Abstract

AbstractField‐scale observations suggest that rock heterogeneities control subsurface fluid flow, and these must be characterized for accurate predictions of fluid migration, such as during CO2 sequestration. Recent efforts characterizing multiphase flow in heterogeneous rocks have focused on simulation‐based inversion of laboratory observations with X‐ray imaging. However, models produced in this way have been limited in their predictive ability for heterogeneous rocks. We address the main challenges in this approach through an algorithm that combines new developments: a 3‐parameter capillary pressure model, spatial heterogeneity in absolute permeability, improved image processing to capture more experimental data in the calibration, and the constraint of history match iterations based on marginal error improvement. We demonstrate the improvements on two sandstones and three carbonate rocks, with varying heterogeneity, some of which could not be previously modeled. The algorithm results in physically representative models of the rock cores, reducing non‐systematic error to a level comparable to the experimental uncertainty.

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