平原区深层隐伏岩溶的重力正演模拟
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  • 英文篇名:Gravity Forward Modeling of Deep Burial Karst in Plain Areas
  • 作者:王立发 ; 雷晓东 ; 何祎
  • 英文作者:WANG Lifa;LEI Xiaodong;HE Yi;Beijing Institute of Geo-exploration Technology;
  • 关键词:重力 ; 岩溶 ; 正演
  • 英文关键词:Gravity;;Karst;;Forward modeling
  • 中文刊名:CSDZ
  • 英文刊名:Urban Geology
  • 机构:北京市地质勘察技术院;
  • 出版日期:2018-12-15
  • 出版单位:城市地质
  • 年:2018
  • 期:v.13
  • 基金:通州城市副中心地区重大地质问题调查与评价项目(PXM2016_158203_000008);; 中国地质调查局项目(12120114033901)联合资助
  • 语种:中文;
  • 页:CSDZ201804004
  • 页数:5
  • CN:04
  • ISSN:11-5519/P
  • 分类号:23-27
摘要
岩溶塌陷一般发生在覆盖层较薄的地区,深层岩溶塌陷虽较少见,但若发生在城市建筑密集区其危害极大。为研究北京东部地区深层岩溶发育的地质条件,对不同尺度的岩溶风化壳和溶洞可能产生的重力异常响应进行了正演模拟,结果表明:厚覆盖层地区开展微重力测量识别一定规模的岩溶是可行的,覆盖层厚度大于200m、半径小于2m的空洞将难以通过微重力方法直接识别出来;岩溶空洞引起重力异常的幅值与其半径、埋深及内部充填物的密度有关;实测剖面长度应大于岩溶风化壳宽度或空洞直径,且需要在实测重力异常中准确去除覆盖层的影响。
        Karst collapse usually occurs in the areas with thin covered strata. Although deep burial karst collapse is rare, it will be extremely harmful when it is located in densely populated areas of urban buildings. In order to study the geological conditions of deep burial karst in the eastern part of Beijing and to prevent the risk of collapse, it is necessary to carry on the gravity forward modeling research on weathering crust and cavity. Based on the gravity forward modeling, the gravity anomaly response characteristics of different scales have been obtained. The results show that:(1) it is feasible to identify a certain scale karst by high-precision gravity survey in thick burial karst areas, however, it is difficult to directly identify the karst cavities with a thickness of more than 200 m and a radius of less than 2 m by microgravity method;(2) The amplitude of gravity anomaly caused by karst cavity is related to its radius, buried depth and the density of internal fillings;(3) To effectively identify the karst cavity, the length of gravity profile should be larger than the width of karst weathering crust or the cavity's diameter, and the influence of the covered strata should be accurately removed from the measured gravity anomaly data.
引文
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