Permeability prediction method of unconsolidated sandstone reservoirs using CT scanning technology and random forest model

Abstract Developing unconsolidated sandstone reservoirs presents a formidable challenge due to their loose formation, which often triggers alterations in pore parameters and seepage characteristics during water injection processes. This study focuses on a specific reservoir, utilizing micro-CT scanning to examine the intricate relationship between permeability and pore throat structure. Leveraging a random forest model, we establish an empirical formula tailored for high permeability reservoirs. Furthermore, we conduct in-situ CT scanning experiments across various displacement multiples to analyze the pore structure of unconsolidated sandstone cores. The derived relationship curves elucidate the positive correlations between porosity and average pore throat radius with displacement multiples, while revealing a negative correlation with tortuosity. These findings enable the formulation of quantitative formulas for permeability and displacement multiples within the studied block. Such insights prove instrumental in devising effective water injection development strategies, predicting dynamic reserves, and projecting water drive development for analogous unconsolidated sandstone reservoirs undergoing high water cut phases.