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From Resources to Reserves through Quantitative Risk Assessment: Decision Support for JORC Compliance

Underground » Geology

Published: July 10Project Number: C15009

Get ReportAuthor: Shuxing Li, Peter Knights, Pedro Valenzuela | CRCMining, University of Queensland

The uncertainties and risks associated with the JORC code modifying factors have a significant impact on the conversion of coal resources to reserves. These factors include geological, geotechnical, metallurgical, mining, environmental, marketing, legal, social and governmental variables.

 

This project develops a methodology for systematically identifying and quantifying the uncertainties and risks associated geological and geotechnical modifying factors which affect the coal resources/reserves estimation and classification process. The methodology consists of a risk evaluation framework and computer toolkit. The framework is essentially a five step process. The first step involves systematically identifying sources of uncertainty. The second step involves qualitative assessment of the identified uncertainties using probabilistic risk assessment (PRA) techniques. The third step involves the quantitative assessment of the magnitude and spatial distribution of select uncertainties. The fourth step involves the quantitative analysis of the higher priority risks by incorporating the cost and revenue impacts of uncertainties. The fifth, and final step proposes the use of cost driver trees that map the relationship of these revenue and cost factors for combining the risks derived from different variables into a single integrated risk. Hazard maps can then be used to display risk weighted areas for assessing marginal coal blocks.

 

Two case studies are provided using the Clearskin open cut dragline operation and the Broadmeadows underground longwall operation. The open cut example demonstrates how uncertainties in overburden thickness and specific gravity can be converted to risks involving the costs of dragline stripping and drilling and blasting. A cost driver tree is used to integrate the risk into a combined risk. The longwall case study demonstrates how uncertainties can be quantified by using advanced geostatistical approaches to model uncertainties in: (i) fault throw and concentration, and (ii) the presence of thick competent intermediate sandstone strata that can cause excessive periodic weighting.

 

This project develops and extends the risk quantification and integration techniques which were developed in the two previous ACARP research projects (C7025 and C11042). The resulting methodology is presented in the form of a guideline for uncertainty and risk management in coal resource/reserve evaluation.

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