三维地震神经网络反演在探明煤层富水灾害层的应用

Application of Three Dimensional Neural Network Inversion in the Prediction of Water Abundance in Coal Seam Roof

摘要:

在常规测井约束反演的的基础上，开展神经网络特征参数反演，将波阻抗等地震属性转化为与含水性更为密切的孔隙度、视电阻率数据体，使地震反演的地质属性与测井上的地质属性达到最优的相关性，从而实现应用三维地震对煤层顶板富水进行评价的目的。由于煤层顶板富水区的特殊性质，它同样也是地震后的易破坏层，因而对它的探明从抗震角度以及震害预测角度都是有价值的。以淮北某采区为例，通过孔隙度及电阻率的神经网络反演对研究区10#煤层顶板的富水性进行预测。反演结果表明采区北部发育一个强富水陷落柱，与钻孔揭示结果吻合。采区西部10#煤层顶板与第四系含水层呈不整合接触关系，神经网络反演结果预测为强富水区，同样与井下工程揭示富水特征吻合。利用多属性融合的神经网络反演可有效预测煤层顶板的富水特征，为煤矿安全生产以及抗震提供重要保障。

Abstract:

Recently, 3D seismic technology has become an important method in coalfield exploration, and great progress has been achieved. However, the prediction of water content in coal seam roof using 3D seismic technology is rarely discussed. In this study, a neural network inversion was carried out based on the logging constrained inversion. Seismic attributes, such as wave impedance, were converted to porosity and resistivity, which were closely related to water content. Taking the mining area of Huaibei coalfield as a case study, the water abundance of 10# coal seam roof in the study region was predicted by the neural network inversion of porosity and resistivity. The results show that a water-rich subsided column develops in the north of mining area, which is consistent with the borehole detection results. There is unconformity contact between the 10# coal seam roof and the Quaternary aquifer in the west of mining area, which is predicted as a water-abundant area by the PPN inversion. The neural network inversion can effectively predict the water abundance characteristics of a coal seam roof, thus providing an important guarantee for coalmine safety production.