基于地震反演方法的太原组灰岩含水性预测

发布时间：2018-06-11 19:32

本文选题：多参数岩性反演 + 概率神经网络反演　；参考：《地球物理学进展》2016年03期

【摘要】：阳泉煤业集团五矿赵家分区水文地质条件复杂,太原组K2灰岩是15煤层上部的主要含水层.由于煤系地层构造复杂,陷落柱比较发育,因此查明K2灰岩的空间展布和含水性,对于深部15煤层的安全开采具有重要意义.电磁勘探方法由于存在体积效应,很难准确预测K2灰岩的空间展布和含水性.与正常灰岩相比,含水灰岩的波阻抗与视电阻率较小,且孔隙度较大.鉴于此,首先利用多参数岩性反演方法,获得K2灰岩的波阻抗信息;然后利用概率神经网络反演方法,获得K2灰岩的孔隙度和视电阻率信息;最后综合波阻抗、孔隙度和视电阻率三种岩性信息,对K2灰岩进行了含水性评价,为煤矿防治水提供了重要的水文地质依据.
[Abstract]:The hydrogeological conditions of Zhaojia subzone of Yangquan Coal Industry Group are complex, and the K _ 2 limestone of Taiyuan formation is the main aquifer in the upper part of No. 15 coal seam. Because the strata of coal measures are complicated and the collapse columns are relatively developed, it is of great significance to find out the spatial distribution and water-bearing capacity of K _ 2 limestone for the safe mining of deep 15 coal seams. Because of the volume effect, it is difficult to accurately predict the spatial distribution and water content of K _ 2 limestone. Compared with the normal limestone, the wave impedance and apparent resistivity of the hydrated limestone are smaller and the porosity is larger. In view of this, the wave impedance information of K _ 2 limestone is obtained by using multi-parameter lithology inversion method, and then the porosity and apparent resistivity information of K _ 2 limestone is obtained by using probabilistic neural network inversion method. Based on three lithological information of porosity and apparent resistivity, the water-bearing evaluation of K _ 2 limestone is carried out, which provides an important hydrogeological basis for water control in coal mines.
【作者单位】：煤层气资源与成藏过程教育部重点实验室;中国矿业大学资源与地球科学学院;
【基金】：国家自然科学基金资助项目(u1261202;41430643)资助
【分类号】：P631.4;P641.4

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