Electrical Methods
Electrical resistivity spans more orders of magnitude than any other rock property, which makes current-based methods the workhorses of environmental geophysics. This module covers galvanic resistivity surveying (VES and ERT), the passive self-potential (SP) method, and induced polarization (IP).
Learning Objectives
Undergraduate Core: By the end of this module, you will be able to:
- Explain electrolytic conduction and the roles of saturation, salinity, porosity, clay, and temperature.
- Calculate geometric factors and distinguish true, apparent, and inverted resistivity.
- Compare Wenner, Schlumberger, and dipole–dipole survey behavior.
- Distinguish ERT, SP, and IP mechanisms and avoid treating any response as a unique hydrologic property.
Graduate Extension
Examine sensitivity functions, regularization, equivalence, Cole–Cole conventions, and uncertainty in petrophysical conversion from resistivity to water content.
Practice this module Teach with active-learning slides
Interactive Lecture
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🖥️ How Do Rocks Conduct Electricity?
Electrolytic conduction, Archie's law, and what controls formation resistivity.
Topic Apps
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🖥️ ERT · Geometric Factor K for Common Arrays
Wenner, Schlumberger, and dipole-dipole geometries and their sensitivity.
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🖥️ ERT · 3-Layer VES Forward Modeling
Build layered models and generate vertical electric sounding curves.
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Streaming, diffusion, and mineral potentials behind self-potential signals.
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Seepage detection, contaminant plumes, and other SP use cases.
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Membrane and electrode polarization, chargeability, and time- vs. frequency-domain IP.
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🖥️ IP · Cole-Cole Model Interactive
Explore how Cole-Cole parameters shape the complex-resistivity spectrum.
Demo
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⚡ Apparent-Resistivity Pseudosection Builder
Place a conductive or resistive body in the subsurface, pick an array, and build the pseudosection measurement by measurement.
Classroom Lab
🧰 Three-layer VES group investigation — divide into curve-type, suppression, and equivalence teams, then explain why apparent resistivity and electrode spacing are not a literal depth section.
Research Code: PyHydroGeophysX
From resistivity to water content
The petrophysics in this module (Archie's law, and its clay-corrected cousin the Waxman-Smits model) is exactly how field ERT becomes hydrology. PyHydroGeophysX, developed in Dr. Chen's group, implements these transforms together with full 2D and 3D ERT forward modeling and inversion, including time-lapse and structure-constrained inversion for watershed monitoring.
- Full ERT workflow: mesh, forward model, invert.
- Time-lapse ERT inversion: track moisture change over time.
- Structure-constrained inversion: sharpen boundaries using seismic structure.
Background reading: Archie (1942), Loke et al. (2013), and Binley & Slater (2020) on the References page.