Characterization of pores and microfractures in tight conglomerate reservoirs

This study aimed to carry out the data-driven evaluation of pores and microfractures in tight conglomerate reservoirs combining machine learning complex geometric analysis, then investigate internal control factors reservoir damage. Results show that for Upper Wuerhe formation Mahu sag Xinjiang China, average contribution rate fluid storage seepage is 7.1 times pores, dominate seepage. Besides, contact probability between fluids 3.0 pores. Compared with microfractures, are more conducive form a homogeneous distribution flow expand sweep efficiency. On contrary, microfracture dominant factor aggravate heterogeneity The conclusions will provide crucial theoretical support practical basis effective exploitation oil.