Data goldmines: Advanced analytics optimise brownfields in uncertain times

In an era marked by volatile commodity prices and increasing environmental scrutiny, brownfield mining – mining operations on existing, mature sites – remains a pragmatic and strategic option for many resource companies. Rather than starting from scratch with greenfield exploration, such projects leverage historical data, existing infrastructure and legacy operations. Today, advanced data analytics is proving to be the catalyst that transforms these brownfields into high-performance, efficient, and more sustainable mining operations.

The promise of digital transformation in brownfield mines

Digital transformation in mining integrates diverse data sources like geological logs, sensor data, remote sensing and processing plant performance into unified analytical frameworks. According to industry surveys, centralised analytics platforms — whether cloud-based or on-premises – now enable mining operators to unify previously disparate datasets, delivering actionable insights across exploration, production and processing. For brownfield sites, this creates a unique opportunity. Legacy file logs, past drilling records, periodic assays, and production-history data combined with real-time sensor streams and modern analytics can yield high-resolution models of the deposit, orebody behaviour and processing performance. It effectively 're-mines' the data before re-mining the ground.

Enhancing resource estimation and exploration

Historically, exploration of brownfield sites suffered from limited insight, as old drill core data or outdated geological models often lacked precision. Today, artificial intelligence (AI) and machine learning techniques are enabling geoscientists to extract significantly more information from both legacy and new data. By analysing drilling reports, assays, geophysical surveys, satellite imagery and sensor data, AI models detect subtle spatial anomalies. Sub-centimetre geographic information systems data improves accuracy, decision-making, record-keeping, and communication while reducing unnecessary re-drilling.

Unlocking hidden value in existing infrastructure

Data-driven process optimisation can significantly enhance mineral-processing plant performance without requiring major investments. A study of Ma’aden Barrick Copper Company’s flotation circuit used historical operational data – including slurry density, concentrate grade and mill power – to identify optimal conditions for maximising copper recovery and concentrate quality. Maintaining slurry solids between 65wt% and 71wt% and first rougher concentrate grade above 26 wt% correlated with high performance, while deviations reduced efficiency. Balancing SAG and Ball mill power further enhanced results. Machine learning combined with metallurgical insight created a multivariate 'corridor' of optimal operating parameters, allowing engineers to adjust variables in tandem. Once harmonised and analysed, legacy plant data enables the optimisation of flotation circuits and other processing stages. This transforms underutilised infrastructure into efficient, modern operations with reduced waste, energy consumption and operational costs.

Brownfield rebirth through data

For mining professionals rooted in traditional practices, revisiting old mines may feel like a conservative approach. Yet, in a world of tighter capital, evolving environmental, social, and governance pressures, and demand for cost control, brownfield mining offers one of the most pragmatic paths forward.

Advanced analytics, AI, remote sensing and continuous-monitoring platforms provide a bridge between the legacy and the future, enabling companies to unlock hidden value, improve recovery, reduce their environmental footprints and extend mine life, often with less risk and lower capital expenditure than greenfield ventures. When managed properly, brownfield operations become living assets – dynamic, optimisable, and capable of delivering meaningful returns even in uncertain times.

Author bio

Jane Marsh is a seasoned environmental journalist and the Editor-in-Chief of Environment.co, specialising in in-depth coverage of environmental trends, sustainability, and the evolving energy landscape. With her work featured on leading platforms like Renewable Energy Magazine, Manufacturing.net, and Nation of Change, Jane brings a keen perspective on the intersection of energy innovation and industry practice.

Read the article online at: https://www.globalminingreview.com/exploration-development/24122025/data-goldmines-advanced-analytics-optimise-brownfields-in-uncertain-times/