Geodetic Monitoring of Elastic and Inelastic Deformation in Compacting Reservoirs Due To Subsurface Operations
Abstract
A variety of geo-energy operations involve extraction or injections of fluids, including hydrocarbon production or storage, hydrogen storage, CO2 sequestration, and geothermal energy production. The surface deformation resulting from such operations can be a source of information on reservoir geomechanical properties as we show in this study. We analyze the time-dependent surface deformation in the Groningen region in northeastern Netherlands using a comprehensive geodetic data set, which includes InSAR (Radarsat2, TerraSAR-X, Sentinel-1), GNSS, and optical leveling spanning several decades. We resort to an Independent Component Analysis (ICA) to isolate deformation signals of various origins. The signals related to gas production from the Groningen gas field and from seasonal storage at Norg Underground Gas Storage are clearly revealed. Surface deformation associated to the Groningen reservoir show decadal subsidence, with spatially variable subsidence rates dictated by local compressibility. The ICA reveals distinct seasonal fluctuations at Norg, closely mirroring the variations of gas storage. By comparing the observed long-term subsidence within the Groningen reservoir and seasonal oscillations at Norg from a linear poroelastic compaction model, we quantify the fraction of inelastic deformation of the reservoir in space and time and constrain the reservoir compressibility. In Groningen, increased compressibility indicates inelastic compaction that has built over time and might account for as much as 20% of the total compaction cumulated until 2021, while Norg shows no signs of inelastic deformation and a constant compressibility. This study provides a methodology to monitor and calibrate models of the subsurface deformation induced by geo-energy operations or aquifer management.
Copyright and License
© 2025. American Geophysical Union.
Acknowledgement
We would like to thank Manoochehr Shirzaei and an anonymous reviewer for their suggestions, which helped improve the manuscript. This study was supported by the NSF/Industry-University Collaborative Research Center ‘Geomechanics and Mitigation of Geohazards' (National Science Foundation award 1822214), and the Enhancement Project GMG-3 funded by Nederlandse Aardolie Maatschappij (NAM). M.A acknowledges funding from the Swiss National Science Foundation through Grant P2ELP2195127 and from Caltech's Resnick sustainability institute. We would like to acknowledge for granting the access and permitting to publish the InSAR and GNSS data.
Data Availability
All InSAR, GNSS, and optical data were provided by Nederlandse Aardolie Maatschappij (NAM). The InSAR data were processed by SkyGeo (https://skygeo.com). Surface temperature data were retrieved from KNMI (https://dataplatform.knmi.nl/dataset/). The relevant InSAR, GNSS, and optical data necessary for the analysis in this article are available through Li et al. (2024) (https://doi.org/10.5281/zenodo.14184369). The vbICA software for ICA decomposition is available from Gualandi and Liu (2020) (https://doi.org/10.5281/zenodo.4322548). The reservoir modeling code is from Acosta et al. (2023a) (https://doi.org/10.5281/zenodo.8329298).
Supplemental Material
Supporting Information S1 (DOCX)
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Additional details
- National Science Foundation
- 1822214
- Swiss National Science Foundation
- P2ELP2195127
- Accepted
-
2025-03-07
- Available
-
2025-03-20Version of record online
- Available
-
2025-03-20Issue online
- Caltech groups
- Center for Geomechanics and Mitigation of Geohazards (GMG), Resnick Sustainability Institute, Seismological Laboratory, Division of Geological and Planetary Sciences (GPS)
- Publication Status
- Published