Interpretation of Gas/Water Relative Permeability of Coal Using the Hybrid Bayesian-Assisted History Matching: New Insights

The relative permeability of coal to gas and water exerts a profound influence on fluid transport in seams both primary enhanced coalbed methane (ECBM) recovery processes where multiphase flow occurs. Unsteady-state core-flooding tests interpreted by the Johnson–Bossler–Naumann (JBN) method are commonly used obtain coal. However, JBN fails capture multiple gas–water–coal interaction mechanisms, which inevitably results inaccurate estimations permeability. This paper proposes an improved assisted history matching framework using Bayesian adaptive direct search (BADS) algorithm interpret from unsteady-state flooding test data. validation show that BADS is significantly faster than previous algorithms terms convergence speed. proposed can accurately reproduce true curves without presumption endpoint saturations given small end-effect number <0.56. As comparison, routine produces abnormal interpretation (with estimated connate saturation ?33% higher water/gas only ?0.02 value) under comparable conditions. promising computationally effective alternative derive relations for systems with fluid–rock mechanisms.