Non-stationary Geostatistical Modeling: A Case Study Comparing LVA Estimation Frameworks

Non-stationary Geostatistical Modeling: A Case Study Comparing LVA Estimation Frameworks Natural Resources Research ( 2018) https://doi.org/10.1007/s11053-018-9384-5 Original Paper Non-stationary Geostatistical Modeling: A Case Study Comparing LVA Estimation Frameworks 1,3 2 2 1 Ryan Martin , David Machuca-Mory, Oy Leuangthong, and Jeff B. Boisvert Received 10 March 2018; accepted 20 May 2018 Incorporating locally varying anisotropy (LVA) in geostatistical modeling improves esti- mates for structurally complex domains where a single set of anisotropic parameters mod- eled globally do not account for all geological features. In this work, the properties of two LVA-geostatistical modeling frameworks are explored through application to a complexly folded gold deposit in Ghana. The inference of necessary parameters is a significant requirement of geostatistical modeling with LVA; this work focuses on the case where LVA orientations, derived from expert geological interpretation, are used to improve the grade estimates. The different methodologies for inferring the required parameters in this context are explored. The results of considering different estimation frameworks and alternate methods of parameterization are evaluated with a cross-validation study, as well as visual inspection of grade continuity along select cross sections. Results show that stationary methodologies are outperformed by all LVA techniques, even when the LVA framework has minimal guidance on parameterization. Findings also show that additional http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Natural Resources Research Springer Journals

Non-stationary Geostatistical Modeling: A Case Study Comparing LVA Estimation Frameworks

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Publisher
Springer US
Copyright
Copyright © 2018 by International Association for Mathematical Geosciences
Subject
Earth Sciences; Mineral Resources; Fossil Fuels (incl. Carbon Capture); Geography, general; Sustainable Development; Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences; Mathematical Modeling and Industrial Mathematics
ISSN
1520-7439
eISSN
1573-8981
D.O.I.
10.1007/s11053-018-9384-5
Publisher site
See Article on Publisher Site

Abstract

Natural Resources Research ( 2018) https://doi.org/10.1007/s11053-018-9384-5 Original Paper Non-stationary Geostatistical Modeling: A Case Study Comparing LVA Estimation Frameworks 1,3 2 2 1 Ryan Martin , David Machuca-Mory, Oy Leuangthong, and Jeff B. Boisvert Received 10 March 2018; accepted 20 May 2018 Incorporating locally varying anisotropy (LVA) in geostatistical modeling improves esti- mates for structurally complex domains where a single set of anisotropic parameters mod- eled globally do not account for all geological features. In this work, the properties of two LVA-geostatistical modeling frameworks are explored through application to a complexly folded gold deposit in Ghana. The inference of necessary parameters is a significant requirement of geostatistical modeling with LVA; this work focuses on the case where LVA orientations, derived from expert geological interpretation, are used to improve the grade estimates. The different methodologies for inferring the required parameters in this context are explored. The results of considering different estimation frameworks and alternate methods of parameterization are evaluated with a cross-validation study, as well as visual inspection of grade continuity along select cross sections. Results show that stationary methodologies are outperformed by all LVA techniques, even when the LVA framework has minimal guidance on parameterization. Findings also show that additional

Journal

Natural Resources ResearchSpringer Journals

Published: May 29, 2018

References

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