Modeling the Economics of Seabed Mining

Transcription

1 Modeling the Economics of Seabed Mining Richard Roth and Randolph Kirchain Research Team: Frank Field and Thomas Peacock

2 Overview of the Project Goal Analyze the expected financial outcome of various market and technical outcomes under several royalty schemes Approach Develop a process based model of seabed extraction Develop a cashflow simulation model Key issues to consider Major sources of capital and operating expenditures Future market prices for extracted metals Risk that derives from uncertainty about technology and markets Note: Throughout we use the term royalty to mean any tax specifically targeted to minerals extraction.

3 The fundamental challenge: Mining involves risks, but concession holders must receive compensation Contractors Profit Risk World / UN Compensation for lost resources

4 The fundamental challenge: Mining involves risks, but concession holders must receive compensation World / UN Compensation for lost resources Contractors Profit Risk Basic mining cash flow Significant up front investments Long delays before production Need returns that merit opportunity cost High risks Metal price can go down Yield can be lower Costs can be higher Need returns that merit taking the risk But

5 The fundamental challenge: Mining involves risks, but concession holders must receive compensation Contractors Profit Risk What royalty scheme provides sufficient incentive to make mining worth the risk while maximizing return to nations? World / UN Compensation for lost resources

6 Overall Approach to Analysis Investments Operation Costs Nodule Production Prices Cash Flows Financial Metrics Contractor Net Present Value Rate of Return Owner Net Present Value of Royalty

7 Key Elements of the Analysis Estimating cash flows Revenues Estimated from ProcModel Price projection models Estimated from Expenses Process based cost model Example Only. Not real values

8 Key Elements of the Analysis Quantifying Value to Contractor and UN Revenues Financial Metrics Net Present Value to Owner Net Present Value to Contractor Expenses Example Only. Not real values

9 Analysis Part 1: Process Based Cost Modeling of Nodule Mining Production Variables Planned Capacity Operating Times Accounting Variables Equipment & Factor Prices Equipment Price Wages/Salaries Electricity Price Diesel Price Technical Conditions & Constraints Process Rates Efficiencies Equipment Capacities Physical Requirements Equipment Needs Sizes Quantities # of Workers Power Required Consumables Used CAPEX & OPEX By Process Type By Cost Element

10 Modeling the Mining Process (including transport) Mining Support Vessel Bulk Carrier Processing Plant Estimating Physical Capital Requirements Collectors Riser Systems Platform Process Water System Bulk Carriers Estimating Operational Requirements # of Workers Power Diesel Maintenance Needs Other Assign Monetary Need for Each Physical Item * * Assign Factor Price to Each Operational Need CAPEX OPEX Image from: Marvasti, A. Env. and Resource Econ (2000) 17:

11 Modeling the Refining & Smelting Processes Estimating Physical Capital Requirements Equipment Building Site Preparation Utility Provisions Waste Disposal Assign Monetary Need for Each Physical Item Estimating Operational Requirements # of Workers Power Diesel Maintenance Needs Other * * Assign Factor Price to Each Operational Need Image from minerals llc technology/ CAPEX OPEX

12 Data Types & Sources Production Variables Scenarios (eg. Capacity) Industry Averages (eg. Uptime) Earlier Seabed Mining Studies Technical Variables Physical Relationship (eg. Process Rates) Geophysical Data (eg. Coverage, topology) Engineering Rules of Thumb (eg. Efficiencies) Equipment Prices & Factor Costs Published Price Data Estimates from Similar Industries (eg. Land based Mining) Regional Economic Data Leveraged previous seabed mining studies and related literature whenever possible Reverse engineered inputs from high level results and performed reality checks to validate the approach

13 Analysis Part 2: Price Forecasting Model Developed econometric, time series models (i.e. statistical models) to project future price of Manganese, Nickel, Copper and Cobalt Models generated with extensive historical data: from 40 to 100+ years These price models capture: Long run underlying trends for each commodity Short run price dynamics for each commodity Intertemporal correlation of price shocks between the commodities Statistical models CANNOT capture revolutionary changes in a market Large new sources of supply Changes in future demand (e.g., EVs)

14 Price Forecast Observations Large historic variation for all relevant metals Large uncertainty in future prices Cu, Co, and Ni No statistical trend up or down Mn Statistical indication of upward trend Statistical models CANNOT capture revolutionary changes in a market

15 Modeling Revolutionary Market Changes: Supply Curve Evolution from Opening New Mines Price S1 S2 Mine Openings D1 Q1 Quantity

16 Aggregate Supply Curve Reflect Capacity and Cost of Each Mine Cost Price 1 Individual mines represented by cost and capacity Mines are ordered with increasing costs D1 Price is determined by the intersection of demand with supply Quantity

17 Adding New Mines to Supply Curve Reduces Price Cost Price 1 Price 2 New mines are added according to their initial capacity and cost Inserted into the supply curve at their cost point Results in stretching of the supply curve Demand now intersects supply at a lower price Quantity D1 Effect is most pronounced when demand intersects supply on a steep part of the curve

18 Analysis Part 3: Royalty Schemes Considered Specific Fixed charge per unit extracted Ad Valorum Proportional to extracted value Profit based Proportional to revenues net of costs Risk to the Contractor Risk to the Owner Other issues Two stage introduction lower burden as facility starts up Costs considered in evaluating profit.

19 Example Result HYPOTHETICAL SCENARIO: 1 stage Ad Valorem Return to Contractor Threshold required to invest NPV to UN 0% 1% 2% 3% 4% 5% 6% 7% 8% 9%

20 Next Steps Finish model by end of February Preliminary results: March LTC meeting Contractors Profit Risk Looking for feedback on Costs Risks Royalty schemes World / UN Compensation for lost resources