WO2023272384A1 - System and method for matching an investor to a mineral holding - Google Patents

Abstract

A computer-implemented method is provided for matching an investor with unmined mineral assets in at least one mine site, the method consisting of mineral assets steps and investor steps, which can be in any order in relationship to one another, the mineral asset steps comprising: quantitative and qualitative analysis of minerals in the at least one mine site to provide an objective data set; hierarchical ranking of the at least one mine based on the objective data set to provide an objective hierarchical ranking; predictive modelling of the value of the minerals to provide a predictive model hierarchical ranking; and merging of the objective hierarchical ranking and the predictive model hierarchical ranking to provide a return on investment and a risk assessment of the unmined mineral assets in the at least one mine, the investor steps comprising: conducting a decision tree based on a multiplicity of objective characteristics of the investor to provide an objective classification of the investor; applying predictive modelling to the objective classification to determine an investor risk level and an investment time frame; merging the return on investment and risk assessment of the unmined mineral assets with the investor risk level and investment time frame to match the investor with the unmined mineral assets.

Description

SYSTEM AND METHOD FOR MATCHING AN INVESTOR TO A MINERAL HOLDING

FIELD

The present technology is a system for matching an investor’s level of risk, based on demographics and other investor parameters, to investing in a long-term mineral holding. More specifically, it is a system and method that assesses the value of a mineral holding, the expected growth in value of the mineral holding, the predicted time-frame for the investor to hold the mineral holding and the risk associated with the mineral holding.

BACKGROUND

Minerals have been used for centuries as tradeable currency. A prime example of this is gold. Presently, approximately 30% of the total global gold production is for investment purposes. Other minerals such as copper, titanium, silver, lead, nickel, iron ore, lithium, bauxite, platinum and palladium are other non-limiting examples of valuable minerals.

Mineral-rich ores are mined by the mining company that owns or has a lease to the mineral rights. The minerals are extracted from the ore and are refined, before being sold. Investors may be given opportunities to invest in the mine or to purchase the refined mineral as an investment product. The investor generally relies on an investment brokerage that has ascribed a risk tolerance rating to the investor for such investments.

United States Patent Application Publication No. 20140095409 discloses a web platform for automated investment management services. The platform may enable the automated management of client funds, invested in stocks and other traded assets such as commodities and gold, as well as other traded securities and financial instruments like stock options, stock funds, stock indexes, bonds and structured products. The platform may support customization based on each client's investment profile and policy. Agents may be dynamic and thus may enable the implementation of portfolio strategies that automatically adapt to changes in global financial and stock markets risk, as well as return and currency factors. In some embodiments, the platform may utilize genetic learning algorithms. The platform may support market making and distribution of third-party funds and instruments, as well as an investor community, where clients can provide agents to allow others to co invest. Such a system is focused on the risk assessment of the investor and does not objectively categorize the product to be invested in, unless it is an already traded commodity.

United States Patent Application Publication No. 20100205117 discloses a method, computer system, and computer program product for performing an asset analysis for at least one asset, using the Required Yield Method (RYM). The method provides first economic data relating to a first economy. The economic data includes a gross domestic product (GDP) per capita growth rate for the first economy. The economic data may further include an expected inflation rate for the first economy over a time interval. At least one asset characteristic (e.g. asset valuation) of each asset of the least one asset is computed. The at least one asset characteristic is a function of a portion of the economic data. The computing is in accordance with the RYM. The computed at least one asset characteristic is transferred to a tangible medium. The at least one asset may include an equity index, a bond, gold, a currency, a derivative, etc. Such a system is focused on the asset assessment of the investor and does not objectively categorize the product to be invested in, unless it is an already traded commodity.

What is needed is a computer-implemented categorization system for objectively categorizing a proposed mine site, as well as a recommended decision tree which investors can utilize in order to navigate mineral categories and match their risk level with the potential investment. It would be preferable if objective data were collected at the proposed mine site, including defining the minerals in the ore, the concentration of the minerals in the ore, the ease of mining and extracting the minerals in the ore (quality of the ore) and the cost thereof and the current value of the minerals in the ore. It would then be preferable if the mines sites were hierarchically grouped based on the objective data. It would be preferable if a predictive model was developed based on the objective data, current consumption, current price, predicted consumption and predicted world-wide sources to ascribe a risk value and a return on investment model over time frames relating to short, medium and long term investments. It would be preferable if the system then matched the potential investor with the mineral holding (unmined mine site).

SUMMARY

A computer-implemented categorization system for objectively categorizing a proposed mine site, as well as a recommended decision tree which investors can utilize in order to navigate mineral categories and match their risk level with the potential investment is provided. Objective data are collected at the proposed mine site, including defining the minerals in the ore, the concentration of the minerals in the ore, the ease of mining and extracting the minerals in the ore (quality of the ore) and the cost thereof and the current value of the minerals in the ore. The mines sites are hierarchically ranked based on the objective data. Predictive models based on historical data examine current consumption, current price, predicted consumption and predicted world-wide sources to develop a hierarchical ranking based on the models. By merging the two rankings, a risk value and a return on investment (ROI) model overtime frames relating to short, medium and long term investments can be made for each mine site. The system then matches the potential investor with the mineral holding (unmined mine site).

In one embodiment, a computer-implemented method is provided for matching an investor with unmined mineral assets in at least one mine site, the method consisting of mineral assets steps and investor steps, which can be in any order in relationship to one another, the mineral asset steps comprising: quantitative and qualitative analysis of minerals in the at least one mine site to provide an objective data set; hierarchical ranking of the at least one mine based on the objective data set to provide an objective hierarchical ranking; predictive modelling of the value of the minerals to provide a predictive model hierarchical ranking; and merging of the objective hierarchical ranking and the predictive model hierarchical ranking to provide a return on investment and a risk assessment of the unmined mineral assets in the at least one mine, the investor steps comprising: conducting a decision tree based on a multiplicity of objective characteristics of the investor to provide an objective classification of the investor; applying predictive modelling to the objective classification to determine an investor risk level and an investment time frame; merging the return on investment and risk assessment of the unmined mineral assets with the investor risk level and investment time frame to match the investor with the unmined mineral assets.

The method may further comprise suggesting one or more specific unmined mineral assets.

In the method, the mineral assets may be selected from the group consisting of gold, silver, copper, iron ore, titanium, bauxite, lead, nickel, lithium, platinum and palladium.

In the method, the mineral asset may be gold.

In another embodiment, a non-transitory computer-readable medium storing instructions is provided for matching an investor with unmined mineral assets in at least one mine site that, when executed by one or more computer processors, cause a computing system to perform mineral assets steps and investor steps, which can be in any order in relationship to one another, the mineral asset steps comprising: quantitative and qualitative analysis of minerals in the at least one mine site to provide an objective data set; hierarchical ranking of the at least one mine based on the objective data set to provide an objective hierarchical ranking; predictive modelling of the value of the minerals to provide a predictive model hierarchical ranking; and merging of the objective hierarchical ranking and the predictive model hierarchical ranking to provide a return on investment and a risk assessment of the unmined mineral assets in the at least one mine, the investor steps comprising: conducting a decision tree based on a multiplicity of objective characteristics of the investor to provide an objective classification of the investor; applying predictive modelling to the objective classification to determine an investor risk level and an investment time frame; merging the return on investment and risk assessment of the unmined mineral assets with the investor risk level and investment time frame to match the investor with the unmined mineral assets.

The non-transitory computer-readable medium may further comprise storing instructions for the step of suggesting one or more specific unmined mineral assets.

In the method, the mineral assets may be selected from the group consisting of gold, silver, copper, iron ore, titanium, bauxite, lead, nickel, lithium, platinum and palladium. In the method, the mineral asset may be gold.

In another embodiment, a computing system is provided comprising: one or more computer processors; and memory storing instructions that, when executed by the one or more computer processors, cause the computing system to match an investor with unmined mineral assets in at least one mine site, the matching consisting of mineral assets steps and investor steps, which can be in any order in relationship to one another, the mineral asset steps comprising: quantitative and qualitative analysis of minerals in the at least one mine site to provide an objective data set; hierarchical ranking of the at least one mine based on the objective data set to provide an objective hierarchical ranking; predictive modelling of the value of the minerals to provide a predictive model hierarchical ranking; and merging of the objective hierarchical ranking and the predictive model hierarchical ranking to provide a return on investment and a risk assessment of the unmined mineral assets in the at least one mine, the investor steps comprising: conducting a decision tree based on a multiplicity of objective characteristics of the investor to provide an objective classification of the investor; applying predictive modelling to the objective classification to determine an investor risk level and an investment time frame; merging the return on investment and risk assessment of the unmined mineral assets with the investor risk level and investment time frame to match the investor with the unmined mineral assets.

In the computing system, the matching may further comprise suggesting one or more specific unmined mineral assets.

In the computing system the mineral assets may be selected from the group consisting of gold, silver, copper, iron ore, titanium, bauxite, lead, nickel, lithium, platinum and palladium.

In the computing system, the mineral asset may be gold.

There is also provided a method of trading in minerals. The method involves securing rights to exploit a mine, wherein the mine comprises a predetermined three-dimensional area mapped in three dimensions for unearthed minerals. The method involves dividing the three-dimensional area into a plurality of cubic units corresponding to a predetermined cubic unit of measurement. The method involves labelling for identification purposes each of the cubic units within the three-dimensional area. The method involves calculating the type and amount of the unearthed minerals within each of the cubic units. The method involves recording in a computer database each of the cubic units and the unearthed minerals contained in each of the cubic units. The method involves assigning ownership to each of the cubic units. The method involves brokering trading in the form of purchase or sale of each of the cubic units, with ownership of each of the cubic units being updated.

The rationale behind the above-described method is that an investor wishing to acquire a specific number of grams of a mineral for investment purposes is only concerned that the gold is held at a secure location. With the above-described method, the existence of the mineral is verified, but the mineral is held in the ground. This saves the investor from having to pay for secure storage of the mineral.

BRIEF DESCRIPTION OF THE DRAWINGS

These and other features will become more apparent from the following description in which reference is made to the appended drawings, the drawings are for the purpose of illustration only and are not intended to be in any way limiting, wherein:

FIG. 1 is a flow chart of steps in accordance with the method of collecting objective data of the minerals of interest.

FIG. 2 is a three-dimensional model of mineral mapping.

FIG. 3 is a block diagram showing the steps in predictive modelling of the value of the minerals of interest.

FIG. 4A is a block diagram showing the decision tree for an investor of unmined mineral holdings; Figure 4B is a flow chart showing how selected investors are categorized; and Figure 4C is a block diagram showing the decision tree for each type of investor in Figure 4B regarding a suitable mine in which to invest.

FIG. 5A is a flow chart of how to determine unearthed mineral resources; Figure 5B is a flow chart relating to grid creation. FIG. 6 is a diagram of a two-dimensional grid.

FIG. 7 is a diagram of a three-dimensional grid.

FIG. 8 is a diagram of an expanded three-dimensional grid.

FIG. 9 is a table of a geological report.

FIG. 10 is flow chart of trading in minerals.

FIG. 11 is a schematic diagram of an application programming interface (API).

FIG. 12 is a flow diagram of calculating mine carbon emissions.

FIG. 13 is a schematic diagram illustrating principles behind carbon offsets.

FIG. 14 is a flow diagram of calculating carbon offsets.

DESCRIPTION

Except as otherwise expressly provided, the following rules of interpretation apply to this specification (written description and claims): (a) all words used herein shall be construed to be of such gender or number (singular or plural) as the circumstances require; (b) the singular terms "a", "an", and "the", as used in the specification and the appended claims include plural references unless the context clearly dictates otherwise; (c) the antecedent term "about" applied to a recited range or value denotes an approximation within the deviation in the range or value known or expected in the art from the measurements method; (d) the words "herein", "hereby", "hereof, "hereto", "hereinbefore", and "hereinafter", and words of similar import, refer to this specification in its entirety and not to any particular paragraph, claim or other subdivision, unless otherwise specified; (e) descriptive headings are for convenience only and shall not control or affect the meaning or construction of any part of the specification; and (f) "or" and "any" are not exclusive and "include" and "including" are not limiting. Further, the terms "comprising," "having," "including," and "containing" are to be construed as open-ended terms (i.e. , meaning "including, but not limited to,") unless otherwise noted.

Recitation of ranges of values herein are merely intended to serve as a shorthand method of referring individually to each separate value falling within the range, unless otherwise indicated herein, and each separate value is incorporated into the specification as if it were individually recited herein. Where a specific range of values is provided, it is understood that each intervening value, to the tenth of the unit of the lower limit unless the context clearly dictates otherwise, between the upper and lower limit of that range and any other stated or intervening value in that stated range, is included therein. All smaller sub ranges are also included. The upper and lower limits of these smaller ranges are also included therein, subject to any specifically excluded limit in the stated range.

Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the relevant art. Although any methods and materials similar or equivalent to those described herein can also be used, the acceptable methods and materials are now described.

DEFINITIONS

Computing device - in the context of the present technology, a computing device includes at least one processor, a network adapter, and computer-readable storage media. A computing device may be, for example, a desktop or laptop personal computer, a personal digital assistant (PDA), a smart mobile phone, a server, or any other suitable computing device. A network adapter may be any suitable hardware and/or software to enable the computing device to communicate wired and/or wirelessly with any other suitable computing device over any suitable computing network. The computing network may include wireless access points, switches, routers, gateways, and/or other networking equipment as well as any suitable wired and/or wireless communication medium or media for exchanging data between two or more computers, including the Internet. Computer-readable media may be adapted to store data to be processed and/or instructions to be executed by processor. The processor enables processing of data and execution of instructions. The data and instructions may be stored on the computer-readable storage media.

A computing device may additionally have one or more components and peripherals, including input and output devices. Examples of output devices that can be used to provide a user interface include printers or display screens for visual presentation of output and speakers or other sound generating devices for audible presentation of output. Examples of input devices that can be used for a user interface include keyboards, and pointing devices, such as mice, touch pads, and digitizing tablets.

Communication network - in the context of the present technology a communication network includes but is not limited to a wireless fidelity (Wi-Fi [IEEE 802.11]) network, a light fidelity (Li-Fi) network, a satellite network, the internet, a cellular data network, a local area network (LAN), a wireless local area network (WLAN), or any combination thereof. The network adapter of the computing device communicates via the communication network.

Computer executable instructions - in the context of the present technology, computer executable instructions include software, including as application software, system software, firmware, middleware, embedded code, or any other suitable type of computer code and also may be compiled as executable machine language code or intermediate code.

Computer readable media - in the context of the present technology, computer readable media includes magnetic media such as a hard disk drive, optical media such as a Compact Disk (CD) or a Digital Versatile Disk (DVD), a persistent or non-persistent solid-state memory (e.g., Flash memory, Magnetic RAM, etc.), or any other suitable storage media. Such a computer-readable medium may be implemented in any suitable manner. Computer-readable media is non-transitory and has at least one physical, structural component.

In the description that follows the preferred form of cubic unit will be described as a cubic tonne. It will be understood that this is arbitrary, and any other cubic unit could be used.

In the description that follows the preferred form of unit used to measure the amount of the unearthed minerals is described as being grams or milligrams. It will again be understood that this is arbitrary, and any other convenient unit of measurement could be used.

In some jurisdictions, “carbon credits” are given. Where there is a forest located at a site of the mine, it may be possible to claim such carbon credits with a forest density being used to calculate potential C02 sequestration. DETAILED DESCRIPTION

The first phase of computer-implemented method of the present technology involves exploration of potential mine sites through techniques including geological mapping, geophysical surveys, drilling and geochemical sampling, and geophysical mapping. Once a potential mine site is found, the geographical location of the proposed mine site is identified and the size of the mine site both in two dimensions and three dimensions is determined. The details of size determination include the area of the lease and the depth of the minerals. Depth is determined by drilling, seismic surveys and the like. Core sampling and analysis provides information about the depth of the deposit and the concentration of the mineral of interest in the deposit. Data are stored in the memory of the computer.

Mineral resources have globally recognized geological resource confirmation standards such as: 43-101 (Canada), JORC (Australia), SMAREC (South Africa). These standards are based on a scientific methodology to accurately estimate the amount of mineral resources in the ground and the ability to economically exploit them. Geological modelling software is used to determine the geological resource confirmation. Gold deposits, for example, will have detailed 3-dimensional in the ground deposit models based on exploration activities. An exact location can be ascribed to every gram of the mineral deposit in this 3-dimensional model to a record with a corresponding trade value.

Geological modelling software facilitates the computer-implemented mineral resource estimation which is used to determine and define the ore tonnage and grade of a geological deposit, from the developed block model. There are different estimation methods used for different scenarios dependent upon the ore boundaries, geological deposit geometry, grade variability and the amount of time and money available. A typical resource estimation involves the construction of a geological and resource model with data from various sources. Depending on the nature of the information and whether the data is hard copy or computerized, the principal steps of computer resource estimation are:

Creation, standardization and validation of the database;

Section plotting and interactive geological modelling; Geostatistical analysis; and Block modelling and block estimation.

An orebody model serves as the geological basis of all resource estimation, an orebody modelling project starts with a critical review of existing drill hole and surface or underground sample data as well as maps and plans with current geological interpretation. Drill hole and/or sample databases are set up to suit all the quantitative and qualitative information necessary to build a resource model. The creation of a geological model may include the following steps:

Computer-based 3D orebody modelling;

Sectional, longitudinal, 3D and multi-seam modelling; and Geostatistical analysis, variographic analysis of composite spatial continuity

The initial steps to the objective assessment are shown in the flowchart of Figure 1 :

Step 11 is securing the rights to exploit a mine, wherein the mine comprises a predetermined area that has been mapped for unearthed natural resources, in which the unearthed resources comprise one or more minerals of interest.

Step 12 is mapping in three dimensions the location of the unearthed resources, wherein each three-dimensional area is divided into cubic areas corresponding to a predetermined cubic unit of measurement. In a different embodiment of the technology the predetermined unit of measurement is a cubic tonne.

Step 13 is labelling each predetermined cubic unit.

Step 14 is identifying the type of unearthed mineral of interest within each cubic unit.

Step 15 is measuring the amount of each mineral of interest within each cubic unit. Step 16 is determining the quality of the ore.

Step 17 is hierarchical grouping of mine sites based on their objective data.

FIG. 2 shows a perspective view of a three-dimensional model of a typical mineral deposit which comprises a predetermined area, wherein the predetermined area has been mapped for unearthed natural resources. A typical mineral deposit is explored using various methods such as drilling and seismic. When combined with a geochemical review and labs, a detailed 3-dimensional model of the underground mineral deposit can be created. The geological model will be used as the basis by globally recognized and certified geological certification experts to issue a report on the size of the mineral deposit. Based on these reports and the 3-dimensional model, one will attribute a corresponding trade value to a specific weight and volume of the mineral deposit.

FIG. 3 shows a flow chart showing the steps in computer-implemented predictive modelling of the value of the minerals of interest. Predictive models based on historical data examine current consumption, current price, predicted consumption and predicted world-wide sources to develop a numerical rating for the mine site based on the predictive modelling. A hierarchical ranking is then ascribed to each mine. As a last step, the hierarchical ranking of mine sites based on objective data are merged with hierarchical ranking of mine sites based on predictive modelling are merged. From this, a risk value and a return on investment (ROI) model over time frames relating to short, medium and long term investments can be made for each mine site, noting that sales can only occur through trading as the assets remain in the ground.

As shown in Figures 4A, 4B and 4C a computer-implemented decision tree is developed for potential investors in the unmined mineral holdings for each mine. Figure 4A shows the decision tree for investment using two different investors as an example and selected objective parameters. The demographics of the potential investors are taken into consideration. This includes age, income, effect of a substantial drop in the value of the investment on the investor’s lifestyle, financial transactions, current investments, taxation, death, expenditures, and any other events that may be relevant to determining the risk assessment, on an individual basis. Each branch of the decision tree leads to the next parameter. As shown in Figure 4B predictive model based on historical data for a population of investors representative of the individual investor is then employed. This allows for an estimation of the financial status of the individual investor and their risk assessment over the selected investment time frame. As shown in Figure 4C the system then matches the potential investor with the mineral holding (unmined mine site) and as an example, suggests the mineral or minerals to be bought. Additionally, the size of the holding the investor should purchase and the investment time frame can be determined by the outcome of the processes outlined in Figures 4A-C.

The system of the present technology includes: an aerial vehicle, for example an unmanned aerial vehicle (UAV), equipped with a camera, for example, a video camera, Global Navigation Satellite System (GNSS) receivers for example a Global Positioning System (GPS) receivers, a computing device with a wireless communication transceiver and sensors; analytical equipment to assess the quality of the ore received from core samples; a land-based computing device with a memory, processor and a wireless communication transceiver, wherein the memory is configured to instruct the processor to conduct analysis of data received from the UAV and the analytical devices, to conduct analysis of the mine value, risk and return on investment based on the objective data and predicted data, to conduct analysis of the potential investor profile using decision trees, to arrive at a risk factor for the investor based on predictive modelling of the investor and using a decision tree, match, when possible, the investor with a mine site, mine sites, specific mineral mines and the like. For example, but not limited to, matching a lithium mine with a short term, high risk investor.

Structure and Relationship of Parts:

In one embodiment, a trade value is attached to the geologically certified mineral resource which is then left in the ground for a predetermined amount of time, the currency of the investment can still hold value, but the gold stays in the ground, thus protecting the environment. Additionally, this would help solve other problems related to the global fintech industries and the virtual currency markets, i.e. cryptocurrencies like bitcoin which do not have an underlying basis for value. By fixing a corresponding trade value to a predetermined unit of measurement, i.e. a gram of geologically proven mineral in the ground, it gives a potential value to the virtual currency or token to be based on.

A grid was used on properties that only have Indicated Mineral Resource or an Inferred Mineral Resource. Each property was broken down into a grid of X, Y, and Z coordinates. The X, Y and Z were divided into 1 meter by 1 meter by 1 meter square, which is a cubic meter (m3).

FIG. 5A shows a diagram with a different embodiment of the algorithm of the technology, wherein the algorithm assigns an asset count to a specified cubic area of the land based on the data gathered by the geological modelling software.

Step 51 is the computer running the software with the algorithm of the technology receives the data from the data gathered by the geological modelling software.

Step 52 is the algorithm dividing the area mapped by the geological modelling software by a predetermined cubic size allocating coordinates X, Y, and Z

Step 53 is the algorithm calculating the amount of unearthed resources or assets a predetermined cubic amount of land contains, based on the geological modelling software mapping.

Step 54 is the algorithm sending the amount of unearthed resources or assets a predetermined cubic amount of land contains back to the database.

FIG. 5B shows a flowchart with a different embodiment of the technology describing the process to create a 1 square meter grid on a mine property and assign a value to each unit in that grid.

Step 56: Input the number of acres and convert to Square Kilometres at a ratio of 1 : 0.0040468564224. Round to the nearest meter. This will give you the square Kilometres of the mine. Set this value to S.

Step 57: Find the X, Y coordinates for the property centre of the mine, and place a marker at this location. This is Marker A. Take the Value of the square kilometres of the mine and divide by 2. Assign this value the letter B.

Step 58: Using marker A as a starting location, and ensuing that the map is aligned North place 4 markers on the map as follows:

Marker C: Directly North of Marker A at a distance of Value B Marker D: Directly East of Marker A at a distance of Value B Marker E: Directly South of Marker A at a distance of Value B.

Market F: Directly West of Marker A at a distance of Value B.

Step 59: On the map, draw the following lines:

Line 1 : From Marker C draw a line with a total distance of Value B, that is directly West.

Line 2: From Marker C draw a line with a total distance of Value B, that is directly East.

Line 3: From Market D draw a line with a total distance of Value B, that is directly North.

Line 4: From Market D draw a line with a total distance of Value B, that is directly South.

Line 5: From Marker E draw a line with a total distance of Value B, that is directly West.

Line 6: From Marker E draw a line with a total distance of Value B, that is directly East.

Line 7: From Market F draw a line with a total distance of Value B, that is directly North. Line 8: From Market F draw a line with a total distance of Value B, that is directly South. This will produce a square that represents the Square Kilometres of the property.

Give the upper left corner of the square the value G.

Give the upper right corner of the square the value H.

Give the lower right corner of the square the value I.

Give the lower left corner of the squire the value of J.

Step 510: Divide into Blocks.

Multiply value S by 1e + 6 to get the number of square meters. Give value a label of SM. Starting in the upper left of the grid (G), mark a one meter cube as L1 R1 C1 , directly to the right of L1 R1 C1 , create another meter cube and mark it as L1 R1 C2. Continue this until you reach value H.

After reaching Value H, go back to Cube L1 R1 C1 and mark a one meter cube directly south of it. Name this new cube L1 R2C1.

Step 71 : Depth Calculations.

Once all the square meter blocks have been created, add 3 more layers, named L2, L3, L4 (as shown in FIG. 7).

Step 72: Assign a value to each block.

To assign a gold in grams value to each block, take the total number of blocks (SM ^* 4) and divide by the Indicated Mineral Resource of gold in Grams. The end result will be the creation of a grid that is broken down into square meters, with each square meter having a unique identifier, as well as a gold in grams value (as shown in FIG. 8).

FIG. 6 shows a two-dimensional grid as an example of the process described in FIG. 5, showing an example of a map that is 6 square meters.

FIG. 7 shows a three-dimensional representation of how each block is assigned labels.

FIG. 8 shows a 3-dimensional grid of the second embodiment of the technology where the grid is to be used for properties that have Measured Mineral Resource.

Step 1 : Using the geological map that was generated from the data, a definable mass of gold producing ore will have been identified. Determine the volume of this mass.

Step 2: Using the volume of the mass from step 1 , divide it evenly into square meters. This will create X number of square meter units, referred to as blocks.

Step 3: Give each block a unique identifier that will reference the coordinates and depth of that specific block.

Step 4: Using the Measured Mineral Resource in gold grams, divide into the number of blocks to give each block an AU Grams Value. The result will be a diagram that shows the gold producing ore, broken down into square meters, and each square meter given a unique identifier and a gold in grams value.

FIG. 9 shows a chart table as a representation of the Geological modelling software report described in FIG. 1.

FIG. 10 is a flowchart that shows how the software application operates. The software application can run on one or more devices including the following: a computer, a server, a smart gadget, a mobile phone or similar device.

Following the steps described above on FIG. 8, the method is then paired with a software application for the brokerage of individual assets.

Step 121 accessing the unearthed resources database where the information for individual assets is. To access such information a computer or smart gadget must run the software application and connect to a local or remote server and then access the resources database.

Step 122: View the list of individual assets. Once an individual accesses the resources database, the information is displayed.

Step 123: Select an individual asset, wherein an individual asset has different information to show.

Step 124: Display a list of the individual asset features including the mine location, the X, Y, and Z coordinates, the reference value and the owner of the individual asset. One familiar with the art will appreciate that the individual asset is co-related to a specific natural resource unearthed.

Step 125: Brokering a transaction to sell or buy an individual asset. One can buy that asset or sell an asset to another person via the same application or by connecting to other applications such as banks, online financial portals, cyber currency portals to name a few. Step 126: recording the transaction into the resources database.

FIG. 11 shows how the application software (13100), from the process described in FIG. 10, comprises an application programming interface (API) (13101) that integrates with one or more from the group of external databases (13102), cyber currency (13103), smart contracts (13104), blockchain (13105), financial technology services (13106).

FIG. 12 shows a flowchart describing how the application software calculates the outputs of C02 and other emissions of the mine’s predetermined area if that mine was to be exploited.

Step 141 : Calculating the mine’s emission’s outputs using traditional methodology. The output C02 and other emissions of the mine’s predetermined area can be calculated, as if that mine was to be exploited. There are several well-known technologies and methodologies to make these calculations. The output of a mine includes a mineral, along with outputs of C01 and other emissions. A person familiar with the art will appreciate that the mining industry generates between 1 .9 and 5.1 gigatons of C02 equivalent (C02 e) of GFIG emissions annually. The majority of emissions in this sector originate from fugitive coal-bed methane that is released during coal mining (1.5 to 4.6 gigatons), mainly at underground operations. Power consumption in the mining industry contributes 0.4 gigaton of C02 e. Further down the value chain — what could be considered Scope 3 emissions — the metal industry contributes roughly 4.2 gigatons, mainly through steel and aluminum production. Coal combustion for the power sector contributes up to roughly ten gigatons of C02. Any serious effort to implement the Paris Agreement goals would require a major contribution from the entire value chain. To stay on track for a global 2°C scenario, all sectors would need to reduce C02 emissions from 2010 levels by at least 50 percent by 2050. To limit warming to 1.5°C, a reduction of at least 85 percent would likely be needed. Mining companies’ published emission targets tend to be more modest than that, setting low targets, not setting targets beyond the early 2020s, or focusing on emission intensity rather than absolute numbers. Step 142: Dividing the outputs C02 and other emissions by the total number of individual assets in the unearthed resources database, this way each individual record has a monetary value set by the methodology described above and a “sustainability” metric that generates a value perceived by the owner of the individual asset.

Step 143: Recording at the individual asset entry the corresponding C02 and other emission amounts.

FIG. 13 shows a diagram on how the carbon offset credits work. A carbon offset is a reduction in emissions of carbon dioxide or other greenhouse gases in order to compensate for emissions made elsewhere. Offsets are measured in tonnes of carbon dioxide equivalent (C02e). One tonne of carbon offset represents the reduction of one tonne of carbon dioxide or its equivalent in other greenhouse gases.

FIG. 14 is a flowchart describing how the application software manages the metrics for carbon offset credits equivalents.

Step 161 : Calculating the total C02 sequestration of the mine’s predetermined area to calculate a carbon credit equivalent. A carbon credit is a generic term for any tradable certificate or permit representing the right to emit one tonne of carbon dioxide or the equivalent amount of a different greenhouse gas (tC02e).

Carbon credits and carbon markets are a component of national and international attempts to mitigate the growth in concentrations of greenhouse gases (GFIGs). One carbon credit is equal to one tonne of carbon dioxide, or in some markets, carbon dioxide equivalent gases. Carbon trading is an application of an emissions trading approach. Greenhouse gas emissions are capped and then markets are used to allocate the emissions among the group of regulated sources.

The goal is to allow market mechanisms to drive industrial and commercial processes in the direction of low emissions or less carbon intensive approaches, than those used when there is no cost to emitting carbon dioxide and other GHGs into the atmosphere. Since GHG mitigation projects generate credits, this approach can be used to finance carbon reduction schemes between trading partners and around the world.

Step 162: Dividing the calculated C02 sequestration by the total number of individual assets.

Step 163: Recording the individual asset entry and the corresponding C02 sequestration amounts.

While example embodiments have been described in connection with what is presently considered to be an example of a possible most practical and/or suitable embodiment, it is to be understood that the descriptions are not to be limited to the disclosed embodiments, but on the contrary, is intended to cover various modifications and equivalent arrangements included within the spirit and scope of the example embodiment. Those skilled in the art will recognize or be able to ascertain using no more than routine experimentation, many equivalents to the specific example embodiments specifically described herein.

Claims

1. A computer-implemented method for matching an investor with unmined mineral assets in at least one mine site, the method consisting of mineral assets steps and investor steps, which can be in any order in relationship to one another, the mineral asset steps comprising: quantitative and qualitative analysis of minerals in the at least one mine site to provide an objective data set; hierarchical ranking of the at least one mine based on the objective data set to provide an objective hierarchical ranking; predictive modelling of the value of the minerals to provide a predictive model hierarchical ranking; and merging of the objective hierarchical ranking and the predictive model hierarchical ranking to provide a return on investment and a risk assessment of the unmined mineral assets in the at least one mine, the investor steps comprising: conducting a decision tree based on a multiplicity of objective characteristics of the investor to provide an objective classification of the investor; applying predictive modelling to the objective classification to determine an investor risk level and an investment time frame; merging the return on investment and risk assessment of the unmined mineral assets with the investor risk level and investment time frame to match the investor with the unmined mineral assets.

2. The method of claim 1 , further comprising suggesting one or more specific unmined mineral assets.

3. The method of claim 2, wherein the mineral assets are selected from the group consisting of gold, silver, copper, iron ore, titanium, bauxite, lead, nickel, lithium, platinum and palladium.

4. The method of claim 3, wherein the mineral asset is gold.

5. A non-transitory computer-readable medium storing instructions for matching an investor with unmined mineral assets in at least one mine site that, when executed by one or more computer processors, cause a computing system to perform mineral assets steps and investor steps, which can be in any order in relationship to one another, the mineral asset steps comprising: quantitative and qualitative analysis of minerals in the at least one mine site to provide an objective data set; hierarchical ranking of the at least one mine based on the objective data set to provide an objective hierarchical ranking; predictive modelling of the value of the minerals to provide a predictive model hierarchical ranking; and merging of the objective hierarchical ranking and the predictive model hierarchical ranking to provide a return on investment and a risk assessment of the unmined mineral assets in the at least one mine, the investor steps comprising: conducting a decision tree based on a multiplicity of objective characteristics of the investor to provide an objective classification of the investor; applying predictive modelling to the objective classification to determine an investor risk level and an investment time frame; merging the return on investment and risk assessment of the unmined mineral assets with the investor risk level and investment time frame to match the investor with the unmined mineral assets.

6. The non-transitory computer-readable medium of claim 5, further comprising storing instructions for the step of suggesting one or more specific unmined mineral assets.

7. The method of claim 6, wherein the mineral assets are selected from the group consisting of gold, silver, copper, iron ore, titanium, bauxite, lead, nickel, lithium, platinum and palladium.

8. The method of claim 7, wherein the mineral asset is gold.

9. A computing system comprising: one or more computer processors; and memory storing instructions that, when executed by the one or more computer processors, cause the computing system to match an investor with unmined mineral assets in at least one mine site, the matching consisting of mineral assets steps and investor steps, which can be in any order in relationship to one another, the mineral asset steps comprising: quantitative and qualitative analysis of minerals in the at least one mine site to provide an objective data set; hierarchical ranking of the at least one mine based on the objective data set to provide an objective hierarchical ranking; predictive modelling of the value of the minerals to provide a predictive model hierarchical ranking; and merging of the objective hierarchical ranking and the predictive model hierarchical ranking to provide a return on investment and a risk assessment of the unmined mineral assets in the at least one mine, the investor steps comprising: conducting a decision tree based on a multiplicity of objective characteristics of the investor to provide an objective classification of the investor; applying predictive modelling to the objective classification to determine an investor risk level and an investment time frame; merging the return on investment and risk assessment of the unmined mineral assets with the investor risk level and investment time frame to match the investor with the unmined mineral assets.

10. The computing system of claim 9, wherein the matching further comprises suggesting one or more specific unmined mineral assets.

11. The computing system claim 10, wherein the mineral assets are selected from the group consisting of gold, silver, copper, iron ore, titanium, bauxite, lead, nickel, lithium, platinum and palladium.

12. The computing system of claim 11 , wherein the mineral asset is gold.

13. A method of trading in minerals, comprising: securing rights to exploit a mine, wherein the mine comprises a predetermined three-dimensional area mapped in three dimensions for unearthed minerals; dividing the three-dimensional area into a plurality of cubic units corresponding to a predetermined cubic unit of measurement; labelling for identification purposes each of the cubic units within the three- dimensional area; calculating the type and amount of the unearthed minerals within each of the cubic units; recording in a computer database each of the cubic units and the unearthed minerals contained in each of the cubic units; assigning ownership to each of the cubic units; and brokering trading in the form of purchase or sale of each of the cubic units, with ownership of each of the cubic units being updated.

14. The method of claim 13, wherein the unearthed minerals comprise more than one type of mineral.

15. The method of claim 13, wherein each of the cubic units is a cubic tonne.

16. The method of claim 13, wherein a unit used to measure the amount of the unearthed minerals is selected from one of grams or milligrams.

17. The method of claim 13, wherein there is a forest located at a site of the mine and a forest density is measured to calculate potential C02 sequestration.