[Dataset] An Electrical Parameter Characterizing Solute Heterogeneity: The Mixing Factor M

Quantitative estimates of hydrological state variables using electrical or electromagnetic geophysical methods are systematically biased by overlooked heterogeneity below the spatial scale resolved by the method. We generalize the high-salinity asymptotic limit of electrical conduction in porous med...

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Detalles Bibliográficos
Autores: Fernandez Visentini, Alejandro, Linde, Niklas
Tipo de recurso: conjunto de datos
Fecha de publicación:2024
País:España
Institución:Consejo Superior de Investigaciones Científicas (CSIC)
Repositorio:DIGITAL.CSIC. Repositorio Institucional del CSIC
OAI Identifier:oai:digital.csic.es:10261/383682
Acceso en línea:http://hdl.handle.net/10261/383682
https://digital.csic.es/handle/10261/361924
Access Level:acceso abierto
Palabra clave:Solute mixing and spreading
Electrical conductivity upscaling
Electrical resistivity tomography
Hydrogeophysics
Petrophysical relationship
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Descripción
Sumario:Quantitative estimates of hydrological state variables using electrical or electromagnetic geophysical methods are systematically biased by overlooked heterogeneity below the spatial scale resolved by the method. We generalize the high-salinity asymptotic limit of electrical conduction in porous media at the continuous (e.g., Darcy) scale, by introducing a new petrophysical parameter, the mixing factor M, which accounts for the effect of fluid conductivity heterogeneity on the equivalent electrical conductivity tensor; it is expressed in terms of the volume-average of the product of mean-removed fluid conductivity and electric fields. We investigate the behavior of M for static and evolving fluid conductivity scenarios. Considering 2-D ergodic log-normal random fields of fluid conductivity, we demonstrate, in absence of surface conductivity, that observing the components of the M-tensor allows univocally determining the variance and anisotropy of the field. Further, time-series of the M-tensor under diffusion-limited mixing allows distinguishing between different characteristic temporal scales of diffusion, which are directly related to the initial integral scales of the salinity field. Under advective-diffusive transport and for a pulse injection, the time-series of M have a strong dependence on the Péclet number. Since M is defined in the absence of surface conductivity, we investigate how to correct measurements for surface conductivity effects. The parameter M provides conceptual understanding about the impact of saline heterogeneity on electrical measurements. Further work will investigate how it can be incorporated into hydrogeophysical inverse formulations and interpretative frameworks.