The prediction research on fracture-cavity reservoirs by geostatistical inversion based on Markov Chain and Monte-Carlo algorithm in the Tahe oilfeild
HAN Dong1, HU Xiang-Yang1, WU Xing-Wei1, LIU Kun-Yan1, SI Chao-Nian1, FU Xin2, JIA Zhi-Kun3
1. SINOPEC Exploration & Production Research Institute, Beijing 100083, China;
2. Logging Company of PetroChina Great Wall Drilling Company, Panjin 124010, China;
3. Sinochem Petroleum Exploration & Production Co. Ltd, Beijing 100031, China
The spatial heterogeneity of carbonate fractured-vuggy reservoir is very strong in the Tahe oilfeild.Interwell reservoir prediction mainly depends on the application of seismic data.However,the results of deterministic seismic interpretation have multi-solutions.A geostatistical inversion method based on Markov Chain and Monte-Carlo algorithm is adopted for fractured-vuggy reservoir quantitative prediction and uncertainty evaluation.Firstly,geological prior information of the target zone can be obtained by geological regularity and deterministic interpretation results from well logging and seismic survey.Then,controlled by suitable geostatistical simulation parameters of the study area,the geostatistical inversion can be done, yielding many equal probability results of reservoir type volume and impedance data volume.Based on these results,the uncertainty of inversion can be analyzed.The method provides an effective seismic-driven way for quantitative prediction of fractured-vuggy reservoir,giving better solutions to the problems of the cave vertical depth positioning and the uncertainty evaluation of seismic prediction results.It is of great guiding significance for the modeling and characterization of fractured-vuggy reservoir.
韩东, 胡向阳, 邬兴威, 刘坤岩, 司朝年, 付鑫, 贾志坤. 基于马蒙算法地质统计学反演的缝洞储集体预测[J]. 物探与化探, 2015, 39(6): 1211-1216.
HAN Dong, HU Xiang-Yang, WU Xing-Wei, LIU Kun-Yan, SI Chao-Nian, FU Xin, JIA Zhi-Kun. The prediction research on fracture-cavity reservoirs by geostatistical inversion based on Markov Chain and Monte-Carlo algorithm in the Tahe oilfeild. Geophysical and Geochemical Exploration, 2015, 39(6): 1211-1216.