Development of tools to predict rockburst potential using microseismic and geotechnical data: a case study of Konkola mine no.1 shaft, Zambia.
Date
2023
Authors
Chishimba, Donald
Journal Title
Journal ISSN
Volume Title
Publisher
The University of Zambia
Abstract
Since 1995, Konkola Mine No.1 Shaft in Zambia has been experiencing increased seismic activity, leading to more rockburst incidents, which could present significant safety and production challenges at deeper levels. This study aimed to develop tools to predict rockburst from microseismic and geotechnical data. The specific objectives were to review and compile the global factors or conditions that cause rockburst, determine the site-specific rockburst indicators at Konkola Mine No. 1 Shaft, develop the tools that can be used to predict rockburst potential based on the determined rockburst indicators and validate the predictive tools on rockburst data from other mines. Seventeen rockburst case histories were collected from different mines around the world and analysed to identify contributing factors to rockbursts. Next, 40 rockburst events captured by the microseismic (MS) monitoring system at the Konkola Mine No.1 Shaft were back analyzed. The 3D modelling software, Leapfrog Geo and Surpac, were used to analyse and visualise the rockburst events and to estimate hypocentral distances from the stopes, respectively. The study found that the global contributing factors to rockburst included geological structures, mining depth, rockmass strength, stress conditions, mining methods and MS. The analysis results revealed that the mines with an orebody dip of 610 to 850 had a higher risk of rockbursts. Additionally, the study found that open stoping and cut and fill mining methods had a higher risk of rockbursts than other mining methods. The study found significant correlations between rockburst at Konkola Mine No.1 Shaft and rock quality designation (RQD), tangential stress (σθ), uniaxial compressive strength (σc), uniaxial tensile strength (σt), linear elastic energy (Wet), and principal in-situ stress (σ1). The results further showed that rockburst patterns were confined by fault zones in the south and north, most rockbursts occurred in excavations within a distance of 0 to 53 m from the ore shale or stopes, and argillaceous sandstone (AGSST), porous conglomerate (PC), footwall sandstones (FWSS), and ore shale (OS) rock types were more susceptible to rockbursts. The study then developed two rockburst predictive tools (RPTs) to forecast rockburst potential based on geotechnical and MS data. The geotechnical-based RPT used RQD, σθ, σc, σt, Wet, and σ1, while the MS-based tool used ML, E, and P factors. Sixteen rockburst cases from a different mine (Mufulira Mine) were used to independently validate the RPTs. The results showed that the MS factor-based RPT had an accuracy of 94 percent, while the geotechnical factor-based RPT had an accuracy of 87.5 percent.
Description
Thesis of Doctor of Philosophy in Mining Engineering