Flagship gold mining project sees $10 million NPV upside using idoba technology

One of Australia’s newest gold miners works with our seasoned mining consultants, expert data scientists and Dynamic Driver Modelling to make data-informed decisions on the design and operation of its flagship mine.

“Mining is about making superior decisions,” says Dr Grant Wellwood, idoba’s minerals processing SME. The output is valuable, but its extraction is expensive. Success lies in optimising the entire mine-to-market process.

As the business began planning production for its newest mine, it faced the challenge met by all mine operators – large, and largely irreversible, capital decisions must be made at an early stage. Inevitably, the most profound decisions are made when knowledge is at its minimum. Most often, they’re based on gut feel and simple spreadsheets. Get them wrong and project profitability is compromised before the first ore is hauled.

Fresh thinking is central to the mining company’s strategy as it develops its gold producing capability. Rather than rush through the study phase to making irreversible capital commitments, it wanted to take a “measure twice, cut once” approach. Its search for a better-than-gut-feel-and-spreadsheet solution to mine feasibility and planning led the business to idoba.

From instinct to data-informed decisions

Our new client needed a fit-for-purpose decision support tool on which to run their study phase scenarios, helping to model different capital costs and recoveries, under various operating and market conditions, to make better decisions on the set-up and operation of the new mine.

They wanted a tool that could grow with the project and which, once in operation, would take live sensor data and provide actionable insights for the decisions faced by the operations team.

A team of idoba’s ore processing experts, data scientists and consultants worked with the client to take a fresh look at how to model gold processing. The traditional approach uses standard processing plant flow spreadsheets but these fail to properly account for the repetitive, probabilistic nature of modelling ore processing. Instead, we took a data science approach to consider value trees and decision loops.

Using the secure, cloud-based technology of Dynamic Driver Modelling, we drew on the combined experience of our client’s team and our own experts to co-create a digital prototype of the intended mine processing system. The prototype will evolve alongside the physical processing operation from a detailed feasibility model into a digital twin of the physical process plant; from using manually-input base assumptions to applying machine learning to the near-real-time data feeds that will support near-real-time decision-making.

The Dynamic Driver Modelling solution can instantly run and compare scenario analyses based on different capital decisions and plant configurations; changing operating variables such as ore grade, recovery rate or operating hours; and market conditions such as energy or gold prices.

The solution also bridges between the spaghetti world of engineering dependencies and the structured requirements of Finance and the exec team. It produces both operational and financial metrics on intuitive dashboards of revenue, costs, capital, cashflow, production volumes and overall project net present value (NPV).

It also maintains an audit trail of input variables to help analysts and decision-makers revisit the cases on which decisions were previously made.

Superior decisions for plant configuration and operations

The co-created solution has enabled this mining newcomer to accurately model and compare the effect of different capital decisions and operating variables, before making large capital commitments.

With a more complete picture of potential operations, our client is able to make better, data-informed capital and operating decisions, such as whether or not to add a scrubber.

Using Dynamic Driver Modelling to analyse baseline and alternative processing plant scenarios, our gold-mining client identified a potential $10 million upside for project NPV.

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