Characterizing hydraulic fracture formation during enhanced geothermal system experiments using coda waves

Abstract Seismic waves are valuable for detecting structural variations in the subsurface and can be used to investigate enhanced geothermal systems (EGS). Classic methods, like seismic reflection, struggle to resolve these effects when the perturbations are confined to small volumes of rock, thus requiring other methods. Multiply scattered waves are better suited to resolving small structural changes due to their cumulative sensitivity acquired by their longer propagation times within the medium. With the growing focus on renewable energy production, an improved characterization of fracture network geometry created during EGS stimulations is crucial. In this study, we leverage coda from waveforms generated by a continuous active seismic source to investigate fracture development during the EGS Collab Experiment 1 at the Sanford Underground Research Facility (SURF). By measuring waveform decorrelation, we use scattering cross-section density as a proxy for the induced hydraulic fractures. Our approach implements a genetic algorithm to invert for scattering distributions, posing the problem as a nonlinear optimization. We also constrain the scattering perturbations to plane structures, enforcing realistic sparsity in fracture patterns that is otherwise poorly resolved in linearized approaches. Results from synthetic examples demonstrate the effectiveness of this approach in recovering scattering density, highlighting its potential to complement methods that utilize induced seismicity for improving characterization of fracture networks in enhanced geothermal reservoirs.

Authors

Institutions

Publication Details

Journal
The Leading Edge
Published
2025-03-01
DOI
https://doi.org/10.1190/tle44030163.1
Primary Topic
Seismic Imaging and Inversion Techniques
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Characterizing hydraulic fracture formation during enhanced geothermal system experiments using coda waves

P. Sprinkle, Hunter Knox, Kailash Chandra Pradhan, Julien Chaput
The Leading Edge
Seismic Imaging and Inversion Techniques
article

Characterizing hydraulic fracture formation during enhanced geothermal system experiments using coda waves

P. Sprinkle, Hunter Knox, Kailash Chandra Pradhan, Julien Chaput
article en

Abstract

Abstract Seismic waves are valuable for detecting structural variations in the subsurface and can be used to investigate enhanced geothermal systems (EGS). Classic methods, like seismic reflection, struggle to resolve these effects when the perturbations are confined to small volumes of rock, thus requiring other methods. Multiply scattered waves are better suited to resolving small structural changes due to their cumulative sensitivity acquired by their longer propagation times within the medium. With the growing focus on renewable energy production, an improved characterization of fracture network geometry created during EGS stimulations is crucial. In this study, we leverage coda from waveforms generated by a continuous active seismic source to investigate fracture development during the EGS Collab Experiment 1 at the Sanford Underground Research Facility (SURF). By measuring waveform decorrelation, we use scattering cross-section density as a proxy for the induced hydraulic fractures. Our approach implements a genetic algorithm to invert for scattering distributions, posing the problem as a nonlinear optimization. We also constrain the scattering perturbations to plane structures, enforcing realistic sparsity in fracture patterns that is otherwise poorly resolved in linearized approaches. Results from synthetic examples demonstrate the effectiveness of this approach in recovering scattering density, highlighting its potential to complement methods that utilize induced seismicity for improving characterization of fracture networks in enhanced geothermal reservoirs.

The Leading EdgeVol. 44(3)
Pacific Northwest National Laboratory (US), The University of Texas at El Paso (US)
U.S. Department of Energy, Directorate for Geosciences, Office of Energy Efficiency and Renewable Energy, Division of Earth Sciences, Geothermal Technologies Office, Office of Renewable Power
Openalex Percentile: Top 96%
Seismic Imaging and Inversion Techniques
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.