock-property heterogeneity to derive dynamic reservoir models and improve hydrocarbon recovery. Rock properties are measured at different scales by using advanced measurements ranging from 3D surface seismic inversion to log data and core data. The advancement of rock digital imaging has been proven to enhance interpretation results. Digital rock physics plays a vital role by utilizing new technologies such as machine learning to get the best outcome.
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