NL2028671B1 - Quantitative Evaluation Method for Seamount Cobalt-rich Crusts Resource - Google Patents

Quantitative Evaluation Method for Seamount Cobalt-rich Crusts Resource Download PDF

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NL2028671B1
NL2028671B1 NL2028671A NL2028671A NL2028671B1 NL 2028671 B1 NL2028671 B1 NL 2028671B1 NL 2028671 A NL2028671 A NL 2028671A NL 2028671 A NL2028671 A NL 2028671A NL 2028671 B1 NL2028671 B1 NL 2028671B1
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crust
slope
cobalt
seamount
grid
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NL2028671A
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Du Dewen
Yang Fengli
Yang Gang
Yan Shijuan
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Pilot Nat Laboratory For Marine Science And Technolgoy Qingdao
The First Inst Of Oceanography Mnr
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Abstract

The present invention relates to the field of ocean mineral resource research and development, and provides a quantitative evaluation method for a seamount cobalt-rich crusts resource. The method comprises the following steps: 81. dividing a target seamount slope into a plurality of adjacent grid units; 82. according to the geological station survey data, taking the grid units as objects, obtaining seamount cobalt-rich crusts resource parameters of various grid units by spatial interpolation calculation, wherein the seamount cobalt-rich crusts resource parameters comprise a crust thickness, a crust water ratio, a crust wet density, a crust coverage rate, a metal concentration and the like; meanwhile, extracting seamount slope mineralization characteristics of the various grid units according to the regional survey data, wherein the seamount slope mineralization characteristics comprise a macroscopic crust coverage rate, a ratio of slope suitable for mineral distribution, a slope surface area, and the like; 83. calculating resource quantities of the various grid units; and 84. delineating key areas and resource quantities thereof according to the sorting and combination of the resource quantities of the various grid units. The present invention achieves a quantitative evaluation of seamount cobalt-rich crusts resources.

Description

Quantitative Evaluation Method for Seamount Cobalt-rich Crusts Resource
TECHNICAL FIELD The present invention belongs to the field of ocean mineral resource research and development, and particularly relates to a quantitative evaluation method for a seamount cobalt-rich crusts resource.
BACKGROUND Tens of thousands of underwater seamounts spread across the world's oceans. Some metal oxide crusts rich in various strategic and key metals are attached to the surface of these seamounts, and are commonly called cobalt- rich crusts. Under the organization of the International Seabed Authority, many countries in the world, as pioneer investors, have been granted the mineral survey and delineation rights in relevant seamount areas, i.e. a right to survey and identify the ore-rich areas and their resource quantities, and delineate the scope of future resource rights and interests. To achieve these goals, a quantitative evaluation of the seamount cobalt-rich crusts resources is necessary. However, there is a lack of systematic and comprehensive quantitative evaluation methods for seamount cobalt-rich crusts resources at home and abroad. In China, the geostatistical method was applied earlier to analyze and estimate polymetallic nodule resources, the Kriging method was used to calculate nodule resources in the Pacific CC area within the China’s pioneer area, the image recognition and processing technology was used to estimate nodule abundance and coverage rate according to seabed photos, the artificial neural network technology was used to calculate polymetallic nodule abundance value, the fractal theory was used to estimate nodule distribution characteristics, the collaborative regionalization theory and collaborative Kriging method for mineral resources evaluation were used to evaluate the mineral resources in the western area of CC area in the eastern Pacific Ocean, the weight of evidence and posterior probability interval were used to divide the favorable areas for mineralization, and the linear regression method was used to estimate the polymetallic nodule resources in CC area and its surrounding areas in the Pacific Ocean. These resource evaluation methods are mainly applicable to polymetallic crusts in suboceanic basins.
In the evaluation of cobalt-rich crusts resource, some people have combined the nearest regional method with the geological block method to comprehensively evaluate and analyze the seamount crusts resources in the East Pacific Ocean; some people have extracted evaluation parameters and evaluation methods on the basis of studying the metallogenic background and distribution law of cobalt-rich crusts; some people have studied the spatial distribution and resource quantity of cobalt-rich crusts resources according to the fractal theory; some people have discussed and compared several main methods for evaluating cobalt-rich crusts resource at present; and some people have put forward eight parameter indexes beneficial to delineation of cobalt crust mining area and resource evaluation, on the basis of in-depth study and analysis of the thickness and abundance of cobalt crusts in seamounts of the western Pacific Ocean. Although these technologies are all relevant, there is a lack of comprehensive and systematic technical methods at present.
To sum up, the prior art has the following shortcomings: (1) the average value is calculated based on the observation of survey data, which lacks the analysis of spatial autocorrelation; the traditional Kriging method is ineffective as the seamount spatial data is not controlled by the direction; (2) moreover, the resource parameters involved in the prior art, such as the coverage rate of cobalt-rich crusts, are only suitable for local observation, but not for regional calculation and analysis; (3) previous resource evaluation is based more on the natural state of cobalt-rich crust, without considering its exploitable state; not all slopes covered by cobalt-rich crusts are suitable for mining, for example, a slope above 15 degrees is difficult to support underwater mechanical operation; (4) the estimation method of a seamount slope area is relatively rough; and (5) some processes of traditional methods are based on manual judgment, and cannot achieve a whole process calculation. The obstructing function of an uitra-thick water layer, the limitation of survey technology and the high survey cost make it greatly difficult for mankind to find out the spatial distribution of deep-sea mineral resources and estimate their resource quantities. Therefore, an effective, systematic and comprehensive quantitative evaluation technology for a seamount mineral resource will bring great benefits.
SUMMARY In order to meet the actual needs of research and development of seamount cobalt-rich crusts resource, the present invention overcomes the shortcomings of the prior art, and the technical problem to be solved is a quantitative evaluation method for a seamount cobalt-rich crusts resource. In order to solve the above technical problems, the technical solution adopted by the present invention is a quantitative evaluation method for a seamount cobalt-rich crusts resource, wherein the method includes the following steps: S1. dividing a target seamount slope into a plurality of grid units with the same area at intervals of equal length and width; S2. obtaining seamount cobalt-rich crusts resource parameters of various grid units by spatial interpolation calculation according to the geological station survey data, wherein the seamount cobalt-rich crusts resource parameters include a crust thickness, a crust water ratio, a crust wet density, a crust coverage rate, a metal concentration and the like; meanwhile, taking the grid units as objects, extracting seamount slope mineralization characteristics according to the regional survey data of water depth, wherein the seamount slope mineralization characteristics include a macroscopic crust coverage rate, a ratio of slope suitable for mineral distribution, a slope surface fitting area, and the like; S3. obtaining resource quantities of the various grid units through a joint calculation of the seamount cobalt-rich crusts resource parameters and various seamount slope mineralization characteristic parameters; and S4. sorting the grid units according to the resource quantities thereof, selecting the grid units with large adjacent resources, delineating key areas of cobalt-rich crusts resources and giving resource quantities thereof.
The grid unit is a square area of 1-20 square kilometers.
In the step S2, the geological station survey data are obtained by sampling survey, and the specific method is as follows: geological sampling points are arranged on a seamount slope according to the set distribution density, rock or ore samples are obtained at the sampling points by various mechanical methods, and then geological station samples are tested and analyzed in a laboratory to obtain geological station data; wherein the regional survey data of water depth refers to the data of full coverage or lateral coverage obtained by 5 geophysical means.
In the step S2, when calculating the seamount cobalt-rich crusts resource parameters of the various grid units, a spatial interpolation method is adopted to interpolate geological sampling station data into the various grid units.
The spatial interpolation method is a grid moving average method or a Kriging method. In the step S2, the calculation formula of the macroscopic crust coverage rate is as follows: Recover; = Nae, 19094 where, Rcoveri represents a macroscopic crust coverage rate of an i" grid unit, Ni represents a total number of water depth points or water depth grid nodes in the i" grid unit, g represents a slope gradient of water depth point or data grid node, Qmin and gmax respectively represent a minimum slope suitable for the development of cobalt-rich crusts and a maximum slope suitable for underwater mechanical mining operation; the calculation formula of the ratio of slope suitable for mineral distribution is as follows: Rslope, = “hE Em Seman) 1 00% where, Rslope; represents a ratio of slope suitable for mineral distribution of an in grid unit; the slope surface fitting area is calculated as follows: the 3D spatial surface area of a minimum grid is calculated according to the minimum grid of gridded multi-beam bathymetric survey data, then the 3D spatial surface area of all the minimum data grids in a grid unit i is accumulated, and a slope surface fitting area of the grid unit is obtained by fitting calculation.
(In a case on ME guyot: the minimum slope gm. suitable for the development of a cobalt-rich crust is 4.8°, and the maximum slope gmax suitable for underwater mechanical mining operation is 15°) In the step S4, the calculation formula of the resource quantity of a grid unit is as follows: Owet(ton)=Areai{km2)xCoverage; (%)xThicknessi(cm)xDensity(g/'cm®)xRcover;(%)x 10% Osuiti(ton)=Areai(km?)x Coveragei (%)}xThicknessi{cm)xDensity:(g/cm3}xRslopei{%)x 104; DOi{ton)= Oweti{ton)x[1-Water ratioi(%)]; DOsuiti{ton)=Osuit(ton)x[1-Water ratio %)]; Metai(ton)=DOi(ton)xConcentrationi(%); Msuiti(ton)=DOsuiti{ton)xConcentrationi(%); where, Owet; represents a wet crust tonnage of a grid unit i, Osuit represents a recoverable wet crust tonnage of the grid unit i, Area; represents a slope surface area of the grid unit i, Coverage; represents a crust coverage rate of an i" grid unit, Thickness; represents a crust thickness of the i" grid unit, Density; represents a crust wet density of the i" grid unit, Recover; indicates a macroscopic crust coverage rate of the it" grid unit, Rslope; represents a ratio of slope suitable for mineral distribution of the i" grid unit, DO; and DOsuit; respectively represent the tonnage of dry crust and recoverable dry crust of the it" grid unit, Metal; represents a metal tonnage of the i" grid unit, Msuit represents a recoverable metal tonnage of the i" grid unit, Water ratio; represents a crust water ratio of the i" grid unit, and Concentration; represents the metal concentration of the i" grid unit.
Compared with the prior art, the present invention has the following advantageous effects:
1. In the present invention, a target seamount slope is divided into a plurality of grid units, the seamount cobalt-rich crusts resource parameters of various grid units are obtained by spatial interpolation calculation according to the geological station survey data, the seamount slope mineralization characteristics of the various grid units are calculated and extracted according to the seamount regional survey data, the resource quantities of the various grid units are calculated by combining the seamount cobalt-rich crusts resource parameters and mineralization characteristics of the various grid units, and finally, according to the resource quantity sorting and spatial combination of the various grid units, the key areas are delineated to finally achieve quantitative evaluation of seamount cobalt-rich crusts resources.
2. In the present invention, the seamount slope mineralization characteristics include a macroscopic crust coverage rate, a ratio of slope suitable for mineral distribution, a slope surface area and the like, which are an innovative part of the art. The macroscopic crust coverage rate may eliminate local areas not suitable for resource distribution; and the ratio of slope suitable for mineral distribution is intended to quantify the tonnage of wet crusts resources, delineate a slope area more suitable for future mining, avoid the contradiction between large mineral reserves and small workable reserves, and improve the quantitative evaluation accuracy of crusts resources. In addition, according to the present invention, the minimum grid of water depth data are used to fit and calculate the slope surface area, which greatly improves the estimation accuracy of the slope surface area, determines the resource quantities, accurately estimates the slope surface area, and improves the estimation accuracy of resource quantities.
3. In the present invention, the spatial interpolation method is used to interpolate geological station data into various grid units, which may save the survey cost; and the interpolation method may be a grid moving average method and a Kriging method. The Kriging method is suitable for spatial interpolation of seamount slope, and may solve the spatial autocorrelation of seamount resources.
BRIEF DESCRIPTION OF THE FIGURES Fig.l is a graphical summary of quantitative evaluation of a seamount cobalt-rich crust obtained by the application of the present invention, of which Fig1 (a) is a spatial interpolation result of a cobalt-rich crust thickness, Fig.1(b) is a fitting area result of a slope surface area, Fig.1(c) is a macroscopic crust coverage rate of a cobalt-rich crust, Fig.1(d) is the spatial distribution of geological survey stations and resource parameter value points of cobalt-rich crusts, Fig.1(e) shows resource quantities of various grid units, Fig.1(f) is a sorting result of the resource quantity of various grid units, and Fig.1(g) shows delineated key areas.
DESCRIPTION OF THE INVENTION To make more clearly the technical solution and advantages of the present invention, the technical solution of the present invention will be described clearly and completely with reference to specific embodiments and accompanying drawings. Other applications based on the technology of the present invention, as well as applications implemented by those skilled in the art applying the technology without authorization, shall fall within the scope of protection of the present invention.
The present invention provides a quantitative evaluation method for a seamount cobalt-rich crusts resource, which includes the following steps: S1. dividing a target seamount slope into a plurality of adjacent grid units with the same area at intervals of equal length and width; In an embodiment of the present invention, for the target seamount slope, a unit is defined by a sub-area with a certain area and shape, for example, a square area of 1, 4 or 20 square kilometers; generally, the unit is divided into grids, so the unit is also called a grid unit. In dividing grid units, there should be enough regional survey data such as enough terrain data in each unit. If the grid accuracy of multi-beam topographic survey data is 100 m x 100 m, there are 400 water depth data distributed in the grid unit with an area of 4 km?2. In this embodiment, interpolation of cobalt-rich crusts resource parameters, extraction of slope mineralization characteristics, calculation of ore reserves and other operations are all performed on the basis of various grid units.
S2. according to the geological station survey data, taking the grid units as objects, obtaining seamount cobalt-rich crusts resource parameters of various grid units by interpolation calculation, wherein the seamount cobalt-rich crusts resource parameters include a crust thickness, a crust water ratio, a crust wet density, a crust coverage rate, a metal concentration and the like; meanwhile, extracting seamount slope mineralization characteristics of the various grid units according to the regional survey data, wherein the seamount slope mineralization characteristics include a macroscopic crust coverage rate, a ratio of slope suitable for mineral distribution, a slope surface area, and the like; (1) Geological station survey data and ore resource parameters The geological sampling points are arranged on a seamount slope according to a certain distribution density, and rock or ore samples are obtained at these sampling points by various mechanical methods. These geological station samples are tested and analyzed in a laboratory to obtain geological station data. The measurement data of ore samples, such as a cobalt-rich crust density, a crust thickness, a water ratio, a concentration of certain metal, a crust coverage rate and the like, are all called ore resource parameters, and have the characteristics of sampling investigation.
In this embodiment, geological station sampling data is a cost-effective sampling survey method. Not every grid unit is distributed with geological stations, so the spatial interpolation method should be used to interpolate geological station data into various grid units. There are many interpolation methods, for example, a grid moving average method and a Kriging method.
See the paper Dewen Du“, Chunjuan Wang, Xiaomeng Du, Shijuan Yan, Xiangwen Ren, Xuefa Shi, Hein J .(2017b) Distance-Gradient-Based Variogram and Kriging to Evaluate Cobalt-Rich Crust Deposits on Seamounts. Ore Geology Reviews, 2017, (84):218-227. DOI:10.1018/ j .oregeorev .2016 .12 .028 and the paper Dewen DuKriging Interpolation for
Evaluating the Mineral Resources of Cobalt-Rich Crusts on Magellan Seamounts. Minerals 2018, 8 ,374; doi:10 .3390/min8090374. The Kriging method is suitable for spatial interpolation of seamount slope and can be found in a Patent Application 2016 1 0130598 .5. In this embodiment, the Kriging method may be preferably used to achieve the interpolation of seamount cobalt- rich crusts resource parameters of all grid units. Of course, according to the present invention, the traditional spatial interpolation method may also be used to obtain the seamount cobalt-rich crusts resource parameters of various grid units.
(2) Regional survey data: compared with the geological station survey data, the regional survey data refers to the data of full coverage or lateral coverage obtained by geophysical means, such as multi-beam side-scan sonar sounding data, gravity and magnetic data with the characteristics of wide coverage area and large amount of data. In this embodiment, the regional features extracted from regional data that are beneficial to mineralization are called mineralization features, such as a "macroscopic crust coverage rate", a "ratio of slope suitable for mineral distribution", a “fitting slope surface area", and the like. These data have the regional coverage characteristics.
2.1 Concept and algorithm of macroscopic crust coverage rate and ratio of slope suitable for mineral distribution of seamount cobalt-rich crust If the seamount slope gradient is too small, for example, less than 4.8°, it will be covered by loose sediments, and the slope larger than a certain slope gradient threshold is suitable for the growth of cobalt-rich crust. The proportion of the slope suitable for the growth of cobalt-rich crust in the grid unit area is considered a macroscopic crust coverage rate of cobalt-rich crust.
A too large slope gradient, e.g. 15°, is not conducive to the mining operation of mining machines in underwater environment.
A slope suitable for mineral distribution falls within a suitable range, e.g. 4.8-15°. The proportion of the slope in the grid unit area is called a slope rate suitable for mineral distribution.
It is assumed that many water depth data are distributed in a grid unit i, a slope gradient g of every water depth point or grid node may be jointly estimated according to a surrounding water depth, gmin and gmax are a minimum slope suitable for the development of cobalt-rich crust and a maximum slope suitable for underwater mechanical mining operation.
Then Ni{gmin<g<gmax) is the number of bathymetric points or bathymetric grid nodes in a unit i that are suitable for mineralization, and Ni(gmin<g) is the number of bathymetric points or bathymetric grid nodes in the unit i where the slope gradient is greater than the minimum slope suitable for the development of cobalt-rich crust, and is greater than the total number of Ni when it is bathymetric points or bathymetric grid nodes in unit i.
The ratio of slope suitable for mineral distribution may be calculated by the following formula:
Rslope, = ~\Snin 90 Ena) x 100%: CD Similarly, the macroscopic crust coverage rate may be calculated by the following formula: Reover; = “Ely 100%; (2)
i where, Rcoveri represents a macroscopic crust coverage rate of an i" grid unit, Ni represents a total number of water depth points or water depth grid nodes in the i" grid unit, g represents a slope gradient, gmin and gmex respectively represent a minimum slope suitable for the development of cobalt- rich crust and a maximum slope suitable for underwater mechanical mining operation, and Rslopei represents a ratio of slope suitable for mineral distribution of the i" grid unit. The two slope gradient thresholds suitable for mineral distribution are variable values. Different seamounts may have different values. More accurate slope suitable for mineral distribution may be found with the innovation of investigation technology, and there may be more slopes suitable for mineral distribution with the improvement of mining technology.
2.2 Slope surface area fitting concept and algorithm Slope area is one of the important parameters for calculating ore reserves, and an accurate fit of slope area is an important prerequisite for accurate estimation of ore reserves. The slope area is usually estimated by the quotient of the horizontal projection area of the unit area divided by the cosine of the average gradient of the slope. In an embodiment of the present invention, the following method is used: the 3D spatial surface area product of the minimum grid is calculated according to the minimum grid of gridded multi-beam bathymetric survey data, and then all minimum grid marks in the grid unit i are accumulated to obtain Area.
In this embodiment, the mineral resources parameters of geological stations obtained by geological sampling may be used for spatial interpolation of grid units to estimate the mineral resources parameters of various grid units. The mineralization characteristics of the various grid units (i.e., a ratio of slope suitable for mineral distribution, a macroscopic crust coverage rate and a slope surface area and the like) may be extracted according to the regional survey data in the grid unit.
In this way, mineral resources parameters and mineralization characteristics are fused together by grid units.
S3. obtaining resource quantities of the grid units through a joint calculation of eight parameters including a seamount cobalt-rich crust coverage rate, a density, a metal concentration, a thickness, a water ratio, a macroscopic crust coverage rate, a ratio of slope suitable for mineral distribution and a slope fitting surface area.
Five mineral parameters are obtained by station sampling and allocated to various grid units by spatial interpolation, and three mineralization characteristics are extracted from regional survey data in the grid unit.
Each grid unit corresponds to the above eight quantitative indicators, and each indicator corresponds to a map layer (see Fig.1). These indicators are multiplied to obtain the resource quantity of each unit and achieve the purpose of quantitative evaluation of resources.
For a grid unit i, the calculation formula of tonnage of wet crust is: Oweti(ton)= Areai(km?)xCoveragei{%)x Thicknessi(cm)xDensityi{g/cm®)xRcover{%)x 10%; (3) The calculation formula of tonnage of minable crust resource: Osuiti(ton)= Areai(km?)xCoveragei{%)x Thicknessi(cm)xDensityi{g/cm®)xRslopei(%)*x 104; (4) The calculation formula of tonnage of dry crust: DOiton)= Oweti(ton)x[1-Waterratio(%)]; (5) Tonnage of minable dry crust: DOsuiti(ton)= Osuiti(ton)x{1-Waterratio{(%)]; (6) The calculation formula of tonnage of a metal is: Metai{ton)= DOi(ton)xConcentration{%); {7) Tonnage of a minable metal: Msuiti{ton)= DOsuiti(ton)xConcentration(%); {8)
where, Owet; represents a wet crust tonnage of a grid unit i, Osuit represents a recoverable wet crust tonnage of the grid unit i, Area; represents a slope surface area of the grid unit i, Coverage; represents a crust coverage rate of an i" grid unit, Thickness; represents a crust thickness of the i grid unit, Density represents a crust wet density of the i" grid unit, Rcover; indicates a macroscopic crust coverage rate of the i" grid unit, Rslopei represents a ratio of slope suitable for mineral distribution of the i" grid unit, DO; and DOsuit respectively represent the tonnage of dry crust and recoverable dry crust of the ith grid unit, Metal represents a metal tonnage of the i" grid unit, Msuit represents a recoverable metal tonnage of the i" grid unit, Waterratio; represents a crust water ratio of the i" grid unit, and Concentration; represents the metal concentration of the it" grid unit.
S4. delineating key areas and resource quantities thereof according to the grid resources.
All grid units are sorted according to the recoverable resources or their total market value, and then the ore-rich units are combined in space with reference to the relevant spatial adjacency principles of the International Seabed Authority, and the mineral target area is delineated, as shown in Fig.l, and the references Dewen Du*, Xiangwen Ren, Shijuan Yan, Xuefa Shi, Yonggang Liu, Gaowen He .(2017a) An Integrated Method for the Quantitative Evaluation of Mineral Resources of Cobalt-rich Crusts on Seamounts. Ore Geology Reviews, 2017(84): 174-184 .DOL10 .1016/j .oregeorev .2017 .01 .011.
In the present invention, a target seamount slope is divided into a plurality of grid units, the geological station survey data is gridded to obtain the seamount cobalt-rich crusts resource parameters of various grid units, the slope mineralization characteristic parameters of the various grid units are obtained according to the seamount regional survey data, the resource quantities of the various grid units are calculated by combining the seamount cobalt-rich crusts resource parameters and mineralization characteristic parameters of the various grid units, the resource quantities of the various grid units are calculated and the key areas are delineated to finally achieve quantitative evaluation of seamount cobalt-rich crusts resources. In the present invention, the seamount slope mineralization characteristics of the various grid units include a macroscopic crust coverage rate, a ratio of slope suitable for mineral distribution, and a slope surface area. In addition to the traditional coverage rate, the macroscopic crust coverage rate is added to the method of the present invention, which avoids the defect that the coverage rate can only be observed locally but cannot be calculated regionally; the ratio of slope suitable for mineral distribution is intended to quantify the tonnage of wet crusts resources, which improves the quantitative evaluation accuracy of crusts resources; besides, the fitting calculation method of accumulating the minimum survey data grid slope area is used to calculate a slope surface area of the grid unit, which has the advantage of high precision.
The embodiments of the present invention have been described in detail with reference to the accompanying drawings, but the present invention is not limited to the above embodiments, and various changes can be made within the scope of knowledge available to those of ordinary skill in the art without departing from the purpose of the present invention.
Preferred embodiments of the invention
1. A quantitative evaluation method for a seamount cobalt-rich crusts resource, characterized by comprising the following steps: S1. dividing a target seamount slope into a plurality of grid units with the same area at intervals of equal length and width; S2. obtaining seamount cobalt-rich crusts resource parameters of various grid units by spatial interpolation calculation according to the geological station survey data, wherein the seamount cobalt-rich crusts resource parameters comprise a crust thickness, a crust water ratio, a crust wet density, a crust coverage rate, a metal concentration and the like; meanwhile, taking the grid units as objects, extracting seamount slope mineralization characteristics according to the regional survey data of water depth, wherein the seamount slope mineralization characteristics comprise a macroscopic crust coverage rate, a ratio of slope suitable for mineral distribution, a slope surface fitting area, and the like; S3. obtaining resource quantities of the various grid units through a joint calculation of the seamount cobalt-rich crusts resource parameters and various seamount slope mineralization characteristic parameters; and S4. sorting the grid units according to the resource quantities thereof, selecting the grid units with large adjacent resources, delineating key areas of cobalt-rich crusts resources and giving resource quantities of the key areas.
2. The quantitative evaluation method for a seamount cobalt-rich crusts resource according to embodiment 1, characterized in that the grid unit is a square area of 1-20 square kilometers.
3. The quantitative evaluation method for a seamount cobalt-rich crusts resource according to embodiment 1, characterized in that in the step S2, the geological station survey data are obtained by sampling survey, and the specific method is as follows: geological sampling points are arranged on a seamount slope according to the set distribution density, rock or ore samples are obtained at the sampling points by various mechanical methods, and then geological station samples are tested and analyzed in a laboratory to obtain geological station data; wherein the regional survey data of water depth refers to the data of full coverage or lateral coverage obtained by geophysical means.
4. The quantitative evaluation method for a seamount cobalt-rich crusts resource according to embodiment 1, characterized in that in the step S2, when calculating the seamount cobalt-rich crusts resource parameters of the various grid units, a spatial interpolation method is adopted to interpolate geological sampling station data into the various grid units.
5. The quantitative evaluation method for a seamount cobalt-rich crusts resource according to embodiment 4, characterized in that the spatial interpolation method is a grid moving average method or a Kriging method.
6. The quantitative evaluation method for a seamount cobalt-rich crusts resource according to embodiment 1, characterized in that in the step S2, the calculation formula of the macroscopic crust coverage rate is as follows: Reovery = Bian) xX 10054 Ny where, Rcover represents a macroscopic crust coverage rate of an i grid unit, Ni represents a total number of water depth points or water depth grid nodes in the i" grid unit, g represents a slope gradient of water depth point or data grid node, gmin and gmax respectively represent a minimum slope suitable for the development of cobalt-rich crust and a maximum slope suitable for underwater mechanical mining operation; the calculation formula of the ratio of slope suitable for mineral distribution is as follows: Rslope, = Em Bn) x 100% where, Rslopei represents a ratio of slope suitable for mineral distribution of an i" grid unit; the slope surface fitting area is calculated as follows: the 3D spatial surface area of a minimum grid is calculated according to the minimum grid of gridded multi-beam bathymetric survey data, then the 3D spatial surface area of all the minimum data grids in a grid unit i is accumulated, and a slope surface fitting area of the grid unit is obtained by fitting calculation.
7. The quantitative evaluation method for a seamount cobalt-rich crusts resource according to embodiment 6, characterized in that the minimum slope gmin Suitable for the development of a cobalt-rich crust is 4.8°, and the maximum slope gmax suitable for underwater mechanical mining operation is 15°.
8. The quantitative evaluation method for a seamount cobalt-rich crusts resource according to embodiment 1, characterized in that in the step S4, the calculation formula of the resource quantity of a grid unit is as follows: Oweti(ton)=Areai(km?)x Coverage; (%)x Thicknessi(cm)xDensityi{g/cm?)xReover{%)x 10%; Osuiti(ton)=Areai(km?)x Coverage: (%)xThicknessi(om)xDensityi(g/cm3)xRslopei(%)x 10%; DOi(ton)= Oweti{ton)x[1-Water ratioi(%)];
DOsuit{ton)=Osuit(ton)x[1-Water ratioi%)]; Metai(ton)=DOi(ton)xConcentrationi(%); Msuiti(ton)=DOsuiti{ton)xConcentrationi(%);
where, Owet represents a wet crust tonnage of a grid unit i, Osuit represents a recoverable wet crust tonnage of the grid unit i, Area; represents a slope surface area of the grid unit i, Coverage; represents a crust coverage rate of an i" grid unit, Thickness; represents a crust thickness of the i grid unit, Density; represents a crust wet density of the i" grid unit, Rcover; indicates a macroscopic crust coverage rate of the i" grid unit, Rslope; represents a ratio of slope suitable for mineral distribution of the i" grid unit, DO; and DOsuit respectively represent the tonnage of dry crust and recoverable dry crust of the in grid unit, Metal; represents a metal tonnage of the i" grid unit, Msuit represents a recoverable metal tonnage of the i" grid unit, Water ratio;
represents a crust water ratio of the i" grid unit, and Concentration; represents the metal concentration of the i" grid unit.

Claims (8)

CONCLUSIESCONCLUSIONS 1. Een kwantitatieve evaluatiemethode voor een kobaltrijke korstbron op zee, die wordt gekenmerkt door de volgende stappen: S1. het verdelen van een doelhelling op zee in een veelvoud van rastereenheden met hetzelfde gebied met intervallen van gelijke lengte en breedte; S2. het verkrijgen van zeeberg kobaltrijke korsten resource parameters van verschillende rastereenheden door ruimtelijke interpolatie berekening volgens de geologische station enquête gegevens, waarbij de seamount kobaltrijke korsten resource parameters omvatten een korst dikte, een korst water verhouding, een korst natte dichtheid, een korst dekking tarief, een metaal! concentratie en dergelijke; ondertussen, het nemen van de rastereenheden als objecten, het extraheren van zeeberghelling mineralisatiekenmerken volgens de regionale enquêtegegevens van waterdiepte, waarbij de mineralisatiekenmerken van de zeebergheling een macroscopische korstdekkingsgraad, een verhouding van helling geschikt voor minerale distributie, een hellingsopperviak fitting gebied, en dergelijke omvatten; S3. het verkrijgen van hulpbronnenhoeveelheden van de verschillende rastereenheden door middel van een gezamenlijke berekening van de hulpbronnenparameters van de kobaltrijke korsten op zee en verschillende karakteristieke parameters voor de mineralisatie van de zeeberghelling; en S4. het sorteren van de rastereenheden op basis van de resourcehoeveelheden daarvan, het selecteren van de rastereenheden met grote aangrenzende resources, het afbakenen van belangrijke gebieden van kobaltrijke korstbronnen en het geven van resourcehoeveelheden van de belangrijkste gebieden.1. A quantitative evaluation method for a cobalt-rich marine crustal resource, which is characterized by the following steps: S1. dividing a target sea slope into a plurality of grid units of the same area at intervals of equal length and width; S2. obtain seamount cobalt-rich crust resource parameters from different grid units by spatial interpolation calculation according to the geological station survey data, where the seamount cobalt-rich crust resource parameters include a crust thickness, a crust water ratio, a crust wet density, a crust coverage rate, a metal! concentration and the like; meanwhile, taking the grid units as objects, extracting seamount slope mineralization features according to the regional survey data of water depth, where the seamount slope mineralization features include a macroscopic crust coverage ratio, a ratio of slope suitable for mineral distribution, a slope surface fitting area, and the like; S3. obtaining resource amounts of the different grid units through a joint calculation of the resource parameters of the cobalt-rich marine crusts and different characteristic parameters for the mineralization of the seamount slope; and S4. sorting the grid units based on their resource amounts, selecting the grid units with large adjacent resources, delineating important areas of cobalt-rich crust resources, and giving resource amounts of the most important areas. 2. De kwantitatieve evaluatiemethode voor een kobaltrijke korstbron op zee volgens conclusie 1, met als kenmerk dat de rastereenheid een vierkant gebied van 1-20 vierkante kilometer is.The quantitative evaluation method for a cobalt-rich marine crustal resource according to claim 1, characterized in that the grid unit is a square area of 1-20 square kilometers. 3. De kwantitatieve evaluatiemethode voor een kobaltrijke korstbron op zee volgens conclusie 1, met als kenmerk dat in stap S2 de gegevens van het geologische station worden verkregen door midde! van bemonsteringsonderzoek, en de specifieke methode is als volgt: geologische bemonsteringspunten zijn gerangschikt op een zeeberghelling volgens de ingestelde verdelingsdichtheid, rots- of ertsmonsters worden op de bemonsteringspunten verkregen met verschillende mechanische methoden , en vervolgens worden geologische stationsmonsters getest en geanalyseerd in een laboratorium om geologische stationsgegevens te verkrijgen; waarbij de regionale enquêtegegevens van de waterdiepte betrekking hebben op de gegevens van volledige dekking of zijdelingse dekking verkregen met geofysische middelen.The quantitative evaluation method for a cobalt-rich marine crust resource according to claim 1, characterized in that in step S2, the geological station data is obtained by means of! of sampling survey, and the specific method is as follows: geological sampling points are arranged on a seamount slope according to the set distribution density, rock or ore samples are obtained at the sampling points by various mechanical methods, and then geological station samples are tested and analyzed in a laboratory to determine geological obtain station data; wherein the regional water depth survey data refers to the full coverage or lateral coverage data obtained by geophysical means. 4. De kwantitatieve evaluatiemethode voor een kobaltrijke korstbron op zee volgens conclusie 1, met als kenmerk dat in stap S2, bij de berekening van de zeeberg kobaltrijke korsten resource parameters van de verschillende rastereenheden, een ruimtelijke interpolatiemethode wordt toegepast om geologische bemonsteringsstationgegevens in de verschillende rastereenheden te interpoleren.The quantitative evaluation method for a marine cobalt-rich crust resource according to claim 1, characterized in that in step S2, in the calculation of the seamount cobalt-rich crust resource parameters of the different grid units, a spatial interpolation method is applied to obtain geological sampling station data in the different grid units to interpolate. 5. De kwantitatieve evaluatiemethode voor een kobaltrijke korstbron op zee volgens conclusie 4, met als kenmerk dat de ruimtelijke interpolatiemethode een voortschrijdende gemiddelde methode of een Kriging-methode is.The quantitative evaluation method for a cobalt-rich marine crust resource according to claim 4, characterized in that the spatial interpolation method is a moving average method or a Kriging method. 6. De kwantitatieve evaluatiemethode voor een kobaltrijke korstbron op zee volgens conclusie 1, met als kenmerk dat in stap S2 de berekeningsformule van de macroscopische korstdekkingsgraad als volgt is: Reover; = 222 » 109% ’ Ny wanneer Rcover; een macroscopische korstdekkingsgraad van een it rastereenheid vertegenwoordigt, N; een totaal aantal waterdieptepunten of waterdiepterasterknooppunten in de i" rastereenheid, g een hellingsgradiént van waterdieptepunt of gegevensrasterknooppunt, gmin en gmax respectievelijk een minimale helling vertegenwoordigen die geschikt is voor de ontwikkeling van kobaltrijke korst en een maximale helling die geschikt is voor mechanische onderwatermijnbouw; de berekeningsformule van de hellingsverhouding die geschikt is voor minerale distributie is als volgt: Rslope; = inn Emax) x 100% Ny ; waarbij Rslopei een hellingsverhouding vertegenwoordigt die geschikt is voor de minerale verdeling van een it" rastereenheid; het oppervlak van de helling wordt als volgt berekend: het 3D-ruimtelijke oppervlak van een minimumraster wordt berekend op basis van het minimumraster van gerasterde bathymetrische enquêtegegevens met meerdere stralen, vervolgens wordt het 3D-ruimtelijke oppervlak van alle minimale gegevensrasters in een rastereenheid |i verzameld en wordt een hellingsopperviakmontagegebied van de rastereenheid verkregen door montageberekening.The quantitative evaluation method for a cobalt-rich marine crustal resource according to claim 1, characterized in that in step S2, the calculation formula of the macroscopic crustal coverage is as follows: Reover; = 222 » 109% ’ Ny when Rcover; represents a macroscopic crust coverage of an it grid unit, N; a total number of water depth points or water depth grid nodes in the i" grid unit, g a slope gradient of water depth point or data grid node, gmin and gmax represent a minimum slope suitable for cobalt-rich crust development and a maximum slope suitable for mechanical underwater mining, respectively; the calculation formula of the slope ratio suitable for mineral distribution is as follows: Rslope; = inn Emax) x 100% Ny ; where Rslopei represents a slope ratio suitable for the mineral distribution of an it" grid unit; the slope area is calculated as follows: the 3D spatial area of a minimum grid is calculated from the minimum grid of multi-beam gridded bathymetric survey data, then the 3D spatial area of all minimum data grids is collected in a grid unit |i and a slope surface mounting area of the grid unit is obtained by mounting calculation. 7. De kwantitatieve evaluatiemethode voor een kobaltrijke korstbron op zee volgens conclusie 6, met als kenmerk dat de minimale helling Qmin die geschikt is voor de ontwikkeling van een kobaltrijke korst 4,8° is en de maximale helling gmax die geschikt is voor mechanische mijnbouw onder water 15° is.The quantitative evaluation method for a cobalt-rich marine crust resource according to claim 6, characterized in that the minimum slope Qmin suitable for the development of a cobalt-rich crust is 4.8° and the maximum slope gmax suitable for mechanical mining under water is 15°. 8. De kwantitatieve evaluatiemethode voor een kobaltrijke korstbron op zee volgens conclusie 1, met als kenmerk dat in stap S4 de berekeningsformule van de hoeveelheid grondstoffen van een rastereenheid als volgt is: waar Owet; een natte korsttonnage van een rastereenheid i vertegenwoordigt, Osuiti een herwinbare natte korsttonnage van de rastereenheid i, Area een hellingsopperviak van de rastereenheid i, Coverage; een korstdekkingsgraad van een i rastereenheid vertegenwoordigt, Thicknessi een korstdikte van de i" rastereenheid vertegenwoordigt, Densityi vertegenwoordigt een natte korstdichtheid van de i rastereenheid, Rcoveri geeft een macroscopische korstdekkingsgraad van de it" rastereenheid aan, Rslopei vertegenwoordigt een hellingsverhouding die geschikt is voor minerale distributie van de i rastereenheid, DO; en DOsuit; vertegenwoordigen respectievelijk de tonnage van droge korst en herwinbare droge korst van de i" rastereenheid, Metal, vertegenwoordigt een metaaltonnage van de i" neteenheid, Msuit; vertegenwoordigt een terugwinbare metaaltonnage van de i" neteenheid, Water ratio i vertegenwoordigt een korstwaterverhouding van de i" neteenheid en Concentration; vertegenwoordigt de metaalconcentratie van de it" neteenheid.The quantitative evaluation method for a cobalt-rich marine crust resource according to claim 1, characterized in that in step S4, the raw material amount calculation formula of a grid unit is as follows: where Owet; a wet crust tonnage of a grid unit i, Osuiti represents a recoverable wet crust tonnage of the grid unit i, Area represents a slope area of the grid unit i, Coverage; represents a crust coverage of an i grid unit, Thicknessi represents a crust thickness of the i" grid unit, Densityi represents a wet crust density of the i grid unit, Rcoveri indicates a macroscopic crust coverage of the it" grid unit, Rslopei represents a slope ratio suitable for mineral distribution of the i grid unit, DO; and DOsuit; represent respectively the tonnage of dry crust and recoverable dry crust of the i" grid unit, Metal, represents a metal tonnage of the i" net unit, Msuit; represents a recoverable metal tonnage of the i" net unit, Water ratio i represents a crust water ratio of the i" net unit and Concentration; represents the metal concentration of the it" net unit.
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