# Box 1 Scenario Evaluator for Electrical Resistivity (SEER)

As discussed in Section 2, synthetic modeling provides useful insight for 1) designing geophysical surveys, and 2) understanding the ability of a given survey to resolve a hypothetical target. Synthetic modeling provides a basis for ‘go/no-go’ decisions on geophysical field campaigns, i.e., whether a survey can adequately resolve expected targets so is worth the expense. Many public-domain and commercially available off-the-shelf software packages for electrical imaging provide synthetic modeling capabilities. In this exercise, we consider the public-domain tool SEER, the Scenario Evaluator for Electrical Resistivity. Available for free from the U.S. Geological Survey, SEER is a spreadsheet-based tool for synthetic modeling of resistivity experiments. SEER is user friendly but limited in its functionality.

To get started with the SEER software, proceed through the steps described in the following bullets, then set up a simple model as described and continue with the activities.

• Download the zip file containing SEER from the USGS repository at https://doi.org/10.5066/F7028PQ1. The README file on the web page provides a brief overview and background information about the software.
• Extract the contents of the zip file into a folder on your computer. This will produce the SEER.xlsm spreadsheet, the SEERhelp.chm file which is an electronic user’s manual that can be accessed by double clicking on the file, and a folder titled “ResponseArrays” that contains the results of previously executed simulations. There is also an instructional video that describes electrical resistivity imaging and explains how SEER can be useful to designing electrical resistivity surveys.
• Open the spreadsheet. You will need to enable macros when requested to do so by Excel. After reading the INTRO worksheet, navigate to the “Survey” worksheet. There are four template models available from the Scenario drop-down menu in cell B1 of the worksheet. These include 1) DNAPL pool, 2) LNAPL pool, 3) underground storage tank (UST), and 4) block targets (BLOCKS); these can all be modified by the user. In cells B4 through B7, the user may adjust survey parameters including the number of electrodes, type of survey, measurement error levels, and whether borehole electrodes will be used. Familiarize yourself with the operation of the spreadsheet and the three template models, by making selections and clicking the “Simulate” button.

To explore how to make a custom model by selecting a template and modifying the parameters. Begin by selecting the UST template model. Starting from this template of a layered system, you can create a homogeneous background. Be sure to unclick the ‘Using specified scenario checkbox’ to enable a custom model. You will assess the ability of electrical imaging to resolve a water filled cavity. Change the background for the UST model to 500 ohm-m. Assume 1-m electrode spacing, 10% measurement error, and a dipole-dipole survey. Next. explore what you can do with the SEER software through the following activities.

Activity 1) Assume the electrical conductivity of the water-filled cavity is 200 micro-S/cm. Convert the fluid conductivity to resistivity for input to the spreadsheet. (Hint: resistivity is the reciprocal of conductivity, and 10 S is equivalent to 0.1 ohms.)

Solution to activity 1

Activity 2) Assume the cavity occupies the space from cells in columns AL to AO and rows 13 to 15, and assign the resistivity you calculated to these cells. Press the ‘Simulate’ button and the spreadsheet will produce the predicted inversion result for your hypothetical model. Evaluate how well your predicted inversion result compares to your true cavity model. Consider its resolution of the top, sides, and bottom of the cavity, as well as how well the estimated resistivity compares to the true resistivity.

Solution to activity 2

Activity 3) Explore how changing the measurement error to 1% and pressing the ‘Simulate’ button changes the result.

Solution to activity 3

Activity 4) Explore how changing the survey type to ‘Combined’ and pressing the ‘Simulate’ button changes the result.

Solution to activity 4

Activity 5) Explore how adding borehole electrodes and pressing the ‘Simulate’ button changes the result.

Solution to activity 5

Having gained familiarity with how to change both subsurface properties and survey parameters, we encourage you to explore other subsurface systems and combinations of survey configurations. Given the level of importance of precisely defining subsurface properties for a given project, simulating the resistivity survey before undertaking the field work provides the information needed to design the field survey by balancing the cost of conducting the survey against the expected resolution in the result. Of course, one needs to have an estimate of the size, depth, and relative resistivity of the features of interest.

Solution to Activity 1

To calculate the cavity resistivity based on the conductivity of 200 micro-S/cm, first convert to S/m.

$\displaystyle \frac{200\ \textrm{micro-S}}{\textrm{cm}}\frac{1\ \textrm{micro-S}}{1\times 10^{6}\ \textrm{S}}\frac{100\ \textrm{cm}}{1\ \textrm{m}}=0.02\frac{\textrm{S}}{\textrm{m}}$

$\displaystyle \textrm{Resistivity}=\frac{1}{\textrm{Conductivity}}=\frac{1}{0.02\frac{\textrm{S}}{\textrm{m}}}=50\ \textrm{ohm-m}$ → the inverse of Seimens is ohm

Solution to Activity 2

The predicted inversion result is blurry and blunt compared to the true model. The top is relatively well resolved, the sides less so, and the bottom is poorly resolved. The estimated resistivity does not capture all of the contrast between the background resistivity (500 ohm-m) and the cavity resistivity (50 ohm-m); the minimum value estimated inside the cavity is about 370 ohm-m compared to 50 ohm-m.

Solution to Activity 3

By assuming a smaller measurement error of 1%, the general pattern is the same, but the estimated resistivity is closer to the actual resistivity of the target, with a minimum estimated resistivity of ~320 ohm-m.

Solution to Activity 4

Changing the survey type to ‘Combined’ results in the same general pattern of estimated resistivity, so one concludes that adding Wenner measurements alone does not improve the results sufficiently to warrant the additional field effort.