Thin-sandstone reservoir prediction in coal-bearing strata
Chen Zhigang1,2, Liu Leisong2, Liu Yaqin2, Bi Litao2, Shang Aihui3, Xu Feng2
1. School of Energy Resources, China Univevsity of Geosciences(Beijing), Beijing 100083, China;
2. BGP Geological Research Center, BGP Inc., CNPC, Zhuozhou, Hebei 072751, China;
3. Tarim Geophysical Prospecting Division, BGP Inc., CNPC, Korla, Xinjiang 841000, China
Abstract：Targets in Block K in Turgai Basin are sets of coal-bearing layers composed of sandstones and mudstones (lakeshore and swamp facies). They are characterized by thin beds and thickness quick changes,and seismic data quality is rather poor due to coal bed influence. It is very difficult to predict thin reservoirs on seismic data processed by conventional inversion methods. We propose here an approach to predict this kind of thin reservoirs based on multi-discipline data. Based on analysis of drilling,logging,and seismic data,we find out a few parameters sensitive to lithological interpretation and build a lithological interpretation template. Then with a wave impedance inversion genetic algorithm and cloud-transform gamma-ray attribute prediction,we derive the impedance and gamma attribute volumes. Finally,with the lithological interpretation template we predict thin-sandstone reservoirs in coal-bearing strata on the impedance and gamma attribute volumes.
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