• Title/Summary/Keyword: Anomaly Identification

Search Result 51, Processing Time 0.016 seconds

Case Studies of Geophysical Mapping of Hazard and Contaminated Zones in Abandoned Mine Lands (폐광 부지의 재해 및 오염대 조사관련 물리탐사자료의 고찰)

  • Sim, Min-Sub;Ju, Hyeon-Tae;Kim, Kwan-Soo;Kim, Ji-Soo
    • The Journal of Engineering Geology
    • /
    • v.24 no.4
    • /
    • pp.525-534
    • /
    • 2014
  • Environmental problems typically occurring in abandoned mine lands (AML) include: contaminated and acidic surface water and groundwater; stockpiled waste rock and mill tailings; and ground subsidences due to mining operations. This study examines the effectiveness of various geophysical techniques for mapping potential hazard and contaminated zones. Four AML sites with sedimentation contamination problems, acid mine drainage (AMD) channels, ground subsidence, manmade liner leakage, and buried mine tailings, were selected to examine the applicability of various geophysical methods to the identification of the different types of mine hazards. Geophysical results were correlated to borehole data (core samples, well logs, tomographic profiles, etc.) and water sample data (pH, electrical conductivity (EC), and heavy metal contents). Zones of low electrical resistivity (ER) corresponded to areas contaminated by heavy metals, especially contamination by Cu, Pb, and Zn. The main pathways of AMD leachate were successfully mapped using ER methods (low anomaly peaks), self-potential (SP) curves (negative peaks), and ground penetrating radar (GPR) at shallow penetration depths. Mine cavities were well located based on composite interpretations of ER, seismic tomography, and well-log records; mine cavity locations were also observed in drill core data and using borehole image processing systems (BIPS). Damaged zones in buried manmade liners (used to block descending leachate) were precisely detected by ER mapping, and buried rock waste and tailings piles were characterized by low-velocity zones in seismic refraction data and high-resistivity zones in the ER data.