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Comparing implicit boundary and hierarchical plurigaussian simulation for modeling geological domains using hard and
Veronica Veliz1, Jordan Plaza-Carvajal1, Mohammad Maleki2
1Department of Metallurgical and Mining Engineering, Universidad Católica del Norte, Antofagasta, Chile.
Scientific Reports
|June 2, 2026
Summary
This study compares Implicit Boundary Simulation (IBS) and Hierarchical Plurigaussian Simulation (HPGS) for geological domain modeling. HPGS better integrates interpreted geological models as soft data, improving accuracy in mineral resource evaluation, especially with limited data.
Area of Science:
- Geosciences
- Computational Geology
- Mineral Resource Evaluation
Background:
- Accurate geological domain delineation is vital for mineral resource evaluation.
- Geostatistical simulation offers multiple scenarios to assess uncertainty in geological domain layouts.
- Existing frameworks require refinement for optimal integration of interpreted geological models.
Purpose of the Study:
- To compare Implicit Boundary Simulation (IBS) and Hierarchical Plurigaussian Simulation (HPGS) for geological domain modeling.
- To propose methods for incorporating interpreted geological models as soft data in geostatistical simulations.
- To evaluate the performance of IBS and HPGS in a data-scarce porphyry copper deposit.
Main Methods:
- Implicit Boundary Simulation (IBS) using signed-distance covariates.
- Hierarchical Plurigaussian Simulation (HPGS) using local domain proportions informed by interpreted models.
- Application to a porphyry copper deposit with five mineralization zones.
- Generation of 100 conditional realizations for each method.
Main Results:
- Both IBS and HPGS benefited from incorporating soft data from interpreted models.
- HPGS demonstrated greater consistency with the interpreted geological model.
- HPGS showed particular strength in modeling mineralization zones with small-scale variability.
Conclusions:
- HPGS provides a more robust framework for integrating interpreted geological models as soft data in geostatistical simulations.
- The proposed pathways enhance the accuracy of geological domain modeling, especially under data scarcity.
- This research offers practical solutions for improving mineral resource evaluation through advanced geostatistical techniques.
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