Non-invasive geophysical imaging and facies analysis in mining tailings

Stratigraphy and facies analysis in a mining waste domain such as in tailings storage facilities (TSFs) is still a complex task due to sparsely distributed field data. Geophysical techniques and the interpretation of geophysical data in terms of stratigraphy and facies get relevance for integrating geophysics with other models investigating mining waste domains (e.g., hydrogeological-geochemical). In this paper, we introduce a conventional application of differential operators for interpreting geophysical data in terms of stratigraphy and facies analysis in TSFs. The geophysical data is acquired in a tailings area in the Pyhäsalmi mine, Finland, using seismic refraction (SR) and electric resistivity imaging (ERI) techniques. The SR inversion model constrained by a geological model approximated the ground and bedrock layers by delineating P-wave velocities (Vp). The SR layered model served as a constraint for the electrical resistivity (ρ) model in the ERI method. ERI inversion model data was used for facies analysis and interpretation in terms of other subsurface variables (e.g., water saturation, salinity). For this, a first-order derivative (gradient approach) and a second-order derivative combined with a Gaussian filter (Laplacian approach) were applied to highlight facies and transition zones. The approach embeds the data as scalar functions within a space domain defined by the model local structure. When applied to the ERI data, the gradient and the Laplacian functions captured the local extrema and the minimum threshold crossings respectively enhancing local geoelectric zones and layered contacts in line with field observations. This paper demonstrated that such image analysis can be proposed for interpretation of geophysical data in terms of segmentation and analysis of local facies, relevant in model conceptualization and parameterization of hydrogeological models.