Improved methodology for deep aquifer characterization using hydrogeological, self-potential, and magnetotellurics data
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arXiv
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| Auteurs principaux: | , , , |
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| Format: | Preprint |
| Publié: |
2023
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| _version_ | 1866929678821883904 |
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| author | Seo, Young-Ho Lee, Jonghyun El-Kadi, Aly I. Grobbe, Niels |
| author_facet | Seo, Young-Ho Lee, Jonghyun El-Kadi, Aly I. Grobbe, Niels |
| contents | Estimating subsurface properties like hydraulic conductivity using hydrogeological data alone is challenging in field sites with sparse wells. Geophysical data, including Self-potential (SP) and Magnetotelluric (MT), can improve understanding of hydrogeological structures and interpolate data between wells. However, determining hydraulic conductivity requires a proper petrophysical relationship between hydraulic conductivity and inferred geophysical properties, which may not exist or be unique. In this work, we propose a joint-inversion approach without assuming petrophysical relationships, using self-potential data to connect groundwater flow velocity to electrical potential differences, and MT data to estimate hydraulic conductivity and electrical conductivity. A spectral method is employed for the self-potential forward problem. To accelerate joint data inversion, a dimension reduction technique through the Principal Component Geostatistical Approach is used. The applicability and robustness of the joint-inversion method are demonstrated through inversion tests using hydrogeophysical data sets generated from subsurface models with and without petrophysical relationships. The joint hydraulic head-SP-MT data inversion can reasonably estimate hydraulic conductivity and electrical resistivity, even without knowledge of a one-to-one petrophysical relationship. On average, joint inversion yields a 25% improvement in hydraulic conductivity estimates compared to single data-type inversion. Our proposed joint inversion approach, with SP-data compensating for the absence of a known petrophysical relationship, provided close agreement with joint inversion of head and MT data using a known petrophysical relationship. Successful inversion tests demonstrate the usefulness of SP data in connecting hydrogeological properties and geophysical data without requiring a petrophysical relationship. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2304_10083 |
| institution | arXiv |
| publishDate | 2023 |
| record_format | arxiv |
| spellingShingle | Improved methodology for deep aquifer characterization using hydrogeological, self-potential, and magnetotellurics data Seo, Young-Ho Lee, Jonghyun El-Kadi, Aly I. Grobbe, Niels Geophysics Computational Physics Estimating subsurface properties like hydraulic conductivity using hydrogeological data alone is challenging in field sites with sparse wells. Geophysical data, including Self-potential (SP) and Magnetotelluric (MT), can improve understanding of hydrogeological structures and interpolate data between wells. However, determining hydraulic conductivity requires a proper petrophysical relationship between hydraulic conductivity and inferred geophysical properties, which may not exist or be unique. In this work, we propose a joint-inversion approach without assuming petrophysical relationships, using self-potential data to connect groundwater flow velocity to electrical potential differences, and MT data to estimate hydraulic conductivity and electrical conductivity. A spectral method is employed for the self-potential forward problem. To accelerate joint data inversion, a dimension reduction technique through the Principal Component Geostatistical Approach is used. The applicability and robustness of the joint-inversion method are demonstrated through inversion tests using hydrogeophysical data sets generated from subsurface models with and without petrophysical relationships. The joint hydraulic head-SP-MT data inversion can reasonably estimate hydraulic conductivity and electrical resistivity, even without knowledge of a one-to-one petrophysical relationship. On average, joint inversion yields a 25% improvement in hydraulic conductivity estimates compared to single data-type inversion. Our proposed joint inversion approach, with SP-data compensating for the absence of a known petrophysical relationship, provided close agreement with joint inversion of head and MT data using a known petrophysical relationship. Successful inversion tests demonstrate the usefulness of SP data in connecting hydrogeological properties and geophysical data without requiring a petrophysical relationship. |
| title | Improved methodology for deep aquifer characterization using hydrogeological, self-potential, and magnetotellurics data |
| topic | Geophysics Computational Physics |
| url | https://arxiv.org/abs/2304.10083 |