Enhancing production rates at El Teniente’s black cave mine through optimizing HF hole distribution using discrete fracture network modeling and geostatistical simulation methods

Abstract

This study at the Esmeralda Mine, part of the El Teniente Division of CODELCO, investigates optimizing hydraulic fracturing (HF) holes’ spatial distribution to improve rock material production in one of the world’s largest copper-molybdenum deposits. Utilizing diverse data sources, including borehole, oriented borehole, and photogrammetry data, along with hang-up frequency and hydrofracturing details, we applied discrete fracture network (DFN) modeling to analyze in-situ block size distribution and fragmentation. These results are based on 12,000 realizations of discrete fracture network (DFN) models using R-Dis-Frag computer pacakge at real cave volumes of 200 m x 200 m x 200 m, with varying parameters, which significantly enhances their reliability. The incorporation of DFN modeling and geo- statistical simulation allows for capturing the interaction berween several spatial variables and explaining the variations observed in the production results at the draw points. Key findings of spatio-statistical analysis highlight the significance of volumetric fracture intensity (P32) and extraction column height in reducing hang-up events and enhancing fragmentation efficiency. The study integrates HF-induced and natural fracture intensities, revealing that higher P32 values and higher draw columns correlate with fewer hang-ups and better fragmentation. We recommend non-regular HF patterns for high P32 zones to improve operational efficiency. This research provides insights into optimizing mining operations, acknowledging the limitations of HF propagation efficacy and paving the way for further explo- ration into the interplay between hydraulic fracturing and natural discontinuities.