Stochastic modeling of iron in coal seams using two‐point and multiple‐point geostatistics: A case study (Mining, Metallurgy & Exploration)

Society for Mining, Metallurgy & Exploration
SULTAN ABULKHAIR Nasser Madani
Organization:
Society for Mining, Metallurgy & Exploration
Pages:
19
File Size:
8633 KB
Publication Date:
Mar 30, 2022

Abstract

The abstract of the paper discusses the challenge of quantifying iron content in a coal deposit in Kazakhstan. The iron dataset is limited, coming from only three drill holes and some stope samples, while a large amount of geological information is available from legacy drill hole data. The paper proposes a workflow using multiple-point geostatistics to model geological domains and two-point geostatistics to model iron content within these domains. The results show that the direct sampling (DeeSse) algorithm effectively reproduces the complex seam layers, and sequential Gaussian simulation models the iron within each domain.
Citation

APA: SULTAN ABULKHAIR Nasser Madani  (2022)  Stochastic modeling of iron in coal seams using two‐point and multiple‐point geostatistics: A case study (Mining, Metallurgy & Exploration)

MLA: SULTAN ABULKHAIR Nasser Madani Stochastic modeling of iron in coal seams using two‐point and multiple‐point geostatistics: A case study (Mining, Metallurgy & Exploration). Society for Mining, Metallurgy & Exploration, 2022.

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