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应用地球物理  2012, Vol. 9 Issue (1): 80-86    DOI: 10.1007/s11770-012-0317-5
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基于D-S证据理论的地震多属性融合方法在煤层气富集区预测中的应用
祁雪梅1,2 ,张绍聪3
1. 中国矿业大学资源与地球科学学院,徐州 221116;
2. 中国矿业大学岩土力学与工程国家重点实验室,徐州 221116;
3. 江西有色地质勘查局,南昌 330001
Application of seismic multi-attribute fusion method based on D-S evidence theory in prediction of CBM-enriched area*
Qi Xue-Mei1,2 and Zhang Shao-Cong3
1. School of Resource and Earth Sciences, China University of Mining and Technology, Xuzhou 221116
2. State Key Laboratory of Deep Geomechanics and Underground Engineering, China University of Mining and Technology,Xuzhou 221116
3. Non-Ferrous Metal Exploration and Development Bureau of Jiangxi Province, Nanchang 330001
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摘要 D-S证据理论为融合不确定信息提供了一条很好的思路。本文提出将D-S证据理论用于地震多属性融合的方法,首先在钻孔实测煤层气含量值的指导下优选对煤层气含量值变化敏感的地震属性,然后基于D-S证据理论对优选的地震属性进行融合处理,并将融合结果用于煤层气富集区的预测。实际应用效果表明:预测结果与钻孔实测煤层气含量值基本吻合,本文提出的基于D-S 证据理论的地震多属性融合方法用于预测煤层气富集区是可行的。
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祁雪梅
张绍聪
关键词D-S证据理论   煤层气   地震属性   融合     
Abstract: D-S evidence theory provides a good approach to fuse uncertain information. In this article, we introduce seismic multi-attribute fusion based on D-S evidence theory to predict the coalbed methane (CBM) concentrated areas. First, we choose seismic attributes that are most sensitive to CBM content changes with the guidance of CBM content measured at well sites. Then the selected seismic attributes are fused using D-S evidence theory and the fusion results are used to predict CBM-enriched area. The application shows that the predicted CBM content and the measured values are basically consistent. The results indicate that using D-S evidence theory in seismic multi-attribute fusion to predict CBM-enriched areas is feasible.
Key wordsD-S evidence theory   CBM   seismic attributes   fusion   
收稿日期: 2012-01-08;
基金资助:

国家重点基础研究发展计划(973计划)项目(2009CB219603)、国家科技重大专项项目(2008ZX05035 )和江苏高校优势学科建设工程资助项目联合资助。

引用本文:   
祁雪梅,张绍聪. 基于D-S证据理论的地震多属性融合方法在煤层气富集区预测中的应用[J]. 应用地球物理, 2012, 9(1): 80-86.
QI Xue-Mei,ZHANG Shao-Cong. Application of seismic multi-attribute fusion method based on D-S evidence theory in prediction of CBM-enriched area*[J]. APPLIED GEOPHYSICS, 2012, 9(1): 80-86.
 
[1] Beynon, M., Cosker, D., and Marshall, D., 2001, An expert system for multi-criteria decision making using Dempster
[2] -Shafer theory: Expert Syst. Appl., 20, 357 - 367.
[3] Chen, S. Q., Wang, S. X., Zhang, Y. G., and Ji, M., 2009, Reservoir prediction using pre-stack inverted elastic
[4] parameters: Applied Geophysics, 6(4), 349 - 358.
[5] Cheng, Q. S., 2006, Digital signal processing: Peking University Press, Beijing, 172 - 178.
[6] Dempster, A. P., 1976, Upper and lower probabilities induced by a multi-valued mapping: Annals of
[7] Mathematical Statistics, 38(2), 325 - 339.
[8] Deng, Y., Su, X. Y., Wang, D., and Li, Q., 2010, Target recognition based on fuzzy Dempster data fusion
[9] method: Defense Science Journal, 60(5), 525 - 530.
[10] Hall, D. L., 1992, Mathematical techniques in multisensor data fusion: Artech House, Boston, London, 12-20.
[11] Hart, B. S., 1999, Geology plays key role in seismic attributes studies:,Oil & Gas Journal, 97( 12), 76 - 80.
[12] He′garat-Mascle, S. L., Richard, D., Ottle′, C., 2003, Multiscale data fusion using Dempster-Shafer evidence
[13] theory: Integrated Comput. Aided Eng., 10, 9 - 22.
[14] Ivan, D M., and Bruce, S. H., 2004, Seismic attributebased characterization of coalbed methane reservoirs: An
[15] example from the Fruitland Formation, San Juan basin, New Mexico: The American Association of petroleum
[16] Geologists, 88(11), 1603 - 1621
[17] Kang, Y. H., 2006, Data fusion theory and application: Xian University of Electronic Science and Technology Press,
[18] Xian, 100 - 105.
[19] Kalkomey, C. T., 1997, Potential risks when using seismic attributes as predictors of reservoir properties: The
[20] Leading Edge, 16, 247 - 251.
[21] Liu, W. L., 2009, Geophysical response characteristics of coal bed methane: Lithologic Reservoirs (in Chinese),
[22] (2), 113 - 115.
[23] Peng, S. P., Gao, Y. F., and Yang, R. Z., 2005, Theory and application of AVO for detection of coal-bed methane—
[24] A case from the Huainan coalfield: Chinese Journal of Geophysics (in Chinese), 48(6), 1475 - 1486.
[25] Ramos, A. C. B., Davis, T. L.,1997, 3-D AVO analysis and modeling applied to fracture detection in coalbed
[26] reservoirs: Geophysics, 62, 1683 - 1695.
[27] Shafer, G., 1976, A mathematical theory of evidence: Master’s Thesis, Princeton N. J., Princeton University
[28] Press, 1 - 24.
[29] Yang, A. M., 2008, The fuzzy classification model and its integration method: Science Press, Beijing, 10 - 20.
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