Simulation -- An Approach to Risk Analysis in Coal Mining

Costa, João Felipe Coimbra Leite; Zingano, André Cezar; Koppe, Jair Carlos

doi:10.2113/0090043

Cited by 17 publications

(11 citation statements)

References 5 publications

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“…Resources comprise the estimated amount of coal in the subsurface. Typically, thickness maps have been used for assessing resources, either using: a) interpolation (Starks et al, 1982;Schuenmeyer and Power, 2000;Tercan and Karayigit, 2001;Watson et al, 2001;Koike, 2008a and2008b;Tercan et al, 2013;Saikia and Sarkar 2013), or b) geostatistical simulation methods (Costa et al, 2000;2001a and2001b;de Souza et al, 2004;Olea et al, 2011;Olea and Luppens 2012;Hohn and Britton, 2013;Cornah et al, 2013;Pardo-Iguzquiza et al, 2013). Interpolation methods applied in this context are appropriate when the goal is to provide a unique composite global estimate for resources.…”

Section: Coal Resources Reserves and 3d Facies Modelsmentioning

confidence: 99%

Forecasting coal resources and reserves in heterogeneous coal zones using 3D facies models (As Pontes Basin, NW Spain)

Falivene

Cabrera

Sáez

2014

International Journal of Coal Geology

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Forecasting coal resources and reserves is critical for coal mine development. Thickness maps are commonly used for assessing coal resources and reserves; however they are limited for capturing coal splitting effects in thick and heterogeneous coal zones. As an alternative, threedimensional geostatistical methods are used to populate facies distribution within a densely sampled heterogeneous coal zone in the As Pontes basin (NW Spain). Coal distribution in this zone is mainly characterized by coal-dominated areas in the central parts of the basin interfingering with terrigenousdominated alluvial fan zones at the basin margins. Resultant models are applied to forecast coal resources and reserves. Predictions using subsets of available well data are also generated to understand performance under limited data constraints. Facies interpolation methods tend to overestimate coal resources and reserves due to interpolation smoothing. Facies simulation methods yield similar resource predictions than conventional thickness map approximations. Reserves predicted by facies simulation methods are mainly influenced by: a) the specific coal proportion threshold used to determine if a block can be recovered or not, and b) the method capability to reproduce areal trends in coal proportions and splitting between coal-dominated and terrigenous-dominated areas of the basin. Reserves predictions differ between the simulation methods, even with dense conditioning datasets. Simulation methods are ranked according to the correlation of their outputs with predictions to the directly interpolated coal proportions: with lowdensity datasets sequential indicator simulation with trends yields the best correlation, with highdensity datasets sequential indicator simulation with post-processing using maximum a posteriori selection yields the best correlation. AbstractForecasting coal resources and reserves is critical for coal mine development. Thickness maps are commonly used for assessing coal resources and reserves; however they are limited for capturing coal splitting effects in thick and heterogeneous coal zones. As an alternative, three-dimensional geostatistical methods are used to populate facies distribution within a densely sampled heterogeneous coal zone in the As Pontes basin (NW Spain). Coal distribution in this zone is mainly characterized by coaldominated areas in the central parts of the basin interfingering with terrigenousdominated alluvial fan zones at the basin margins. Resultant models are applied to forecast coal resources and reserves. Predictions using subsets of available well data are also generated to understand performance under limited data constraints.Facies interpolation methods tend to overestimate coal resources and reserves due to interpolation smoothing. Facies simulation methods yield similar resource predictions than conventional thickness map approximations. Reserves predicted by facies simulation methods are mainly influenced by: a) the specific coal proportion threshold used to determine if a ...

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Section: Coal Resources Reserves and 3d Facies Modelsmentioning

confidence: 99%

Forecasting coal resources and reserves in heterogeneous coal zones using 3D facies models (As Pontes Basin, NW Spain)

Falivene

Cabrera

Sáez

2014

International Journal of Coal Geology

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“…Costa et al, 2000;Castrignano and Buttafuoco, 2004;Cinnirella et al, 2005). The algorithm, in very simple terms, defines randomly through all grid nodes.…”

Section: Conditional Simulationmentioning

confidence: 99%

“…There were many examples of successful applications of the conditional simulation in fields such as mining and geology (e.g. Journel, 1994;Gòmez Hernandez and Cassiraga, 1994;Lipton et al, 1998;Costa et. al., 2000;Journel and Kyriakidis, 2004); most of them conducted the research for the continuity variables, but a few researches are related to the categorical variables (e.g.…”

Section: Introductionmentioning

confidence: 99%

Geostatistical conditional simulation for the assessment of contaminated land by abandoned heavy metal mining

Ersoy

Yünsel

Atici

2008

Environmental Toxicology

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Abandoned mine workings can undoubtedly cause varying degrees of contamination of soil with heavy metals such as lead and zinc has occurred on a global scale. Exposure to these elements may cause to harm human health and environment. In the study, a total of 269 soil samples were collected at 1, 5, and 10 m regular grid intervals of 100 3 100 m area of Carsington Pasture in the UK. Cell declustering technique was applied to the data set due to no statistical representativity. Directional experimental semivariograms of the elements for the transformed data showed that both geometric and zonal anisotropy exists in the data. The most evident spatial dependence structure of the continuity for the directional experimental semivariogram, characterized by spherical and exponential models of Pb and Zn were obtained. This study reports the spatial distribution and uncertainty of Pb and Zn concentrations in soil at the study site using a probabilistic approach. The approach was based on geostatistical sequential Gaussian simulation (SGS), which is used to yield a series of conditional images characterized by equally probable spatial distributions of the heavy elements concentrations across the area. Postprocessing of many simulations allowed the mapping of contaminated and uncontaminated areas, and provided a model for the uncertainty in the spatial distribution of element concentrations. Maps of the simulated Pb and Zn concentrations revealed the extent and severity of contamination. SGS was validated by statistics, histogram, variogram reproduction, and simulation errors. The maps of the elements might be used in the remediation studies, help decision-makers and others involved in the abandoned heavy metal mining site in the world. # 2008 Wiley Periodicals, Inc. Environ Toxicol 23: 96-109, 2008

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“…The SGS is an efficient method widely used in the mining industry (Lipton et al,1998;Costa, et al, 2000;Vann et al, 2002;Lantuéjoul, 2002;Gambin et al, 2005). A flow chart from characterisation of accumulated data to uncertainty assessment is given in Figure 1 for illustration of geostatistical conditional simulation.…”

Section: Process Of Sequential Gaussian Simulationmentioning

confidence: 99%

“…There is a variety of techniques for obtaining conditionally simulated models which have been applied to metal mining (Journel, 1974(Journel, , 1994Gomez-Hernandez and Cassiraga, 1994;Gubial et al, 1997;Lipton et al, 1998;Journel and Kyriakidis, 2004). The conditional simulation of a case study of risk analysis in coal mining focused on coal accumulation and sulphur content was carried out by Costa et al (2000). An assessment of the uncertainty associated with grade-tonnage curves using geostatistical simulation in a coalmine has been studied by Tercan and Akcan (2004).…”

Section: Introductionmentioning

confidence: 99%

Geostatistical Conditional Simulation for the Assessment of the Quality Characteristics of Cayırhan Lignite Deposits

Ersoy

Yünsel

2006

Energy Exploration & Exploitation

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Traditional estimation techniques based on block models with interpolation such as inverse distance and kriging methods do not take into account the uncertainty associated with the estimates and variability of a deposit. These methods are also inadequate for short range mine planning. However, conditional simulation models (Sequential Gaussian Simulation) reproduce the actual variability (histogram) and spatial continuity (variogram) of the attributes of interest. Sequential Gaussian Simulation (SGS) method was used to address the problem of measuring the uncertainty associated with an estimate for Çayırhan coal deposits. The coal seam is split by a 0.5-1 m thick tuffaceous siltstone and claystone into the upper (Tv), and lower (Tb) seams, which contain essentially different mineral matter and quality parameters. Directional and omni-directional experimental semivariograms of the variables for the transformed data showed that neither geometric nor zonal anisotropy exist in the data. The most evident spatial dependence structure of the continuity for omnidirectional experimental variogram, characterised by spherical and experimental models of the quality variables were obtained. The case study addresses the spatial distribution and uncertainty of quality variables at the study area using a probabilistic approach. This approach was based on SGS used to yield a series of conditionally images characterised by equally probable spatial distributions of the quality variables across the area. The advantages of SGS were illustrated through the case study. The simulated models can be incorporated into mine planning and scheduling.

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Simulation -- An Approach to Risk Analysis in Coal Mining

Cited by 17 publications

References 5 publications

Forecasting coal resources and reserves in heterogeneous coal zones using 3D facies models (As Pontes Basin, NW Spain)

Forecasting coal resources and reserves in heterogeneous coal zones using 3D facies models (As Pontes Basin, NW Spain)

Geostatistical conditional simulation for the assessment of contaminated land by abandoned heavy metal mining

Geostatistical Conditional Simulation for the Assessment of the Quality Characteristics of Cayırhan Lignite Deposits

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