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采区构造三维地震精细解释蚁群算法及其应用

Ant Colony Optimization and Application of 3-d Seismic Information for Refined Explaination of Structure in Mining Section

【作者】 李香臣

【导师】 秦勇;

【作者基本信息】 中国矿业大学 , 矿产普查与勘探, 2010, 博士

【摘要】 蚁群优化算法是非线性科学理论的一个分支。本文通过研究,奠定了应用蚁群优化算法进行矿井构造三维地震信息精细全空间解释的理论、方法和基础,提高了构造解释的效率和精度。研究表明,相干/方差体等地震属性技术能够突出地震波的空间不连续性,相干/方差切片对断层和构造异常体的分辨能力大大高于常规振幅切片,使显示断层和地质异常体的能力大大提高,可用于三维地震精细构造解释;首次将蚁群优化算法应用于煤层构造解释,结合蚁群优化算法的特点,确定蚁群优化聚类算法(ACOC)和基于图搜索式(GBAS)蚁群优化算法,并将其应用于兴隆庄煤矿七采区三维地震勘探资料的处理和解释,取得了较好的效果。本文插图70幅,附表4个,参考文献100篇。

【Abstract】 Ant colony optimization algorithm is a branch of the theory of non-linear science. This study established the theory, method and basis for the full space fine interpretation of mine structure using the ant colony optimization algorithm in 3-D seismic information, improved the accuracy and efficiency of structural interpretation. Research shows that such seismic attributes technology as coherent/variance can highlight the discontinuity in space, and the distinguishing ability of the coherent/variance slice is greatly higher than the conventional amplitude slice in the display of faults and anomalous body structure, which make the distinguishing ability of faults and geologic abnormal body greatly improved, and can be used for the fine interpretation of the 3-D seismic structure. This paper firstly apply the ant colony optimization algorithm into coal structure interpretation, and based on the characteristics of ant colony optimization algorithms, determines the ant colony optimization clustering (ACOC) and graph-base search (GBAS) algorithm. Good results have achieved in the application of 3-D seismic exploration data processing and interpretation in the seven panel of Xinglongzhuang colliery.

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