煤与瓦斯突出预测的岩性地震反演方法研究

发布时间：2018-02-23 23:16

  本文关键词： 煤与瓦斯突出预测 构造煤 PNN反演 弹性波阻抗反演 同步反演　出处：《中国矿业大学》2013年博士论文　论文类型：学位论文

【摘要】：煤与瓦斯突出灾害已经成为导致中国煤矿特大恶性事故的“头号杀手”，“瓦斯不治，矿无宁日”。中国煤系地层构造十分复杂且地应力大，采掘时极易发生瓦斯突出现象。面对如此严峻的煤矿安全形势，深入研究矿井和瓦斯地质赋存情况，为矿井安全生产提供可靠的地质保障和科学依据刻不容缓。构造煤作为煤与瓦斯突出的高危煤体是发生突出的必要条件，预测煤层中构造煤发育程度是评价瓦斯突出危险可能性的重要依据之一。 论文利用岩性地震反演方法(包括概率神经网络反演方法、弹性波阻抗反演方法和同步反演方法)，，研究了阳煤集团新景煤矿佛洼区15#煤层构造煤发育情况，以煤层中构造煤分布的角度评价来完成煤层瓦斯突出危险性预测。 第一，从构造煤岩石地球物理特征出发，分析了构造煤与原生煤在物理性质和化学性质方面的显著差异，总结归纳出几种常见岩石物理量的相互转化经验公式，为识别煤层中构造煤提供理论依据。 第二，从地震属性技术和基于模型反演理论入手，分析了地震属性反演的各种方法，研究了基于概率神经网络的叠后地震反演方法。 第三，从叠前地震反演的理论基础Zeoppritz方程出发，研究了基于Zeoppritz方程近似公式的弹性波阻抗反演理论，以及另一种叠前地震反演方法同步反演。 第四，完成阳煤集团新景煤矿佛洼区三维地震资料处理和地震岩性反演计算。利用概率神经网络反演方法获得孔隙度数据体；利用声波阻抗反演方法获得声波阻抗数据体；利用弹性波阻抗反演方法获得弹性波阻抗数据体；利用同步反演方法获得λ*ρ和μ*ρ岩性指示因子数据体。 第五，利用各种岩性数据体对15#煤层中构造煤分布进行预测。将孔隙度数据作为定性解释依据；弹性波阻抗(≤0.17)和声波阻抗(≤0.2)交会区域，λ*ρ值(≤15)和值(≤10)交会区域作为定量解释依据联合解释。 最后，提出了综合评价因子X的概念，实质是各类岩性数据体给定权重的线性组合。通过综合评价因子将15#煤层划分为5个岩性区域，即无构造煤分布区域、几乎无构造煤分布区域、构造煤分布范围较小区域、构造煤分布范围较大区域和构造煤分布区域。利用综合岩性指标预测了15#煤层瓦斯突出危险的可能性。
[Abstract]:The disaster of coal and gas outburst has become the "number one killer" that leads to serious accidents in coal mines in China. Gas outburst is easy to occur in mining. In the face of such a severe coal mine safety situation, in-depth study of mine and gas geological occurrence, It is urgent to provide reliable geological guarantee and scientific basis for mine safety production. Structural coal, as a high risk coal body for coal and gas outburst, is a necessary condition for outburst. Predicting the development degree of tectonic coal in coal seam is one of the important bases for evaluating the possibility of gas outburst. Using lithologic seismic inversion methods (including probabilistic neural network inversion method, elastic wave impedance inversion method and synchronous inversion method), the paper studies the development of structural coal in 15 # coal seam in Fuwa area of Xinjing Coal Mine of Yangmai Coal Group. The risk prediction of coal seam gas outburst is accomplished by evaluating the distribution of tectonic coal in coal seam. First, based on the geophysical characteristics of tectonic coal and rock, the significant differences between tectonic coal and primary coal in physical and chemical properties are analyzed, and the empirical formulas for the mutual transformation of several common rock physical quantities are summarized. It provides theoretical basis for identifying structural coal in coal seam. Secondly, based on seismic attribute technology and model-based inversion theory, various methods of seismic attribute inversion are analyzed, and poststack seismic inversion method based on probabilistic neural network is studied. Thirdly, based on the Zeoppritz equation, the elastic wave impedance inversion theory based on the approximate formula of Zeoppritz equation and another method for simultaneous inversion of prestack seismic inversion are studied. In 4th, 3D seismic data processing and seismic lithology inversion calculation were completed in Fuwa area of Xinjing Coal Mine of Yangmei Group. Porosity data volume was obtained by using probabilistic neural network inversion method, acoustic impedance data volume was obtained by acoustic impedance inversion method, and acoustic impedance data volume was obtained by acoustic impedance inversion method. The elastic wave impedance data volume is obtained by the elastic wave impedance inversion method, and the 位 * 蟻 and 渭 * 蟻 lithologic indicator factor data volumes are obtained by the synchronous inversion method. In 5th, using various lithologic data bodies to predict the distribution of tectonic coal in coal seam 15#, the porosity data was taken as the basis of qualitative interpretation. Elastic wave impedance (鈮

本文编号：1527983