Thin-sandstone reservoir prediction in coal-bearing strata

被引：0

作者：

Chen Z. ^{[1
,2
]}

Liu L. ^{[2
]}

Liu Y. ^{[2
]}

Bi L. ^{[2
]}

Shang A. ^{[3
]}

Xu F. ^{[2
]}

机构：

[1] School of Energy Resources, China Univevsity of Geosciences (Beijing), Beijing

[2] BGP Geological Research Center, BGP Inc., CNPC, Zhuozhou, 072751, Hebei

[3] Tarim Geophysical Prospecting Division, BGP Inc., CNPC, Korla, 841000, Xinjiang

来源：

Liu, Leisong (lls22716@126.com) | 1600年 / Science Press卷 / 51期

关键词：

Cloud transform; Coal-bearing strata; Genetic algorithm; Sensitive parameter;

D O I：

10.13810/j.cnki.issn.1000-7210.2016.supplement.010

中图分类号：

学科分类号：

摘要：

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. © 2016, Editorial Department OIL GEOPHYSICAL PROSPECTING. All right reserved.

引用

页码：52 / 57

页数：5

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