Geochemical exploration method and system for mire forest coverage area

Abstract

The application discloses a marsh forest coverage area geochemical exploration method and system and belongs to the technical field of geochemical exploration, and solves the problem that the prior art cannot meet the requirement of accurate ore prospecting. The method comprises the following steps: according to the water system development degree, the gully system development degree, the landform type, the marsh distribution, the permafrost distribution and the peat development characteristics of a work area, the work area is divided into multiple sub-landscape areas; a corresponding sampling medium is selected for the sub-landscape area; the sampling particle size of the sampling medium is determined; coarse rinsing and ultrasonic fine rinsing are sequentially performed on the sampling medium, and an analysis sample is obtained; an element content detection operation is performed on the analysis sample, and a preliminary detection result is obtained; according to the preliminary detection result, in combination with the sample quality change before and after rinsing, the target element content change, the element combination characteristics, the element phase state, the geological background and the geophysical prospecting information, the geochemical anomaly is reviewed, and a prospecting target area is delineated. The application improves the accuracy of ore prospecting prediction in a complex landscape area and the reliability of target area delineation.

Description

Technical Field

[0001] This invention belongs to the field of geochemical exploration technology, and specifically relates to a method and system for geochemical exploration in swamp forest-covered areas. Background Technology

[0002] Extensive forest-swamp landscapes are widely distributed in Northeast my country and other regions. These areas are characterized by well-developed permafrost, dense vegetation, and high peat and humus content in soil and aquatic sediments. Surface water is predominantly weakly acidic, and the migration and enrichment patterns of elements are complex. Currently, the mainstream geochemical exploration methods in these areas mainly include conventional aquatic sediment measurements, soil measurements, and gully sediment measurements, supplemented by traditional water washing and rinsing processes.

[0003] However, the landscape conditions in swamp forest-covered areas are complex, with problems such as uneven development of water systems, sediments rich in organic matter such as peat, diverse soil types, and unique element migration patterns.

[0004] Conventional geochemical exploration methods (such as conventional stream sediment measurements and soil measurements) are not optimized for the specific characteristics of such areas. They are easily affected by organic matter adsorption, leading to abnormal ambiguity. Furthermore, the use of a single sampling medium and fixed particle size selection cannot be adapted to the element enrichment characteristics of different mineral types, often resulting in problems such as missed anomalies and inaccurate positioning. This severely restricts the mineral exploration efficiency in swamp forest-covered areas and makes it difficult to meet the needs of precise mineral exploration. Summary of the Invention

[0005] Based on the above analysis, the embodiments of the present invention aim to provide a geochemical exploration method and system for swamp forest-covered areas, in order to solve the problem that the existing technology is difficult to meet the needs of accurate mineral exploration.

[0006] The objective of this invention is achieved as follows:

[0007] A geochemical exploration method for swamp forest cover areas includes:

[0008] Based on the degree of water system development, gully system development, landform type, swamp distribution, permafrost distribution, and peat development characteristics of the work area, the work area is divided into multiple sub-landscape areas;

[0009] Based on the material source accumulation characteristics and surface medium development characteristics of different sub-landscape areas, corresponding sampling media are selected for the sub-landscape areas;

[0010] The sampling particle size of the sampling medium is determined based on the type of the sampling medium, the corresponding climate type, the target mineral type, and the occurrence and enrichment characteristics of the target elements.

[0011] The sampling medium was sequentially subjected to coarse rinsing and ultrasonic fine rinsing to obtain the analytical sample;

[0012] Elemental content detection was performed on the analyzed sample to obtain preliminary detection results;

[0013] Based on the preliminary test results, and in conjunction with the changes in sample quality before and after rinsing, changes in target element content, element combination characteristics, element phases, geological background and geophysical information, the geochemical anomalies were reviewed, and mineral exploration target areas were delineated.

[0014] Optionally, the multiple sub-landscape areas include: a water system development area, a water system undeveloped but a gully system development area, a water system and a gully system undeveloped area, and a meadow marsh area;

[0015] Based on the source accumulation characteristics and surface medium development characteristics of different sub-landscape areas, corresponding sampling media are selected for each sub-landscape area, including:

[0016] In response to the sub-landscape area being the water system development area, water system debris sediments are collected in the water system development area. When peat is rich in the water system and it is difficult to obtain qualified water system debris sediments, mineral residues at the bottom of the peat layer, peat-mineral mixed layer, or peat mineral components after rinsing and separation are collected as the sampling medium.

[0017] In response to the fact that the sub-landscape area is an area with underdeveloped water system but developed gully system, gully sediments were collected;

[0018] In response to the fact that the sub-landscape area is a region where neither water system nor ditch system is developed, residual slope soil, rock debris, or rock debris-soil mixture were collected.

[0019] In response to the sub-landscape area being a meadow-swamp area, swamp soil or meadow soil was collected.

[0020] Optionally, determining the sampling particle size of the sampling medium based on its type, corresponding climate type, target mineral type, and occurrence and enrichment characteristics of the target element includes:

[0021] For the riparian sediments in the cold temperate mid-low mountain permafrost region, select those with a particle size of 4 mesh and retain 40 mesh, or select those with a particle size of 10 mesh and retain 60 mesh.

[0022] For stream sediments in the mid-temperate low and medium mountain and hilly areas, select sediments with a particle size of less than 20 mesh or less than 40 mesh.

[0023] When multiple target elements need to be considered, a mixed particle size of over 10 mesh with 40 mesh and over 60 mesh is adopted.

[0024] Valley sediments should be selected from particle sizes of 20 mesh, 40 mesh, or 60 mesh, with 60 mesh preferred when gold and silver are the target elements.

[0025] When molybdenum is the target element in residual colluvial soil or rock debris, a particle size of 10 mesh or less with a 60 mesh size retained should be selected; when gold or silver is the target element, a particle size of 60 mesh or less should be selected.

[0026] Samples from the humus-developing area were selected from 80-mesh fine-grained samples.

[0027] Optionally, the sampling network and sampling density are set according to the source coverage of different sampling media, wherein:

[0028] Debris sediments from the stream were sampled using a 500m × 500m grid at a density of 4 points / km. 2 ;

[0029] Valley sediments were sampled using a 500m × 400m grid at a density of 5 points / km. 2 ;

[0030] Soil, rock cuttings, or rock cuttings-soil mixtures were sampled using a 500m × 250m grid at a density of 8 points / km. 2 ;

[0031] When the width of the gully exceeds the preset width, multiple sub-sampling points are set up along the vertical direction of the gully, and the samples from multiple sub-sampling points are mixed to form a composite sample; soil, rock debris, or rock debris-soil mixture sampling points are preferentially set up at the foot of the slope, gentle slope, gully mouth, sediment collection site, or source collection site.

[0032] Optionally, the coarse rinsing includes:

[0033] Place the sampling medium into a non-metallic washing dish, add water until the sample is completely submerged, soak for 1 to 3 minutes, and disperse the sample clumps by manually twisting them apart.

[0034] Keep the non-metallic washing tray half-submerged in water, and use the density difference to float out plant residues, dead branches and light organic impurities by circumferential oscillation and small up-and-down agitation, repeating 2 to 3 times;

[0035] Increase the agitation amplitude to remove the free clay, surface peat and loose organic matter attached to the surface of the mineral particles. Stop agitating when the rinsing water reaches the preset turbidity level.

[0036] The tailings generated during the rinsing process are collected and subjected to secondary washing to recover heavy minerals and fine-grained indicator minerals.

[0037] After coarse rinsing, drain the water from the sample and seal it for storage.

[0038] Optionally, the ultrasonic rinsing includes:

[0039] The sample after coarse rinsing is placed in a cleaning container, and deionized water with a volume of 3 times the sample volume is added. The mixture is then mechanically stirred for 5 minutes to pre-disperse peat flocs and organic matter aggregates.

[0040] The pre-dispersed samples were subjected to ultrasonic treatment at 40kHz to 80kHz. The conventional samples were treated for 10 to 15 minutes, and the high peat or high humus samples were treated for 15 minutes.

[0041] The settling time is controlled according to the target particle size and target mineral density. When the target is a fine-grained precious metal carrier or a fine-grained sulfide carrier, the upper suspension is decanted after settling for 5 to 10 seconds. When the target is a coarser sulfide, oxide, or detrital mineral carrier, the upper suspension is decanted after settling for 10 to 15 seconds.

[0042] The final wash was performed with deionized water, and the washed sample was dried at a low temperature not exceeding 60°C.

[0043] Optionally, performing elemental content detection on the analyzed sample to obtain preliminary detection results includes:

[0044] Obtain elemental detection data of the analytical sample, the elemental detection data including the original response data of multiple elements detected in the analytical sample in multiple detection cycles, sample number and sample spatial location data;

[0045] A detection response matrix is ​​constructed based on the original response data. The detection response matrix is ​​used to characterize the response change relationship of different detected elements in the same analytical sample in different detection cycles.

[0046] Based on the response change characteristics of the same detection element in the detection response matrix between adjacent detection cycles, the effective response range of each detection element is determined, and the effective detection value of each detection element is calculated based on the effective response range.

[0047] Based on the preset element rinsing response attribute table, extract the first element data set corresponding to the rinsing stable element and the second element data set corresponding to the rinsing sensitive element from the effective detection values ​​of multiple detection elements of the same analytical sample.

[0048] The rinsing offset index of the analytical sample is determined based on the degree of deviation of the second element data set relative to the first element data set.

[0049] The effective detection values ​​of matrix indicator elements are extracted from the effective detection values ​​of multiple detection elements in the same analytical sample, and the matrix inhibition index of the analytical sample is determined based on the effective detection values ​​of the matrix indicator elements.

[0050] The neighboring samples of the analytical sample are determined based on the spatial location data of the sample, and the local background value of the target element is determined based on the effective detection value of the target element in the neighboring samples.

[0051] Based on the effective detection value of the target element, the rinsing offset index, the matrix inhibition index, and the local background value, the detection value of the target element is reconstructed to obtain the corrected detection value of the target element.

[0052] Preliminary test results for the analyzed sample are generated based on the corrected test values.

[0053] Optionally, based on the preliminary detection results, and in conjunction with changes in sample mass before and after rinsing, changes in target element content, elemental combination characteristics, elemental phases, geological background, and geophysical information, the geochemical anomaly is reviewed to delineate the mineral exploration target area, including:

[0054] In response to the first round of geochemical measurements that delineated anomalies and identified high-value points, sampling and re-testing were performed again for the high-value points and their adjacent background points according to the corresponding sampling medium, target particle size and graded composite rinsing process to obtain verification data.

[0055] The verification data is compared with the first round of geochemical measurement data to eliminate outliers caused by sampling location deviation, sample pretreatment deviation, or analysis and testing deviation, and the recurring high-value outliers are identified as outliers to be verified.

[0056] Centered on the anomaly points to be verified, hierarchical and encrypted sampling is carried out according to their anomaly types. Among them, the anomaly density in the 1:200,000 area is increased to 3 to 5 points / km. 2 1:50,000 fine-grained anomaly encryption reduced to 5 to 8 points / km 2 To obtain encrypted sampling data;

[0057] Based on the encrypted sampling data, the abnormal boundaries are delineated, the abnormal concentration center is determined, and the element combination characteristics are identified. The areas where the abnormal boundaries, abnormal concentration centers, and element combination characteristics are consistent are identified as key areas for verification of abnormalities.

[0058] Geological mapping, alteration surveys, and mineralized rock sampling were carried out in the key verification anomaly area to determine the lithology, structure, alteration, and mineralization characteristics of the key verification anomaly area, and the collection locations of representative samples were determined based on the lithology, structure, alteration, and mineralization characteristics.

[0059] Elemental phase analysis was performed on the representative samples to test the occurrence ratio of the target element in the sulfide phase, oxide phase, organic complex phase and clay adsorption phase.

[0060] When the proportion of sulfide phase and / or oxide phase of the target element is higher than that of organic complex phase and clay adsorption phase, and the abnormal concentration center has a spatial correspondence with geological structure, alteration zone or mineralization body, the corresponding key verification anomaly area will be identified as a candidate mineral-induced anomaly area.

[0061] High-precision magnetic and induced polarization gradient methods were superimposed on the candidate mineral anomaly areas for geophysical verification to obtain geophysical anomaly information;

[0062] When the geophysical anomaly information has a spatial correspondence with the anomaly concentration center, the element combination characteristics, and the geological structure, alteration zone, or mineralized body, the candidate mineralized anomaly area is determined as a favorable mineralized anomaly area.

[0063] Conduct 80 to 250 points / km within the favorable mineralized anomaly zone. 2 Large-scale soil surveys are conducted to further determine the location of anomaly peaks, the direction of anomaly distribution, and the boundary of anomaly closure based on the results of the large-scale soil surveys. Based on this, prospecting target areas are delineated, and engineering verification locations for trenching and / or drilling are determined.

[0064] Optionally, the candidate mineral-induced anomaly zone can be determined using the following method:

[0065] Based on the encrypted sampling data, the key areas for anomaly investigation are divided into an abnormal concentration center zone, an abnormal transition zone, an abnormal edge zone, and a background control zone, and representative samples are collected for each zone.

[0066] The total amount of target elements, organic carbon content, loss on ignition, particle size composition, and the phase ratio of target elements in sulfide phase, oxide phase, organic complex phase, and clay adsorbed phase of the representative sample were tested.

[0067] The effective mineralization phase ratio is determined based on the sulfide phase ratio and the oxide phase ratio, and the organic matter-adsorption interference phase ratio is determined based on the organic complex phase ratio and the clay adsorption phase ratio.

[0068] The ore-forming phase dominance coefficient is determined based on the ratio of the effective ore-forming phase proportion to the organic matter-adsorption interference phase proportion.

[0069] The organic interference coefficient is determined based on the organic matter-adsorption interference phase ratio, organic carbon content, and loss on ignition.

[0070] When the total amount of target elements decreases step by step from the abnormal concentration center zone, abnormal transition zone, abnormal edge zone to the background control zone, and the proportion of effective mineralized facies decreases synchronously, and the mineralized facies dominance coefficient is higher than the preset dominance threshold and the organic interference coefficient is lower than the preset interference threshold, the corresponding anomaly is determined to be a preliminary favorable mineral-induced anomaly.

[0071] When the increase in the total amount of the target element is synchronous with the increase in organic carbon content, loss on ignition, proportion of organic complexes or proportion of clay adsorption, and the organic interference coefficient is higher than the preset interference threshold, the corresponding anomaly is identified as an organic matter interference anomaly or a clay adsorption anomaly.

[0072] A geochemical exploration system for swamp forest cover areas includes:

[0073] The division unit is used to divide the work area into multiple sub-landscape areas based on the degree of water system development, ditch system development, landform type, swamp distribution, permafrost distribution, and peat development characteristics of the work area;

[0074] The selection unit is used to select the corresponding sampling medium for the sub-landscape area based on the material source accumulation characteristics and surface medium development characteristics of different sub-landscape areas.

[0075] The determining unit is used to determine the sampling particle size of the sampling medium based on the type of the sampling medium, the corresponding climate type, the target mineral type, and the occurrence and enrichment characteristics of the target element.

[0076] The rinsing unit is used to sequentially perform coarse rinsing and ultrasonic fine rinsing on the sampling medium to obtain analytical samples;

[0077] The exploration unit is used to perform elemental content detection on the analytical sample, obtain preliminary detection results, and, based on the preliminary detection results and in combination with the changes in sample quality before and after rinsing, changes in target element content, elemental combination characteristics, elemental phases, geological background and geophysical information, to verify geochemical anomalies and delineate mineral exploration target areas.

[0078] Compared with existing technologies, the geochemical exploration method and system for swamp forest cover areas provided by this invention can achieve at least one of the following beneficial effects:

[0079] This application divides the work area into multiple sub-landscape zones based on the development levels of the water system, gully system, landform type, swamp distribution, permafrost distribution, and peat development characteristics. This division effectively reflects the differences in material migration, enrichment, and preservation environments under different geomorphological conditions, thus avoiding the distortion of anomalous information caused by using a single sampling method. Furthermore, based on the provenance and surface media development characteristics of different sub-landscape zones, suitable sampling media are selected for each sub-landscape zone. This ensures that the collected samples better represent the geochemical background and mineralization information of their respective sub-landscape zones, improving sampling specificity. Further, by combining the sampling media type, climate type, target mineral type, and the occurrence and enrichment characteristics of target elements, the sampling particle size of the corresponding sampling media is determined. This enhances the enrichment effect of target elements, reduces interference from ineffective components, and improves the indicative significance of the detection results. Simultaneously, by sequentially performing coarse rinsing and ultrasonic fine rinsing on the sampling media, light impurities, clay inclusions, and non-target interfering substances can be effectively removed, resulting in analytical samples more suitable for elemental content detection, thereby improving the stability and comparability of the test data. After obtaining preliminary test results, the geochemical anomalies are comprehensively reviewed by combining the changes in sample quality before and after rinsing, changes in target element content, element combination characteristics, element phases, geological background and geophysical information. This can effectively distinguish between real mineralization anomalies and landscape background anomalies, transport anomalies or disturbance anomalies, thereby improving the accuracy of mineral exploration prediction in complex landscape areas and the reliability of target area delineation.

[0080] In this invention, the above-described technical solutions can be combined with each other to achieve more preferred combinations. Other features and advantages of this invention will be set forth in the following description, and some advantages may become apparent from the description or be learned by practicing the invention. The objects and other advantages of this invention can be realized and obtained from what is particularly pointed out in the description and drawings. Attached Figure Description

[0081] To more clearly illustrate the technical solutions in the embodiments of this specification or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in the embodiments of this specification. For those skilled in the art, other drawings can be obtained based on these drawings.

[0082] Figure 1 This is a flowchart of a geochemical exploration method for swamp forest cover areas provided by the present invention;

[0083] Figure 2 This is a schematic diagram of the structure of a geochemical exploration system for swamp forest cover areas provided by the present invention. Detailed Implementation

[0084] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0085] To facilitate understanding of the embodiments of this application, further explanation and description will be provided below with reference to the accompanying drawings and specific embodiments. These embodiments do not constitute a limitation on the embodiments of this application. In the drawings, the dimensions and relative dimensions of components may be exaggerated for clarity and / or descriptive purposes. When exemplary embodiments can be implemented differently, a specific process sequence may be performed in a different order than described. For example, two consecutively described processes may be performed substantially simultaneously or in the reverse order of their description. Furthermore, the same reference numerals denote the same components.

[0086] The terminology used herein is for the purpose of describing particular embodiments and is not intended to be limiting. As used herein, unless the context clearly indicates otherwise, the singular forms “a” and “the” are intended to include the plural forms as well. Furthermore, when the terms “comprising” and / or “including” and variations thereof are used in this specification, it indicates the presence of the stated features, integrals, steps, operations, parts, components, and / or groups thereof, but does not exclude the presence or addition of one or more other features, integrals, steps, operations, parts, components, and / or groups thereof. It should also be noted that, as used herein, the terms “substantially,” “about,” and other similar terms are used as approximate terms rather than as terms of degree, thus explaining the inherent biases in measurements, calculated values, and / or provided values ​​that will be recognized by those skilled in the art.

[0087] As described in the background section, conventional geochemical exploration methods are insufficient to meet the demands of precise mineral exploration, specifically in the following ways:

[0088] Regarding sampling media, traditional exploration methods employ a one-size-fits-all approach, failing to select sampling media based on the development level of the water system, the distribution of gullies, and the differences in landform types within the work area. In areas with underdeveloped water systems, waterless valleys, and gentle hills, conventional water system sediment sampling cannot be carried out, creating exploration blind spots. Furthermore, the mixing of peat and clastic media without distinguishing the elemental indication capabilities of different media can easily lead to anomalies and distortions.

[0089] Regarding sampling grain size, traditional exploration methods generally use a fixed and uniform grain size, without taking into account climate zones, landscape characteristics, target mineral types, and element occurrence patterns for refined selection. Fine-grained enriched elements such as gold and silver share the same grain size as coarse-grained enriched elements such as lead, zinc, and copper, leading to a decrease in anomaly response sensitivity and the masking of anomalies in some weak minerals.

[0090] In terms of rinsing processes, traditional methods only employ a single, simple water rinse, which can only remove surface plant residues and cannot effectively remove organic matter, clay, and organic complexes adsorbed on the mineral surface. High-content peat will adsorb a large amount of ore-forming elements, resulting in numerous false anomalies, shifts in anomaly concentration centers, and blurred anomaly boundaries. At the same time, traditional rinsing lacks a standardized process, which can easily lead to over-rinsing causing the loss of fine-grained minerals, or incomplete rinsing interfering with the residue.

[0091] In terms of sampling layout, the sampling density and network specifications were set uniformly without being designed differently according to the source coverage of different media. Either the sampling points were sparse and omissions were missed, or the sampling points were too dense, increasing the exploration cost. It was difficult to balance exploration efficiency and coverage.

[0092] In terms of anomaly verification, traditional anomaly verification methods are singular, relying solely on intensive sampling and macro-geological observation, without combining elemental phase analysis and joint verification using multiple geophysical methods. They lack the ability to distinguish false anomalies caused by organic matter and weak deep anomalies, and anomaly evaluation is highly subjective.

[0093] In summary, existing geochemical exploration techniques in forest and swamp areas suffer from a series of problems, including limited media selection, crude particle size matching, poor rinsing and impurity removal, unreasonable sampling layout, and insufficient anomaly identification methods. Organic matter interference cannot be effectively eliminated, and anomalies are frequently missed or misidentified, which seriously hinders the progress of mineral exploration in forest and swamp-covered areas.

[0094] Based on this, the embodiments of this application construct an integrated geochemical exploration system for landscape zoning, media differentiation selection, targeted particle size matching, graded composite washing, zonal sampling and deployment, and full-process anomaly verification, targeting the landscape characteristics and mineral element migration patterns of swamp forest covered areas.

[0095] Specifically, in the geochemical exploration method for swamp forest-covered areas according to the embodiments of this application, the working area is divided into multiple sub-landscape zones based on the degree of water system development, gully development, landform type, swamp distribution, permafrost distribution, and peat development characteristics. This fully reflects the differences in material migration, enrichment, and preservation environments under different geomorphic landscape conditions, thereby avoiding the distortion of abnormal information caused by using a single sampling method. Based on this, suitable sampling media are selected for each sub-landscape zone according to the source accumulation characteristics and surface medium development characteristics of different sub-landscape zones. This makes the collected samples more representative of the geochemical background and mineralization information of the respective sub-landscape zone, improving the sampling targeting. Furthermore, by combining the sampling medium type, climate type, target mineral type, and the occurrence and enrichment characteristics of target elements, the sampling particle size of the corresponding sampling medium is determined. This helps to enhance the enrichment effect of target elements, reduce interference from invalid components, and improve the indicative significance of the detection results. Simultaneously, by sequentially performing coarse rinsing and ultrasonic fine rinsing on the sampling medium, light impurities, clay inclusions, and non-target interferences can be effectively removed, resulting in analytical samples more suitable for elemental content detection, thereby improving the stability and comparability of test data. After obtaining preliminary detection results, the geochemical anomalies are comprehensively reviewed by combining the changes in sample mass before and after rinsing, changes in target element content, elemental assemblage characteristics, elemental phases, geological background, and geophysical information. This can effectively distinguish between genuine mineralization anomalies and landscape background anomalies, transport anomalies, or interference anomalies, improving the accuracy of mineral exploration prediction in complex landscape areas and the reliability of target area delineation.

[0096] See Figure 1 , Figure 1 This is a flowchart of a geochemical exploration method for swamp forest cover areas provided by the present invention. Figure 1 As shown, it may include:

[0097] S101. Based on the degree of water system development, ditch system development, landform type, swamp distribution, permafrost distribution, and peat development characteristics of the work area, the work area is divided into multiple sub-landscape areas.

[0098] In some embodiments, based on the geological information of the work area, the development level of the water system can be determined in accordance with the technical requirements of hydrogeological surveys. Furthermore, by combining the distribution characteristics of swamps, permafrost, and gullies, the work area can be divided into multiple sub-landscape zones, enabling the matching of specific sampling media for each zone and completely eliminating blind spots in the exploration.

[0099] For example, based on the above geological information, the work area can be divided into at least one landscape unit. The landscape unit includes a water system development zone, a water system-less but gully system-developed zone, a zone with neither water system nor gully system development, and a meadow-marsh zone.

[0100] In this way, we can abandon the traditional single-media exploration model and, by implementing a landscape zoning and multi-media collaborative sampling system, configure corresponding media for different sub-landscapes of forests and swamps, thus completely solving the problem of exploration blind spots in areas such as water systems, gullies, and waterless hills.

[0101] S102, based on the material source accumulation characteristics and surface medium development characteristics of different sub-landscape areas, select the corresponding sampling medium for the sub-landscape area.

[0102] In some embodiments, different sub-landscape areas have their own corresponding source accumulation characteristics and surface medium development characteristics, thereby enabling the determination of the sampling medium for each sub-landscape area.

[0103] In one example, in response to the sub-landscape area being the river system development area, river system detrital sediments are collected in the river system development area. When peat is enriched in the river system and qualified river system detrital sediments are difficult to obtain, mineral residues at the bottom of the peat layer, peat-mineral mixed layers, or peat mineral components after rinsing and separation are collected as the sampling medium. River system sediments can reflect the migration information of mineral detritus, weathered materials, and target elements within the upstream catchment area, and are suitable for areas with developed river systems and stable sediments.

[0104] In response to the fact that the sub-landscape area is characterized by an underdeveloped drainage system but a well-developed gully system, gully sediments were collected. These sediments can be collected from the bottom of the gully, at gully bends, at seasonal water flow convergence points, at gully mouths, or at slope toe confluence points. The gully sediments can represent the provenance information of the gully sides and upstream slopes.

[0105] In response to the fact that the sub-landscape area is a region where neither water system nor ditch system is developed, residual slope soil, rock debris, or rock debris-soil mixture were collected.

[0106] In response to the sub-landscape area being a meadow-swamp area, swamp soil or meadow soil was collected.

[0107] S103, determine the sampling particle size of the sampling medium based on the type of the sampling medium, the corresponding climate type, the target mineral type, and the occurrence and enrichment characteristics of the target element.

[0108] In some embodiments, after determining the sampling medium for each sub-landscape area, the sampling granularity is further determined based on the type of the sampling medium and other information corresponding to the sampling medium, thereby achieving differentiated processing.

[0109] In this way, the industry practice of fixed sampling particle size and fixed sampling density is broken. The particle size and measurement network density are matched in a targeted manner according to the climate zone, mineral type, element occurrence law and medium source range, so that the sampling parameters are highly adapted to the regional geochemical characteristics and the anomaly response capability is improved.

[0110] In one example, step S103 may include:

[0111] For the riparian sediments in the cold temperate low-mountain permafrost region, either 4 mesh or 10 mesh with 60 mesh particles should be selected.

[0112] For the sediments in the mid-temperate low and medium mountain and hilly areas, a particle size of 20 mesh or 40 mesh or smaller was selected.

[0113] When multiple target elements need to be considered, a mixed particle size of 10 mesh or more with 40 mesh and 60 mesh or more is adopted.

[0114] Valley sediments should be selected from particles larger than 20 mesh, 40 mesh, or 60 mesh, with particles larger than 60 mesh preferred when gold and silver are the target elements.

[0115] When molybdenum is the target element in residual colluvial soil or rock debris, a 10-mesh particle size with a 60-mesh particle size should be selected; when gold or silver is the target element, a 60-mesh particle size should be selected.

[0116] Samples from the humus-developing area were selected from 80-mesh fine-grained samples.

[0117] In some embodiments, the sampling network and sampling density are set according to the source coverage of different sampling media, wherein: for aquatic clastic sediments, a 500m×500m network is used, and the sampling density is 4 points / km. 2 Valley sediments were sampled using a 500m × 400m grid at a density of 5 points / km. 2 Soil, rock cuttings, or rock cuttings-soil mixtures were sampled using a 500m × 250m grid at a density of 8 points / km. 2 When the width of the gully exceeds the preset width, multiple sub-sampling points are set up along the vertical direction of the gully, and the samples from multiple sub-sampling points are mixed to form a composite sample; soil, rock debris, or rock debris-soil mixture sampling points are preferentially set up at the foot of the slope, gentle slope, gully mouth, sediment collection site, or source collection site.

[0118] Thus, by implementing differentiated settings for the measurement network, point spacing, and sampling density, multi-point composite sampling is adopted in wide valleys to improve the anomaly detection rate.

[0119] S105, the sampling medium is subjected to coarse rinsing and ultrasonic fine rinsing in sequence to obtain the analytical sample.

[0120] In some embodiments, after determining the sampling particle size of the sampling medium, the sampling medium can be acquired at the same sampling point or different sampling points according to the sampling particle size. The acquired sampling medium can then be rinsed.

[0121] In this solution, the rinsing process includes coarse rinsing and ultrasonic fine rinsing. A standardized two-stage process is implemented: a field-based coarse rinsing followed by an indoor ultrasonic fine rinsing. The rinsing intensity is adjusted according to different media, balancing the removal of organic interference with the retention of mineral particles. Non-metallic washing trays and containers are used throughout the process to prevent metal contamination.

[0122] In some embodiments, coarse rinsing (corresponding to simultaneous implementation at the sampling site) includes: placing the sampling medium into a non-metallic washing pan, adding water until the sample is completely submerged, soaking for 1 to 3 minutes, and dispersing sample clumps by manually twisting them apart; keeping the non-metallic washing pan partially submerged in water, and using circular oscillation and small up-and-down agitation to float out plant debris, dead branches, and light organic impurities by utilizing density differences, repeating 2 to 3 rounds; increasing the agitation amplitude to detach free clay, surface peat, and loose organic matter attached to the surface of mineral particles, and stopping agitation when the rinsing water reaches a preset turbidity level; collecting the tailings generated during the rinsing process, and performing a second washing on the tailings to recover heavy minerals and fine indicator minerals; and sealing and storing the sample after coarse rinsing after draining excess water.

[0123] It should be noted that when performing sealed storage, double labels are also affixed for use in ultrasonic rinsing.

[0124] Ultrasonic fine rinsing (conducted after the sample is transported back to the site / laboratory) includes: placing the sample after the coarse rinsing into a cleaning container, adding deionized water at a volume three times the sample volume, and mechanically stirring for 5 minutes to pre-disperse peat flocs and organic matter aggregates; using ultrasound at 40kHz to 80kHz to vibrate the pre-dispersed sample, with conventional samples treated for 10 to 15 minutes and high-peat or high-humicity samples treated for 15 minutes; controlling the settling time according to the target particle size and target mineral density, when the target is a fine-grained precious metal carrier or a fine-grained sulfide carrier, settling for 5 to 10 seconds and then decanting the supernatant; when the target is a coarser-grained sulfide, oxide, or detrital mineral carrier, settling for 10 to 15 seconds and then decanting the supernatant; performing a final wash with deionized water, and drying the final-washed sample at a low temperature not exceeding 60°C.

[0125] Among these methods, performing low-temperature drying can prevent sulfide oxidation and changes in element valence.

[0126] In some optional examples, different rinsing adaptation rules are configured according to the type of medium. For aquatic clastic sediments, a medium rinsing intensity is performed to retain 60-mesh fine particles. For peat and marsh soils, the ultrasonic treatment time is extended to focus on removing organic carbon interference. For rock debris and colluvial soils, the ultrasonic time is shortened to only clean surface dust and protect the original mineral phases.

[0127] S105, Perform elemental content detection on the analyzed sample to obtain preliminary detection results.

[0128] In some embodiments, after ultrasonic rinsing, elemental content analysis is performed on the analytical sample to obtain preliminary detection results for delineating mineral exploration target areas. These preliminary detection results are used to determine the likelihood of the existence of the mineral target area.

[0129] In one embodiment, step S105 may include:

[0130] S1051, Obtain the elemental detection data of the analytical sample, the elemental detection data including the original response data of multiple elements detected in the analytical sample in multiple detection cycles, sample number and sample spatial location data.

[0131] In some embodiments, the analytical samples are geochemical samples collected from forest swamp areas and then rinsed. The analytical samples can be soil samples, sediment samples, humus mixtures, or fine-grained geochemical samples.

[0132] After performing multi-element detection on the analytical sample, the elemental detection data of the analytical sample can be obtained.

[0133] The sample number is used to uniquely identify the analyzed sample; the sample spatial location data may include sampling point coordinates, sampling line numbers, sampling grid numbers, or relative sampling point position data. Multiple detection elements may include one or more of the following: rinsing-stabilized elements, rinsing-sensitive elements, matrix indicator elements, and target elements.

[0134] It should be noted that rinsing-stabilizing elements, rinsing-sensitive elements, matrix indicator elements, and target elements are not different analytical samples, but rather element types categorized from multiple detectable elements of the same analytical sample according to different data processing purposes.

[0135] S1052, construct a detection response matrix based on the original response data, the detection response matrix being used to characterize the response change relationship of different detection elements in the same analytical sample within different detection cycles.

[0136] In some embodiments, the raw response data of the same analytical sample corresponding to multiple detection elements in multiple detection cycles are represented as follows: ,in, Indicates the sample number being analyzed. Indicates the element number being detected. Indicates the testing cycle number. Indicates the first The first analytical sample The detected element is in the first The original response values ​​within each detection period. Based on this, a detection response matrix can be constructed.

[0137] S1053, based on the response change characteristics of the same detection element in the detection response matrix between adjacent detection cycles, determine the effective response range of each detection element, and calculate the effective detection value of each detection element based on the effective response range.

[0138] In some embodiments, the response change rate can be determined based on the ratio between the difference between the original response values ​​of two adjacent detection cycles and the original response value of the previous detection cycle.

[0139] If the rate of change of response within a certain continuous detection period is less than a first preset threshold, and the relative standard deviation of response within the continuous detection period is less than a second preset threshold, then the continuous detection period is determined as a candidate stable interval.

[0140] Furthermore, abnormal segments are eliminated from the candidate stable intervals to obtain the effective response intervals. These abnormal segments may include a sudden spike in the initial sample injection period, a signal tailing period, and abnormal fluctuations. The sudden spike in the initial sample injection period can be caused by the instantaneous entry of residual washing solution, soluble salts, or suspended fine particles from the analytical sample into the detection system; the signal tailing period can be caused by hysteresis responses due to organic colloids, iron-manganese colloids, or clay particles; and the abnormal fluctuations can be caused by non-uniform sample injection or instantaneous instrument disturbances. By determining the effective response interval, the impact of unstable detection cycles on elemental detection data can be reduced.

[0141] After determining the effective response interval, the original response values ​​within the effective response interval can be calculated using the mean, median, weighted mean, blank-corrected mean, or standard-sample-corrected mean to obtain the effective detection value for the corresponding detection element. This effective detection value is used for subsequent calculations of the rinsing offset index, matrix inhibition index, local background value, and corrected detection value.

[0142] S1054, according to the preset element rinsing response attribute table, extract the first element data set corresponding to the rinsing stable element and the second element data set corresponding to the rinsing sensitive element from the effective detection values ​​of multiple detection elements of the same analytical sample.

[0143] In some embodiments, the element rinsing response attribute table is used to record the rinsing response attributes of different detected elements in rinsing samples in forest swamp areas.

[0144] Rinse response attributes can include rinse-stable attributes and rinse-sensitive attributes. Detection elements with rinse-stable attributes are identified as rinse-stable elements, and detection elements with rinse-sensitive attributes are identified as rinse-sensitive elements.

[0145] Rinse-stabilizing elements are elements used to characterize the mineral framework of analytical samples. These elements are relatively unaffected by dissolution, migration, colloidal adsorption and redistribution, or fine particle loss during the rinsing process, thus serving as a reference for a relatively stable mineral framework in the analytical sample. Rinse-stabilizing elements may include one or more of Ti, Zr, Al, Sc, Y, Nb, and Hf.

[0146] Rinse-sensitive elements are elements used to characterize the degree to which an analytical sample is affected by the rinsing process. These elements are easily affected by water washing, dissolution, adsorption, desorption, colloidal migration, or fine particle loss during rinsing, and therefore can be used to characterize the extent to which an analytical sample is affected by the rinsing process. The rinsing-sensitive elements may include one or more of Na, K, Ca, Mg, Sr, Ba, Fe, Mn, S, and P.

[0147] It should be noted that both the first and second element datasets originate from the element detection data of the same analytical sample. In other words, this implementation does not treat different samples as separate rinsing stable and rinsing sensitive samples, nor does it set up additional control samples. Instead, it extracts different element datasets from the valid detection values ​​of multiple elements within the same analytical sample according to a preset element rinsing response attribute table.

[0148] S1055, determine the rinsing offset index of the analytical sample based on the degree of deviation of the second element data set relative to the first element data set.

[0149] In some embodiments, the valid detection values ​​in the first and second element datasets can be standardized first. The standardization process can employ one or more of the following: logarithmic transformation, robust Z-score transformation, median normalization, quantile normalization, or batch standardization.

[0150] After standardization, first and second standardized data are obtained. Then, the overall deviation of the second standardized data from the first standardized data is calculated, and this overall deviation is used as the rinsing offset index of the analytical sample.

[0151] For example, the absolute value of the difference between the standardized mean of the rinsing-sensitive elements and the standardized mean of the rinsing-stable elements can be calculated, and this absolute value can be used as the rinsing deviation index. Alternatively, weights can be assigned to different rinsing-sensitive elements, and the rinsing deviation index can be calculated based on the weighted deviation. The larger the rinsing deviation index, the greater the deviation of the rinsing-sensitive elements in the analytical sample from the mineral framework reference, indicating that the analytical sample is more strongly affected by element migration, loss, enrichment, or re-adsorption caused by the rinsing process.

[0152] S1056, extract the effective detection value of the matrix indicator element from the effective detection values ​​of multiple detection elements of the same analytical sample, and determine the matrix inhibition index of the analytical sample based on the effective detection value of the matrix indicator element.

[0153] In some embodiments, the matrix indicator element is an element used to characterize the matrix interference state of the analytical sample. This matrix indicator element is derived from elemental detection data of the same analytical sample, rather than from a separately set matrix control sample. The matrix interference state includes one or more of the following: the influence state of iron-manganese colloids, the influence state of clay particles, the influence state of soluble salts or exchangeable ions, and the influence state of organic matter.

[0154] Specifically, the influence of iron-manganese colloids is determined based on the effective detection values ​​of Fe and Mn. The effective detection values ​​of Fe and Mn are used to characterize the effects of iron-manganese oxides, iron-manganese colloids, or changes in redox conditions in the sample on the adsorption, co-precipitation, or release of the target elements.

[0155] The influence of clay fine particles was determined based on the effective detection values ​​of Al, Ti, and Zr. The effective detection values ​​of Al, Ti, and Zr were used to characterize the influence of clay fine particles, fine-grained minerals, or mineral framework components in the sample on the detection results of the target elements.

[0156] The influence of soluble salts or exchangeable ions is determined based on the effective detection values ​​of Na, K, Ca, and Mg. The effective detection values ​​of Na, K, Ca, and Mg are used to characterize the impact of residual soluble salts, ion-exchange components, or changes in water-soluble components after rinsing on the detection results of the target elements.

[0157] The influence of organic matter is determined based on one or more of the following: sulfur (S), phosphorus (P), organic matter content, and loss on ignition. S, P, organic matter content, and loss on ignition are used to characterize the effects of peat, humus, or reducing organic matrix in the sample on the complexation, adsorption, or signal suppression of target elements.

[0158] The matrix inhibition index of the sample was calculated and analyzed based on the influence components of iron and manganese colloids, clay fine particles, soluble salts or exchangeable ions, and organic matter.

[0159] In one implementation, each influencing component can be standardized, and then a weighted sum of the standardized components can be performed to obtain the matrix suppression index. The weights of each influencing component can be preset based on the sample type, target element type, or historical detection data of the sampling area. The larger the matrix suppression index, the stronger the influence of the matrix interference state of the analyzed sample on the detection results of the target element.

[0160] S1057, determine the neighboring samples of the analyzed sample based on the sample spatial location data, and determine the local background value of the target element based on the effective detection value of the target element in the neighboring samples.

[0161] In some embodiments, neighboring samples can be determined based on a preset search radius, centered on the sampling point of the currently analyzed sample; alternatively, neighboring samples can be determined based on a preset number of sampling points that are spatially closest to the currently analyzed sample. The neighboring samples are those located in the same sampling area, the same sampling grid, the same sampling line, or whose spatial distance meets preset conditions as the currently analyzed sample.

[0162] After identifying neighboring samples, obtain the effective detection values ​​of the target element within those samples. To avoid local extreme outliers affecting background calculations, outlier removal can be performed on the effective detection values ​​of the target element in the neighboring samples. After outlier removal, the local background value of the target element can be calculated using the weighted median, truncated mean, or distance-weighted mean. Neighboring samples closer to the currently analyzed sample can be assigned higher weights.

[0163] S1058, based on the effective detection value of the target element, the rinsing offset index, the matrix inhibition index, and the local background value, the detection value of the target element is reconstructed to obtain the corrected detection value of the target element.

[0164] In some embodiments, the correction detection value can be calculated in the following manner: .

[0165] in, Indicates the first The first analytical sample The corrected detection value of each target element. Indicates the first The first analytical sample The effective detection value of each target element Indicates the first The analytical sample corresponds to the first The local background value of a target element. This represents the rinsing correction factor determined based on the rinsing offset index. This represents the matrix correction factor determined based on the matrix inhibition index.

[0166] S1059, Generate preliminary test results for the analytical sample based on the corrected detection values.

[0167] In some embodiments, preliminary detection results may include one or more of the following: sample number, sample spatial location data, original detection value of target element, effective detection value of target element, rinsing offset index, matrix inhibition index, local background value of target element, corrected detection value of target element, background deviation factor, data quality marker, and anomaly confidence level.

[0168] The background deviation factor can be determined based on the ratio between the corrected detection value of the target element and the local background value. The data quality label can be determined based on factors such as the effective response interval length, the relative standard deviation of the response, the detection limit, the blank correction result, and whether there are abnormal fluctuations in the effective response interval. The anomaly confidence level can be determined jointly based on the degree of deviation of the corrected detection value from the local background value, the wash-off index, the matrix suppression index, and the data quality label.

[0169] In this way, without introducing additional control samples, this embodiment utilizes multi-element, multi-period detection data within the same analytical sample to complete the extraction of effective detection values, quantification of rinsing effects, evaluation of matrix interference, determination of local background, and reconstruction of target element detection values, thereby obtaining preliminary detection results suitable for geochemical anomaly identification in forest and swamp areas.

[0170] S106. Based on the preliminary test results, and in conjunction with the changes in sample quality before and after rinsing, changes in target element content, element combination characteristics, element phases, geological background and geophysical information, the geochemical anomalies are reviewed, and the mineral exploration target area is delineated.

[0171] In some embodiments, when determining the preliminary detection results, a verification process of "anomaly review, graded encryption, geological survey, elemental phase analysis, geophysical exploration combined with target area delineation" is further executed to distinguish between true and false anomalies from multiple dimensions and accurately locate mineral exploration target areas.

[0172] In one embodiment, step S106 may include:

[0173] S1061, in response to the first round of geochemical measurements delineating anomalies and identifying the existence of anomalous high-value points, for the anomalous high-value points and their adjacent background points, sampling and re-testing are performed again according to the corresponding sampling medium, target particle size and graded composite rinsing process to obtain verification data.

[0174] In some embodiments, when anomaly high-value points are identified, each anomaly high-value point and its adjacent background points are selected for verification sampling. Adjacent background points are preferably located within the same sub-landscape unit, the same sampling medium type, and similar geomorphic locations, avoiding obvious anthropogenic pollution sources. During verification sampling, the coordinates, elevation, geomorphic location, sampling medium, sampling depth, sample color, apparent characteristics of organic matter content, water content, and surrounding geological phenomena of the sampling point are recorded.

[0175] The verification sampling was conducted using the same sampling medium, target particle size, and graded composite rinsing process as the first round of measurements. At least one master sample was collected from each verification point, and field replicates were set up at a ratio of no less than 5% of the total number of samples. For points with significantly prominent outliers, parallel or adjacent sample points could be set up. Samples underwent coarse rinsing in the field, fine rinsing indoors, drying, sieving, homogenization, and fraction reduction before analysis and testing.

[0176] S1062, compare the verification data with the first round of geochemical measurement data, eliminate abnormal points caused by sampling location deviation, sample pretreatment deviation or analysis and testing deviation, and identify abnormal high value points that can be repeated as abnormal points to be verified.

[0177] In some embodiments, the verification data is compared with the initial geochemical measurement data. If the content of the target element in the verification sample is still higher than the corresponding anomaly lower limit, and the relative deviation between the verification data and the initial data is within a preset allowable range, such as no more than 30%, then the high-value anomaly is considered to be reproducible and is identified as an anomaly to be verified. If the verification data is significantly lower than the anomaly lower limit, or there are abnormal differences between field duplicate samples and parallel samples, and verification reveals deviations in sampling location, sampling medium, pretreatment, or analysis and testing, then the corresponding anomaly is removed. For points where the verification data deviates significantly from the initial data but the cause cannot be determined, samples are recollected and a second retest is performed.

[0178] S1063, Taking the anomaly points to be verified as the center, perform hierarchical and encrypted sampling according to their anomaly types, wherein the anomaly sampling in a 1:200,000 scale area is encrypted to 3 to 5 points / km. 2 1:50,000 fine-grained anomaly encryption reduced to 5 to 8 points / km 2 , to obtain encrypted sampling data.

[0179] In some embodiments, the encrypted sampling points are preferably arranged along the long axis of the anomaly, perpendicular to the long axis of the anomaly, and along the main water system, ditch system, or structural distribution direction, in order to control the anomaly boundary, the anomaly concentration center, and the anomaly migration direction.

[0180] S1064, Based on the encrypted sampling data, delineate the abnormal boundary, determine the abnormal concentration center, and identify the element combination characteristics, and identify the area where the abnormal boundary, abnormal concentration center, and element combination characteristics are consistent as the key abnormal area for investigation.

[0181] In some embodiments, the samples obtained by encrypted sampling are processed according to the sampling medium, target particle size, and graded composite rinsing process specified in this invention, and the contents of the target element and its associated elements are tested. After the test results pass quality control, an element anomaly map is drawn using the contour line method, inverse distance weighted interpolation method, Kriging interpolation method, or gridded statistical method. The anomaly boundary is determined based on the lower limit of the anomaly, the anomaly concentration center is determined based on the local maximum value or continuous high value area of ​​the element content, and the element combination characteristics are identified based on the correlation between the target element and the associated elements, the degree of superposition of combined anomalies, or the zonal characteristics of the element combination.

[0182] An area is designated as a key anomaly area for investigation when it simultaneously meets the following conditions: First, the encrypted sampling results can form a relatively continuous anomaly boundary; second, one or more anomaly concentration centers exist within the anomaly area; third, the target element and indicator elements or associated elements form an element combination that matches the target mineral type; fourth, the anomaly area is not controlled by a single isolated sample point. If the anomaly boundary is not closed or the anomaly concentration center is unclear, supplementary sampling can be continued in the direction of the anomaly opening.

[0183] S1065, Conduct geological mapping, alteration surveys and mineralized rock sampling within the key verification anomaly area, determine the lithology, structure, alteration and mineralization characteristics of the key verification anomaly area, and determine the location for collecting representative samples based on the lithology, structure, alteration and mineralization characteristics.

[0184] In some embodiments, the geological mapping scale can be 1:50,000, or it can be adjusted to a larger scale depending on the scale of the anomaly and the stage of the work. The geological survey content includes lithological assemblage, stratigraphic contact relationships, fault structures, fold structures, rock mass boundaries, vein distribution, alteration type, alteration intensity, mineralization type, and mineralization occurrence.

[0185] During the investigation, geological routes traversing the anomaly concentration center, anomaly transition zone, and anomaly edge zone are preferred. The route direction should ideally be perpendicular to the anomaly's long axis, major tectonic lines, or the direction of alteration zone distribution. Locations and descriptions should be made of any discovered silicification, sericitization, chloritization, carbonatization, limonite mineralization, pyrite mineralization, malachite mineralization, lead-zinc mineralization, or other alteration and mineralization phenomena related to the target mineral, and mineralized rock samples, altered rock samples, and surrounding rock control samples should be collected.

[0186] Based on the anomaly boundaries, anomaly concentration centers, and elemental assemblage characteristics determined by encrypted sampling data, and combined with geological mapping, alteration surveys, and mineralized rock sampling results, the key anomaly areas were divided into anomaly concentration center zones, anomaly transition zones, anomaly edge zones, and background control zones. The anomaly concentration center zone is the area with the highest target element content, good elemental assemblage, or proximity to mineralized alteration sites; the anomaly transition zone is the area outside the anomaly concentration center zone where element content begins to decrease; the anomaly edge zone is the area close to the lower limit of the anomaly; and the background control zone is the area within the same sub-landscape unit, with consistent sampling media, and where no anomalies are observed in the target elements.

[0187] S1066, Perform elemental phase analysis on the representative sample to test the occurrence ratio of the target element in the sulfide phase, oxide phase, organic complex phase and clay adsorbed phase.

[0188] S1067, when the proportion of the sulfide phase and / or oxide phase of the target element is higher than that of the organic complex phase and clay adsorption phase, and the abnormal concentration center has a spatial correspondence with the geological structure, alteration zone or mineralization body, the corresponding key verification anomaly area is determined as a candidate mineral-induced anomaly area.

[0189] In one example, the candidate mineralization anomaly zone is determined as follows: Based on the encrypted sampling data, the key anomaly zone is divided into anomaly concentration center zone, anomaly transition zone, anomaly edge zone, and background control zone, and representative samples are collected for each zone; the total amount of target elements, organic carbon content, loss on ignition, particle size distribution, and the phase ratio of target elements in sulfide phase, oxide phase, organic complex phase, and clay adsorbed phase are tested in the representative samples; the effective mineralization phase ratio is determined based on the sulfide phase ratio and oxide phase ratio, and the organic matter-adsorption interference phase ratio is determined based on the organic complex phase ratio and clay adsorbed phase ratio; the mineralization is determined based on the ratio of the effective mineralization phase ratio to the organic matter-adsorption interference phase ratio. The dominance coefficient is determined based on the proportion of organic matter-adsorption interference phase, organic carbon content, and loss on ignition. When the total amount of target elements decreases progressively from the abnormal concentration center zone, abnormal transition zone, abnormal edge zone to the background control zone, and the proportion of effective ore-forming phase decreases synchronously, and the dominance coefficient of ore-forming phase is higher than the preset dominance threshold and the organic interference coefficient is lower than the preset interference threshold, the corresponding anomaly is determined as a preliminary favorable mineral-induced anomaly. When the increase in the total amount of target elements is synchronous with the increase in organic carbon content, loss on ignition, proportion of organic complex phase, or proportion of clay adsorption phase, and the organic interference coefficient is higher than the preset interference threshold, the corresponding anomaly is determined as an organic matter interference type anomaly or a clay adsorption type anomaly.

[0190] Specifically, representative samples were tested for total target element content, organic carbon content, loss on ignition, particle size distribution, and elemental phase state.

[0191] The total amount of the target element can be determined using inductively coupled plasma mass spectrometry (ICP-MS), inductively coupled plasma atomic emission spectrometry (ICP-AES), atomic absorption spectrometry (AES), atomic fluorescence spectrometry (AES), or X-ray fluorescence spectrometry (XRF). The specific testing method depends on the type of target element. For example, copper, lead, zinc, nickel, and cobalt can be tested using ICP-AES or mass spectrometry; arsenic, antimony, and mercury can be tested using AES or mass spectrometry; and gold can be tested using foam adsorption, fire assay, or plasma mass spectrometry.

[0192] Organic carbon content can be tested using a total organic carbon analyzer or conventional methods such as the potassium dichromate titration method. Loss on ignition can be calculated by burning the sample at a preset temperature and determining the mass loss; preferably, it is obtained by burning at 550°C for 2 to 4 hours. Particle size distribution can be determined using sieving, laser particle size analysis, or a combination of both.

[0193] Elemental phase analysis is used to determine the occurrence ratio of target elements in sulfide, oxide, organic complex, and clay adsorbed phases. It can be performed using either continuous chemical extraction or stepwise selective extraction. Taking continuous chemical extraction as an example, the sample is first extracted from the clay adsorbed phase to obtain the content of target elements adsorbed or weakly bound on the clay surface; then, the organic complex phase is extracted to obtain the content of target elements complexed with humic substances, organic acids, or organic colloids; next, the oxide phase is extracted to obtain the content of target elements bound to iron and manganese oxides, hydroxides, or secondary oxides; finally, the sulfide phase is extracted to obtain the content of target elements bound to sulfide minerals. The target elements in each phase extract are then tested separately.

[0194] To ensure the reliability of elemental phase analysis results, blank samples, parallel samples, and standard substances or internal control samples are prepared for each batch of samples. The recovery rate between the sum of the extraction results of each phase and the total amount of the target element is preferably controlled within the range of 80% to 120%; the relative deviation of parallel samples is preferably no more than 20%. If the recovery rate or the deviation of parallel samples exceeds the preset range, the sample extraction and testing are repeated.

[0195] S1068, geophysical verification is performed by superimposing high-precision magnetic and induced polarization methods on the candidate ore-induced anomaly area to obtain geophysical anomaly information.

[0196] In some embodiments, high-precision magnetic surveys and induced polarization gradient measurements are superimposed on candidate mineral-induced anomaly zones for comprehensive verification. Geophysical survey lines are preferably laid out perpendicular to the long axis of the anomaly, the main structural direction, or the direction of the alteration zone. Depending on the size of the candidate mineral-induced anomaly zone, the magnetic survey line spacing can be set to 50m to 200m, and the point spacing can be set to 10m to 50m; the induced polarization gradient measurement line spacing can be set to 100m to 200m, and the point spacing can be set to 20m to 50m. Specific parameters can be adjusted according to topographic conditions, anomaly size, and target mineral type.

[0197] High-precision magnetic surveys are used to identify magnetic anomalies associated with magnetic minerals, basic or ultrabasic rock masses, pyrrhotite-bearing mineralization, and tectonic fracture zones. Induced polarization gradient measurements are used to identify apparent polarizability and apparent resistivity anomalies associated with sulfide mineralization, disseminated mineralization, graphitization, or conductive mineral bodies. After diurnal variation correction, topographic correction, noise removal, smoothing, and anomaly interpretation, geophysical anomaly information is obtained, including the peak location, direction, extent, intensity, and gradient changes of geophysical anomalies.

[0198] S1069, when the geophysical anomaly information has a spatial correspondence with the anomaly concentration center, the element combination characteristics, and the geological structure, alteration zone, or mineralized body, the candidate mineralized anomaly area is determined as a favorable mineralized anomaly area.

[0199] In some implementations, spatial correspondence may include at least one of the following: the distance between the peak location of the geophysical anomaly and the anomaly concentration center is less than one densified sampling point distance; the angle between the geophysical anomaly distribution direction and the long axis direction of the geochemical anomaly is not greater than 30°; the geophysical anomaly is located in the direction of the extension of the fault structure, alteration zone, or mineralized body; the induced polarization anomaly center coincides with the concentration area of ​​sample points with a high proportion of effective mineralized facies; the magnetic anomaly gradient zone corresponds to the tectonic fracture zone or the contact zone of the rock mass.

[0200] If a candidate mineral-induced anomaly area lacks obvious geophysical anomalies, but has strong geochemical anomalies, elemental phase analysis results, and geological mineralization phenomena, it can be listed as an anomaly area to be further verified. If the geophysical anomalies of a candidate mineral-induced anomaly area are significantly misaligned with geochemical anomalies, geological structures, or alteration mineralization phenomena, and cannot be explained by topography, overburden, or physical property differences, its evaluation level will be reduced.

[0201] S1070, conduct 80 to 250 points / km within the favorable mineralization anomaly zone. 2 Large-scale soil surveys are conducted to further determine the location of anomaly peaks, the direction of anomaly distribution, and the boundary of anomaly closure based on the results of the large-scale soil surveys. Based on this, prospecting target areas are delineated, and engineering verification locations for trenching and / or drilling are determined.

[0202] In some embodiments, 80 to 250 points / km are conducted within favorable mineralized anomaly zones. 2 Large-scale soil surveying. Preferably, the survey scale is 1:10000. The sampling grid can be set to 100m×100m, 100m×50m, 80m×80m, or other grids that can meet the requirements of 80 to 250 points / km, depending on the anomaly scale and terrain conditions. 2 The sampling density grid can be further densified at locations with abnormal peaks, structural intersections, areas of intense alteration, or the center of geophysical anomalies.

[0203] Large-scale soil samples were collected using the same sampling medium, target particle size, and sample pretreatment process as the aforementioned intensive sampling. After testing the content of the target element and its associated elements, a large-scale geochemical anomaly map was drawn, and the anomaly peak location, anomaly distribution direction, and anomaly closure boundary were determined. The anomaly peak location is the area with the highest content of the target element or the strongest superposition of element combinations; the anomaly distribution direction is determined based on the long axis direction of the anomaly contour lines, the direction of the arrangement of consecutive high-value points, or the zonal direction of element combinations; the anomaly closure boundary is delineated based on the lower limit of the large-scale anomaly measurement.

[0204] The results of large-scale soil measurements are overlaid with the aforementioned geological mapping, alteration surveys, mineralized rock samples, elemental phase analysis results, and geophysical anomaly information. When the anomaly peak location, high-value area of ​​effective ore-forming facies, tectonic alteration zone, mineralized body or mineralization clue, and geophysical anomaly center correspond spatially, they are delineated as mineral exploration target areas.

[0205] The location for engineering verification is determined based on the degree of overlap of multi-source information within the target area. Preferably, trenching is deployed perpendicular to the long axis of the anomaly, allowing the trench lines to traverse the anomaly peak area, alteration zone, and structural zone; drilling is deployed where the target element anomaly peak, high effective ore-forming facies, induced polarization anomaly center, magnetic anomaly gradient zone, and geological structures or alteration mineralization areas coincide. The borehole azimuth and dip are determined based on the mineralization body occurrence, structural dip, geophysical anomaly dip, and topographic conditions.

[0206] Through the above steps, this embodiment can start from the first round of abnormal high value points, eliminate human error, organic matter interference anomalies and clay adsorption anomalies step by step, and finally delineate the mineral exploration target area and engineering verification location through the joint verification of geochemical, elemental phase, geological and geophysical information.

[0207] The geochemical exploration methods for swamp forest-covered areas have been described in detail above through some embodiments. To enable those skilled in the art to better understand and implement them, the corresponding systems are also described in detail below through some embodiments.

[0208] See Figure 2 , Figure 2This is a schematic diagram of the structure of a geochemical exploration system for swamp forest cover areas provided by the present invention. Figure 2 As shown, the geochemical exploration system 200 for swamp forest cover areas may include:

[0209] Division unit 210 is used to divide the work area into multiple sub-landscape areas based on the degree of water system development, ditch system development, landform type, swamp distribution, permafrost distribution and peat development characteristics of the work area;

[0210] The selection unit 220 is used to select the corresponding sampling medium for the corresponding sub-landscape area according to the material source accumulation characteristics and surface medium development characteristics of the different sub-landscape areas.

[0211] The determining unit 230 is used to determine the sampling particle size of the corresponding sampling medium based on the type of the sampling medium, the corresponding climate type, the target mineral type, and the occurrence and enrichment characteristics of the target element.

[0212] The rinsing unit 240 is used to sequentially perform coarse rinsing and ultrasonic fine rinsing on the sampling medium to obtain an analytical sample.

[0213] The exploration unit 250 is used to perform elemental content detection on the analytical sample, obtain preliminary detection results, and, based on the preliminary detection results and in combination with the changes in sample quality before and after rinsing, changes in target element content, element combination characteristics, element phases, geological background and geophysical information, verify geochemical anomalies and delineate mineral exploration target areas.

[0214] For further details regarding the division unit 210, selection unit 220, determination unit 230, rinsing unit 240, and exploration unit 250, please refer to the aforementioned examples.

[0215] It is understandable that the above division of units is only a logical functional division. In actual implementation, they can be fully or partially integrated into a single physical entity, or they can be physically separated. Furthermore, the above units can be implemented by the processor calling software.

[0216] The specific embodiments described above further illustrate the purpose, technical solution, and beneficial effects of this application. It should be understood that the above description is only a specific embodiment of this application and is not intended to limit the scope of protection of this application. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the scope of protection of this application.

Claims

1. A method for geochemical exploration of swamp forest cover areas, characterized in that, include: Based on the degree of water system development, gully system development, landform type, swamp distribution, permafrost distribution, and peat development characteristics of the work area, the work area is divided into multiple sub-landscape areas; Based on the material source accumulation characteristics and surface medium development characteristics of different sub-landscape areas, corresponding sampling media are selected for the sub-landscape areas; The sampling particle size of the sampling medium is determined based on the type of the sampling medium, the corresponding climate type, the target mineral type, and the occurrence and enrichment characteristics of the target elements. The sampling medium was subjected to coarse rinsing and ultrasonic fine rinsing in sequence to obtain the analytical sample; Elemental content detection was performed on the analyzed sample to obtain preliminary detection results; Based on the preliminary test results, and in conjunction with the changes in sample quality before and after rinsing, changes in target element content, element combination characteristics, element phases, geological background and geophysical information, the geochemical anomalies were reviewed, and mineral exploration target areas were delineated.

2. The geochemical exploration method for swamp forest cover areas according to claim 1, characterized in that, The multiple sub-landscape areas include: water system development area, water system undeveloped but gully system developed area, water system and gully system undeveloped area, and meadow marsh area; Based on the source accumulation characteristics and surface medium development characteristics of different sub-landscape areas, corresponding sampling media are selected for each sub-landscape area, including: In response to the sub-landscape area being the water system development area, water system debris sediments are collected in the water system development area. When peat is rich in the water system and it is difficult to obtain qualified water system debris sediments, mineral residues at the bottom of the peat layer, peat-mineral mixed layer, or peat mineral components after rinsing and separation are collected as the sampling medium. In response to the fact that the sub-landscape area is an area with underdeveloped water system but developed gully system, gully sediments were collected; In response to the fact that the sub-landscape area is a region where neither water system nor ditch system is developed, residual slope soil, rock debris, or rock debris-soil mixture were collected. In response to the sub-landscape area being a meadow-swamp area, swamp soil or meadow soil was collected.

3. The geochemical exploration method for swamp forest cover areas according to claim 2, characterized in that, The step of determining the sampling particle size of the sampling medium based on its type, corresponding climate type, target mineral type, and occurrence and enrichment characteristics of the target elements includes: For the riparian sediments in the cold temperate mid-low mountain permafrost region, select those with a particle size of 4 mesh and retain 40 mesh, or select those with a particle size of 10 mesh and retain 60 mesh. For stream sediments in the mid-temperate low and medium mountain and hilly areas, select sediments with a particle size of less than 20 mesh or less than 40 mesh. When multiple target elements need to be considered, a mixed particle size of over 10 mesh with 40 mesh and over 60 mesh is adopted. Valley sediments should be selected from particle sizes of 20 mesh, 40 mesh, or 60 mesh, with 60 mesh preferred when gold and silver are the target elements. When molybdenum is the target element in residual colluvial soil or rock debris, a particle size of 10 mesh or less with a 60 mesh size retained should be selected; when gold or silver is the target element, a particle size of 60 mesh or less should be selected. Samples from the humus-developing area were selected from 80-mesh fine-grained samples.

4. The geochemical exploration method for swamp forest cover areas according to claim 3, characterized in that, The sampling network and sampling density are set according to the source coverage of different sampling media, wherein: Debris sediments from the stream were sampled using a 500m × 500m grid at a density of 4 points / km. 2 ; Valley sediments were sampled using a 500m × 400m grid at a density of 5 points / km. 2 ; Soil, rock cuttings, or rock cuttings-soil mixtures were sampled using a 500m × 250m grid at a density of 8 points / km. 2 ; When the width of the gully exceeds the preset width, multiple sub-sampling points are set up along the vertical direction of the gully, and the samples from multiple sub-sampling points are mixed to form a composite sample; soil, rock debris, or rock debris-soil mixture sampling points are preferentially set up at the foot of the slope, gentle slope, gully mouth, sediment collection site, or source collection site.

5. The geochemical exploration method for swamp forest cover areas according to claim 1, characterized in that, The coarse rinsing includes: Place the sampling medium into a non-metallic washing dish, add water until the sample is completely submerged, soak for 1 to 3 minutes, and disperse any sample clumps. Keep the non-metallic washing tray half-submerged in water, and use the density difference to float out plant residues, dead branches and light organic impurities by circumferential oscillation and small up-and-down agitation, repeating 2 to 3 times; Increase the agitation amplitude to remove the free clay, surface peat and loose organic matter attached to the surface of the mineral particles. Stop agitating when the rinsing water reaches the preset turbidity level. The tailings generated during the rinsing process are collected and subjected to secondary washing to recover heavy minerals and fine-grained indicator minerals. After coarse rinsing, drain the water from the sample and seal it for storage.

6. The geochemical exploration method for swamp forest cover areas according to claim 1 or 5, characterized in that, The ultrasonic rinsing includes: The sample after coarse rinsing is placed in a cleaning container, and deionized water with a volume of 3 times the sample volume is added. The mixture is then mechanically stirred for 5 minutes to pre-disperse peat flocs and organic matter aggregates. The pre-dispersed samples were subjected to ultrasonic treatment at 40kHz to 80kHz. The conventional samples were treated for 10 to 15 minutes, and the high peat or high humus samples were treated for 15 minutes. The settling time is controlled according to the target particle size and target mineral density. When the target is a fine-grained precious metal carrier or a fine-grained sulfide carrier, the upper suspension is decanted after settling for 5 to 10 seconds. When the target is a coarser sulfide, oxide, or detrital mineral carrier, the upper suspension is decanted after settling for 10 to 15 seconds. The final wash was performed with deionized water, and the washed sample was dried at a low temperature not exceeding 60°C.

7. The geochemical exploration method for swamp forest cover areas according to claim 1, characterized in that, The step of performing elemental content detection on the analytical sample to obtain preliminary detection results includes: Obtain elemental detection data of the analytical sample, the elemental detection data including the original response data of multiple elements detected in the analytical sample in multiple detection cycles, sample number and sample spatial location data; A detection response matrix is ​​constructed based on the original response data. The detection response matrix is ​​used to characterize the response change relationship of different detected elements in the same analytical sample in different detection cycles. Based on the response change characteristics of the same detection element in the detection response matrix between adjacent detection cycles, the effective response range of each detection element is determined, and the effective detection value of each detection element is calculated based on the effective response range. Based on the preset element rinsing response attribute table, extract the first element data set corresponding to the rinsing stable element and the second element data set corresponding to the rinsing sensitive element from the effective detection values ​​of multiple detection elements of the same analytical sample. The rinsing offset index of the analytical sample is determined based on the degree of deviation of the second element data set relative to the first element data set. The effective detection values ​​of matrix indicator elements are extracted from the effective detection values ​​of multiple detection elements in the same analytical sample, and the matrix inhibition index of the analytical sample is determined based on the effective detection values ​​of the matrix indicator elements. The neighboring samples of the analytical sample are determined based on the spatial location data of the sample, and the local background value of the target element is determined based on the effective detection value of the target element in the neighboring samples. Based on the effective detection value of the target element, the rinsing offset index, the matrix inhibition index, and the local background value, the detection value of the target element is reconstructed to obtain the corrected detection value of the target element. Preliminary test results for the analyzed sample are generated based on the corrected test values.

8. The geochemical exploration method for swamp forest cover areas according to claim 1, characterized in that, Based on the preliminary detection results, and in conjunction with changes in sample mass before and after rinsing, changes in target element content, elemental combination characteristics, elemental phases, geological background, and geophysical information, the geochemical anomalies are reviewed to delineate prospecting target areas, including: In response to the first round of geochemical measurements that delineated anomalies and identified high-value points, sampling and re-testing were performed again for the high-value points and their adjacent background points according to the corresponding sampling medium, target particle size and graded composite rinsing process to obtain verification data. The verification data is compared with the first round of geochemical measurement data to eliminate outliers caused by sampling location deviation, sample pretreatment deviation, or analysis and testing deviation, and the recurring high-value outliers are identified as outliers to be verified. Centered on the anomaly point to be verified, hierarchical encrypted sampling is performed according to its anomaly type to obtain encrypted sampling data; Based on the encrypted sampling data, the abnormal boundaries are delineated, the abnormal concentration center is determined, and the element combination characteristics are identified. The areas where the abnormal boundaries, abnormal concentration centers, and element combination characteristics are consistent are identified as key areas for verification of abnormalities. Geological mapping, alteration surveys, and mineralized rock sampling were carried out in the key verification anomaly area to determine the lithology, structure, alteration, and mineralization characteristics of the key verification anomaly area, and the collection locations of representative samples were determined based on the lithology, structure, alteration, and mineralization characteristics. Elemental phase analysis was performed on the representative samples to test the occurrence ratio of the target element in the sulfide phase, oxide phase, organic complex phase and clay adsorption phase. When the proportion of sulfide phase and / or oxide phase of the target element is higher than that of organic complex phase and clay adsorption phase, and the abnormal concentration center has a spatial correspondence with geological structure, alteration zone or mineralization body, the corresponding key verification anomaly area will be identified as a candidate mineral-induced anomaly area. High-precision magnetic and induced polarization gradient methods were superimposed on the candidate mineral anomaly areas for geophysical verification to obtain geophysical anomaly information; When the geophysical anomaly information has a spatial correspondence with the anomaly concentration center, the element combination characteristics, and the geological structure, alteration zone, or mineralized body, the candidate mineralized anomaly area is determined as a favorable mineralized anomaly area. Large-scale soil surveys are conducted within the favorable mineral-causing anomaly zone. Based on the results of the large-scale soil surveys, the location of the anomaly peak, the direction of the anomaly distribution, and the anomaly closure boundary are further determined. Based on this, the prospecting target area is delineated, and the engineering verification locations for trenching and / or drilling are determined.

9. The geochemical exploration method for swamp forest cover areas according to claim 8, characterized in that, The candidate mineral-induced anomaly zone is determined using the following method: Based on the encrypted sampling data, the key areas for anomaly investigation are divided into an abnormal concentration center zone, an abnormal transition zone, an abnormal edge zone, and a background control zone, and representative samples are collected for each zone. The total amount of target elements, organic carbon content, loss on ignition, particle size composition, and the phase ratio of target elements in sulfide phase, oxide phase, organic complex phase, and clay adsorbed phase of the representative sample were tested. The effective mineralization phase ratio is determined based on the sulfide phase ratio and the oxide phase ratio, and the organic matter-adsorption interference phase ratio is determined based on the organic complex phase ratio and the clay adsorption phase ratio. The ore-forming phase dominance coefficient is determined based on the ratio of the effective ore-forming phase proportion to the organic matter-adsorption interference phase proportion. The organic interference coefficient is determined based on the organic matter-adsorption interference phase ratio, organic carbon content, and loss on ignition. When the total amount of target elements decreases step by step from the abnormal concentration center zone, abnormal transition zone, abnormal edge zone to the background control zone, and the proportion of effective mineralized facies decreases synchronously, and the mineralized facies dominance coefficient is higher than the preset dominance threshold and the organic interference coefficient is lower than the preset interference threshold, the corresponding anomaly is determined to be a preliminary favorable mineral-induced anomaly. When the increase in the total amount of the target element is synchronous with the increase in organic carbon content, loss on ignition, proportion of organic complexes or proportion of clay adsorption, and the organic interference coefficient is higher than the preset interference threshold, the corresponding anomaly is identified as an organic matter interference anomaly or a clay adsorption anomaly.

10. A geochemical exploration system for swamp forest cover areas, characterized in that, include: The division unit is used to divide the work area into multiple sub-landscape areas based on the degree of water system development, ditch system development, landform type, swamp distribution, permafrost distribution, and peat development characteristics of the work area; The selection unit is used to select the corresponding sampling medium for the sub-landscape area based on the material source accumulation characteristics and surface medium development characteristics of different sub-landscape areas. The determining unit is used to determine the sampling particle size of the sampling medium based on the type of the sampling medium, the corresponding climate type, the target mineral type, and the occurrence and enrichment characteristics of the target element. The rinsing unit is used to sequentially perform coarse rinsing and ultrasonic fine rinsing on the sampling medium to obtain analytical samples; The exploration unit is used to perform elemental content detection on the analytical sample, obtain preliminary detection results, and, based on the preliminary detection results and in combination with the changes in sample quality before and after rinsing, changes in target element content, elemental combination characteristics, elemental phases, geological background and geophysical information, to verify geochemical anomalies and delineate mineral exploration target areas.

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