PREDICTIVE NUMERICAL GEOFILTRATION MODEL OF GROUNDWATER INFLOW INTO THE GOREVSKY GOK QUARRY

Abstract

Gorevskoe zinc-lead ore deposit is located within a unique terrain: it follows the left bank of the Angara River and lies underneath its current river bed, starting 38 km far from the Angara River mouth. This plays a significant role in the ore field hydrogeology and has a great impact on its further development. The complexity of ore field hydrogeology is defined by a number of natural factors, i.e., the occurrence of both aquifers as well as low-permeable and water-proof layers; tectonic failures (if any) and their functioning in terms of hydrogeology dynamics; variability in terms of water-bearing rocks hydraulic properties; water bodies on the surface and their connection with groundwater flows. All the above mentioned features allow us to classify Gorevskoe deposit hydrogeology as rather complex and complicated. The main task of the work performed was to evaluate and forecast the water inflow to Gorevskii open-pit mine and to determine the groundwater level at the end of mining operations. Because of the deposit rather complex hydrogeology, it was decided to perform the task on the basis of numerical geohydraulic modelling using finite difference method (FDM) in the environment of Visual MODFLOW software tools. The paper describes the following steps of works performed within the project: input data acquisition, processing and analysis; creation of concept-based hydrogeology model; development of hindcasting numerical model; model calibration in the context of environmental conditions and actual mining operations hosted within the open-pit; sensitivity analysis and advanced simulation to develop the forecasting numerical model. When performed, the forecast value in terms of groundwater inflow to the pit has been calculated. Thus, pit groundwater level at the end of mining operations has been developed. Following a number of scenarios applied, model sensitivity analysis has been made and this provided the basis to identify the factors that have the most essential impact on water inflow to the pit.