Research progress on the method of determining gas–water relative permeability curve in unconventional reservoirs

Abstract Unconventional reservoirs have unique characteristics such as low porosity, low permeability, complex pore structure, and strong heterogeneity. Conventional gas–water relative permeability curve determination methods no longer apply to unconventional reservoirs. Therefore, this paper clarifies the necessity of accurately obtaining the gas–water relative permeability curve, investigates a variety of direct measurement and indirect calculation methods suitable for unconventional reservoirs proposed by scholars, concludes the advantages, disadvantages and applicability of various methods, and prospects for the future research direction of the gas–water relative permeability curve determination method. The research results show: (1) The gas–water relative permeability curve has broad applications, and its precise measurement is essential for the efficient and economical development of gas reservoirs. (2) Current research on the unsteady-state method in unconventional reservoir applications generally focuses on improving the experimental method by combining the NMR, CT, and DPT techniques or optimizing the JBN method by considering the threshold pressure gradient, stress sensitivity, and gas slippage effect. (3) When experimenting with relative permeability curves in ultra-low permeability core samples is difficult or impossible, the indirect calculation can be used as an alternative to quickly obtaining numerous relative permeability curves. However, most of the relative permeability determination methods proposed by scholars remain at the laboratory stage, and how to apply them to the field is a significant challenge for current research. Future research should accelerate the development and release of standards for determining relative permeability curves in unconventional reservoirs, continuously improve the reliability verification scheme for relative permeability curve indirect calculation methods in unconventional reservoirs, and actively explore the gas–water relative permeability curve determination method based on machine learning.