At the early stages of mine development, owners don’t always have the data they need. Incomplete data isn’t as big a problem as you might think.
At Ausenco, we spend a lot of time helping clients gain certainty about their project costs. Many of our clients are junior mining companies that own property containing mineral resources such as gold, copper or nickel. To realize a return on their initial investment, they typically look to us to perform a study which includes estimating the costs associated with bringing the asset into production. These studies vary in the level of effort and accuracy from a Preliminary Economic Analysis (PEA) to a Pre-Feasibility Study (PFS) to a Feasibility Study (FS).
The challenge is that the earlier the project is in its life cycle, the less data the client will have available to them. Some examples would be the expected level of precipitation, mineral resource estimate, the geotechnical conditions, and the metallurgical deposit. This data has a real impact on the total installed cost – using the previous data gaps for example, how large the emergency pond needs to be, recovery grades, what amount of excavation and backfilling is required and what parameters should the process equipment be sized for. They also don’t have the experience or data needed to accurately predict the development and lifecycle costs – for example, what will be the annual maintenance and operational labour costs or what will be the cost and availability of reagents needed in the production process.
In the earliest stages of a project, this requires relying on assumptions to fill in the data gaps. The better the assumptions, the greater the confidence which, in turn, improves the owner’s ability to raise capital to advance the project.
The benchmark of success
There are two key elements to a good assumption – source data and interpretation. Having good data is critical. At Ausenco, we use benchmark data collected from the hundreds of projects we’ve executed over the past thirty years. After each project, our engineers populate our databases with ‘actuals’ from the projects they have delivered. As a result, we can tell you how much process plant piping was installed for a certain-sized project with a given flowsheet in a specific geographical location.
We continuously update our data to reflect ‘real’ numbers (if we have them) and to improve our assumptions and estimates. Geotechnical data, precipitation data, core measurements, distances to usable ports – every piece of real data we can include makes our estimates more reliable.
When selecting benchmark data, it is important to consider where it comes from. It needs to be reliable, accurate, recent and clean. It is also important to draw the data from projects that have the same characteristics as the project in question. Ausenco is widely recognized for delivering reliable and capital-efficient projects – which means our data is perfect for companies that are looking to advance their project into production as soon as possible.
Going beyond the data
The second key element is interpretation. Every project is different, requiring people with the right experience and capabilities to interpret the benchmark data to reflect your situation. It is also imperative to understand the context that surrounds your comparator data.
For example, it’s easy to say a similar project used X cubic meters of concrete to construct the processing plant. But why did they use concrete instead of steel? Was there something about the site preparation or design that required more concrete to be poured? Was there a concrete batch plant especially close to site, or was the nearest suitable steel fabrication yard a long distance from site? What were the site geotechnical and seismic conditions? Understanding the context and interpreting the data is central to developing a reliable estimate.
This is where our engineers excel. With a deep bench of engineering talent and experience, we bring the right engineering capabilities and specialties to the table at the right time to ensure we are interpreting the data appropriately. We ask our senior engineers to challenge the assumptions. We sit down as a team to assess any interdependencies or integration challenges. Our goal is to provide our clients with a high degree of confidence in the estimates and calculations we provide them with, as early in the process as possible.
Building confidence
At Ausenco, we live our purpose – to find a better way. Our approach to benchmarking data and interpretation allows us to do that. It lets us understand the core elements of the project cost early and focus on how we can deliver the project more efficiently right from the start. We look at a range of comparable experiences and consider various options for each client. It empowers our engineers to invest their time into improving the project and enhancing its economic feasibility.
In my experience, incomplete data isn’t usually the problem at the early stages of mine development. If you have access to the right benchmark data, and know how to interpret it in different contexts, you can confidently fill in the gaps. This is part of what makes us stand out from the crowd.
Contact me with any questions.