Bayesian lithofacies discrimination and pore fluid detection in tight sandstone reservoirs
Yan Xinfei1,2, Cao Hong1,2, Yao Fengchang1,2, Ba Jing1,2
1. Geophysical Department,Research Institute of Petroleum Exploration and Development,PetroChina,Beijing 100083,China;
2. Key Laboratory of Geophysical Prospecting,PetroChina,Beijing 100083,China
Abstract：Applying statistical petrophysics can quantitatively predict the distribution of subsurface lithofacies and pore lluid in reservoirs.According to the characteristics of tight sandstone reservoirs in the Central Sichuan, P-wave and S-Wave impedances were selected for 2-D Bayesian classiiication in this paper.Classification results of well data show that using P-wave and S-wave impedance could distinguish lithofacies, even preliminarily recognize pore lluid.Therefore, applying this classiiication technique to invert seismic attributes, we obtain the li-thology lateral distribution and pore Huid around targets.The predicted lithofacies distribution reflects basically sedimentary characteristics of targets.Besides, gas bearing sandstones distribute mainly in the interior of the Formation Xu 2 and concentrate around Well B.
