一种基于重磁数据智能融合的深部地质建模方法  

Intelligent fusion based on gravity and magnetic data-deep geologic modeling method

作　　者：葛藤菲 黄旭钊 范正国 何敬梓 王思浔 GE Teng-fei;HUANG Xu-zhao;FAN Zheng-guo;HE Jing-zi;WANG Si-xun(China University of Geosciences,Beijing 100083,China;China AeroGeophysical Survey and Remote Sensing Center for Natural Resources,Beijing 100083,China)

机构地区：[1]中国地质大学(北京),北京100083 [2]中国自然资源航空物探遥感中心,北京100083

出　　处：《地球物理学进展》2020年第6期2323-2331,共9页Progress in Geophysics

基　　金：国家重点研发计划重点专项的课题(2017YFC0602206);秦岭—大别造山带航空物探遥感调查(dd20190551)联合资助。

摘　　要：三维地质建模可应用于地质体深部构造研究、地下水资源调查、裂缝变形监测、地质灾害预测等方面.地表地质填图已有多种成熟的方法,但是地下深部地质建模依然面临诸多挑战.理论上,地下深部地质构造尽管肉眼不可见,但重、磁、电、震等地球物理信息可以在某种程度上间接反映深部地质构造情况.本文结合近年来快速发展的现代信息处理技术,基于较为成熟的重磁数据反演方法,尝试提出了一种基于重磁数据融合的地下深部岩性智能识别及建模方法,并通过试验数据验证和戈壁荒漠地区实测数据应用,表明该方法具对于深部地质构造的分析及矿产发现有很好的应用潜力.Three dimensional geological mapping and modeling can be applied to many fields such as deep geological structure, prediction of mineral resource and geological disasters, investigation of groundwater resources, fracture deformation monitoring. There are many mature methods for surface geological mapping, but underground geological modeling still faces many challenges. In theory, although the underground geological structure cannot be observed directly, the deep geological structure can be reflected indirectly to some extent by the geophysical information such as gravity, magnetism, electricity and seismic. In this paper, a intelligent fusion classification and geologic modelling is put forward using the gravity and magnetic data inversion. The application in Gobi-desert area shows that the method is effective and can be used for the deep geologic modeling and mineral prediction.

关 键 词：航磁 重力 智能融合 概念聚类 深部地质建模 

分 类 号：P631[天文地球—地质矿产勘探]