Reservoir Connectivity Characterization and Controlling Factor Analysis by Advanced Logging-While-Drilling Electrical Image Data and MDT Data for Offshore Sandy Conglomerate Reservoirs
Authors:   CNOOC Ltd. Tianjin Branch, Cui Yunjiang , Xiong Lei ,   CNOOC Ltd. Tianjin Branch, Wang Peichun ,   CNOOC Ltd. Tianjin Branch, Wu Fangfang ,   SLB, Wang Ruihong ,   CNOOC Ltd. Tianjin Branch, Li Shenzhuan ,   SLB, Zhao Xianran ,   SLB, Wu Jinlong ,   SLB, Gong Hongjie ,   SLB, Zhou Xin ,   SLB, Han Shim Yen ,   SLB
Published: November 2024

The sandy conglomerate reservoir has a wide distribution in the Bahai Bay Basin, which has become one of the most important exploration targets. However, the characterization of reservoir connectivity is quite difficult due to strong reservoir heterogeneity and complex logging responses of conventional logs. To identify the characteristics of good connectivity reservoirs, advanced logging-while-drilling (LWD) electrical image data and modular formation dynamic tester (MDT) data were integrated, and the controlling factors were investigated. First, based on LWD electrical image data as well as conventional logs, the lithology, including shale, siltstone, fine sandstone, gravel-bearing sandstone, and conglomerate, was identified. Second, formation beddings, cross beddings, fractures, and faults were identified and classified based on the LWD electrical images. Third, the resistivity spectrum, grain size, and sorting index were obtained quantitatively to characterize the reservoir. And innovatively, gravels were extracted using the image segmentation method, and gravel concentration and gravel size were computed. Finally, the characteristics of tight reservoirs and effective reservoirs were summarized by combining the MDT data, and the controlling factors of reservoir connectivity were concluded. The heterogeneity of sandy conglomerate in Bohai Bay Basin can be well characterized by the resistivity spectrum; the stronger the heterogeneity, the wider the resistivity spectrum, and the greater the sorting index. The resistivity spectrum was divided into four parts according to resistivity ranges. Generally, the greater the high-resistivity part, the more gravel content there is; the greater the low-resistivity part, the more clay content there is. There were a total of 49 MDT results, and 16 of which were tight reservoirs due to calcareous cementation or high clay content. Calcareous cementation was characterized by a wide resistivity spectrum, more high resistivity part, high sorting index, and high bulk density. High clay content was characterized by more low resistivity part and high or medium gamma rays. Calcareous cementation was caused by diagenesis, and high clay content resulted from deposition. Both made the reservoir connectivity poor with low permeability. There were 26 MDT results with high mobility, which were normally located at gravel-bearing sandstone and conglomerate layers. These points can be characterized by a relatively narrow resistivity spectrum, more high resistivity part, less low resistivity part, medium gravel content, medium to fine gravel size, and relatively low sorting index. Calcareous cementation and clay content have a negative influence on reservoir connectivity, while sorting, gravel content, and gravel size have a relatively positive influence on reservoir connectivity. Without knowing the controlling factors, it is difficult to choose the proper depth for MDT to avoid tight and invalid results. The achievements have dramatically improved the geological understanding of the reservoir and provided valuable information for MDT point selection and deployment of new wells, especially for horizontal wells.