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Quantitative Prediction of Coalbed Gas Content Based on Seismic Multiple-Attribute Analyses

机译:基于地震多属性分析的煤层气含量定量预测

摘要

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.
机译:气体平面分布的准确预测对于选择和开发新的煤层气勘探区至关重要。根据地震属性,测井和测试数据,我们发现,在消除了埋藏深度的影响后,地震吸收衰减与煤层气中的气体含量存在明显的相关性。 (正)结构曲率与气体含量呈负相关;密度与气体含量呈负相关。使用烃指数(P * G)和拟泊松比属性来检测气体富集区是可行的。基于地震多属性分析,在地震属性与钻井气含量之间建立了多元线性回归方程。将该方程应用于除钻井之外的其他位置的地震属性,可以定量预测平面气体的分布。对两种不同的模型进行了预测计算,一种使用叠前反演,另一种忽略叠前反演。结果的比较表明,两个模型都预测了相似的气体含量分布趋势,只是使用叠前反演的模型产生的预测结果比其他模型的精度高得多。

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