Creating a geological model in Geovia Surpac starts with a structured exploration database and ends with a 3D representation of lithology, mineralization, and grade distribution that supports nickel exploration, resource estimation, and mine planning.

Geological modeling in the supplied literature centers on three linked themes: what a geological model is, which datasets are needed, and why Surpac improves accuracy and usefulness in nickel exploration workflows [1] [2] [3].

Geological Model Concept

A geological model is a simplified 3D representation of subsurface geology that summarizes the geometry and distribution of major geological elements [4]. Drillholes are the main data source because they provide the detailed subsurface information that can be classified into geological units for 3D modeling [4] [5]. In Surpac-focused work, geological databases are built first, then used to interpret ore bodies, faults, stratigraphy, and finally construct 3D models and resource estimates [3] [1].

• Geological models support reserve evaluation, geological interpretation, and mine planning [1] [3].
• In nickel laterites, models help separate limonite, saprolite, and bedrock domains before grade estimation [6] [7].
• A model is always a simplification, so domain definitions and upscaling choices affect reproducibility and interpretation quality [4].

Figure 1: Geovia Surpac Geological Modeling Workflow

Exploration Database

The exploration database used to create a geological model in Surpac is built mainly from collar, survey, assay, and lithology tables [8] [2] [9]. The studies consistently treat drillhole data as the core input for nickel laterite modeling, with topography and sometimes mapping or geophysical data added later for validation or interpretation [8] [10] [11].

Key Drillhole Tables

Table Typical fields Purpose in Surpac Example evidence Collar Hole ID, X, Y, Z, max depth, hole path Locates each hole in space [5] Survey Hole name, depth, dip, azimuth Defines hole trajectory [8] Assay Hole ID, from, to, grade fields Stores interval chemistry [8] Lithology Hole ID, from, to, lithology code or description Defines rock or weathering units [8] [7] Optional extras Dates, drilling type, project, quality flags Improves metadata and QA/QC [5]

Figure 2: Core drillhole tables used Suroac geological databases

• Assay tables are interval tables, commonly storing From, To, lithology, and grades such as Ni, Co, Fe, SiO2, and MgO [8].
• Collar tables store the hole location and usually the maximum drilled depth and path descriptor [5] [8].
• Survey tables store downhole orientation data needed to position intervals accurately in 3D space [8] [10].

Nickel Exploration Use

In nickel exploration, geological modeling is used to map the distribution, thickness, and continuity of laterite zones and then estimate resources in 3D [2] [9] [12]. The database usually combines collar coordinates, assay values, survey data, and lithology so Surpac can generate models of nickel distribution and ore-waste boundaries [2] [9]. Because lateritic nickel deposits show strong vertical variability and complex geometry, integrating lithology and grade within one framework is especially important [13].

• Laterite nickel models commonly define limonite, saprolite, and bedrock zones as separate domains [6] [11].
• These models help estimate tonnage and grade, such as HGSO and LGSO distributions or cut-off-based ore classes [2].
• Modeling also supports targeting and drilling strategy by quantifying uncertainty and drillhole spacing effects [13] [12].

Surpac Advantages

Geovia Surpac is used because it combines drillhole data management, geological modeling, block modeling, geostatistics, and resource estimation in one platform [1]. The software is described as flexible for creating real 3D orebody models from drilling data and for generating maps, sections, profiles, and reserve outputs [8] [14]. This integration reduces manual transfer steps and tends to improve consistency across the workflow [8] [15].

• High accuracy depends on validated input data and correct drillhole positioning, not only on the software itself [10].
• Surpac helps with 3D visualization, orebody geometry definition, and block-based resource calculation [8] [12].
• It also supports efficient map and section production, including borehole columns and block model sections [14] [3].

Figure 3: Geovia Surpac Advantages High Accuracy

Case Study Example

A clear Surpac nickel case study comes from the Gllavica nickel deposit in Kosovo, where drilling data were organized into assay, collar, and survey files for 3D orebody evaluation [8]. The assay file stored interval grades and lithology for each meter drilled, the collar file stored coordinates and total depth, and the survey file stored drill depth, bit orientation, and azimuth [8]. The study used these tables to define orebody geometry and support reserve estimation within a 25×25 m drilling grid [8].

• The assay table included Hole ID, From, To, generalized lithology, and Ni, Co, Fe, SiO2, MgO grades [8].
• The model supported ore quality evaluation and discretization of reserves into miniblocks [8].
• The case shows that a well-structured Surpac database is the basis for accurate 3D nickel modeling [8].

A second nickel laterite example from Indonesia used assay, collar, survey, and lithology data in Surpac to estimate HGSO and LGSO resources, showing that the same database logic applies across laterite settings [2].

Geological modeling in Geovia Surpac is therefore best built on a clean drillhole database with collar, survey, assay, and lithology tables, then extended into 3D domains and block models for nickel exploration. The literature supports Surpac as a strong platform for accurate geological modeling because it integrates database management, visualization, geostatistics, and resource estimation in one workflow, while the final accuracy still depends on disciplined data validation and sound geological interpretation.

References

1. Kumar M, Sailaja P, Kumar A, Chiranjeevi M, Kumar SS. Ore Reserve Estimation and Ore body Modelling. Journal of emerging technologies and innovative research. 2020.

2. Asmiani N, Thamsi A, Nompo S, Bakri S, Tukloy MYA, Harmitun H. MODEL OF LATERITE NICKEL DEPOSITS BASED ON LGSO AND HGSO VALUES PT MITRA KARYA AGUNG LESTARI. JGE (Jurnal Geofisika Eksplorasi). 2024. doi:10.23960/jge.v10i1.305

3. Chang L. Deposit 3D modeling based on visible interpretation of drillhole information. 2010.

4. Vaillant M, Hill J, Barnes S. Simplifying drill-hole domains for 3D geochemical modelling: An example from the Kevitsa Ni-Cu-(PGE) deposit. Ore Geology Reviews. 2017;90:388-398. doi:10.1016/j.oregeorev.2017.05.020

5. Zhu W, Wang Y, Chen J, Chen R. Based on Surpac Geological Database Research. Acta Geologica Sinica-english Edition. 2014;88:491-492. doi:10.1111/1755-6724.12373_36

6. Bargawa W. NICKEL LATERITE RESOURCES MODELING USING GEOLOGICAL DOMAIN ALGORITHM. International Journal of Geomate. 2021;20. doi:10.21660/2020.77.j2011

7. Joshi R, Madaiah K, Jessell M, Lindsay M, Pirot G. dh2loop 1.0: an open-source python library for automated processing and classification of geological logs. Geoscientific Model Development Discussions. 2021. doi:10.5194/gmd-2020-391

8. Zeqiri R. Nickel discretization and quality review in Gllavica mine, Kosovo. Mining of Mineral Deposits. 2021;15:35-41. doi:10.33271/mining15.01.035

9. Anwar A. Identifikasi Sebaran Endapan Nikel Laterit Berdasarkan Data Pengeboran PT. Timah Investasi Mineral Kecamatan Kabaena Barat Kabupaten Bombana Provinsi Sulawesi Tenggara. Mining Science And Technology Journal. 2025. doi:10.54297/minetech-journal.v3i3.686

10. Opong JW, Amedjoe CG, Asante A, Wilson MC. The Importance of Integrating Geological Mapping Information with Validated Assay Data for Generating Accurate Geological Wireframes in Orebody Modelling of Mineral Deposit in Mineral Resource Estimation: A Case Study in AngloGold Ashanti, Obuasi Mine. International Journal of Geosciences. 2022. doi:10.4236/ijg.2022.136023

11. Nur I, Widodo S, Aditya D, et al. Reconstruction of Subsurface Geological Model of Laterite Nickel Ore Deposit using Resistivity Geoelectric Method at PT Baula Petra Buana Mining Permit Area, South Konawe Regency, Southeast Sulawesi. Journal of Physics: Conference Series. 2025;2973. doi:10.1088/1742-6596/2973/1/012001

12. Ardi A, Jafar N. Estimation Of Laterite Nickel Resources Using The Inverse Distance Weight Method PT Premlog Offshore Indonesia Kolaka Regency, Southeast Sulawesi Province. Journal of Geology and Exploration. 2024. doi:10.58227/jge.v3i1.172

13. Rolo R, Arief J, Yuminti S. Probabilistic Modeling of Lateritic Nickel Mineral Resources. Minerals. 2026. doi:10.3390/min16050551

14. Tao-Fa Z. SURPAC-BASED GEOLOGICAL EXPLORATION AUTOMATIC MAP-MAKING APPLICATION STUDY. Geology of Anhui. 2011.

15. Shahri AA, Shan C, Larsson S, Johansson F. Normalizing Large Scale Sensor-Based MWD Data: An Automated Method toward A Unified Database. Sensors (Basel, Switzerland). 2024;24. doi:10.3390/s24041209