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Huanhuan Gao, Huanhuan
College of Earth Science, Yangtze University, Hubei Wuhan 430100
Engineering

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Quantitative Prediction of Coalbed Gas Content Based on Seismic Multiple-Attribute Analyses Pan, Renfang; Gao, Huanhuan; Lei, Kehui; Zhu, Zhengping
Journal of Engineering and Technological Sciences Vol 47, No 4 (2015)
Publisher : ITB Journal Publisher, LPPM ITB

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1038.311 KB) | DOI: 10.5614/j.eng.technol.sci.2015.47.4.7

Abstract

Accurate prediction of gas planar distribution is crucial to selection and development of new CBM exploration areas. Based on seismic attributes, well logging and testing data we found that seismic absorption attenuation, after eliminating the effects of burial depth, shows an evident correlation with CBM gas content; (positive) structure curvature has a negative correlation with gas content; and density has a negative correlation with gas content. It is feasible to use the  hydrocarbon index (P*G) and pseudo-Poisson ratio attributes for detection of gas enrichment zones. Based on seismic multiple-attribute analyses, a multiple linear regression equation was established between the seismic attributes and gas content at the drilling wells. Application of this equation to the seismic attributes at locations other than the drilling wells yielded a quantitative prediction of planar gas distribution. Prediction calculations were performed for two different models,  one using pre-stack inversion  and  the other one disregarding pre-stack inversion. A comparison of the results indicates that both models predicted a similar trend for gas content distribution, except that the model using pre-stack inversion yielded a prediction result with considerably higher precision than the other model.
Co-Authors Kehui Lei, Kehui Renfang Pan, Renfang Zhengping Zhu, Zhengping