Unit 4: The Magic of Geophysical Inversion

Compiled by Lee Slater, Rutgers University Newark (lslater@newark.rutgers.edu)

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This page first made public: Feb 3, 2022

Summary

This unit introduces the student to the concept of geophysical inversion, which is the process of estimating the geophysical properties of the subsurface from the geophysical observations. The basic mechanics of the inversion process used to estimate spatial variations in electrical conductivity from electrical imaging (EI) datasets are introduced in a way that avoids the heavy mathematics. The challenges of inverting two dimensional geophysical datasets and the strategies for limiting the inversion to geologically reasonable solutions are described. The unfortunate characteristics of geophysical images (blurriness, imaging artifacts) are explained to highlight the limitations of inversion and to emphasize that the inverted images never match with geological reality. Students use the Excel-based Scenario Evaluator for Electrical Resistivity (SEER) tool introduced in Unit 3, Field Geophysical Measurements, to investigate key inversion concepts associated with measurement errors and the benefits of adding boreholes to surface data using synthetic datasets. Students are then led through an inversion of the two-dimensional EI dataset acquired in Harrier Meadow using ResIPy, a Python-based graphical user interface developed for instructional use. Following the instructional video, students then perform the inversion in ResIPy themselves and explore how variations in inversion settings related to the errors in the measurements result in distinctly different images.

Electrical Conductivity/Resistivity, Surface Water , Wetlands, Point ...(more) | College Introductory | Demonstrate Relevance, Introductory Courses

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Topics

Electrical Conductivity/Resistivity, Surface Water , Wetlands, Point Source Pollution, Landfills, Sustainability, Ecosystems, Environmental Chemistry, Environmental Science

Grade Level

College Introductory

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Learning Goals

Students will be able to :

Understand the mechanics of the geophysical inversion of resistivity imaging datasets
Identify the effects of measurement errors on the inversion of resistivity datasets through application of an Excel-based modeling tool
Explore the benefits of adding boreholes to surface resistivity imaging measurements through application of the same Excel-based modeling tool
Use the open-source interface ResIPy to complete a guided inversion of an electrical resistivity dataset from data entry, basic data processing, inversion and visualization.
Explain the critical importance of accurately quantifying the measurement errors by experimenting with how the error estimates impact inversion performance using ResIPy

Context for Use

This unit is designed as a guided learning project that is foremost to be used as part of a series for an introductory geophysics lab. It is the fourth of a sequence of five units and designed to take approximately 1.5-2.0 hours, with students doing independent exploration in an Excel spreadsheet and also using the open source software ResIPy. The target audience is first year or sophomore earth and environmental science students with little prior experience with near surface geophysics. However, the materials could easily be adapted and expanded by faculty teaching an upper level undergraduate course in geophysics. The materials needed to use this unit are all provided as embedded links, handouts and resistivity imaging datafiles. This unit could also be used as an independent (of the remaining units) module to teach electrical resistivity inversion concepts. The video that introduces ResIPy can be used by instructors and/or students who need training on basics of resistivity imaging using ResIPy before attempting to process their own datasets.

Description and Teaching Materials

Students use the Excel-based Scenario Evaluator for Electrical Resistivity (SEER ) tool introduced in Unit 3 to investigate key inversion concepts associated with measurement errors and the benefits of adding boreholes to surface data using synthetic datasets. Students are then led through an inversion of the two-dimensional EI dataset acquired in Harrier Meadow using ResIPy, a Python-based graphical user interface developed for instructional use on PCs. Following the instructional video, students then perform the inversion in ResIPy themselves and explore how variations in inversion settings related to the errors in the measurements result in distinctly different images. Note that SEER and ResIPY run on PCs but not on most Macs. ResIPY will run on some Macs, depending on operating system, processing chip, and other installed software.

Materials provided:

Tutorial on geophysical inversion (PowerPoint Slideshow (.ppsx) 21.4MB Oct22 21): Narrated slideshow that covers the basics of the "magic" of geophysical inversion focused on the inversion of 2D resistivity datasets. Please see the note about colorblindness in the "Teaching notes and tips" section of this page.
Student handout, Wetlands unit 4 (Microsoft Word 2007 (.docx) 85kB Oct22 21): Student activities handout that leads the student through three primary activities making up the unit

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Approximating resistivity inversions using SEER
Provenance: Lee Slater, Rutgers University-Newark
Reuse: This item is in the public domain and maybe reused freely without restriction.
USGS-developed Excel-based tool, Scenario Evaluator for Electrical Resistivity (SEER) , for simulating electrical imaging datasets that might be recorded over some common near surface Earth structures (used to explore the effects of measurement errors). This was used in Unit 3 of this module, Field Geophysical Measurements.
ResIPy handout (Microsoft Word 2007 (.docx) 487kB Oct22 21): Handout that describes a guided exercise to be completed with the open-source resistivity imaging software ResIPy
A tutorial on using ResIPy (MP4 Video 15.6MB Sep11 20): Supporting video file providing a step by step guide on inverting the 2D dataset from Harrier Meadow in ResIPy.
The two resistivity data files from Harrier Meadow. Both files are needed for the ResIPy exercise. They must be located in the working directory specified in ResIPy (see the video tutorial):
1. Normal measurements: Harrier Meadow normals.csv (Comma Separated Values 184kB Jun20 20)
2. Reciprocal measurements: Harrier Meadow reciprocals.csv (Comma Separated Values 150kB Jun20 20)
Student worksheet, Wetlands unit 4 (Microsoft Word 2007 (.docx) 94kB Oct22 21): Student worksheet where students perform and/or report calculations and observations related to the items above. This worksheet can be used for assessment.

Answer keys and solution sets are available for instructors. See the "Assessment" section of this page, below.

Teaching Notes and Tips

Students should first watch the narrated slideshow that provides a high-level introduction to the mechanics of resistivity inversion. Note that the PPSX file can be opened as a regular Powerpoint file if Powerpoint is running. The students then complete the tasks in the order described in the student handout. Hopefully, the video tutorial on ResIPy is sufficiently explanatory to allow the students to then experiment with the inversion settings. However, the instructor is advised to go through the video and the ResIPy exercise on their own first.

ResIPy is very intuitive to use and the adopter of this unit is encouraged to attempt an inversion of their own datasets if they have an opportunity to use them. Both SEER and ResIPy require the student to download fairly large files onto a local computer. If this is a problem, the instructor might consider putting the software onto a shared PC that can be accessed using remote desktop software. For ResIPy it is critical to download the two data files (included in the teaching materials section, above) to a working directory that is specified in ResIPy (described in the video tutorial, also included in the teaching materials). Note that SEER and ResIPY run on PCs but not Macs.

Note: approximately one in 12 males and one in 200 females are red-green colorblind; for these people, the red and green portions of the resistivity datasets and models are indistinguishable from each other. (If you have "normal" color vision, you can use this color blindness simulator to see what the images look like to people with many different kinds of color vision deficiencies.) One way to accommodate students with colorblindness is to have students work in pairs or small groups.

Assessment

The Student worksheet, Wetlands unit 4 (Microsoft Word 2007 (.docx) 94kB Oct22 21) is designed to help evaluate whether students have grasped the main concepts related to the resistivity and electromagnetic conductivity mapping methods introduced in this assignment. Note: This file is also linked above, in the Teaching Materials section of this page.

Solutions for instructors

Answer key, student worksheet, Wetlands unit 4 -- private instructor-only file
Answer key, Wetlands unit 4 ResIPy exercise -- private instructor-only file
. Provides a solution to Table 1 in the ResIPy assignment.

References and Resources

Open source software:

SEER, an Excel-based Scenario Evaluator for Electrical Resistivity (for PCs only)
ResIPy, a Python-based graphical user interface (doesn't run on most MacOS).

References:

Blanchy, G., Saneiyan, S., Boyd, J., McLachlan, P. and Binley, A. (2020) ResIPy, an intuitive open source software for complex geoelectrical inversion/modeling, Computers and Geosciences. Elsevier Ltd, 137(February), p. 104423. doi: 10.1016/j.cageo.2020.104423.

Terry, N., Day-Lewis, F. D., Robinson, J. L., Slater, L. D., Halford, K., Binley, A., Lane, J. W. and Werkema, D. (2017) Scenario Evaluator for Electrical Resistivity Survey Pre-modeling Tool, Groundwater, 55(6), pp. 885–890. doi: 10.1111/gwat.12522.

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