Economic evaluation method for deep sea polymetallic nodule mining

Abstract

The invention discloses an economic evaluation method for deep sea polymetallic nodule exploitation, and belongs to the cross technical field of marine resource exploitation and mining industry economic evaluation, and the method comprises the following steps: S1, selecting a processing technology for extracting metal from nodules; s2, calculating economic elements of a metal processor; s3, using the data obtained in the S2 to generate a cash flow table of the metal processor; s4, calculating the noisy purchase price of the target return on investment of the metal processor; s5, calculating economic factors of the tuberculosis collector; s6, using the data obtained in the S5 to generate a cash flow table of the tuberculosis collector; s7, calculating required economic indexes of the tuberculosis acquirers and summarizing economic index simulation results of all the tuberculosis acquirers; and S8, evaluating the economic feasibility of the deep sea polymetallic nodule mining activity scheme. According to the economic evaluation method for deep sea polymetallic nodule exploitation, the uncertainty of metal price fluctuation is effectively captured, and the prediction reliability is improved.

Description

Technical Field

[0001] The present invention relates to the cross-technical field of marine resource exploitation and mining economic evaluation, and in particular to an economic evaluation method for deep-sea polymetallic nodule mining. Background Art

[0002] Deep-sea polymetallic nodules are rich in strategic metals such as cobalt, nickel, copper, and manganese. With increasing global demand for these metals, deep-sea mining is becoming an important way to address resource shortages. However, deep-sea mining projects are time-consuming, require significant investment, and carry a high degree of uncertainty.

[0003] Existing economic evaluation methods often rely on linear extrapolation of historical data or expert judgment, lacking quantitative modeling of long-term mean-reversion and random price fluctuations. This makes forecasts difficult to reflect true market dynamics. Furthermore, traditional methods treat nodule collectors and metal processors as a single entity, ignoring the cost-price linkage inherent in the common exchange of funds between the two. While some literature has attempted to separate mining and smelting, these methods lack a mechanism for inverse price determination. This leads to a disconnect between nodule procurement prices and market selling prices, making it difficult to align with investment return objectives.

[0004] Therefore, a dynamic, multi-scenario economic evaluation method is urgently needed to improve the scientific nature of decision-making and risk controllability of deep-sea mining projects. Summary of the Invention

[0005] The purpose of this invention is to provide an economic evaluation method for deep-sea polymetallic nodule mining, form a closed-loop prediction system, improve prediction reliability, provide a quantitative basis for project pricing and investment decisions, and assist enterprises in predicting profit expectations.

[0006] To achieve the above objectives, the present invention provides an economic evaluation method for deep-sea polymetallic nodule mining, comprising the following steps:

[0007] S1. Select the processing technology for extracting metal from nodules;

[0008] S2. Calculate the economic factors of metal fabricators, including costs, revenues, and expenses;

[0009] S3. Generate a cash flow statement for the metal processor using the data obtained in S2;

[0010] S4. Calculate the nodule purchase price for the metal processor's target return on investment using a discounted cash flow analysis method;

[0011] S5. Calculate the economic factors of nodule collectors, including costs, expenses, and revenues;

[0012] S6. Generate a cash flow statement for the nodule collector using the data obtained in S5;

[0013] S7. Calculate the required economic indicators of nodule collectors using a discounted cash flow analysis method and summarize the simulation results of the economic indicators of all nodule collectors;

[0014] S8. Evaluate the economic feasibility of deep-sea polymetallic nodule mining activities.

[0015] Preferably, S2 specifically includes the following steps:

[0016] S2.1. Calculate the metal fabricator's costs, which include pre-feasibility study costs, feasibility study costs, and initial investment;

[0017] S2.2. Calculate the expenses of metal processors, which include operating expenses, nodule purchase expenses, and tax expenses;

[0018] S2.3. Calculate the income of metal processors. The income of metal processors includes the income from metal sales. The income from metal sales is calculated by "forecasted metal price × metal output".

[0019] Preferably, the cash flow statement of the metal processor in S3 includes year, forecasted metal price, annual metal production, operating expenses, revenue, nodule purchase expenditure, initial investment, pre-tax cash flow, and post-tax cash flow.

[0020] Preferably, in S4, the purchase price of tuberculosis is calculated based on a numerical method, and reverse iteration is performed using the determined internal rate of return (IRR). IRR is the discount rate when the net present value (NPV) of the cash flow statement is equal to zero. The formula for calculating IRR based on NPV is as follows:

[0021]

[0022] Among them, C t is the cash flow in period t, with positive values ​​indicating inflows and negative values ​​indicating outflows; n is the total number of periods in the project; IRR is the discount rate that needs to be solved so that the sum of the present values ​​of all cash flows is zero.

[0023] Preferably, S5 specifically includes the following steps:

[0024] S5.1. Calculate the cost of the nodule collector, which includes the cost of the pre-feasibility study, the feasibility study, and the initial investment.

[0025] S5.2. Calculate the nodule collector's expenses, which include operating expenses, royalties, and corporate taxes;

[0026] S5.3. Calculate the income of nodule collectors. The income of nodule collectors includes the income from the sale of nodules. The income from the sale of nodules is calculated by "nodule sale price × number of nodules sold."

[0027] Preferably, the factors affecting the initial investment in S2.1 are baseline production, primary extraction process investment, refining investment, terminal cost, and production scaling factor;

[0028] The operating expenses in S2.2 include energy costs, consumables costs, labor costs and other costs incurred during the operation of the deep-sea mining project;

[0029] In S2.3, metal prices are predicted using a combination of expert predictions and an autoregressive model. Assuming that the value at the current time point can be obtained by linearly combining the values ​​at previous time points, the basic form of the autoregressive model is:

[0030] y t =c+φ1y t-1 +φ2y t-2 +…+φ p y t-p +ε t ;

[0031] Among them, y t is the current value, y t-1 ,y t-2 ,……,y t-p is the metal price at the previous time point, i.e., the lagged value, φ1, φ2, ..., φ p is the model parameter, ε t is the error term;

[0032] Due to the uncertainty of metal price fluctuations, Monte Carlo simulation is used to generate random samples within a reasonable range based on the current average price of the metal (i.e., the initial price), the long-term expert forecast value (i.e., the long-term price), and the historical change parameter (i.e., the uncertainty parameter). The initial price P0 is set to simulate the future year T. z , divide the time step Δt, and use the mean regression process formula to generate random samples:

[0033]

[0034] Among them, P t is the price in year t, μ is the long-term price, k is the regression speed, which is set based on historical data or expert judgment, σ is the volatility, and ε is a random number that obeys the standard normal distribution N(0,1).

[0035] Preferably, the initial investment in S5.1 includes the investment in the nodule collector, the investment in the nodule lifting system, the investment in the pump, the investment in the buffer zone, the investment in the hose, the investment in the cable, the investment in the mining vessel, the investment in the process water system, the average cost of the berthing point, the basic vessel cost, and the cost of additional systems;

[0036] The royalty expenses in S5.2 are fees paid to the International Seabed Authority, including contract application fees and annual management fees during the exploration period and contract application fees, annual reporting fees and fixed annual fees during the mining period.

[0037] Therefore, the present invention adopts the above-mentioned economic evaluation method for deep-sea polymetallic nodule mining, forms a closed-loop prediction system by analyzing economic activities from mining, metal extraction to market sales, and effectively captures the uncertainty of metal price fluctuations through the comprehensive use of autoregressive analysis and Monte Carlo simulation, thereby improving the reliability of predictions. Through cash flow discounting analysis and reverse solution of internal rate of return, the investment return target and mining cost are directly linked, providing a quantitative basis for project pricing and investment decisions. Through multi-scenario simulation, the probability distribution of project returns is intuitively displayed, assisting enterprises in predicting their expected returns.

[0038] The technical solution of the present invention is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] Figure 1 This is a flow chart of an economic evaluation method for deep-sea polymetallic nodule mining according to the present invention;

[0040] Figure 2 It is a model factor diagram of a metal processor of an economic evaluation method for deep-sea polymetallic nodule mining of the present invention;

[0041] Figure 3 The present invention discloses a method for economic evaluation of deep-sea polymetallic nodule mining and a model factor diagram of nodule collectors. DETAILED DESCRIPTION

[0042] The technical solution of the present invention is further described below with reference to the accompanying drawings and embodiments.

[0043] Unless otherwise defined, technical or scientific terms used in the present invention shall have the same meaning as commonly understood by one of ordinary skill in the art to which the present invention belongs.

[0044] Example 1

[0045] like Figure 1 As shown, the present invention provides an economic evaluation method for deep-sea polymetallic nodule mining, comprising the following steps:

[0046] S1. Select the processing technology for extracting metal from nodules;

[0047] S2. Calculate the economic factors of the metal processor, including costs, revenues, and expenses, and generate a model factor diagram of the metal processor in the economic model, such as Figure 2 As shown; specifically including the following steps:

[0048] S2.1. Calculate the metal fabricator's costs, which include pre-feasibility study costs, feasibility study costs, and initial investment;

[0049] The cost of the pre-feasibility study is calculated using a given percentage; the cost of the feasibility study is calculated using a given percentage; the main factors affecting the initial investment are the baseline production, primary extraction process investment, refining investment, terminal costs, and production scaling factor;

[0050] S2.2. Calculate the expenses of metal processors, which include operating expenses, nodule purchase expenses, and tax expenses;

[0051] Operating expenses include energy costs, consumables costs, labor costs and other expenses incurred during the operation of deep-sea mining projects; tuberculosis procurement expenditures are calculated based on the tuberculosis purchase price and the tuberculosis purchase quantity; tax expenditures refer to taxes paid to the host country.

[0052] S2.3. Calculate the income of metal processors. The income of metal processors includes the income from metal sales. The income from metal sales is calculated by "forecasted metal price × metal output".

[0053] Metal production refers to the amount of each metal that can be recovered from seafloor nodules. This is calculated using the total amount of dry nodules collected, the metals contained in the nodules, the proportion of each metal in the nodules, and the recovery efficiency of each metal. The production of each metal (tons / year) is calculated using the formula:

[0054] Metal production = total dry nodule collection amount × percentage of the metal composition × metal recovery rate;

[0055] Metal prices are predicted using a combination of expert forecasts and an autoregressive model. The parameters of the autoregressive model are derived from changes in historical price data. Assuming that the value at the current time point can be obtained by linearly combining the values ​​at previous time points, the basic form of the autoregressive model is:

[0056] y t =c+φ1y t-1 +φ2y t-2 +…+φ p y t-p +ε t ;

[0057] Among them, y t is the current value, y t-1 ,yt-2 ,……,y t-p is the metal price at the previous time point, i.e., the lagged value, φ1, φ2, ..., φ p is the model parameter, ε t is the error term;

[0058] Due to the uncertainty of metal price fluctuations, Monte Carlo simulation is used to generate random samples within a reasonable range based on the current average price of the metal (initial price), the long-term expert forecast value (long-term price) and the historical change parameter (uncertainty parameter). The initial price P0 is set to simulate the future year T. z , divide the time step Δt, and use the mean regression process formula to generate random samples:

[0059]

[0060] Among them, P t is the price in year t, μ is the long-term price, k is the regression speed, which is set based on historical data or expert judgment, σ is the volatility, and ε is a random number that obeys the standard normal distribution N(0,1).

[0061] S3. Generate a cash flow statement for the metal processor using the data obtained in S2;

[0062] The cash flow statement of a metal processor includes elements such as the year, forecast metal prices, annual metal production, operating expenses, revenue, nodule purchase expenditures, initial investment, pre-tax cash flow, and post-tax cash flow.

[0063] S4. Calculate the nodule purchase price for the metal processor's target return on investment using a discounted cash flow analysis method;

[0064] The purchase price of tuberculosis is calculated based on numerical methods, and reverse iteration is performed using the determined internal rate of return (IRR). IRR is the discount rate when the net present value (NPV) of the cash flow statement is equal to zero. The formula for calculating IRR based on NPV is as follows:

[0065]

[0066] Among them, C t is the cash flow in period t, with positive values ​​indicating inflows and negative values ​​indicating outflows; n is the total number of periods in the project; IRR is the discount rate that needs to be solved so that the sum of the present values ​​of all cash flows is zero.

[0067] The resulting metal fabricator's nodule purchase price is the same as the nodule collector's nodule selling price and will be used to calculate the nodule collector's nodule sale revenue.

[0068] S5. Calculate the economic factors of tuberculosis collectors and generate a model factor diagram of tuberculosis collectors in the economic model, such as Figure 3As shown, including costs, expenses and income; specifically including the following steps:

[0069] S5.1. Calculate the cost of the nodule collector, which includes the cost of the pre-feasibility study, the feasibility study, and the initial investment.

[0070] The cost of the pre-feasibility study is calculated using a given percentage; the cost of the feasibility study is calculated using a given percentage; the initial investment mainly includes the investment in the nodule collector, the investment in the nodule lifting system, the investment in the pump, the investment in the buffer zone, the investment in the hose, the investment in the cable, the investment in the mining vessel, the investment in the process water system, the average cost of the berthing point, the basic vessel cost, and the cost of additional systems;

[0071] S5.2. Calculate the nodule collector's expenses, which include operating expenses, royalties, and corporate taxes;

[0072] Operating expenses include energy costs, consumables costs, labor costs and other expenses incurred during the operation of deep-sea mining projects; royalty expenses are fees paid to the International Seabed Authority, including contract application fees and annual management fees during the exploration period and contract application fees, annual reporting fees and fixed annual fees during the mining period; corporate tax expenses refer to taxes paid to the sponsoring country.

[0073] S5.3. Calculate the income of nodule collectors. The income of nodule collectors includes the income from the sale of nodules. The income from the sale of nodules is calculated by "nodule sale price × number of nodules sold."

[0074] S6. Generate a cash flow statement for the nodule collector using the data obtained in S5;

[0075] S7. Calculate the required economic indicators of nodule collectors using a discounted cash flow analysis method and summarize the simulation results of the economic indicators of all nodule collectors;

[0076] S8. Evaluate the economic feasibility of deep-sea polymetallic nodule mining activities.

[0077] Example 2

[0078] The four metals with significant economic value in deep-sea polymetallic nodules are cobalt (Co), nickel (Ni), copper (Cu), and manganese (Mn), accounting for approximately 30% of the total, far exceeding terrestrial mineral resources. This example selects Co, Ni, Cu, and Mn as target metals, and assumes a 30-year timeframe for deep-sea polymetallic nodule mining activities.

[0079] Taking the ammonia leaching process at a baseline metal recovery rate as an example, assuming the metal processor's initial investment consists of three main components: $969 million for the primary extraction process, $1,050 million for refining, and $52.5 million for terminal costs, the total capital expenditure is $969 + $1,050 + $52.5 million = $2,071.5 million. The pre-feasibility study cost is estimated at 1% of the capital expenditure, or $2,071.5 million x 1% = $21 million. The feasibility study cost is estimated at 5% of the capital expenditure, or $2,071.5 million x 5% = $104 million.

[0080] The specific annual operating expenses are energy costs of US$130 / ton, consumables costs of US$77 / ton, labor costs of US$10 / ton, and other costs of US$1 / ton, which are the operating expenses.

[0081] = 130 + 77 + 10 + 1 = $218 / ton. Based on the annual collection of 3,000,000 tons of dry nodules, operating expenses = 218 x 3,000,000 = $654 million / year. Terminal operating expenses are already included in operating expenses. Assuming the metal processor's nodule purchase price (the nodule collector's selling price) is $J / ton and the nodule purchase quantity is the total dry nodule collection quantity (3,000,000 tons / year), the metal processor's nodule purchase expenditure = $J / ton.

[0082] × 3,000,000 tons = US$3 million. Tax expenses will need to be calculated later using pre-tax cash flow.

[0083] Assuming that 3,000,000 tons of dry nodules are collected annually, the mass percentages of each metal in the dry nodules are Co (0.2%), Ni (1.3%), Cu (1.1%), and Mn (28.4%), and the actual recovery efficiencies of the metals during the refining process are Co (85%), Ni (95%), Cu (90%), and Mn (90%), the recoverable amounts of each metal are obtained as follows:

[0084] Co: 3,000,000 × 0.2% × 85% = 5,100 tons / year

[0085] Ni: 3,000,000 × 1.3% × 95% = 37,050 tons / year

[0086] Cu: 3,000,000 × 1.1% × 90% = 29,700 tons / year

[0087] Mn: 3,000,000 × 28.4% × 90% = 766,800 tons / year

[0088] Assuming initial prices of $38,000 / ton for Co, $10,800 / ton for Ni, $5,600 / ton for Cu, and $450 / ton for Mn, a combination of an autoregressive model and expert forecasts yields long-term prices of $55,000 / ton for Co, $24,717 / ton for Ni, $7,000 / ton for Cu, and $450 / ton for Mn. Uncertainty parameters are $3,000 / ton for Co, $800 / ton for Ni, $500 / ton for Cu, and $50 / ton for Mn.

[0089] Taking the price prediction parameters of Co as an example, set P0 = 38,000 US dollars / ton and determine the total number of time steps N = T z / Δt=30. Generate an independent standard normal random number ε for each time step, and gradually update the price according to the discretization formula to ensure that the price returns to the long-term mean during fluctuations. For example, in the first year (assuming k is 0.2 and ε is 0.5):

[0090] P1 = 38,000 + 0.2 × (55,000 - 38,000) × 1 + 3,000 × 1 × 0.5 = US$42,900 / ton.

[0091] By the same token, Ni: P1 = 10,800 + 0.2 × (24,717 - 10,800) × 1 + 800 × 1 × 0.5 = 13,983 USD / ton (assuming k is 0.2 and ε is 0.5).

[0092] Cu: P1 = 5,600 + 0.2 × (7,000-5,600) × 1 + 500 × 1 × 0.5 = 6,130 USD / ton (

[0093] Set k to 0.2 and ε to 0.5).

[0094] Mn: P1 = 450 + 0.2 × (450 - 450) × 1 + 50 × 1 × 0.5 = 475 USD / ton (assuming k is 0.2 and ε is 0.5).

[0095] The simulation was performed 1,000 times to generate a large amount of random data for subsequent calculations, covering different random scenarios.

[0096] The cash flow statement of a metal processor is organized horizontally with the year as the horizontal column and vertically with elements such as the forecast metal price, annual metal production, operating expenses, revenue, nodule purchase expenditure, initial investment, pre-tax cash flow, and after-tax cash flow.

[0097] In Year 0, a metal processor invests $2,071.5 million upfront. At this point, no production has commenced and no taxes have been incurred. Therefore, the projected metal price, annual metal production, operating expenses, and revenue are all zero, resulting in both pre-tax and after-tax cash flows of -$2,071.5 million. Years 1 to 30 are the operational phase, during which the initial investment is zero. The fixed parameters are annual metal production (5,100 tons / year for Co, 37,050 tons / year for Ni, 29,700 tons / year for Cu, and 766,800 tons / year for Mn) and operating expenses ($654 million / year). The variable parameter is the projected metal price. For example, in Year 1, the projected price for Co is $42,900 / ton, for Ni is $13,983 / ton, for Cu is $6,130 / ton, and for Mn is $475 / ton.

[0098] Year 1 Revenue = $42,900 / ton x 5,100 tons + $13,983 / ton x 37,050 tons + $6,130 / ton x 29,700 tons + $475 / ton x 766,800 tons = $1,283 million. Pre-tax cash flow is the net result after deducting revenue from expenses. For example, Year 1 Pre-tax Cash Flow = $1,283 million - $654 million - $3J million = $629 - $3J million. Post-tax cash flow is the net cash flow after deducting income taxes. In this example, the typical corporate income tax rate is 25%. So, Year 1 Post-tax Cash Flow = $629 - $3J million x (1 - 25%) = $472 - $2.25 million. The cash flows for Years 2-30 are calculated using the same principles as above.

[0099] Assume that the metal fabricator expects an 18% return on investment (IRR = 18%). Starting with the current assumed nodule purchase price variable, J, the algorithm gradually adjusts the value, repeatedly calculating until the result approaches 18%. When the value is sufficiently close (within an acceptable error range), the iteration stops and the current value of J is returned.

[0100] Assume nodule collector capital expenditures of $80 million and annual operating expenses of $15.6 million. Nodule lifting system capital expenditures of $429 million and annual operating expenses of $78.8 million. Mining vessel capital expenditures of $900 million and annual operating expenses of $193.7 million. Process water system capital expenditures of $123 million and annual operating expenses of $17.5 million. Environmental monitoring activities capital expenditures of $6 million and annual operating expenses of $20 million. Nodule transportation activities capital expenditures of $105 million and annual operating expenses of $57.9 million. The nodule collector's upfront investment is calculated as follows: $80 + $429 + $900 + $123 + $6 + $105 = $1,643 million. Annual operating expenses are calculated as follows: $15.6 + $78.8 + $193.7 + $17.5 + $20 + $57.9 = $383.5 million. Pre-feasibility study costs are calculated as follows: $1,643 million × 1% = $16 million. Since environmental monitoring costs incurred during exploration need to be allocated to the feasibility study, feasibility study costs are calculated as follows: $1,643 million × 5% + T2 × $20 million = $182 million.

[0101] Assume that the nodule collector pays the International Seabed Authority a royalty of $1.1 million per year. Based on the above, the nodule collector's nodule sales revenue = $J per ton x 3,000,000 tons = $3J million. Similar to metal processors, the typical corporate income tax rate for nodule collectors is 25%, and tax expenses must be calculated later using pre-tax cash flow.

[0102] The above logic also allows us to derive a cash flow statement for the nodule collector. This cash flow statement is organized horizontally with year as the column, and vertically with elements such as nodule sales price, annual nodule production, operating expenses, revenue, royalties, upfront investment, pre-tax cash flow, and post-tax cash flow. The IRR (Income Tax Rate) is selected as the core metric for the economic evaluation of deep-sea polymetallic nodule mining activities. The IRR for the nodule collector, calculated using 1,000 simulations, ranges from 13.15% to 22.30%. The nodule collector's target return on investment is 18%, which is at the 45th percentile within this range. This means that the probability of achieving the nodule collector's investment expectations in this example is 55%.

[0103] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit the same. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that they can still modify or replace the technical solutions of the present invention with equivalents, and these modifications or equivalent replacements cannot cause the modified technical solutions to deviate from the spirit and scope of the technical solutions of the present invention.

Claims

1. An economic evaluation method for deep-sea polymetallic nodule mining, characterized by: The following steps are involved: S1. Select the processing technology for extracting metal from nodules; S2. Calculate the economic factors of metal fabricators, including costs, revenues, and expenses; S3. Generate a cash flow statement for the metal processor using the data obtained in S2; S4. Calculate the nodule purchase price for the metal processor's target return on investment using a discounted cash flow analysis method; S5. Calculate the economic factors of nodule collectors, including costs, expenses, and revenues; S6. Generate a cash flow statement for the nodule collector using the data obtained in S5; S7. Calculate the required economic indicators of nodule collectors using a discounted cash flow analysis method and summarize the simulation results of the economic indicators of all nodule collectors; S8. Evaluate the economic feasibility of deep-sea polymetallic nodule mining activities.

2. The economic evaluation method for deep-sea polymetallic nodule mining according to claim 1, characterized in that: S2 specifically includes the following steps: S2.

1. Calculate the metal fabricator's costs, which include pre-feasibility study costs, feasibility study costs, and initial investment; S2.

2. Calculate the expenses of metal processors, which include operating expenses, nodule purchase expenses, and tax expenses; S2.

3. Calculate the income of metal processors. The income of metal processors includes the income from metal sales. The income from metal sales is calculated by "forecasted metal price × metal output".

3. The economic evaluation method for deep-sea polymetallic nodule mining according to claim 1, characterized in that: The cash flow statement of metal processors in S3 includes the year, forecast metal price, annual metal production, operating expenses, revenue, nodule purchase expenditure, upfront investment, pre-tax cash flow, and post-tax cash flow.

4. The economic evaluation method for deep-sea polymetallic nodule mining according to claim 1, characterized in that: In S4, the purchase price of tuberculosis is calculated based on a numerical method, and reverse iteration is performed using the determined internal rate of return (IRR). IRR is the discount rate when the net present value (NPV) of the cash flow statement is equal to zero. The formula for calculating IRR based on NPV is as follows: Among them, C t is the cash flow in period t, with positive values ​​indicating inflows and negative values ​​indicating outflows; n is the total number of periods in the project; IRR is the discount rate that needs to be solved so that the sum of the present values ​​of all cash flows is zero.

5. The economic evaluation method for deep-sea polymetallic nodule mining according to claim 1, characterized in that: S5 specifically includes the following steps: S5.

1. Calculate the cost of the nodule collector, which includes the cost of the pre-feasibility study, the feasibility study, and the initial investment. S5.

2. Calculate the nodule collector's expenses, which include operating expenses, royalties, and corporate taxes; S5.

3. Calculate the income of nodule collectors. The income of nodule collectors includes the income from the sale of nodules. The income from the sale of nodules is calculated as "nodule sale price × nodule sale quantity." 6. The economic evaluation method for deep-sea polymetallic nodule mining according to claim 2, characterized in that: The factors affecting the initial investment in S2.1 are baseline production, primary extraction process investment, refining investment, terminal costs, and production scaling factor; The operating expenses in S2.2 include energy costs, consumables costs, labor costs and other costs incurred during the operation of the deep-sea mining project; In S2.3, expert forecasting and autoregressive model are used to comprehensively predict metal prices. Assuming that the value at the current time point can be obtained by linearly combining the values ​​at previous time points, the basic form of the autoregressive model is: y t =c+φ1y t-1 +φ2y t-2 +…+φ p y t-p +e t ; Among them, y t is the current metal price, i.e., the current value, y t-1 ,y t-2 ,……,y t-p is the metal price at the previous time point, i.e., the lagged value, φ1, φ2, ..., φ p is the model parameter, ε t is the error term; Due to the uncertainty of metal price fluctuations, Monte Carlo simulation is used to generate random samples within a reasonable range based on the current average price of the metal (i.e., the initial price), the long-term expert forecast value (i.e., the long-term price), and the historical change parameter (i.e., the uncertainty parameter). The initial price P0 is set to simulate the future year T. z , divide the time step Δt, and use the mean regression process formula to generate random samples: Among them, P t is the price in year t, μ is the long-term price, k is the regression speed, which is set based on historical data or expert judgment, σ is the volatility, and ε is a random number that obeys the standard normal distribution N(0,1).

7. The economic evaluation method for deep-sea polymetallic nodule mining according to claim 5, characterized in that: The initial investment in S5.1 includes the investment in nodule collectors, nodule lifting systems, pumps, buffer zones, hoses, cables, mining vessels, process water systems, average berthing point costs, basic vessel costs, and additional system costs; The royalty expenses in S5.2 are fees paid to the International Seabed Authority, including contract application fees and annual management fees during the exploration period and contract application fees, annual reporting fees and fixed annual fees during the mining period.

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