Koroviakа Ye., Zabolotna Yu., Pashchenko O., Rastsvietaiev V. Integration of surveying data into BIM models for effective management of mining projects

Geoteh. meh. 2024, 171, 111-127

https://doi.org/10.15407/geotm2024.171.111

INTEGRATION OF SURVEYING DATA INTO BIM MODELS FOR EFFECTIVE MANAGEMENT OF MINING PROJECTS

Koroviakа Ye. 

Zabolotna Yu. 

Pashchenko O. 

Rastsvietaiev V. 

Dnipro University of Technology 

UDC 528.9:622.002.68

Language: English

Abstract. The mining industry faces increasing complexity in managing projects due to the need for precise planning, efficient execution, and rigorous monitoring to ensure safety, productivity, and environmental compliance, yet integrating diverse data sources into a cohesive framework remains a challenge. This article examines the integration of mine surveying data into Building Information Modeling (BIM) systems as a transformative approach to enhance the management of mining projects, focusing on open-pit and underground operations. The study tackles the challenges of combining geospatial data from LiDAR, GPS, and drone-based photogrammetry with geotechnical data from borehole logging into BIM frameworks to improve project planning, execution, and monitoring in the mining industry. By leveraging advanced surveying technologies, such as high-precision total stations and laser scanning, alongside BIM tools like Autodesk Revit and Bentley OpenRoads, the proposed methodology facilitates real-time data integration, enabling better decision-making and operational efficiency. The research adopts a mixed-methods approach, incorporating case studies of a copper open-pit mine and a coal underground mine, alongside software simulations in platforms like Agisoft Metashape for modeling, to evaluate the effectiveness of the integration process. Results demonstrate significant improvements, including a 15–20% increase in project accuracy through precise geological modeling, a 10–12% enhancement in cost estimation by reducing budget overruns, and a 30% improvement in risk management by identifying high-risk zones like unstable slopes. Challenges such as data interoperability issues between surveying formats and BIM platforms, as well as the high initial cost of software and training, were noted. The article concludes with practical recommendations for implementing BIM in mining, such as phased adoption and staff training programs, and outlines prospects for future research, including automation of data workflows using robotic process automation and AI-driven analytics for predictive risk assessment, aiming to further streamline operations and enhance safety in mining projects.

Keywords: mine surveying, BIM (Building Information Modeling), mining project management, geospatial data, geotechnical data, data integration, digital twins, modeling, real-time monitoring, operational efficiency.

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About the authors:

Koroviakа Yevhеn, Candidate of Technical Sciences (Ph.D), Associate Professor, Head of the Department of Oil and Gas Engineering and Drilling, Dnipro University of Technology, Dnipro, Ukraine, This email address is being protected from spambots. You need JavaScript enabled to view it. , ORCID 0000-0002-2675-6610

Zabolotna Yuliia, Candidate of Technical Sciences (Ph.D), Associate Professor, Associate Professor of the Department of Geodesy, Dnipro University of Technology, Dnipro, Ukraine, This email address is being protected from spambots. You need JavaScript enabled to view it. , ORCID 0000-0003-4360-5707

Pashchenko Oleksandr, Candidate of Technical Sciences (Ph.D), Director of the Interbranch Institute of Continuing Education (MIBO), Associate Professor at the Department of Oil and Gas Engineering and Drilling, Dnipro University of Technology, Dnipro, Ukraine, This email address is being protected from spambots. You need JavaScript enabled to view it. , ORCID 0000-0003-3296-996X

Rastsvietaiev Valerii, Candidate of Technical Sciences (Ph.D), Associate Professor, Associate Professor of the Department of Oil and Gas Engineering and Drilling, Dnipro University of Technology, Dnipro, Ukraine, This email address is being protected from spambots. You need JavaScript enabled to view it. е (Corresponding author), ORCID 0000-0003-3120-4623