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.
Similar content being viewed by others
References
Beynon, M., Cosker, D., and Marshall, D., 2001, An expert system for multi-criteria decision making using Dempster-Shafer theory: Expert Syst. Appl., 20, 357–367.
Chen, S. Q., Wang, S. X., Zhang, Y. G., and Ji, M., 2009, Reservoir prediction using pre-stack inverted elastic parameters: Applied Geophysics, 6(4), 349–358.
Cheng, Q. S., 2006, Digital signal processing: Peking University Press, Beijing, 172–178.
Dempster, A. P., 1976, Upper and lower probabilities induced by a multi-valued mapping: Annals of Mathematical Statistics, 38(2), 325–339.
Deng, Y., Su, X. Y., Wang, D., and Li, Q., 2010, Target recognition based on fuzzy Dempster data fusion method: Defense Science Journal, 60(5), 525–530.
Hall, D. L., 1992, Mathematical techniques in multisensor data fusion: Artech House, Boston, London, 12–20.
Hart, B. S., 1999, Geology plays key role in seismic attributes studies:, Oil & Gas Journal, 97(12), 76–80.
He’garat-Mascle, S. L., Richard, D., Ottlé, C., 2003, Multiscale data fusion using Dempster-Shafer evidence theory: Integrated Comput. Aided Eng., 10, 9–22.
Ivan, D M., and Bruce, S. H., 2004, Seismic attributebased characterization of coalbed methane reservoirs: An example from the Fruitland Formation, San Juan basin, New Mexico: The American Association of petroleum Geologists, 88(11), 1603–1621
Kang, Y. H., 2006, Data fusion theory and application: Xian University of Electronic Science and Technology Press, Xian, 100–105.
Kalkomey, C. T., 1997, Potential risks when using seismic attributes as predictors of reservoir properties: The Leading Edge, 16, 247–251.
Liu, W. L., 2009, Geophysical response characteristics of coal bed methane: Lithologic Reservoirs (in Chinese), 21(2), 113–115.
Peng, S. P., Gao, Y. F., and Yang, R. Z., 2005, Theory and application of AVO for detection of coal-bed methane—A case from the Huainan coalfield: Chinese Journal of Geophysics (in Chinese), 48(6), 1475–1486.
Ramos, A. C. B., Davis, T. L., 1997, 3-D AVO analysis and modeling applied to fracture detection in coalbed reservoirs: Geophysics, 62, 1683–1695.
Shafer, G., 1976, A mathematical theory of evidence: Master’s Thesis, Princeton N. J., Princeton University Press, 1–24.
Yang, A. M., 2008, The fuzzy classification model and its integration method: Science Press, Beijing, 10–20.
Author information
Authors and Affiliations
Corresponding author
Additional information
This work is supported by the National Basic Research Program of China (973 Program) (No. 2009CB219603), the Key Special National Project (No. 2008ZX05035), and the Priority Academic Program Development of Jiangsu Higher Education Institutions.
Qi Xue-Mei graduated from the School of Resource and Earth Sciences, China University of Mining and Technology in 2004. She is now a lecturer and doctoral candidate with a research interest in seismic prospecting.
Rights and permissions
About this article
Cite this article
Qi, XM., Zhang, SC. Application of seismic multi-attribute fusion method based on D-S evidence theory in prediction of CBM-enriched area. Appl. Geophys. 9, 80–86 (2012). https://doi.org/10.1007/s11770-012-0317-5
Received:
Revised:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11770-012-0317-5