Slope Stability Management Using 2d Analysis Methods at Chingola Open Pits F and D of Konkola Copper Mines

Abstract

Chingola Open Pits F and D (COPF/D) is a copper open-cast mine located in the town of Chingola on the Copperbelt in Zambia. It is approximately 330 m deep, 1.3 km wide and 2.1 km long. The mine was opened in 2003. COPF/D comprises a rock mass which is currently classified as poor to fair using the Mining Rock Mass Rating (MRMR) system. Despite the implementation of consultants’ recommendations, structural slope failures on the south and east slopes have continued to occur. The research described in this report showed that the recommendations were based on inaccurate strength parameters and discontinuity orientations. The consequence has been an increase in stripping ratios and exposure of both equipment and personnel to dangerous conditions. An effective slope management plan was determined to address the uncertainties. This included site-specific recommendations for the high risk of slope failure, to predict or prevent unexpected slope failures in the next three years. The pit was divided into three distinct domains (Domain 1, Domain 2 and Domain 3) based on the observed failure mechanisms, data analysis and the rock mass strength. The structural and stability analysis showed that the domains susceptible to wedge and planar failures covered an area of 4,892 m2 and 71,650 m2, respectively. Domain 3, which was also susceptible to circular failures in the upper and lower stack, covered an area of 1,556,769 m2 and 20,685 m2, respectively. To mitigate circular failures, it was recommended that the pore pressure coefficient (Ru) be reduced from 0.23 to less than 0.19 and the lower stack angle be reduced from 51° to 42°. To mitigate structural failures in Domain 2, the slope angle should be reduced from 60° to 50°. The unstable portion of Domain 1 should be supported with cable anchors and fibre-reinforced shotcrete to make it stable. An appropriate slope monitoring strategy was recommended for each domain to ensure proactive detection of ground deformation. New technologies such as drones and data acquisition scanners were also recommended for future developments to improve the quality of data assessments.