High-density point-receiver seismic survey of a deep carbonate cave reservoir system: a case study from the Tarim Basin, Western China

In the northern rim of the Tarim Basin, western China, oil is being produced from an extensive system of interconnected caves, faults and fractures in Ordovician carbonates buried about 6000 to 7000 m below the surface. Although onshore, drilling costs are high due to the depth of the field, so, to produce the field economically, wells must be accurately located within the cavernous features to access as large a drainage area as possible. However, imaging fine details of the reservoir structures presents challenges due to a complex overburden. While the surface terrain and near-surface geology are relatively benign for land seismic operations, the subsurface exhibits large lateral velocity changes related to widely distributed Permian volcanic formations around 1000 and 1200 m above the target zone. These formations are considered to have led to errors in the imaging of the target layers in legacy datasets due to incorrect velocity modelling of the overburden. Improved imaging of detailed features of the deep cavernous carbonate reservoir beneath the complex overburden would require an accurate velocity model in addition to seismic data with both high temporal and spatial resolution. To determine whether new land seismic acquisition and processing technologies could provide a significant uplift in imaging quality, in 2013 PetroChina Tarim Oil Company (TOC) acquired a high-density full-azimuth 3D seismic survey using a point-source and point-receiver geometry. The dataset was recorded using an advanced high-channel count acquisition system and processed with high-end processing techniques designed to address the various challenges presented in the area. Three approaches were used over different depth ranges to develop an accurate velocity model for prestack depth migration (PSDM). Model velocities were constrained using available well data, providing confidence in the accuracy of the resulting image. Relative amplitude preserving (RAP) methods were used for noise attenuation and signal processing to maximise the reliability of subsequent inversion and interpretation work.