Three-dimensional geological and geotechnical models constructed by geostatistical interpolation

This paper proposes to construct three-dimensional geological-geotechnical models using the geostatistical interpolation from geomechanics parameters of rocks as lithology and fracturing, plus Rock Designation Quality and Rock Mass Rating classification systems. Generally, the geostatistical interpolation is used to analyze the mining, but this project aims to optimize the prediction of the geological conditions during the initial assessment for infrastructure projects. In this way, the correct predictions of the geological conditions allow us to minimize the inherent risks of failures in the predictability of the structural and geometric patterns of the rocky mass in depth. The proposed procedure aims to ensure the safety of the workers during a complex enterprise. The control of the expenses, as well as the enterprise’s durability after construction, promotes social, financial, and environmental security. This methodology has been applied using data from the construction of two different sites, located in Minas Gerais state (Brazil). It was used 44 drill data, 28 from site I and 15 from site II. The results of models showed that it is possible to predict the geological conditions using this geostatistical interpolation; it is possible to affirm that geostatistical interpolation has been effective in the evaluation of geomechanical parameters.

Authors

Publication Details

Journal
Soils and Rocks
Published
2025-09-25
DOI
https://doi.org/10.28927/sr.2026.007822
Primary Topic
Geological Modeling and Analysis
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Three-dimensional geological and geotechnical models constructed by geostatistical interpolation

Georg Robert Sadowski, Marcos Egydio‐Silva, Bruna Catarino Xavier, Jorge Kazuo Yamamoto
Soils and Rocks
Geological Modeling and Analysis
article

Three-dimensional geological and geotechnical models constructed by geostatistical interpolation

Georg Robert Sadowski, Marcos Egydio‐Silva, Bruna Catarino Xavier, Jorge Kazuo Yamamoto
article en

Abstract

This paper proposes to construct three-dimensional geological-geotechnical models using the geostatistical interpolation from geomechanics parameters of rocks as lithology and fracturing, plus Rock Designation Quality and Rock Mass Rating classification systems. Generally, the geostatistical interpolation is used to analyze the mining, but this project aims to optimize the prediction of the geological conditions during the initial assessment for infrastructure projects. In this way, the correct predictions of the geological conditions allow us to minimize the inherent risks of failures in the predictability of the structural and geometric patterns of the rocky mass in depth. The proposed procedure aims to ensure the safety of the workers during a complex enterprise. The control of the expenses, as well as the enterprise’s durability after construction, promotes social, financial, and environmental security. This methodology has been applied using data from the construction of two different sites, located in Minas Gerais state (Brazil). It was used 44 drill data, 28 from site I and 15 from site II. The results of models showed that it is possible to predict the geological conditions using this geostatistical interpolation; it is possible to affirm that geostatistical interpolation has been effective in the evaluation of geomechanical parameters.

Soils and RocksVol. 49(1)
Openalex Percentile: Top 78%
Geological Modeling and Analysis
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.