Stochastic Simulation of Coal Bed Thickness and Economic Decision-Making

Hohn, Michael Edward; McDowell, Ronald R.

doi:10.1007/978-1-4615-1359-9_14

Cited by 2 publications

(2 citation statements)

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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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“…It is well recognised that traditional methods of estimating the spatial distribution of quality parameters in geostatistics, such as kriging, fail in mapping variability due to the smoothing effect (Ravenscroft, 1994;Goovaerts, 1997;Chiles and Delfiner, 1999;Dimitrakopoulos, 2004 and others). Applications of conditional simulation in coal mining operations were until few years ago, with exceptions of some simplified case studies (Costa et al, 2000;Hohn and McDowell, 2001) not very well documented. Benndorf (2009) demonstrated first time in a full scale application in a large lignite field its benefits in terms of economic evaluation and strategic decision making in a continuous mining environment.…”

Section: Introductionmentioning

confidence: 99%

Investigatingin situvariability and homogenisation of key quality parameters in continuous mining operations

Benndorf

2013

Mining Technology

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The delivery of in-spec qualities out of the mine is essential for an efficient and environmental friendly operation of the subsequent beneficiation process. One goal of the extraction and production process in mining operations is to reduce the deposit inherent grade variability to a usually contractual defined level. The design of blending opportunities along the mining chain plays a key role in homogenising variability and improving the prediction of key parameters, such as the calorific value in the case of coal deposits. Geological conditions of deposits to exploit are becoming more complex. Typical currently exploited coal deposits in Europe are already characterised by multiple seams with multiple splits, each split representing a different variability in seam geometry and quality. Modern methods of conditional simulation in geostatistics allow for generating several spatial models or possible scenarios for large deposits capturing in situ variability. Integrating simulated models with the excavation sequence and transport and blending models of the mining operation leads to valuable insights into the expected performance as a function of the technical design and operational mode. The presented case study uses the technique of conditional simulation in geostatistics to investigate the variability of the calorific value in exploiting a complex lignite deposit. The study analyses the behaviour along the extraction, transportation and blending process in a continuous mining environment. Results provide valuable inside into the performance of a continuous mining system in terms of homogenisation and allow identifying sources for controlling variability. Conclusions can be drawn to adjust the mine design and scheduling of key equipment as well as to adjust the operation mode according to the customer's requirements in terms of coal quality variability.

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Stochastic Simulation of Coal Bed Thickness and Economic Decision-Making

Cited by 2 publications

References 4 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)

Investigatingin situvariability and homogenisation of key quality parameters in continuous mining operations

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