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Quantification of Fault Uncertainty and Risk Management in Underground Longwall Coal Mining

Underground » Mining Technology and Production

Published: June 01Project Number: C7025

Get ReportAuthor: Roussos Dimitrakopoulos | WH Bryan Mining Geology Research Centre University of Queensland

Fault uncertainty and risk have widely recognized adverse impacts on the exploration and mining of underground coal deposits, especially longwall mining. Geological uncertainties may cause significant delays in production schedules, impose substantial changes to mine plans, reduce expected recoverable coal quantities, adversely affect safety, and heavily influence the financial viability of a mine. As Australia's coal mining industry is becoming increasingly reliant upon longwall mining, there is a need to implement a more effective, quantitative and yet practical approach to geological risk modelling, uncertainty assessment and integration of risk management so that mining companies can better plan both underground exploration activities and longwall operations.

The present ACARP project, developed to assist in meeting the above need, aims to demonstrate and establish the practical use of state-of-the-art technologies in quantifying geological (fault) uncertainty and link the quantification of uncertainty to geological risk management and decision making both in exploration and mine planning. A key element of the research project is the introduction of risk modelling that is by nature quantitative and in turn generates a different way of 'thinking and problem solving' compared to the traditional approaches commonly used in the coal mining industry. An important aspect of quantitative uncertainty modelling and risk assessment is that it adds flexibility: this flexibility may be expressed as the increase in an assets value from the mere fact that uncertainty is explicitly quantified and integrated into financial analysis and decision making. This is also true for any undertaking in terms of both coal exploration and longwall mining.

To deal with the quantification of fault uncertainty in coal seams, the project has developed a new fault simulation algorithm based on fractal (power-law) model for fault size distributions and length versus maximum throw relationships. The project's thorough review of the technical literature on fractal models for modelling fault systems documents the current technological understanding and wide support of fractal relations for characterizing fault systems as used in this project. In addition, the review of the technical literature documents several approaches used for fault simulations in the petroleum industry. The algorithm developed has three distinct characteristics worth stressing: (i) it uses underlying spatial patterns to place faults within a study area; (ii) it integrates 'soft' geological information that serves as background in the simulation process; and (ii) it extrapolates the fault placement based on available information and underlying fault spatial patterns.

Case studies from Moranbah North, Goonyella-Riverside, and Newlands Coal Mine demonstrate the application of the methods developed in three different cases. All case studies have two or more fault populations and use various forms of soft geological information coded as 'soft' or prior probabilities and provide a variety of environments in which the methods developed are tested.

Initial examples of the downstream use of the technologies in this project point to benefits from the technologies developed in this study. Examples include the use of fault probability maps to optimise longwall designs based on maximizing mineable coal reserves, categorisation of coal reserves based on geological risk, and how to combine quantified geological risk with different longwall layouts in order to assess and minimise fault impact on mine economics. It is worth stressing that all examples, be they related either to exploration or mine design as investigated in the back analysis section, demonstrate that any 'risk' assessment based on an exploration dataset 'as is' can seriously underestimate risk and should be avoided. It should also be noted that traditional longwall design and planning based on exploration information only implicitly assumes and reflects such risk underestimation.

The fault simulation and risk quantification method developed in this project was implemented in a 'computerised model' named GeoStructure. GeoStructure is a computationally complex program further developed into a windows-driven, user-friendly program with graphics. It is one of the project deliverables, aiming to assist the use of the technologies in the coal mining industry. The practical implementation of all the methods developed and used in this study are available to ACARP members in the program "GeoStructure" included in this report. A full user's manual and complementary 'fault data analysis tool kit' aim to facilitate technology transfer to mine sites and document practical guidelines for quantifying fault uncertainty.

Several geological and mine planning issues that require further development have been identified. Some of the more critical ones are the following: the development of cost effective methodologies for optimal data collection and data "worth" assessment , including optimal drilling programs and 3D seismic surveys for structure identification that can be uniquely accommodated by further developing the basic outcomes of this project; the development of computerized methods that facilitate the integration of fault uncertainty into optimal longwall design, including NPV considerations; downstream integration of technologies to the scheduling working of sequences, and planning the insurance of longwall operations.

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