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What is Wenner Array? A Comprehensive Guide to High-Density Electrical Resistivity Imaging

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​1. Definition and Principles of Wenner Array

The ​Wenner Array is a classic four-electrode configuration widely used in resistivity and high-density electrical surveys. It employs four equally spaced electrodes (A, M, N, B) to measure apparent resistivity based on Ohm’s Law:
ρa​=2πa⋅IΔV​
where a is electrode spacing, ΔV is voltage difference, and I is injected current.

This symmetrical design minimizes lateral interference, making it ideal for homogeneous media (e.g., aquifers, backfill soil) and shallow-depth surveys (<100m).

​2. Method Comparison

Wenner Array vs. Schlumberger vs. Dipole-Dipole

  • ​Wenner Array:
    • ​Strengths: High horizontal resolution (error <5%), simplicity, and stability in layered media.
    • ​Limitations: Fixed spacing limits depth exploration; lower efficiency than Schlumberger.
  • ​Schlumberger Array:
    • ​Strengths: Flexible spacing for deeper surveys (>200m) and vertical stratification analysis.
    • ​Limitations: Requires advanced software (e.g., Res2Dinv) for complex data processing.
  • ​Dipole-Dipole Array:
    • ​Strengths: High lateral resolution for complex structures (e.g., faults, caves).
    • ​Limitations: Weak signals and susceptibility to noise.

2D vs. 3D ERT Imaging

  • ​2D ERT: Cost-effective for linear targets (e.g., leakage channels) but limited to single profiles.
  • ​3D ERT: Reveals 3D structures (e.g., contaminant plumes) but requires extended data collection and computational resources.

​3. Applications & Case Studies

Groundwater Contamination Assessment

  • ​Case: A chemical plant combined Wenner-Schlumberger arrays to map chlorinated hydrocarbon diffusion, achieving 90% alignment with borehole data.

Landfill Boundary Detection

  • ​Technique: High-density method + Wenner Array identified low-resistivity anomalies (2–15 Ω·m) with <3m error margins.

Karst Cave Detection

  • ​Result: Pseudo-3D Wenner Arrays pinpointed cave boundaries, reducing grouting costs by 30%.

​4. Forward Modeling & Inversion

Forward Modeling

  • ​Purpose: Validates theoretical models (e.g., layered media) using finite element analysis (FEM)5.
  • ​Tools: COMSOL Multiphysics, FEMM.

Inversion Algorithms

  • ​Least Squares: Smooth models but prone to local minima.
  • ​Occam Inversion: Regularization-based optimization improves stability (e.g., GeoTom software).

Case Study: A geothermal project initially misjudged fracture orientations using 2D inversion. Switching to 3D inversion improved accuracy by 35%.

  • ​AI Integration: Convolutional Neural Networks (CNNs) reduce inversion computation time by 50%.
  • ​Multi-Physics Fusion: ERT + seismic imaging resolves ambiguities (e.g., aquifer vs. clay layers).
  • ​Hardware Innovations: Distributed systems (e.g., 64-channel Geopen E60DN) enable real-time data transmission.

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Further reading | Technical solutions related to this article

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