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Rural homelessness has largely been silenced in homelessness narratives and social policy in Australia and throughout the world. This paper reports on data from a larger qualitative study about homelessness in rural and regional Central Queensland mining communities located within the Bowen Basin region, inland from Australia's eastern seaboard. Semi-structured, qualitative interviews and focus groups were conducted with people who had lived experience of homelessness in the rural mining communities of Mackay (regional), Moranbah and Dysart (rural), and service provider representatives and community advocates. The qualitative analysis revealed that people experience homelessness in rural and regional communities in unique ways that are different to metropolitan constructions of homelessness. This research identified rural and regional poverty, the nature of boom or bust economies, over-stressed human service providers, social isolation and lack of affordable housing as factors contributing to homelessness in rural and regional mining communities. This paper highlights the urgent need for more scholarly research to inform and promote more critical social policy approaches that frame homelessness as a public policy priority in rural and regional mining communities. • The article highlights the urgent need for Australian social policy makers to address housing and homelessness in rural and regional mining communities. • Rural and regional communities have largely been silenced in the development and implementation of housing and homelessness policy. • The unique contextual factors associated with rural and regional mining communities such as boom/bust cycles and associated demand and supply issues need to be better addressed in policy processes. • Learnings from previous boom phases of the cycle need to better inform policy development and resource allocation. • The lived experiences of people in rural and regional mining communities need to inform future policy design and implementation. [ABSTRACT FROM AUTHOR]

Inaccuracies in spatial modelling of coal properties can impact coal resource and reserve estimates. Geostatistical methods which account for compositional data have previously been recommended as a preferred method for modelling of coal properties. These methods can quantify uncertainty, can use auxiliary information to improve estimates, and ensure that compositional data (such as coal proximate analysis) is modelled in a mathematically consistent way. However, geostatistical methods have drawbacks in that have rigid statistical assumptions about the distribution and stationarity of the target variable and require variogram interpretation which can be onerous when then number of domains and target variables are numerous. Due to these drawback, inverse distance weighting (a simple deterministic method) remains the most popular method for modelling coal properties in Australian resource estimates. To address the drawbacks of geostatistical methods, a machine learning approach based on the quantile regression forest algorithm is proposed as an alternative method to spatially model coal properties. This newly proposed method, accounts for spatial arrangement of data, requires minimal pre-processing steps, can quantify uncertainty and can easily incorporate auxiliary information of various types. To evaluate the performance of this method, the accuracy of predictions of coal proximate analysis properties, and coal density are compared to the predictions of inverse distance weighting and regression kriging. All methods incorporate isometric log ratio transform and back-transform of data in order to account for the compositional nature of coal proximate analysis. Data from an active coal mine in the Bowen Basin, Queensland Australia was used as basis of the results. A unique feature of the mine site in this basin is the presence of intrusion which impacts coal quality properties to various degrees. Using evaluation metrics from leave-one-out cross-validation, this paper demonstrates that quantile regression forest has higher accuracy, lower bias and higher precision than inverses distance weighting across all coal properties. The paper also shows that results of the new method are very similar or better than regression kriging. It is also demonstrated that the prediction maps produced by quantile regression forest could be used to more accurately map out coal impacted by intrusion compared to inverse distance weighting, and that inverse distance weighting overestimates the impact of intrusion and intrusion extent. A drawback of the method compared to inverse distance weighting, is that it is more computationally demanding, less intuitive and is currently not available in existing geological packages. [ABSTRACT FROM AUTHOR]

Abstract: There is a broad consensus that the corporate sector has an active role in facilitating community development through corporate-community investment. However, there remains uncertainty as to how much the sector should invest without taking on responsibilities and influencing decisions which are traditionally within the realm of the state. This paper explores the contemporary role of mining companies in regional governance through a case study of housing and residential land use planning and supply within the Bowen Basin coal mining and coal seam gas extraction region in Queensland, Australia. Mining companies were found to have a broad role in planning and development with far-reaching implications for land use and the wider regional community. These arrangements have emerged in response to corporate sensibilities, some recent policy requirements and most importantly, in pragmatic response to the institutional void apparent in many regional communities. In the absence of an effective regional framework with a clear and defined role for governments and corporations, powerful corporate interests risk effectively ‘capturing’ the regional development agenda within a framework that works on short-term paternalism rather than long-term regional partnerships. This also has implications for the efficiency of governance. Stronger institutional arrangements need to be developed to strengthen the capacity of the state to oversee these relationships. Regional governance and planning theory also needs to address this deficit. [Copyright &y& Elsevier]

Abstract: Late Permian age samples of black coal from the coeval Bandanna Formation and Baralaba Coal Measures of Queensland''s Bowen Basin, as well as Carboniferous coal from Germany''s Ruhr Basin, were investigated. This paper presents scanning electron microscope (SEM) analysis of the mode of occurrence of minerals within these coals, and characterisation of the natural fractures present within the samples. The coal samples located proximal to orogenic fronts in both basins are structurally complex, with multiple generations of mineralisation evident. Stable isotope analyses of carbonates from selected samples indicate that methanogenesis-related CO2 reduction has occurred at two of the Bowen Basin sampling locations. Ankerite precipitated from a magmatic fluid or basinal brine is associated with significant sulphide mineralisation within brecciated Ruhr coal proximal to major fault intersections with anticlines, and has been meteorically altered to ferroan calcite and sulphates in coal from immediately below the Carboniferous/Cretaceous unconformity. Similar alteration has occurred within a Bowen Basin coal sample close to the present day land surface. Variation of mineralisation within both the cleats and the coal matrix occurs on a fine scale, with crystals of multiple mineral species often being present within micrometres of each other. [Copyright &y& Elsevier]

Abstract: This paper describes the methodology used to derive the economics of CO2 storage in coal with enhanced coalbed methane recovery. A significant difference between CO2 storage in coal seams and storage in saline aquifers is that the incrementally recovered natural gas constitutes an additional revenue stream. In the case of CO2 storage in coal it is necessary to distinguish between CBM (primary coalbed methane recovery), CO2-ECBM (enhanced coalbed methane recovery caused by and including the injection of CO2), and CO2 storage with incremental CBM recovery (Storage-ICBM). The methodology is demonstrated by means of a case study that evaluates the economics of carbon capture and storage with incremental CBM recovery (CCS-ICBM) at the Spring Gully CBM prospect in the Bowen Basin, QLD, Australia–Australia’s most productive CBM basin. Economic analyses of the Spring Gully development show that the specific cost of CO2-ECBM is A$37/t CO2 avoided (equivalent to US$31/t at an assumed long term exchange rate of A$1.00 = US$0.85) including capture costs. However, this incorporates the benefits of the underlying CBM project and therefore underestimates the cost of CCS-ICBM. The incremental cost of CCS-ICBM is A$92/t (US$78/t) excluding these benefits. The results demonstrate the importance of using an appropriate methodology to determine and present storage economics. If no distinction between CO2-ECBM and Storage-ICBM is made, the real costs of storage will for most cases be significantly underestimated and could potentially lead to poor investment decisions and the selection of economically unviable storage sites. [Copyright &y& Elsevier]

This paper introduces the development of a new predictive model in support of proppant injection in naturally fractured coal seam gas (CSG) reservoirs. In the proposed model, the finite element method (FEM) is used for the prediction of proppant embedment and elastoplastic deformation of the coal. The lattice Boltzmann method (LBM) is applied to the modelling of fluid flow through propped fractures, in which the modified partially saturated method (MPSM) is implemented to characterise the fluid–solid interactions. Permeability diagrams of the fractures are then generated as functions of particle packing ratio and effective stress. Finally, these results are incorporated into a radial Darcy flow analytical solution to predict the productivity index of the CSG wells under various proppant injection pressures and cleat compressibilities. The developed model is applied to selected coal samples from the Bowen and Surat Basins in Queensland, Australia. Modelling results indicate that proppant injection leads to increased fracture permeabilities and enhanced well productivity indexes. The elastoplastic deformation results in smaller permeability increase and less production enhancement when compared to the traditional linear elastic models. Although focused on Australian coals, the developed workflow can be broadly applicable to the assessment of potential stimulation efficacy in other unconventional reservoirs. In addition, a better understanding and implementation of the proppant injection scheme can effectively improve the post-fracturing performance, particularly in low-permeability coal intervals, which benefits the CSG industry. • Elastoplasticity is incorporated into computational models of proppant embedment. • The deformation of idealised coal cleats is assessed for residual permeability. • Optimal monolayer packing is determined for selected Bowen and Surat Basin coals. • Resulting fracture permeaibilities used in well productivity sensitivity analyses. [ABSTRACT FROM AUTHOR]