Joint inversion of elastic-electrical data for gas hydrate reservoirs based on Bayesian theory
Pan Haojie1, Zhang Yan1, Li Hongbing1, Liu Tanyan2, Deng Jian3, Zhao Yi3
1. Research Institute of Petroleum Exploration and Development, CNPC, Beijing 100083, China 2. State Key Laboratory of Marine Geology(Tongji University), Shanghai 200092, China 3. Exploration and Development Research Institute, Huabei Oilfield Company, PetroChina, Renqiu, Hebei 062552, China
Abstract：A single set of sonic velocity or resistivity data are usually used to estimate hydrate reservoir parameters based on simple linear or logarithmic linear rock physics.However,elastic data and electrical data have different sensitivity of reservoir parameters;the estimation based on different data may generate different values of reservoir parameters.In order to solve this problem,we propose a new method of elastic-electrical joint inversion based on a nonlinear simplified three-phrase equation and a modified Archie equation under the frame of Bayesian theory,with which we can simultaneously predict gas hydrate saturation,porosity,clay content,and their corresponding uncertainty.The feasibility of the joint inversion method is verified by both synthetic data tests and real well logging data tests.The results indicate that the joint inversion of elastic-electrical data can not only produce reliable reservoir parameter estimations,but also reduce effectively the uncertainty caused by different sensitivity and noise.
潘豪杰, 张研, 李红兵, 刘堂晏, 邓健, 赵懿. 基于贝叶斯理论的天然气水合物储层弹性—电性数据联合反演[J]. 石油地球物理勘探, 2018, 53(3): 568-577,586.
Pan Haojie, Zhang Yan, Li Hongbing, Liu Tanyan, Deng Jian, Zhao Yi. Joint inversion of elastic-electrical data for gas hydrate reservoirs based on Bayesian theory. Oil Geophysical Prospecting, 2018, 53(3): 568-577,586.
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