Application of multi-point statistics to irregular core sampling data in modeling of copper-porphyry deposits

DOI: https://doi.org/10.30686/1609-9192-2026-5-159-163

Читать на русском языке Ilya O. Panichkin, Georgy O. Abramyan
National University of Science and Technology “MISIS”, Moscow, Russian Federation
Mining Industry Journal (Gornaya Promyshlennost) №5/ 2026 p. 159-163

Summary: The article discusses a procedure for adapting multi-point statistics to interval-based core sampling data obtained from a copper-porphyry system. The procedure uses irregular borehole sampling and generates local category-based patterns within an anisotropic ellipsoidal neighborhood of a point. The calculation includes the geological domain, lithological rock type, composite type, and aggregated class of the ore potential. Single-layer and multi-layer patterns, distance-weighted and balanced variants of multi-point statistics, indicative kriging, and hybrid schemes were compared for verification. The quality was assessed using a post-hoc validation against the borehole data, employing the proportion of the correct answers, the balanced proportion of the correct answers and the macro-averaged F1 score. For the geological domains, the best result was achieved by a hybrid variant combining multi-point statistics and indicative kriging: the macro-F1 score was 0.401, and the proportion of the correct answers was 0.495. For the lithological types, the best macro-F1 score was obtained by jointly considering the domain, lithological, and composite contexts. For the composite type and the aggregated ore potential class, the best macro-F1 scores were achieved using a distance-weighted approach with class balancing. The results show that the multilayer and distance-weighted templates improve the accuracy of category-based modeling and can be used to refine a geological model.

Keywords: copper-porphyry system, interval data, core sampling, multi-point statistics, indicative kriging, category-based modeling, geological domain, lithological type, composite type, macro-averaged F1 score

For citation: Panichkin Ilya O., Abramyan Georgy O. Application of multi-point statistics to irregular core sampling data in modeling of copper-porphyry deposits. Mining Industry Journal (Gornaya Promyshlennost). 2026;(5):159–163. https://doi.org/10.30686/1609-9192-2026-5-159-163

Article info

Received: 03.06.2026

Revised: 09.07.2026

Accepted: 16.07.2026

Authors info

Panichkin Ilya O. – Postgraduate Student, Department of Geology and Mine Surveying, College of Mining, National University of Science and Technology “MISIS”, Moscow, Russian Federation; e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.

Abramyan Georgy O. – Cand. Sci. (Eng.), Associate Professor, Department of Geology and Mine Surveying, College of Mining, National University of Science and Technology “MISIS”, Moscow, Russian Federation; https://orcid.org/0000-0002-0493-6290; e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.

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