利用岩性地震反演方法评价煤层突水危险性
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摘要
针对葛亭煤矿的构造地质和水文地质条件,利用概率神经网络岩性反演方法获得岩性数据体,该数据体包含了煤系地层到奥陶系灰岩顶部的构造、岩性和水文地质信息,构成了评价煤层突水危险性所需的基本数据。将其各种信息进行融合后对3煤层顶板的突水危险性进行定量评价:其中波阻抗反演的岩浆侵入及煤层变焦区域(含水层)与视电阻率反演结果高度一致,同时依据孔隙度反演结果证实该区域具有相应的低孔隙度反应。将该区域3煤层顶板视电阻率与孔隙度值进行乘积归一化处理,计算其突水隶属度,依此划分了该层位的突水程度。
In allusion to the structural geological and hydrogeological conditions in the Geting coalmine,using probabilistic neural network lithologic inversion obtained lithologic data volume.Therein is information from coal measures strata to structure,lithology and hydrogeology of Ordovician limestone top part and composed basic data needed to evaluate coalmine water bursting hazard.After syncretizing of various data and carried out quantitative evaluation of No.3 coal roof water bursting hazard.In which,wave impedance inversed results of magmatic intrusion and coal seam natural coking area(aquifer) are highly identical with the apparent resistivity inversed results,meanwhile,based on porosity inversed results have identified low porosity response in the area.Taking No.3 coal roof apparent resistivity and porosity values carry out product normalization and computed its water bursting membership grade,hereby the water bursting hazard grade scored out.
引文
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