Prediction of in situ rock strength using sonic velocity

Uniaxial Compressive Strength (UCS) and sonic velocity correlations are used widely in the Australian coal mining industry to predict in situ rock strength. These models are cheap, fast and easy to produce, as well as easy to understand and have a number of practical applications in mine planning and design. The major downfall of these models is that there is a large variation in UCS values at high sonic velocities limiting their predictive ability. The aim of this research project is to improve the reliability of UCS/Sonic velocity correlations by reducing the variability in the underlying data. This is performed by identifying and eliminating sources of error affecting the data and looking at the impact of certain factors on the quality of the correlations. Results show that improved models can be obtained by filtering the datasets to remove samples with high length-to-height ratios, conglomerate or pebbly lithologies, and large sonic velocity ranges

Modelling of the Occurrence of Hydrogen Sulphide in Coal Seams

Hydrogen Sulphide (H2S) has been encountered within a number of Bowen Basin collieries, Central Queensland, Australia. High concentration occurrence during mining of a longwall panel raises a number of potential problems, which demand greater understanding to allow efficient mining while maintaining safe and healthy environmental conditions. Longwall panels at Mine A and Mine B have recently mined through H2S zones. The high H2S zone mined through at Mine A was wide and covering the whole length of the face comparing to the narrow H2S zone which was cutting the panel at 45° at Mine B. Longwall panels had been sampled for H2S in pre-mining phases with vertical and inseam exploration boreholes and rib sampling of gateroad development headings. During mining face coal samples were collected in an intensive program and tested in a drum tumbler to determine an indicated seam concentration level through contouring that could be used to calculate the concentrations of H2S liberated to the atmosphere. Data was analysed to determine a geostatistical method, which would best represent the indicated seam concentration level from the given data and the block dimension of the data set. This study discusses the different sampling methods used, selection of the most suitable geostatistical method and the impact of grid size on results of data analysis. Some general observations are made correlating indicated seam H2S concentrations from production face sampling with both predictions made from exploration and liberation rates during mining of the longwall panel

Recent developments in fibre optic shape sensing

This paper presents a comprehensive critical review of technologies used in the development of fibre optic shape sensors (FOSSs). Their operation is based on multi-dimensional bend measurements using a series of fibre optic sensors. Optical fibre sensors have experienced tremendous growth from simple bend sensors in 1980s to full three-dimensional FOSSs using multicore fibres in recent years. Following a short review of conventional contact-based shape sensor technologies, the evolution trend and sensing principles of FOSSs are presented. This paper identifies the major optical fibre technologies used for shape sensing and provides an account of the challenges and emerging applications of FOSSs in various industries such as medical robotics, industrial robotics, aerospace and mining industry

Characterisation of creep in coal and its impact on permeability: An experimental study

Creep is a time-dependent deformation that affects coal permeability and should be considered in the prediction of Coalbed Methane (CBM) production. This study experimentally characterises and quantifies the impact of creep on coal permeability. The experiments were conducted on a bituminous coal sample, excavated from Bowen Basin, Australia, using a triaxial gas rig equipped with strain and displacement transducers. Two different types of gases (helium and methane) were injected into the sample under various stress and pore pressure conditions. It was found that for the experiments with helium, creep caused permanent partial closure of cleats and pathways under constant effective stress, and hence a reduction in permeability. Under hydrostatic stress only, a Residual Deformation Ratio (RDR) of 14.1% and a Permeability Loss Ratio (PLR) of 71% were found following the removal of the axial load. This can be due to the damage to coal microstructure along with closure of cleats. For the experiments with methane, coal experienced an instantaneous elastic deformation, at the onset of pore pressure depletion, followed by consolidation and matrix shrinkage. Then, creep occurred when gas desorption ceased. A total permeability loss of 26% was achieved due to an increase of 1.91 MPa in effective stress caused by gas desorption. In addition, the model previously developed by authors was validated against the experimental permeability data. A good agreement was found between the model-predicted permeability data and the experimental permeability data, particularly for higher pore pressure ranges

New developments in the Australian mining education

The Australian mining industry is responsible for more than 50% of the export revenues and is the largest exporter of black coal and the second largest exporter of iron ore in the world. As a major export player on the world minerals markets, the Australian mining industry delivers significant benefits to the Australian economy. Graduating good quality engineers for such an important industry requires world-class education. Mining Education Australia (MEA) was developed to deliver a common undergraduate curriculum in mining engineering across Australia. This unique initiative was developed in response to increased demand for mining industry professionals in an environment of limited funding within the traditional university environment and a critical shortage of suitably qualified academic staff. MEA is an unincorporated joint venture between The University of Queensland, The University of New South Wales and Curtin University in Western Australia. In 2009, The University of Adelaide became a member of the MEA Program. This paper discusses the history and governance of MEA as well as the structure of the common curriculum and teaching innovations adopted

Development and Implementation of a Geotechnical Database Management System

Geotechnical Engineering is classified by many mining companies as the highest corporate, investor and operational risk associated with the development and successful exploitation of a mineral resource. Given the shift in culture towards geotechnical engineering and the influx of new exploration projects, the quantity and complexity of geotechnical data is increasing at exponential rates. Unfortunately, in some cases, data management techniques have lagged behind data capture processes, resulting in relatively primitive technologies to store highly sensitive and costly data. Under these primitive systems, there is no quantifiable handling on the quantity or quality of geotechnical data. The rollover effects of poor data management standards are significant and in severe cases, areas require redrilling or revaluation to capture lost data. The aim of this project was to capture, extract and upload geotechnical data into an easily accessible, single source geotechnical database. Using Rio Tinto Coal Australia (RTCA) as a case study, the project formed a framework for future database implementations by outlining the systematic project progression from data extraction to population and application of the database. By providing a single source database, frequent engineering tasks at RTCA were automated which significantly increased engineering efficiency and accuracy. Additionally, comprehensive Quality Assurance and Quality Control (QAQC) checks improved overall data integrity, resulting in enhanced data confidence

The economics of extended pre-strip stripping

Waste stripping involves the most costly processes for any given open cut coal mining operation, As such, it is fundamentally important to optimise material scheduling and the sequences involved in excavating and hauling waste material. In situations constrained by fleet capacity and productivity. The only viable option to potentially yield further cost gains is to modify current mining methods. In the case of many Australian coal mines, truck-shovel systems excavate the initial overlying waste, known as pre-strip, down to a predetermined level known as the pre-strip horizon. This paper provides and analyses a simulation model to derive the optimal strip width for pre-strip activities. Case study data obtained from an established leading coal producer in the Bowen Basin was implemented into a pit simulation model to assess the effect of pre-strip width on the overall pit economics. Pre-strip widths of 60 to 120 m in 10 m increments were assessed whilst keeping dragline and coal stripping widths constant at 60 m. The simulation revealed the potential for cost reductions to be significant when a 90 m pre-strip case is adopted as opposed to the base case of 60 m. The paper presents the simulation findings for each case and discusses the key drivers behind the cost variations for each case

The determination of deformation of soil nailed structures by a simplified method

This paper presents the results of research to develop a simple method of determining deformation at the crest of a soil nailed wall. At the present time there is no established simplified method for accurately predicting soil nail walls deformation, with the current predictive methods being either an empirical approach or based on the use of numerical analysis. By carrying out a parametric study through the use of the finite element program PLAXIS, the effects of soil nail inclination, spacing and length, as well as the soil properties of stiffness and strength on soil nail wall deformation were assessed. The results indicated that although all of these elements had some ef-fect on deformation, soil effective cohesion had the greatest effect. The results were used to create two empirical prediction formulae and a series of design charts to determine wall crest deformation and these formulae were tested against case history data. This led to a minor modification to the formulae. The final calibrated empirical prediction formulae provide an estimation of wall movement to ±5mm with 80% accuracy, when compared to the case history data, and >95% accuracy when considering ±10mm, which is considered acceptable for most preliminary engineering designs. The introduction of these formulae will enable engineers to obtain an estimation of wall movement at an early stage without the necessity of carrying out relatively expensive and time consuming numerical analysis

Improvements in truck requirement estimations using detailed haulage analysis

Accuracy in haulage analysis is fundamental for reliable cost and productivity estimation. The level of detail to which haulage analysis is conducted can significantly influence these estimations. The recent advancement of computer processing has enabled a range of software to manage large datasets and run multiple and complex haulage scenarios, thus increasing the level of detail. Substantial evidence is available to affirm the benefits of detail in haulage analysis through the scope of truck cycle time and truck prediction methods. However, due to the novelty of advanced software, no literature that documents the level of detail and frequency of haul roads required for haulage analysis was found. It was therefore, the objective of ongoing work for this research project to quantify the value added through additional detail in haulage analysis, specifically, the benefit of frequently changing haul roads. To facilitate this process, nineteen haulage scenarios were analysed with varying detail. In addition, a geological model and topography was created. From the analysis conducted, a clear relationship was identified between decreasing haul road calculation frequency and inverse variance error from the mean cycle time. The research showed that performing two as opposed to a single haulage analyses for a strip can affect the calculated truck cycle times from 6% to 14%. Additionally, it was found that changes in horizontal distance from the endwall were more significant than the vertical change for the analysed strip

Risk-Benefit Analysis in Coal Mine Roof Support Design Using Stochastic Modelling Technique

Various roof support design methodologies have been used in Australian coal mines, which include analytical, numerical and empirical models. These models are mainly based on the deterministic approach in which a single factor of safety is calculated for the roof support design. The main limitation of this design methodology is that it fails to account for the inherent variations existing in rock mass properties and other roof reinforcement elements. To overcome this issue, an improved design methodology based on stochastic approaches has been developed in which both the design inputs parameters and the outcomes (i.e., factor of safety) are expressed as probability distribution functions. This paper focuses on the application of stochastic modelling technique to evaluate the underground roof support strategies currently used in an underground coal mine located in the Bowen Basin. The starting point of the analysis is the existing analytical roof support models that identified the relevant design inputs in consideration. Based on the best fit probability distributions of input parameters determined by goodness of fit tests, a risk based design is conducted to quantitatively evaluate the risk of roof fall fatality under specific roof support system by using the probability of failure from Monte Carlo simulation and the associated underground personnel exposure