What is Electrical Resistivity Imaging (ERI)?

DC electrical resistivity surveying introduces an electrical field into the subsurface at two points and measures the resulting difference in electrical potential between two other surface points. The current applied using two point electrodes travels into the subsurface ideally along arc-shaped paths as shown in Fig. 1 (bold lines). Orthogonal to these current flowlines are bowl-shaped surfaces of equal electrical potential (Fig. 1, light lines) that intersect the surface.

Subsurface materials possess a wide range of electrical resistivities that distort current flowlines and cause variations in the equipotential surfaces. The spatial pattern of potential differences at surface provides information about the subsurface resistivity distribution which can be related to the types and geometry of rock and sediment, water properties, and even contaminants. Where only surface electrodes are used, this surveying is referred to as electrical resistivity imaging (ERI).

Fig. 1. Vertical section of equipotential surfaces orthogonal to current flowlines (bold) between point current source C1 and C2 in homogenous ground of resistivity ρ. Lines of current flow are labelled with cumulative percentages of total current flowing above the lines. *

ERI is implemented using electrodes either planted in the ground surface or towed through water. All electrodes are connected via cable to a multichannel resistivity meter (Fig. 2) that applies current using various pairs of electrodes and measures the induced electrical potential at the other electrode pairs. Measurement involves sequencing between many different configurations for the current electrodes and potential electrodes. The configurations include increasing the spacing between electrodes which increases the depth to which current penetrates.

Fig. 2.  Resistivity meter (yellow box) with cables connected to electrodes spread across field. Two batteries on left supply power.

WP Platform usage

Fig. 3.  A “pseudo-section” showing apparent resistivity data in color with units of Ohm-m (Ωm) on a plot of distance along the surface versus depth. Electrodes on the surface are depicted by filled boxes.  The enlarged apparent resistivity data point plotted at 7 m depth resulted from current applied at the enlarged orange and red electrodes and potential measured at the enlarged cyan and dark blue electrodes. Each data point is a weighted average of the subsurface resistivity distribution. The depth of an apparent resistivity point in the diagram positively correlates to electrode separation.

An ERI survey produces a large number of resistivity – more precisely, apparent resistivity – data points that are displayed in a pseudo-section (Fig. 3). Inverse modeling techniques are used to converge on a subsurface resistivity distribution that, if measured, would give apparent resistivities that closely resemble the observed data. A typical subsurface resistivity distribution resulting from inversion is shown in Fig. 4. The subsurface resistivity distribution reproduces the observed apparent resistivity data to a specified level of uncertainty but it is not a unique solution.

ERI is a reliable, moderate-resolution geophysical technique that has been used with success in a wide variety of hydrological, geotechnical, environmental, and mining applications.  Geologic control is vital for interpreting resistivity in terms of local geologic units, subsurface fluids, and contaminants.

Fig. 4.  Vertical section of a typical subsurface resistivity image to a depth of 100 ft along a Minnesota highway. Color scale indicates resistivity. Geologic interpretation is based on the two boreholes in the image center (vertical black lines). Areas exhibiting high resistivity (red) are confirmed gravelly sand. Low resistivities (blues) represent confirmed sandy clay loam. Intermediate resistivity areas (yellow) are dominantly sand.  Note that images give a spatially continuous representation of resistivity and also that delineation of unit contacts is based on independent data.**

* Burger, H. R., Sheehan, A. F., and Jones, C. H., 2006, Introduction to Applied Geophysics: Exploring the Shallow Subsurface, New York, W.W. Norton, 554 p.
** Image courtesy of MNDOT