煤炭工程 ›› 2014, Vol. 46 ›› Issue (9): 106-108.doi: 10.11799/ce201409035

• 研究探讨 • 上一篇    下一篇

利用地震属性预测煤层顶底板含水性研究

李雪梅   

  1. 中国矿业大学(北京)
  • 收稿日期:2014-04-01 修回日期:2014-05-08 出版日期:2014-09-10 发布日期:2014-09-10
  • 通讯作者: 李雪梅 E-mail:31703492@qq.com

The Prediction of Water-bearing of Coal Roof and Floor Using Seismic Attribute

  • Received:2014-04-01 Revised:2014-05-08 Online:2014-09-10 Published:2014-09-10

摘要:

本文通过地震属性来预测岩性参数,即选择利用多属性线性回归和概率神经网络技术对纵波速度、密度、视电阻率和孔隙度这些岩性参数进行反演,进而从获得的波阻抗体、视电阻率体和孔隙度体来预测煤层顶底板岩石的含水性。应用实例中,预测含水性相对较强的区域为低波阻抗、低视电阻率和高孔隙度分布的区域,这符合岩石物理的认识,同时与矿区地质认识的含水区也是一致的。煤层顶底板含水性的分析,对于防患煤矿突水事故具有现实意义。

关键词: 地震属性技术, 多属性线性回归, 概率神经网络, 煤层顶底板, 含水性

Abstract:

This essay predicts the lithology parameters using seismic attribute, by which to obtain the wave impedance body, the apparent resistivity body and the porosity of body from the inversion of velocity, density, resistivity and porosity of longitudinal wave selectively using multi-attribute linear regression and probabilistic neural network technology. In the pragmatic examples, it is consistent to the knowledge of rock physics that to predict the area with comparatively higher aquosity and meanwhile in line with the aquifer defined by the theory of the mining geological. It’s no doubt significant for the prevention of coal mine water inrush accident by the analysis of aquosity to the coal seam roof and floor.

Key words: seismic attributes technique, multiattribute linear regression, probability neural network, coal roof and floor, property of water-bearing