Work

Using multiple-point geostatistics for geomodeling of a vein-type gold deposit

Year: 2024

Type: article

Abstract: Geostatistical cascade modeling of Mineral Resources is challenging in vein-type gold deposits. The narrow shape and long-range features of these auriferous veins, coupled with the paucity of drill-hole data, can complicate the modeling process and make the use of two-point geostatistical algorithms impractical. Instead, multiple-point geostatistics techniques can be a suitable alternative. However, the most challenging part in implementing the MPS is to use a suitable training data set or training image (TI). In this paper, we suggest using the radial basis function algorithm to build a training image and the DeeSse algorithm, one of the multiple-point statistics (MPS) methods, to model two long-range veins in a gold deposit. It is demonstrated that DeeSse can replicate long-range vein features better than plurigaussian simulation techniques when there is a lack of conditioning data. This is shown by several validation processes, such as comparing simulation results with an interpretive geological block model and replicating geological proportions.

Source: Applied Computing and Geosciences

DOI: 10.1016/j.acags.2024.100177

Authors: Aida Zhexenbayeva, Nasser Madani, Philippe Renard, Julien Straubhaar

Institutions: Nazarbayev University, University of Neuchâtel

Language: English

Topic: Geological Modeling and Analysis

Subfield: Geochemistry and Petrology

Field: Earth and Planetary Sciences

Domain: Physical Sciences

Open Access status: gold

Estimated APC paid: $1,920

Funders: Nazarbayev University, Staatssekretariat für Bildung, Forschung und Innovation