Comparative analysis of discrete fracture network models derived from borehole versus shaft scale discontinuity data for improved mine optimization and risk minimization
Comparative analysis of discrete fracture network models derived from borehole versus shaft scale discontinuity data for improved mine optimization and risk minimization
批准号:
452729-2013
负责人:
Eberhardt, Erik
金额:
$2.99万
依托单位国家:
加拿大
项目类别:
Collaborative Research and Development Grants
财政年份:
2015
资助国家:
加拿大
项目状态:
已结题
起止时间:
2015-01-01 至 2016-12-31
中文摘要
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英文摘要
With ever-increasing demand for mineral resources coupled with the depletion of near-surface deposits, numerous mining operations are making plans to transition from surface to underground mass mining in order to mine deeper resources. The methods being considered (block/panel caving), are being promoted due to their favourable economics, high tonnages and safety. However, these methods require significant underground development upfront, and therefore major capital investment before production and revenue can be generated. Given the higher costs and increased challenges of acquiring data from greater depths, the feasibility of these projects will be based on more limited data, introducing significant uncertainty and geo-risk with respect to the expected rock mass conditions and response to mining. These will challenge the industry's collective experience, raising questions as to whether present knowledge and design methodologies are sufficient.
To address these challenges, the Centre for Excellence in Mining Innovation (CEMI), based in Sudbury, have provided research funding to investigate improved means to forecast the geomechanical characteristics of the rock being mined across different scales and depths. This research will examine the influence of natural fractures present in the rock on rock mass behaviour and strength at depth to aid mine design, mine optimization and risk minimization. Given the ecological sensitivity of the northern regions where many of Canada's large mineral deposits are located, sustainable mining practices are a key priority - i.e. maximizing and optimizing the mining of deep mineral resources, while reducing adverse effects and minimizing risk. Upon completion, the results of this research will significantly enhance Canada's body of knowledge and expertise in deep mining and block caving. The training that will be provided to graduate students will equip them with unique learning experiences and practical skill sets that are in high demand in the mining industry and are of strategic importance for Canada's future natural resource development needs.
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依托单位:
Comparative analysis of discrete fracture network models derived from borehole versus shaft scale discontinuity data for improved mine optimization and risk minimization
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