Expert Mine Valuation Tips with Pros Michael Sinden and Gordon Sobering of Costmine Intelligence

Key Concepts

• PEA (Preliminary Economic Assessment): An early-stage study that provides a conceptual analysis of a mining project's economic viability.
• PFS (Pre-Feasibility Study): A more detailed study than a PEA, providing a higher level of confidence in the project's economics.
• Feasibility Study: The most comprehensive study, providing a high degree of confidence in the project's technical and economic viability, often forming the basis for financing.
• Capex (Capital Expenditure): Costs incurred to acquire or upgrade physical assets, such as property, buildings, and equipment.
• Opex (Operating Expenditure): Ongoing costs associated with running a business, such as labor, fuel, and maintenance.
• ESG (Environmental, Social, and Governance): A set of standards for a company's operations that socially conscious investors use to screen potential investments.
• Carbon Credits: Tradable permits that allow the owner to emit a certain amount of carbon dioxide or other greenhouse gases.
• Scope 1 Emissions: Direct emissions from owned or controlled sources.
• DCF (Discounted Cash Flow): A valuation method used to estimate the value of an investment based on its expected future cash flows.
• OEM (Original Equipment Manufacturer): A company that manufactures products that are then sold to other companies, who then market them under their own brand name.
• Toll Milling: A process where a mining company sends its ore to a third-party facility for processing, often to utilize existing capacity or for specialized treatment.
• Cost Indices: Metrics used to track and forecast changes in costs within a specific industry or sector.

Cost Mine Intelligence: Expertise in Mining Cost Data and Project Evaluation

Cost Mine Intelligence, also known by its alias Infomine, is a company with 40 years of experience providing high-quality, proprietary cost data for the mining industry. Their core offering includes detailed equipment capex and opex, labor, and salary data, all integrated within a cost estimation framework called Sherpa. This allows mining engineers and cost estimators to develop accurate and efficient cost estimates for building and operating mines.

Changes in the Mining Sector Cost Landscape

Michael Syninden, Managing Director at Cost Mine Intelligence, highlighted significant cost shifts over his career, particularly in the early 2020s. The pandemic-driven cycle saw a dramatic increase across the board, with labor costs (both salary and hourly) escalating significantly. Equipment costs also rose due to inflation in steel, hydrocarbon-linked items (fuel, lubricants), and consumables like mill liners and tires.

The current trend suggests that while hydrocarbon-linked input costs have started to decrease, labor costs remain "hot" due to ongoing collective bargaining agreements. Many of the cost increases from the early 2020s are now "baked in," meaning the floor for some costs is higher than before.

The Role of Hydrocarbons and Energy in Mining Costs

The future cost of hydrocarbons is intrinsically linked to the price of crude oil, with Brent crude serving as a benchmark. Syninden suggests that a sustained $70 Brent price would influence many related costs. Geopolitical events remain a wild card.

A significant wild card in the energy equation is the rapidly increasing demand for electricity, driven by AI and data centers, juxtaposed with the rising adoption of solar-generated electricity. The predictability and cost of electricity remain a major question mark.

Alternative Energy Sources and ESG Considerations

Gordon Sorbring, Director of Costing and Engineering at Cost Mine Intelligence, noted the increasing demand for battery electric vehicles (BEVs) and other electric forms of equipment in mining, driven by investor and board pressure for greener operations and ESG compliance. Companies are exploring ways to gain "green credits" and reduce their environmental footprint.

While Cost Mine Intelligence is incorporating BEVs into their cost databases by sourcing data from manufacturers, the integration of solar and other renewable energy sources into cost databases is still in its infancy. The potential for generating carbon credits through renewable energy adoption, particularly in Canada with its grid-connected hydro and solar opportunities, is significant. Cost Mine Intelligence can perform trade-off studies comparing BEVs with hydrocarbon equivalents, analyzing both capex and opex implications. They also offer Scope 1 emissions data for equipment opex, allowing for the attachment of a carbon price to assess exposure.

Disconnects Between Technical Studies and Real-World Costs

A recurring theme is the disconnect between the cost projections in technical studies (PEA, PFS, Feasibility Studies) and the actual costs incurred during project development and operation. Gordon Sorbring attributes this, in part, to downward pressure from clients on consultants to meet specific cash flow metrics. He notes that with the depletion of easily accessible deposits, projects require robust designs and engineering, and commodity prices are paramount.

Key areas of disconnect include:

• Ramp-up Period Assumptions: Overly optimistic timelines for reaching full production can significantly impact opportunity costs and overall capex. A 2-year ramp-up versus a 4-year ramp-up has substantial financial implications, especially concerning the cost of capital and NPV.
• Permitting and Social License: The duration and complexity of permitting processes, along with potential shifts in local populace sentiment, are often underestimated and are largely uncontrollable factors.
• Reclamation Estimates: A quick or absent reclamation estimate is a significant red flag. These costs, which can be substantial (e.g., $50 million for open-pit copper mines in BC), are often overlooked or underestimated in early-stage studies, impacting the DCF model.
• Aggressive Timeline Assumptions: Unrealistic timelines can lead to inflated labor costs due to extended periods of workforce presence on-site.

Sorbring emphasizes that technical reports are "feasible, not optimal," and construction groups often optimize designs, which can lead to deviations from initial estimates.

Investor Red Flags in Technical Studies

Investors should be wary of several factors in technical studies:

• PEA-Level Studies: These are considered early-stage and often lack detailed cost consideration. Syninden advises caution with PEAs, as they can have a wide array of variability.
• Sensible Pre-Production Period: Assess if the projected ramp-up time is realistic.
• Comprehensive Reclamation Estimates: The absence or underestimation of reclamation costs is a major concern.
• Labor Cost Projections: Evaluate if labor costs are realistic, especially considering aggressive timeline assumptions.
• Metallurgical Assumptions: Gordon Sorbring stresses the importance of thorough metallurgical work, as detrimental elements (like arsenic in gold) or unexpected ore characteristics (like clays in heap leach projects) can drastically reduce recoveries and derail project economics.

Jurisdiction and International Costing

Cost Mine Intelligence is North America-focused but is expanding its international data capabilities. While core equipment costs might not vary drastically, factors like shipping, tariffs, and local regulations significantly impact overall project costs. Western companies building mines in developing markets often adhere to Western standards, reducing arbitrage opportunities in equipment and labor.

Jurisdiction plays a crucial role in cost, permitting, environmental regulations, and social license. Investors should consider risk profiles of different jurisdictions, which can influence discount rates and the cost of capital.

AI and Automation in Mining Costs

While AI and automation are the "next frontier," Cost Mine Intelligence has not yet fully incorporated them into their cost models. Early indications suggest that AI and automation are primarily driven by efficiency, safety, and operational improvements rather than direct cost savings. The replacement of certain roles with software engineers, for example, does not necessarily translate to reduced overall costs. Gordon Sorbring sees AI as a tool to help validate cost data from vendors and OEMs.

Processing and Metallurgy: Key Cost Drivers

Mineral processing and energy consumption are identified as critical cost drivers. The complexity and energy intensity of new and exotic methods for extracting metals are increasing. This includes advanced leaching techniques for copper and the production of high-grade beneficiated pellets for the iron ore market.

The importance of metallurgy cannot be overstated. Investors should ensure that metallurgical assessments are robust, considering potential detrimental elements and ore characteristics that could impact recoveries.

Bulk Sampling and Toll Milling

The practice of bulk sampling and toll milling, while potentially a non-dilutive way to raise funds, is viewed with caution. While it can provide valuable data for due diligence, it also involves processing the deposit before full development, which can be seen as "milking" the resource. Hiring consultants to review bulk sample data is recommended for transparency.

Inflation and Cost Forecasting

Cost Mine Intelligence develops mining-specific cost indices using data from the US, Australia, and Canada. These indices are granular and account for industry-specific idiosyncrasies. While currently focused on historical data, they are exploring forecasting capabilities. Key areas for future forecasting efforts include labor costs, steel, and hydrocarbons. They advocate for industry-specific indices over general CPI due to the unique cost structures within mining.

Commodity Focus and Services

Cost Mine Intelligence sees significant interest in gold and copper. They are also observing continued interest in high-grade iron ore, which is seen as an ESG-friendly commodity due to its "clean burning" potential when processed into high-quality pellets. They also provide costing services for coal (including metallurgical coal) and uranium, offering specialized models like in-situ leach for uranium.

For bulk commodities, transportation costs and logistics are paramount, especially for companies located in metropolitan areas or requiring movement to hub-and-spoke mill operations.

Cost Mine Intelligence Services and Resources

Cost Mine Intelligence offers:

• Equipment Cost Service: Detailed opex and capex data for mining equipment.
• Mine Labor Service: Comprehensive and annually updated mine labor cost data.
• Sherpa: A cost modeling layer that utilizes their raw data to create capex and opex estimates for various mining operations (surface, underground, mineral processing, reclamation).
• Project Woody (Upcoming): A new product integrating property databases with their analytical layer to provide independent views on projects and operations, generating high-quality, fast cost curves.

They can be found at Costmine.com, where they offer a newsletter with updates, new content, and data releases. Their primary social media presence is on LinkedIn.

Conclusion

Cost Mine Intelligence emphasizes the critical need for accurate and detailed cost data in mining project evaluation. They highlight the evolving cost landscape, the importance of considering ESG factors and alternative energy, and the persistent disconnects between theoretical studies and practical execution. For investors, a critical review of technical studies, with a focus on realistic ramp-up periods, comprehensive reclamation estimates, and robust metallurgical assessments, is essential. The company's services provide the tools and data necessary to navigate these complexities and make more informed investment decisions in the resource sector.