Geostatistical modelling of mine tailings and comparative analysis of sampling methodologies: A case study of the Otanmäki ilmenite tailings storage facility project

Increasing concerns about the availability of Critical Raw Materials (CRMs) have shifted focus to extractive waste sites as potential sources for secondary resources. Resource assessment requires robust investigation and resource definition, necessitating representative sampling and use of an appropriate modelling method. In this study, spatial sampling sensitivity was tested at the Otanmäki tailings storage facility (TSF) by conducting multiple models at different scales, utilizing both previously collected and new data. Additionally, three tailings sampling methodologies were evaluated to ensure sample representativity and minimize contamination: a tube sampler with a valve, a flow-through blade, and an auger drill. Results indicated that both the auger drill and the tube sampler perform well and provide similar results under low moisture conditions. However, the tube sampler was estimated to be more accurate in varying conditions, despite it having a smaller sample volume and being more time-consuming to use. According to the modelling results, there were minimal changes in grade and tonnage when increasing sampling density or changes in model scale. Thus, the existing resource estimation from the Otanmäki TSF that was based on a 100 × 100 m grid could be considered as having a high-confidence in relation to the G-category in the United Nations Framework Classification for Resources (UNFC) system with effective investigation of tailings sites requires a tailored approach considering factors such as ore deposit type, mineralization style, and information on ore processing and tailings disposal practices. This work provides insights into tailings resource modelling, estimation confidence, sample representativity, and optimal sampling strategies, aiding in the resource classification of tailings sites. • Tube sampler with flapper valve is a representative sampling method for tailings. • Spatial sampling sensitivity analysis is a cost-effective approach in TSF studies. • TSF cases need to have a tailored approach to solve site-specific issues. • The 100 × 100 m sampling grid was found to be sufficient for the Otanmäki TSF.

Authors

Institutions

Publication Details

Journal
Journal of Geochemical Exploration
Published
2025-03-24
DOI
https://doi.org/10.1016/j.gexplo.2025.107759
Citations
2
Primary Topic
Soil Geostatistics and Mapping
Type
article
Field-Weighted Citation Impact
1.60
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Geostatistical modelling of mine tailings and comparative analysis of sampling methodologies: A case study of the Otanmäki ilmenite tailings storage facility project

Tuomas Leskelä, Janne Hokka, Teemu Karlsson
2 citations
Journal of Geochemical Exploration
Soil Geostatistics and Mapping
1.60
article

Geostatistical modelling of mine tailings and comparative analysis of sampling methodologies: A case study of the Otanmäki ilmenite tailings storage facility project

Tuomas Leskelä, Janne Hokka, Teemu Karlsson
article en
2 citations

Abstract

Increasing concerns about the availability of Critical Raw Materials (CRMs) have shifted focus to extractive waste sites as potential sources for secondary resources. Resource assessment requires robust investigation and resource definition, necessitating representative sampling and use of an appropriate modelling method. In this study, spatial sampling sensitivity was tested at the Otanmäki tailings storage facility (TSF) by conducting multiple models at different scales, utilizing both previously collected and new data. Additionally, three tailings sampling methodologies were evaluated to ensure sample representativity and minimize contamination: a tube sampler with a valve, a flow-through blade, and an auger drill. Results indicated that both the auger drill and the tube sampler perform well and provide similar results under low moisture conditions. However, the tube sampler was estimated to be more accurate in varying conditions, despite it having a smaller sample volume and being more time-consuming to use. According to the modelling results, there were minimal changes in grade and tonnage when increasing sampling density or changes in model scale. Thus, the existing resource estimation from the Otanmäki TSF that was based on a 100 × 100 m grid could be considered as having a high-confidence in relation to the G-category in the United Nations Framework Classification for Resources (UNFC) system with effective investigation of tailings sites requires a tailored approach considering factors such as ore deposit type, mineralization style, and information on ore processing and tailings disposal practices. This work provides insights into tailings resource modelling, estimation confidence, sample representativity, and optimal sampling strategies, aiding in the resource classification of tailings sites. • Tube sampler with flapper valve is a representative sampling method for tailings. • Spatial sampling sensitivity analysis is a cost-effective approach in TSF studies. • TSF cases need to have a tailored approach to solve site-specific issues. • The 100 × 100 m sampling grid was found to be sufficient for the Otanmäki TSF.

Journal of Geochemical ExplorationVol. 274
Geological Survey of Finland (FI)
Openalex Percentile: Top 19%
Soil Geostatistics and Mapping
1.60
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.