Hard-rock investigation using a non-invasive geophysical approach

Abstract

Investigation of a hard-rock terrain is essential for the development of engineering infrastructures and groundwater assessment. In such investigations, evaluation of rock mass quality and faults/fractures is a challenging task. Conventionally, borehole tests are conducted to acquire subsurface geological information, and rock mass quality parameters such as rock quality designation (RQD). However, such tests are expensive, slow, limited to some specific locations, require more equipment, provide point measurements, and are hardly conducted in a steep topographic terrain. Generally, the non-invasive geophysical methods, such as geoelectrical methods are performed to assess the hard-rock sites. However, such parameters alone provide ambiguity in interpreting the geological units. In this work, a joint approach of four geophysical parameters (e.g., electrical resistivity (ER), self-potential (SP), magnetic, and induced polarization (IP)) is proposed to assess a highly heterogeneous terrain for the installation of the Accelerator Driven System (ADS) facility in South China. Geophysical data were obtained via a variety of surveyed parameters along different profiles. Electrical resistivity tomography (ERT) was integrated with borehole tests data to determine RQD for rock mass quality evaluation over the entire area. The results of magnetic interpretation were calibrated with well data to constrain the subsurface into distinct layers. ERT and magnetic coupled with Joint Profile Method (JPM) detected several localized faults/fractures. IP was integrated with ERT to distinguish between water and clay. Groundwater flow path was marked using SP. Compared with the past investigations, this novel approach deciphers functional analogous relation of RQD with ERT, magnetic, IP and SP in the hard-rock, provides thorough insights into the subsurface, removes the ambiguity caused by single geophysical parameter or the inadequate well data, and bridges the gaps between accurate geological model and the limited data for the development of engineering structures and groundwater resources.