A resistivity partitioning algorithm of borehole image to improve permeability estimates in shaly sandstones, central Sichuan Basin

Abstract

Abstract Permeability estimates from well logs are essential inputs for reservoir characterization and of great significance to almost all aspects of hydrocarbon development. Borehole image, with high resolution and coverage to highlight subtle heterogeneity of formation, is rarely used for permeability estimation, especially for clastic rocks. Here, we put forward a set of algorithms to automatically extract sand resistivity from microresistivity borehole image to effectively indicate and estimate the intrinsic permeability of porous clastic rocks, and then apply it to the tight sandstone reservoir of Middle Jurassic Shaximiao Formation in Qiulin gas field, central Sichuan Basin. First, equations are deduced, according to the measurement principle and combined with shallow lateral log, to scale borehole image data into resistivity or conductivity depth by depth. Then, based on the volume model and the parallel conductance theory, sand resistivity component R s d is separated from the scaled borehole image by sliding statistics and partitioning with cutoffs equal to the shale volume properly calculated from conventional logs. Subsequently, exponential functions, derived from significant negative correlations between R s d and core permeability K _ c o r e in double logarithmic coordinate, are used to estimate formation permeability. With their correlation coefficients between 0.617 and 0.861, the resultant K_est curves coincide better with subtle variations of K _ c o r e than those estimations derived from conventional logs. This study may also be helpful to the improvement of high-resolution micromodeling and water saturation quantification in shaly sandstones.