Small-scale cave detection based on frequency-segmented imaging
Zhu Bohua1, Yang Jiangfeng1, Lü Qiuling1, Wang Zhen2, Ma Yongqiang1, Zhang Wei1
1. Geophysical Research Institute, SINOPEC, Nanjing, Jiangsu 211103, China; 2. Exploration and Development Research Institute, Northwest Oilfield Branch Co., SINOPEC, Urumqi, Xinjiang 830011, China
Abstract:Aimed at the difficulties of small-scale fracture-cavern reservoir detection in Tarim Basin,we propose in this paper a new small-scale cave detection method.First with the concept of seismic resolution,we demonstrate the importance of high frequency seismic data for improving the detection accuracy of small-scale fracture-carven reservoirs through forward modeling with different dominant frequency.Then we analyze the small-scale bead-like reflection to determine the bandwidth of small-scale caves and obtain frequency segmenting parameters.After that,we carry out the frequency segmenting and prestack time migration for CMP gathers and get high frequency data volume.Finally we conduct small-scale cave detection based on the high frequency data volume.Based on seismic data processing results,small-scale caves can be effectively detected on high frequency data volume,but they cannot be detected on conventional data,and it is also very helpful to characterize cave boundaries.Our prediction is highly consistent with drilling results,which greatly avoids risks in the exploration and development.
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