内蒙古兴安盟吉日根林场地区磁测数据处理解释

发布时间：2018-12-14 02:16

【摘要】：随着国内经济的快速发展,人类社会逐渐步入工业化社会。社会的工业化将使人类越来越重视资源短缺带来的社会影响。因此,进行区域地质调查和矿产勘查更加刻不容缓。磁法勘探是一种利用目标地质体与围岩的磁性差异及磁场特征来直接或间接寻找各类磁性矿体的物探方法,是一种不可缺少的地球物理方法。随着矿产资源的日益减少和勘查精度的不断提高,人们对外围矿和深部矿的关注越来越多。这不仅需要磁测仪器有更高的精度,更重要的是选取合适的数据处理方法,从实测资料中提取更多的有利信息,为矿产勘查提供可靠依据。本文将磁法数据综合处理方法应用于内蒙古兴安盟吉日根林场区,主要的研究内容有:1.对解析延拓法、趋势面分析法、有限元法等三种位场分离方法以及Theta图法、斜导数法、解析信号振幅法、欧拉反褶积等边界识别技术和断裂划分技术进行了较为系统的分析比较并应用于实际资料处理中。2.通过组合模型试验,对Theta图法、斜导数法、解析信号振幅法以及欧拉反褶积等四种边界识别技术在磁异常处理方面的应用进行较为系统的分析比较。根据模型试验结果,发现四种边界识别方法的适用性有一定的差别。综述,在实际的数据处理解释过程中,不要过度依赖于某一种或者是某一类边界识别方法,应当将多种方法综合应用,从而得到较为准确的处理结果。3.对内蒙古兴安盟吉日根林场区地磁数据进行处理,在数据经过化磁极等预处理的基础之上,通过解析延拓对研究区的基底情况进行初步解释。使用向上延拓、趋势面分析以及有限元法对磁异常进行分离,分别利用剩余磁异常和垂向导数推测可能地质体的范围。通过斜导数等边界识别技术,对测区内可能存在的断裂构造进行了划分。通过分层视磁化率计算和磁性界面反演,了解研究区的磁性地质体分布和基底形态。利用上述资料,结合遥感、化探异常区,推断出了研究区内的11条构造线和2个找矿靶区。为该地区后续将要进行的地质地球物理工作提供一定的依据。
[Abstract]:With the rapid development of domestic economy, human society has gradually stepped into the industrialized society. The industrialization of society will make people pay more and more attention to the social impact brought by the shortage of resources. Therefore, it is urgent to carry out regional geological survey and mineral exploration. Magnetic prospecting is a kind of geophysical method which can directly or indirectly find all kinds of magnetic orebodies by using the magnetic difference between the target geological body and the surrounding rock and the magnetic field characteristics. It is an indispensable geophysical method. With the decreasing of mineral resources and the improvement of exploration precision, people pay more and more attention to peripheral and deep ore. It is necessary not only to have higher precision of magnetic measuring instruments, but also to select suitable data processing methods and to extract more favorable information from measured data, thus providing reliable basis for mineral exploration. In this paper, the comprehensive processing method of magnetic data is applied to the Jirgen Forest Farm of XingUNITA, Inner Mongolia. The main research contents are as follows: 1. Three potential field separation methods, such as analytical continuation method, trend surface analysis method, finite element method, Theta diagram method, oblique derivative method, analytical signal amplitude method, etc. Euler deconvolution and fault division techniques are analyzed and compared systematically and applied to practical data processing. 2. The application of four boundary recognition techniques, Theta diagram, oblique derivative method, analytical signal amplitude method and Euler deconvolution in magnetic anomaly processing, are analyzed and compared systematically through combined model tests. According to the model test results, it is found that the applicability of the four boundary recognition methods is different. In this paper, in the process of actual data processing and interpretation, we should not rely too much on one or one kind of boundary recognition methods. This paper deals with the geomagnetic data of Jirgen Forest Farm of XingUNITA, Inner Mongolia. On the basis of the pretreatment of the data through the chemical magnetic pole and other preprocessing, the basic condition of the study area is preliminarily explained by means of analytic extension. The magnetic anomalies are separated by upward continuation, trend surface analysis and finite element method. The range of possible geological bodies is estimated by residual magnetic anomalies and vertical guide numbers, respectively. By means of oblique derivative and other boundary recognition techniques, the possible fault structures in the measured area are divided. By calculating the apparent susceptibility of stratification and inversion of the magnetic interface, the distribution of the magnetic geological bodies and the shape of the basement in the study area are understood. Based on the above data, 11 tectonic lines and 2 ore-prospecting targets in the study area are inferred by combining with remote sensing and geochemical anomalies. It provides some basis for the geological and geophysical work to be carried out in this area.
【学位授予单位】：吉林大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：P631.2

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