Modeling multiple coal seams using signed distance functions and global kriging

Deutsch, Clayton V.; Wilde, Brandon

doi:10.1016/j.coal.2012.11.013

Cited by 20 publications

(15 citation statements)

References 4 publications

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“…However, interpolations provide a representation of facies distribution that can be used to improve the qualitative understanding of the broad spatial distribution on the coal zone (Falivene et al, 2007b;Heriawan and Koike 2008b; Figure 9). Deutsch and Wilde (2013) recently proposed a novel cell-based facies interpolation approach for modelling coal splitting with the potential for respecting coal proportions.…”

Section: Interpolation Methods Smoothing Coal Resources and Reservesmentioning

confidence: 99%

“…These have been widely used to reconstruct or simulate facies distributions in the subsurface, mostly in relation to hydrocarbon reservoirs or aquifers (for example: Johnson and Dreisss, 1989;Langlais and Doyle, 1993;Gotway and Rutherford, 1994;de Marsily et al, 1998 andLee et al, 2007). However, examples of their application to coal zones are limited (Falivene et al, 2007b;Heriawan and Koike, 2008b;Deutsch and Wilde, 2013). …”

Section: Coal Resources Reserves and 3d Facies Modelsmentioning

confidence: 99%

“…Tentative position for Figure 4 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 11 2004), c) do not require or impose extensive correlation of internal heterogeneities such as surface-based methods (Benndorf, 2013;...…”

Section: Coal Proportions Benchmarkmentioning

confidence: 99%

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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: Interpolation Methods Smoothing Coal Resources and Reservesmentioning

confidence: 99%

Section: Coal Resources Reserves and 3d Facies Modelsmentioning

confidence: 99%

Section: Coal Proportions Benchmarkmentioning

confidence: 99%

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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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“…Implicit methods are straightforward and computationally fast. Some well-established implicit methodologies are reviewed in this paper: The Leapfrog © methodology (Cowan et al, 2003), potential field (Chilès et al, 2004) and signed distance function technique (Deutsch and Wilde, 2013;Silva, 2015). For the latter, a special plug-in was developed to run at SGeMS.…”

Section: Geologic Modelingmentioning

confidence: 99%

“…The aim of this article is to investigate the applicability of the signed distance function methodology (Deutsch and Wilde, 2013;Silva, 2015) as a substitute or ancillary method for traditional geologic modeling. The…”

Section: Introductionmentioning

confidence: 99%

Signed distance function implicit geologic modeling

2017

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Prior to every geostatistical estimation or simulation study there is a need for delimiting the geologic domains of the deposit, which is traditionally done manually by a geomodeler in a laborious, time consuming and subjective process. For this reason, novel techniques referred to as implicit modelling have appeared. These techniques provide algorithms that replace the manual digitization process of the traditional methods by some form of automatic procedure. This paper covers a few well established implicit methods currently available with special attention to the signed distance function methodology. A case study based on a real dataset was performed and its applicability discussed. Although it did not replace an experienced geomodeler, the method proved to be capable in creating semi-automatic geological models from the sampling data, especially in the early stages of exploration.

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Spatial Modeling of Geometallurgical Properties: Techniques and a Case Study

et al. 2015

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High-resolution spatial numerical models of metallurgical properties constrained by geological controls and more extensively by measured grade and geomechanical properties constitute an important part of geometallurgy. Geostatistical and other numerical techniques are adapted and developed to construct these high-resolution models accounting for all available data. Important issues that must be addressed include unequal sampling of the metallurgical properties versus grade assays, measurements at different scale, and complex nonlinear averaging of many metallurgical parameters. This paper establishes techniques to address each of these issues with the required implementation details and also demonstrates geometallurgical mineral deposit characterization for a copper-molybdenum deposit in South America. High-resolution models of grades and comminution indices are constructed, checked, and are rigorously validated. The workflow demonstrated in this case study is applicable to many other deposit types.

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Modeling multiple coal seams using signed distance functions and global kriging

Cited by 20 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)

Signed distance function implicit geologic modeling

Spatial Modeling of Geometallurgical Properties: Techniques and a Case Study

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