What is an Electromagnetic Locator? Principles, Methods, and Applications in Geophysical Exploration

1. ​Definition and Principles of Electromagnetic Locators

An electromagnetic locator is a geophysical tool that identifies subsurface targets by analyzing electrical property contrasts and electromagnetic field propagation

Key methods include:

• ​ERT (Electrical Resistivity Tomography): Uses dense electrode arrays to generate 2D/3D resistivity profiles for shallow high-resolution surveys (e.g., karst conduit detection).
• ​DC Resistivity Sounding: Profiles vertical resistivity variations by adjusting electrode spacing, ideal for deep stratigraphic analysis (e.g., coal mine goaf assessment).
• ​Induced Polarization (IP): Measures secondary potential decay to detect clay-rich or metallic deposits, complementing resistivity data.

2. ​2D vs. 3D Resistivity Imaging

1. ​2D ERT:
   • ​Strengths: Cost-effective for linear targets (e.g., railway foundations).
   • ​Limitations: Struggles with complex 3D structures (e.g., cave networks).
2. ​3D ERT:
   • ​Strengths: Cross-line layouts enable precise spatial modeling (e.g., goaf zones).
   • ​Challenges: Requires advanced algorithms (e.g., FEM forward modeling).

3. ​Applications and Case Studies

1. ​Coal Mine Goaf Detection:
   • ​Case Study: The WGMD-9 system identified low-resistivity anomalies in Hubei, China, mapping water-filled goaf boundaries using Wenner Array and pseudo-3D inversion.
2. ​Karst Geological Survey:
   • ​Case Study: ERT delineated dissolution fissures in Guangdong limestone, guiding pile foundation design. High resistivity indicated intact bedrock, while low resistivity reflected water-bearing fractures.
3. ​Underground Pipeline Mapping:
   • ​Challenge: Non-metallic pipes (e.g., PVC) require Dipole-Dipole arrays for enhanced sensitivity.

4. ​Forward Modeling vs. Inversion

1. ​Forward Modeling:
   • ​FEM: High accuracy for complex terrains but computationally intensive.
   • ​Analytical Solutions: Fast calculation for layered models.
2. ​Inversion Algorithms:
   • ​Regularized Inversion (L1/L2 Norm): Enhances stability via smoothness constraints.

5. ​Advantages and Limitations

• ​Advantages:
  1. ​Non-Destructive: Ideal for archaeological surveys.
  2. ​Multi-Parameter Fusion: Resistivity + IP data for contaminant detection.
• ​Limitations:
  1. ​Depth Constraints: Limited penetration (<200 m).
  2. ​Topographic Noise: Requires correction for steep slopes

Further reading | Technical solutions related to this article

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