Field surveys in heterogeneous rock masses aimed at hydraulic conductivity assessment

Abstract

Abstract In heterogeneous and fractured rock masses, joints are the most important elements controlling the hydraulic conductivity. Joints parameters are therefore crucial for estimating transport of mass and energy in many technical problems (e.g., slope stability, tunnels, geothermal and oil and gas studies). Hydraulic conductivity conceptual models follow well understood generalizations, but their quantitative estimation is not simple. Both laboratory and field tests have many limitations due to representativeness and scale effects. This study proposes a methodology for a preliminary hydraulic conductivity estimation in fractured and/or heterogeneous rock masses through a combination of in-situ geomechanical and geophysical measurements. Contact and no-contact geomechanical surveys were coupled with electric resistivity topographies in two selected test sites within a Mexican geothermal area in the framework of the Ge-Mex H2020 project. The test sites are representative of two different geological settings: a faulted rock mass with expected high hydraulic conductivity in proximity of the faulted areas and an abandoned marble quarry, with very good mechanical characteristics and negligible degree of fracturing. Moreover, both of them are located in remote areas with limited accessibility, in which rapid, time and cost-effective procedures are welcomed and recommended. The preliminary findings of this study were promising: estimated hydraulic conductivities were compared with independent laboratory measurements performed by other researchers showing a good correspondence and reliability. The proposed methodology demonstrated its reliability in decision making, in the technical support and its economical applicability also in similar difficult logistic situations. Article Highlights A combination of in-situ geomechanical and geophysical measurements was adopted for a preliminary hydraulic conductivity estimation; Obtained field data were compared with independent laboratory estimations to assess the reliability of the proposed approach and compare representativeness and scale effects; Even given the difficult logistic conditions and the limitations of the available comparisons the proposed methodology demonstrated its reliability in decision making.