Geometallurgical and Predictive Modelling 

Sedgman helps clients use modelling, mass balance discipline and metallurgical accounting to understand how ore characteristics and operating conditions influence plant performance. By combining geometallurgical interpretation, simulation and predictive analysis, we provide insights that support recovery, throughput, product quality and operational optimisation decisions. 

Improvement decisions become stronger when orebody knowledge, plant data and metallurgical performance are interpreted together. The greatest value of geometallurgical modelling lies in predictability. By understanding how different material types are likely to behave before they reach the plant, operators can make better mining, blending, processing and capital planning decisions while reducing operational surprises. Sedgman helps clients connect these inputs through geometallurgical modelling, mass balance development, metallurgical accounting and predictive simulation, providing a clearer view of how resource variability, operating conditions and process response influence performance.

This integrated approach transforms technical data into a practical modelling framework. Geo-metallurgical models link ore characteristics to expected processing behaviour, while mass balances give a structured basis for reconciling material movement and plant performance. By linking geology, mining and processing disciplines within a common decision framework, Sedgman helps clients move beyond siloed datasets and better understand the interactions that drive overall project performance. Metallurgical accounting improves confidence in how recovery, grade, throughput and product quality are measured and interpreted. Predictive modelling then enables the evaluation of sensitivities, operating scenarios and potential performance outcomes.

By combining these activities, Sedgman provides a stronger foundation for operational decisions, optimisation studies and performance conversations. The approach also helps identify and quantify key technical risks associated with ore variability, processing constraints and recovery uncertainty, enabling mitigation strategies to be developed earlier. The aim is to move beyond isolated datasets into a connected understanding of plant performance and which technical choices are most likely to support safer, more reliable and more efficient operation.

Because Sedgman’s specialists are involved across process development, engineering, project delivery, operations and optimization, our modelling frameworks are built around the decisions that ultimately need to be made throughout the asset lifecycle, not simply around theoretical analysis. 

Outcomes We Focus On

Business Outcomes:

  • Reduced uncertainty around future plant performance.
  • Better-informed operational, planning and investment decisions.  
  • Earlier identification of risks and production constraints.  
  • Improved recovery, throughput and product quality outcomes.  
  • More effective optimization initiatives through predictive insights.  
  • Increased confidence in strategic and operational decision-making.  

Technical Outcomes:

  • Stronger integration of orebody, process and operational data.
  • More reliable geometallurgical models and performance forecasts.  
  • Improved metallurgical accounting and reconciliation frameworks.
  • Enhanced scenario modelling and sensitivity analysis.  
  • Better understanding of variability drivers and process performance relationships.  

What We Deliver

Our specialists provide  geometallurgical modelling and simulation to help clients understand how ore variability can influence processing performance. This can include connecting orebody attributes, mineralogical behaviour, recovery drivers and operating constraints so technical teams can better anticipate plant response and target improvement opportunities. 

We develop and review mass balances that provide greater visibility of material movement, process performance and key operating assumptions. A robust mass balance provides a practical foundation for modelling, metallurgical accounting, design inputs, troubleshooting, benchmarking and optimisation. 

We develop metallurgical accounting frameworks that improve confidence in the measurement and reconciliation of production, recovery, grade, product quality and process performance. This helps clients assess performance with clearer data discipline and build a stronger basis for reporting, operational review and continuous improvement. 

We apply predictive modelling and simulation to evaluate future operating conditions, assess sensitivities and evaluate likely performance outcomes. This can support scenario planning, constraint analysis, optimisation studies and decisions about which opportunities merit further evaluation and action. Predictive models help clients move from understanding historical performance to forecasting future outcomes. This supports proactive decision-making, allowing opportunities and risks to be identified before they impact production, recovery, product quality or operating costs. Where appropriate, predictive modelling approaches can support digital-twin style workflows that continuously combine operating data, orebody information and process models to improve performance forecasting and optimization. Modelling can also provide valuable insight into energy intensity, water consumption, emissions performance and resource utilization, helping organizations evaluate pathways to more sustainable and efficient operations.  

We compare operating scenarios and sensitivities so clients can understand trade-offs before changes are implemented. This can include reviewing the potential influence of feed characteristics, process settings, recovery assumptions, throughput targets, product requirements and operating constraints. Scenario assessments allow clients to understand the economic and operational implications of different decisions before implementation. This supports evaluation of trade-offs between throughput, recovery, product quality, energy consumption, operating costs and capital investment.  

We translate modelling, simulation and accounting outputs into decision-ready insights for site, technical and leadership teams. This includes interpreting assumptions, highlighting limitations, connecting results to operational priorities and defining practical actions informed by the analysis. We help operational and technical teams apply modeling insights to production planning, ore scheduling, blending strategies, constraint management and improvement initiatives, ensuring modelling outputs translate into practical actions that improve outcomes.  

Get In Touch

Talk to Sedgman about improving performance through geometallurgical and modelling insights

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