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Electrical Imaging for Hydrogeology

Book cover for Electrical Imaging for Hydrogeology

Publication year: 2022
Number of pages: 74
ISBN: 978-1-77470-011-2

Authors:
Kamini Singha – Colorado School of Mines, USA
Tim Johnson – Pacific Northwest National Laboratory, USA
Frederick Day-Lewis – Pacific Northwest National Laboratory, USA
Lee Slater – Rutgers University, USA

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Updated: 15 March 2023

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Electrical Imaging for Hydrogeology

1 file(s) 4.47 MB
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Spanish translation by Pablo Guerrero y Ángel Intriago

Released: 17 August 2023

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Imágenes Eléctricas en Hidrogeología

1 file(s) 3.71 MB
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Book Description

Geophysical methods offer hydrogeologists unprecedented access to understanding subsurface parameters and processes. In this book, we outline the theory and application of electrical imaging methods, which inject current into the ground and measure the resultant potentials. These data are sensitive to rock type, grain size, porosity, pore fluid electrical conductivity, saturation, and temperature. Here, we describe the physical basis for electrical imaging, parallels between electrical flow equations and the groundwater flow equation, practical considerations for field investigations, data processing and inverse modeling of field data, and how to QA/QC data. We additionally cover two case studies, including a 2-D waterborne survey and a 4-D dataset from a biostimulation experiment.

Contents

1 INTRODUCTION

1.1 Measurement Physics: The Relation Between Data (Voltage Differences) and Parameters (Electrical Conductivity or Chargeability)

1.2 Electrical Imaging Hardware and Field Deployments

2 DESIGNING SURVEYS

2.1 Geometric Factors

2.2 Synthetic Models

3 COLLECTION AND VERIFICATION OF FIELD DATA

3.1 Contact Resistance

3.2 Stacked Measurements

3.3 Reciprocal Measurements

3.4 Error Considerations for Time Lapse Measurements

3.5 Pulse Duration

3.6 Notes on Field Conditions

4 DATA INVERSION

4.1 The Goal of Inversion

4.2 Regularization in Electrical Imaging Inversion

4.3 Selection of Inversion Parameters to Prevent Overfitting/Underfitting of Data

4.4 Definition of Data Misfit

4.5 Quantification of Inversion Quality

4.6 Checks on Inversion Results

5 CASE STUDIES

5.1 2-D Waterborne Resistivity and Induced Polarization Profiling Background

Data Collection
Data Processing
Data Interpretation

5.2 4D Resistivity of a Biostimulation Experiment

ER Monitoring System
Data Collection and Experimental Design
Data Quality Control and Assurance
Effect of Data Weighting and Regularization Weighting on Pre-Injection Inversions
Time-Lapse Inversions

6 OVERVIEW AND FUTURE DIRECTIONS

7 EXERCISES

Exercise 1
Exercise 2
Exercise 3
Exercise 4
Exercise 5
Exercise 6
Exercise 7
Exercise 8

8 REFERENCES

9 BOXES

Box 1 Scenario Evaluator for Electrical Resistivity (Seer)

10 EXERCISES SOLUTIONS

Solution Exercise 1
Solution Exercise 2
Solution Exercise 3
Solution Exercise 4
Solution Exercise 5
Solution Exercise 6
Solution Exercise 7
Solution Exercise 8

11 ABOUT THE AUTHORS

Interview with Authors

English Interview with Spanish Translator

Spanish Interview with Spanish Translator