基于多属性变换的煤田波阻抗反演应用研究

Research on Coalfield Acoustic Impendence Inversion Based on Multi-attribute Transform

随着煤炭资源勘探深度的日益增加,复杂的地质条件对岩性勘探提出了新的要求,常规的反演技术捉襟见肘。本文避开了以褶积模型为基础的常规反演,从基于地震属性技术的反演技术出发,选择利用多元线性回归技术和径向基神经网络技术进行反演研究。论文以山西阳泉某矿地震勘探资料为例进行反演计算,计算研究结果表明,基于多属性变换的反演技术效果优于常规的反演方法,在煤田反演中可以得到广泛的推广。这就为煤田岩性地震勘探提供了一项有效的技术,有很好的应用前景。

With the increasing exploration of coal resources,complex geological conditions set the new demands in lithological exploration,for the conventional inversion methods have many problems.The paper chooses multiple linear regression and radical basis neural network techniques to do some inversion research based on seismic attributes technique.And the results from the computation of coalfield Yangquan Shanxi show the inversion based on multi-attributes technique has better effects,so it can be widely applied to coalfield exploration.