地震多属性反演预测页岩总有机碳含量
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摘要
在单井评价的基础上,采用地震多属性反演方法可实现对页岩总有机碳(TOC)含量(以下称TOC质量分数)分布的横向预测。从井点出发,在地震资料中提取多种属性,结合多元逐步回归分析和神经网络方法进行属性优化训练,获取最佳属性组合,建立起属性组合和目标属性TOC质量分数之间的数学关系,并将其运用到地震数据体中进行TOC质量分数反演。将该方法应用到建南地区下侏罗统东岳庙段进行页岩TOC质量分数分布预测,TOC质量分数预测值与TOC质量分数实测值符合较好。
Based on single well evaluation,the lateral prediction of the total organic carbon(TOC) of the shale was predicted by using seismic multi-attribute inversion method.Starting from well points,various seismic attributes were extracted,combined with multi-element stepwise regression analysis and neural network,optimized attribute training was carried out to acquire optimal attribute combination and establish the mathematical correlation between attribute combination and target attribute TOC,which was applied to the seismic data in the inversion of TOC.The method is applied to predict shale TOC distribution of lower Jurassic Dongyuemiao Formation in Jiannan Area.The predicted TOC is well consistent with the measured TOC.
Based on single well evaluation,the lateral prediction of the total organic carbon(TOC) of the shale was predicted by using seismic multi-attribute inversion method.Starting from well points,various seismic attributes were extracted,combined with multi-element stepwise regression analysis and neural network,optimized attribute training was carried out to acquire optimal attribute combination and establish the mathematical correlation between attribute combination and target attribute TOC,which was applied to the seismic data in the inversion of TOC.The method is applied to predict shale TOC distribution of lower Jurassic Dongyuemiao Formation in Jiannan Area.The predicted TOC is well consistent with the measured TOC.
引文
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[5]焦李成.神经网络的理论和实践[M].西安:西安电子科技大学出版社,1995.218～259.
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