CN-121980533-A - Copper mine target area prediction method and system based on multisource information data analysis

Abstract

The invention provides a copper mine target area prediction method and system based on multi-source information data analysis, and relates to the technical field of computers, wherein multi-source copper mine related basic information such as surface rock outcrop records, soil element content data, regional gravity observation data, remote sensing image characteristic data, geological structure mapping data and the like of a target region are collected; the method comprises the steps of carrying out a cue tracing mapping process on multi-source basic information to generate a plurality of groups of tracing cue sets, carrying out a space-time coupling networking process on the plurality of groups of tracing cue sets to construct a dynamic coupling cue network, carrying out a signal resonance strengthening process on the dynamic coupling cue network to generate a resonance strengthening network, finally carrying out a target zone convergence defining process on the basis of the resonance strengthening network to generate a copper mine target zone prediction result, gradually reducing the range of a potential area of the ore, and the generated target zone copper mine target zone prediction result has higher accuracy and reliability, can effectively guide copper mine exploration work, improves exploration efficiency and success rate, and reduces exploration cost.

Inventors

• LI JUN
• GU TAO
• LING YAJUN
• MENG BIAO
• HUANG DEZHI
• HU JIE
• TANG HU
• CHEN CHAOLIN
• REN HAITAO
• FU MINGZHU

Assignees

• 四川省第四地质大队

Dates

Publication Date

20260505

Application Date

20260409

Claims (10)

1. 1. A copper mine target area prediction method based on multi-source information data analysis, the method comprising: Acquiring multi-source copper mine related basic information which is easy to acquire in a target area, wherein the multi-source copper mine related basic information comprises surface rock outcrop records, soil element content data, regional gravity observation data, remote sensing image characteristic data and geological structure mapping data; performing cue tracing mapping processing on the multi-source copper mine related basic information, tracing the original cue sources related to copper mine formation in each basic information, and generating a plurality of groups of tracing cue sets; performing space-time coupling networking treatment on the plurality of groups of tracing cue sets, and constructing a dynamic coupling cue network by combining the space position corresponding to the tracing cue and the time sequence of the ore formation; performing signal resonance enhancement processing on the dynamic coupling clue network, enhancing the expression of the ore-forming related signals through the ore-forming logic resonance effect among the trace clues, and generating a resonance enhancement network; and based on the signal distribution and coupling relation in the resonance strengthening network, performing target zone convergence definition processing, gradually reducing the range of the potential area of the ore, and generating a copper mine target zone prediction result of the target area.
2. 2. The method for copper mine target area prediction based on multi-source information data analysis according to claim 1, wherein the performing a cue tracing mapping process on the multi-source copper mine related basic information, tracing the original cue sources related to copper mine formation in each basic information, and generating a plurality of groups of tracing cue sets includes: decomposing the surface rock outcrop record into rock type description, mineral composition record, structural feature and outcrop spatial position information, and generating a rock outcrop basic data set, wherein the rock outcrop basic data set is a structured presentation of the surface rock outcrop record; Defining cue traceability dimensions aiming at the rock outcrop basic data set, wherein the cue traceability dimensions comprise mineral cause traceability, rock formation environment traceability and construction influence traceability; Constructing a mineral source tracing path based on a mineral evolution related record of copper mine formation, extracting mineral source tracing clues related to the copper mine formation from the rock outcrop basic data set along the mineral source tracing path, and marking related path related contents of formation of each mineral and the copper mine formation; constructing a rock formation environment tracing path by combining the regional geological evolution related records, screening rock formation environment tracing clues reflecting the favorable environments of the ores from the rock outcrop basic data set according to the rock formation environment tracing path, and marking the geological evolution stage related content corresponding to each trace clue; Constructing a construction influence tracing path by referring to construction movement influence related data on copper mine formation, extracting construction association tracing clues formed by construction movement influence from the rock outcrop basic data set through the construction influence tracing path, and marking corresponding relation related contents formed by construction movement and the tracing clues; Integrating the mineral source tracing clues, the rock forming environment tracing clues and the construction association tracing clues to generate a rock outcrop tracing clue group, wherein the rock outcrop tracing clue group comprises related original clues of the minerals in the surface rock outcrop record; Performing cue tracing processing on the soil element content data, the regional gravity observation data, the remote sensing image characteristic data and the geological structure mapping data by adopting the same cue tracing dimension definition, tracing path construction and tracing cue extraction integration mode, so as to sequentially form a soil element tracing cue group, a gravity observation tracing cue group, a remote sensing image tracing cue group and a geological structure tracing cue group; Adding relevance description of the original source of the copper mine to each trace source in each trace source cue group, classifying and sorting the trace source cue groups added with the relevance description according to basic information types, matching and corresponding each trace source cue group with corresponding basic information related to the multi-source copper mine, and generating a classified trace source cue set; And integrating all the classified trace source thread sets to generate a plurality of groups of trace source thread sets, wherein the groups of trace source thread sets completely trace the original thread sources related to copper ore formation in each basic information.
3. 3. The method for predicting copper mine target area based on multi-source information data analysis according to claim 1, wherein the performing space-time coupling networking processing on the plurality of groups of trace source thread sets and combining the spatial position corresponding to the trace source thread with the ore formation time sequence to construct a dynamic coupling thread network comprises: extracting all tracing threads contained in each tracing thread group in the plurality of groups of tracing thread sets, respectively acquiring spatial position information corresponding to each tracing thread and mining time association information, and generating a space-time basic tracing thread set; Analyzing a time-space evolution related record of copper ore mineralization, and defining a judgment standard of time-space coupling of trace source threads, wherein the judgment standard comprises interaction relations of trace source threads with different time-space dimensions in the mineralization process; Defining a space-time coupling dimension based on the decision criteria, wherein the space-time coupling dimension comprises a space position coupling dimension and a time sequence coupling dimension, and each coupling dimension corresponds to a specific coupling decision criterion; constructing a space-time coupling execution specification, dividing coupling levels according to a space position coupling dimension and a time sequence coupling dimension, and determining coupling modes and coupling ranges of different levels; Labeling the space-time attribute of each trace source thread in the space-time basic trace source thread set, supplementing and perfecting the space position details and the ore forming time association details of the trace source thread, and generating a trace source thread set labeled with the space-time attribute; selecting any one trace from the trace set marked with the space-time attribute as a coupling initial trace, and acquiring the space-time attribute parameter of the coupling initial trace; Screening associated traceable clues, of which the time-space attribute parameters accord with the time-space coupling execution specification requirements, from the traceable clues set of the marked time-space attribute, wherein the associated traceable clues are possible to be coupled with the coupling initial traceable clues on a spatial position or a time sequence; Establishing a space-time coupling relation between the coupling initial tracing clues and the association tracing clues, marking coupling dimensions and coupling basis corresponding to the coupling relation, and generating a single coupling link, wherein the single coupling link records space-time association related content between two tracing clues; Repeating the operations of selecting the coupling initial trace source clues, screening the associated trace source clues and establishing the coupling relation until the trace source clues in all trace source clues sets marked with the space-time attribute participate in the construction of at least one coupling link, and generating an initial coupling link set; And constructing a dynamic coupling clue network by taking the trace clues in each trace clue set marked with the space-time attribute as network nodes and taking the coupling links in the initial coupling link set as connecting channels among the nodes, wherein the dynamic coupling clue network comprises space-time coupling relations among the trace clues.
4. 4. The method for predicting copper mine target area based on multi-source information data analysis according to claim 1, wherein the performing signal resonance enhancement processing on the dynamic coupling clue network, enhancing the expression of the ore-forming related signals by tracing the ore-forming logic resonance effect among clues, and generating a resonance enhancement network comprises: Analyzing the dynamic coupling clue network, extracting all network nodes and coupling links among the nodes, acquiring the traceable clue content corresponding to each network node and the coupling attribute of each coupling link, and generating a resonance processing basic set; defining triggering conditions of trace source thread resonance according to resonance related associated data among different mineral forming factors in the copper mine mineral forming process, wherein the triggering conditions are preconditions for generating a mineral forming logic resonance effect among trace source threads; constructing a resonance strengthening rule set based on the triggering condition, wherein the resonance strengthening rule set prescribes a strengthening mode when different types of traceable clues are combined to generate resonance effect; Performing resonance triggering condition matching on each coupling link in the resonance processing basic set, and judging whether tracing clues corresponding to two network nodes connected by the coupling links meet the resonance triggering condition or not; for the coupling link meeting the resonance triggering condition, strengthening the signal transmission intensity of the coupling link according to a corresponding strengthening mode in the resonance strengthening rule set, and simultaneously supplementing the related information of the tracing clue related to resonance to generate a strengthened coupling link; For the coupling link which does not meet the resonance triggering condition, maintaining the original coupling relation of the coupling link, and incorporating the coupling link into a subsequent network construction according to an original state to generate a basic coupling link; Collecting all the reinforced coupling links and the basic coupling links, and constructing an initial resonance network, wherein the initial resonance network comprises all the coupling links which are reinforced and incorporated in an original state; performing resonance range expansion on the reinforced coupling link in the initial resonance network, and associating other network nodes possibly generating resonance effects in the initial resonance network based on resonance signals of the reinforced coupling link to generate an expanded resonance link; the extended resonance link is fused into the initial resonance network, and the coupling relation and the signal strength between network nodes in the initial resonance network are updated to generate an intermediate resonance network; And carrying out signal integration processing on the intermediate resonance network, unifying signal expression forms of all nodes and links in the intermediate resonance network, and generating a resonance strengthening network.
5. 5. The method for predicting copper mine target area based on multi-source information data analysis according to claim 1, wherein the step of performing target area convergence defining processing based on signal distribution and coupling relation in the resonance strengthening network, gradually narrowing the range of the mine potential area, and generating a copper mine target area prediction result of a target area comprises the following steps: extracting reinforcement signal distribution data and node coupling relation data in the resonance reinforcement network, obtaining dense related data of the spatial concentration area of reinforcement signals and node coupling, and generating target area definition basic data; analyzing the spatial distribution related records of copper ore formation, and defining a target area convergence direction judgment standard, wherein the direction judgment standard is determined based on the spatial distribution related records of the copper ore formation; constructing target area convergence execution specifications, dividing convergence levels according to data related to intensive signal strength and node coupling, wherein each convergence level corresponds to different area reduction amplitude; Boundary division is carried out on the intensive signal space concentrated areas in the target area definition basic data, the initial boundary range of each concentrated area is determined, and a plurality of initial potential areas are generated; performing first-level convergence processing on each initial potential area based on the target area convergence execution specification, and reducing the initial boundary range of the initial potential area according to the strength of the enhanced signal in the initial potential area to generate a first-level convergence area; Analyzing node coupling dense related data in each primary convergence region, carrying out second-level convergence processing on the primary convergence region by combining corresponding convergence levels in the target region convergence execution specification, and further reducing the range of the primary convergence region to generate a secondary convergence region; Extracting the space position coordinates and the region characteristic information of each secondary convergence region, associating the original space data in the related basic information of the multi-source copper mine, and executing the ore formation related matching operation of the secondary convergence region; Performing third-level convergence processing on the secondary convergence region based on the result of the ore-forming related matching operation, reserving a region part with the ore-forming related matching operation result meeting the requirement in the secondary convergence region, removing a region part with the ore-forming related matching operation result not meeting the requirement in the secondary convergence region, and generating a tertiary convergence region; integrating all the three-level convergence regions, eliminating the overlapping part between the three-level convergence regions, and generating a unified convergence region set, wherein each region in the convergence region set bears the association attribute meeting the requirement of the ore formation association matching operation result; based on the convergence region set, acquiring a final boundary range and space coordinates of each region in the convergence region set, and generating a copper mine target region prediction result of the target region, wherein the copper mine target region prediction result defines a region in which copper mine is possibly distributed.
6. 6. The method for predicting copper mine target area based on multi-source information data analysis according to claim 2, wherein the method for performing cue tracing processing on the soil element content data, the regional gravity observation data, the remote sensing image feature data and the geological structure mapping data by adopting the same cue tracing dimension definition, tracing path construction and tracing cue extraction integration mode sequentially forms a soil element tracing cue group, a gravity observation tracing cue group, a remote sensing image tracing cue group and a geological structure tracing cue group, comprises: The soil element content data are disassembled into element type records, element content numerical value records, sampling point space coordinates and sampling depth information, and a soil element basic data set is generated, wherein the soil element basic data set is a structured presentation of the soil element content data; aiming at the soil element basic data set, mineral source tracing, rock forming environment tracing and constructing clue tracing dimension influencing tracing are used for supplementing element migration tracing dimension to generate a soil element tracing dimension set; Constructing an element migration tracing path based on element migration related records of copper ore formation, and generating a soil element complete tracing path set by combining an existing mineral source tracing path, a rock formation environment tracing path and a construction influence tracing path; extracting element source tracing clues, element environment tracing clues and element construction influence tracing clues and element migration tracing clues related to copper mine formation from the soil element basic data set along the soil element complete tracing path set to generate a soil element original tracing clue set; integrating the original trace source cue set of the soil elements to generate a trace source cue set of the soil elements; The regional gravity observation data are disassembled into gravity numerical records, observation point position coordinates, observation time information and observation environment records, a gravity observation basic data set is generated, corresponding clue tracing dimension and path construction modes are used, gravity anomaly cause tracing clues and gravity environment influence tracing clues are extracted, and gravity observation tracing clues are integrated to form a gravity observation tracing clue group; The remote sensing image characteristic data are disassembled into image tone characteristics, texture characteristics, spatial distribution characteristics and abnormal region marks, a remote sensing image basic data set is generated, the image characteristic evolution traceability dimension is supplemented based on a thread traceability dimension definition principle, a complete traceability path is constructed, relevant traceability threads of the remote sensing image in ore formation are extracted, and a remote sensing image traceability thread group is formed in an integrated mode; the geological structure mapping data are disassembled into structure type records, structure scale related descriptions, structure space distribution and structure evolution information, a geological structure basic data set is generated, a structure tracing path set is constructed along a thread tracing dimension definition principle, various tracing threads related to geological structures and mines are extracted, and a geological structure original tracing thread set is generated; integrating and optimizing the geological structure original tracing cue set to generate a geological structure tracing cue group; And comparing the content integrity and the logic consistency of the soil element tracing cue group, the gravity observation tracing cue group, the remote sensing image tracing cue group and the geological structure tracing cue group, and supplementing the trace content of the mine-forming related original cue missing in each tracing cue group through cross matching verification of the tracing cues.
7. 7. The method for copper mine target area prediction based on multi-source information data analysis according to claim 3, wherein the performing space-time attribute labeling on each trace in the space-time basic trace set, supplementing and perfecting spatial position details and ore forming time association details of the trace, and generating a trace set labeled with space-time attributes comprises: extracting each tracing cue in the space-time basic tracing cue set, acquiring the basic information type and core content corresponding to the tracing cue, and generating single tracing cue basic information; searching for the spatial position description in the original record of each trace-source thread aiming at the single trace-source thread basic information of each trace-source thread, and extracting spatial position key information, wherein the spatial position key information comprises geographic identification of the region where the spatial position key information is located, relative reference object position and range description; Based on geographic information standardization correlation requirements, converting the extracted space position key information into uniform space coordinate expression, supplementing precision correlation description of the space position, acquiring a space coverage corresponding to the tracing clue, and generating space attribute details; Analyzing the association relation between the core content of the trace source cue and the copper mine ore forming stage, acquiring an ore forming time interval corresponding to the trace source cue by combining an regional geological evolution time line, and marking the time-dependent positioning of the trace source cue in the ore forming process; Supplementing time-related auxiliary information formed by the tracing clues, wherein the time-related auxiliary information comprises a geological event occurrence sequence corresponding to the tracing clues and time-sequence relations with other tracing clues, and generating time attribute details; Integrating the space attribute details with the time attribute details to generate space-time attribute labeling contents of the single trace source, wherein the space-time attribute labeling contents comprise space position details and ore forming time association details of the trace source; Binding the space-time attribute labeling content with the corresponding tracing clues, establishing a one-to-one correspondence between the labeling content and the tracing clues, and generating a labeling single tracing clue; Repeating the operations of extracting single trace basic information, acquiring space attribute details, acquiring time attribute details, forming labeling content and binding trace source threads until all trace source threads in the space-time basic trace source thread set complete space-time attribute labeling; Classifying and extracting all marked single tracing threads according to basic information types, and complementing the missing space position details or ore forming time association details in each tracing thread through space-time attribute detail cross comparison; And sorting the complemented single trace source clues according to the basic information types to generate trace source clues set of the labeling space-time attribute, wherein the trace source clues set of the labeling space-time attribute contains complete space-time basic data and is used for subsequent space-time coupling networking.
8. 8. The method for copper mine target area prediction based on multi-source information data analysis according to claim 4, wherein the generating the reinforced coupling link by reinforcing the signal transmission intensity of the coupling link according to the corresponding reinforcing mode in the resonance reinforcing rule set and supplementing the related information of the trace source related to resonance comprises: determining a resonance strengthening rule applicable to the coupling link meeting the resonance triggering condition, and extracting a corresponding strengthening mode, strengthening related parameters and associated information supplementing requirements from the resonance strengthening rule set; Based on the extracted strengthening mode, expanding the signal conducting channel of the coupling link, increasing the signal carrying capacity of the signal conducting channel, improving the conducting efficiency of signals in the coupling link, and primarily strengthening the signal conducting strength of the coupling link; according to the requirement of strengthening relevant parameters, the signal output intensity of network nodes at two ends of the coupling link is adjusted, so that the output signals of the network nodes can be adapted to the conduction characteristics of the coupling link, and the signal conduction effect of the coupling link is further strengthened; Analyzing the core content of two traceability clues connected by the coupling link, mining potential mineforming association points between the two traceability clues except the existing coupling relation, and generating potential association information; Based on the potential association information, supplementing specific logic description of association of the two tracing threads, marking the mineforming logic related basis for generating resonance effect between the two tracing threads, and perfecting association information content; integrating the primarily reinforced signal transmission channel, the adjusted node signal output strength and the supplementary associated information content to generate a reinforced basic link; Performing signal stability processing on the reinforced basic link, optimizing a signal conduction path of the reinforced basic link, reducing loss of signals in the transmission process of the reinforced basic link, and maintaining stable transmission of the reinforced signals; adding resonance identification information for the reinforced basic link, wherein the resonance identification information comprises the resonance type and the influence range of the reinforced basic link, and generating reinforced link attributes; Binding the reinforced basic link with the complete reinforced link attribute, recording the reinforced characteristic and attribute information of the reinforced basic link, and generating a reinforced coupling link; and matching and verifying the signal transmission intensity test and the associated information, and complementing the associated information of the resonance related traceable clues missing in the reinforced coupling link to perfect the content related to the resonance effect of the mineralized logic.
9. 9. The method for predicting copper mine target area based on multi-source information data analysis according to claim 5, wherein the performing third-level convergence processing on the second-level convergence region based on the result of the ore formation related matching operation, reserving a region part in the second-level convergence region where the result of the ore formation related matching operation meets the requirement, removing a region part in the second-level convergence region where the result of the ore formation related matching operation does not meet the requirement, and generating a third-level convergence region comprises: Extracting the result of the ore-forming related matching operation of each secondary convergence region, and obtaining the specific distribution of the region segments with the matching result meeting the requirements and the region segments with the matching result not meeting the requirements in the secondary convergence region to generate rationality distribution data; Based on the rationality distribution data, acquiring space boundary coordinates of the region segments with the ore formation related matching operation results meeting the requirements in the secondary convergence region, and positioning the range of the region segments with the ore formation related matching operation results meeting the requirements in the secondary convergence region; Analyzing the space connection relation between the region segments meeting the requirements of the ore-forming related matching operation result in the secondary convergence region, determining the region segments meeting the requirements of the adjacent or similar ore-forming related matching operation result in the secondary convergence region through space coordinate comparison, and defining the integration related conditions of the region segments; carrying out space boundary fusion processing on the region segments meeting the requirements of the ore-forming related matching operation results meeting the integration related conditions, and eliminating gaps between the region segments through boundary coordinate linking calculation to generate continuous region blocks; Extracting space boundary coordinates of the region segments which are not in accordance with the ore formation related matching operation result in the secondary convergence region, and obtaining the positions of the region segments in the secondary convergence region; Dividing a region range to be removed in the secondary convergence region based on the space boundary of the region segment which does not meet the requirement of the ore formation correlation matching operation result in the secondary convergence region, and enabling the region range to completely correspond to the region segment which does not meet the requirement of the ore formation correlation matching operation result in the secondary convergence region through coordinate mapping; The continuous area block is subjected to coordinate comparison with the original boundary of the secondary convergence area, and the boundary coordinates of the continuous area block are adjusted to enable the continuous area block to be completely in the range of the secondary convergence area; Based on the divided region range to be removed, removing the corresponding part in the secondary convergence region through spatial region cutting operation, and reserving the adjusted continuous region blocks to generate a primary tertiary convergence region; Processing the preliminary three-level convergence region through a space integrity detection algorithm, complementing region segments which are missed in the preliminary three-level convergence region and meet the requirements of the ore-forming related matching operation result, and enabling the whole of the preliminary three-level convergence region to be coherent through boundary connection verification; And carrying out boundary processing on the preliminary three-level convergence region, and adjusting the boundary of the preliminary three-level convergence region based on the spatial distribution coordinates of the mine-forming related traceability clues to generate the three-level convergence region.
10. 10. A copper mine target area prediction system based on multi-source information data analysis, comprising: A processor; a machine-readable storage medium storing machine-executable instructions for the processor; Wherein the processor is configured to perform the copper mine target prediction method based on multi-source information data analysis of any one of claims 1 to 9 via execution of the machine executable instructions.

Description

Copper mine target area prediction method and system based on multisource information data analysis Technical Field The invention relates to the technical field of computers, in particular to a copper mine target area prediction method and system based on multi-source information data analysis. Background In the field of copper mine exploration, accurately predicting a copper mine target area has important significance for improving exploration efficiency, reducing exploration cost and discovering new copper mine resources. Currently, traditional copper mine target prediction methods rely mainly on analysis of a single information source or a few related information. For example, the relation between the geologic structure and the mine formation is judged by manual experience only based on the geologic structure mapping data to predict, but the method is limited by subjective experience and knowledge reserve of geologic personnel, and the mine formation rule is difficult to comprehensively and accurately grasp. Still other methods utilize soil element content data to delineate potential mineralisation areas by simple statistical analysis, however, soil element content is affected by a number of factors and it is difficult to accurately reflect the mineralisation of deep copper ores solely by this data. In addition, the remote sensing image feature data can provide a large range of surface information, but when used alone, the prediction capability for deep copper ores is limited. The existing methods lack comprehensive utilization and deep mining of multi-source information, so that internal relations and space-time evolution rules among various information cannot be fully considered, the accuracy and reliability of copper mine target area prediction are low, and the requirements of modern copper mine exploration are difficult to meet. Disclosure of Invention In view of the above-mentioned problems, in combination with the first aspect of the present invention, an embodiment of the present invention provides a copper mine target area prediction method based on multi-source information data analysis, the method including: Acquiring multi-source copper mine related basic information which is easy to acquire in a target area, wherein the multi-source copper mine related basic information comprises surface rock outcrop records, soil element content data, regional gravity observation data, remote sensing image characteristic data and geological structure mapping data; performing cue tracing mapping processing on the multi-source copper mine related basic information, tracing the original cue sources related to copper mine formation in each basic information, and generating a plurality of groups of tracing cue sets; performing space-time coupling networking treatment on the plurality of groups of tracing cue sets, and constructing a dynamic coupling cue network by combining the space position corresponding to the tracing cue and the time sequence of the ore formation; performing signal resonance enhancement processing on the dynamic coupling clue network, enhancing the expression of the ore-forming related signals through the ore-forming logic resonance effect among the trace clues, and generating a resonance enhancement network; and based on the signal distribution and coupling relation in the resonance strengthening network, performing target zone convergence definition processing, gradually reducing the range of the potential area of the ore, and generating a copper mine target zone prediction result of the target area. In still another aspect, an embodiment of the present invention further provides a copper mine target area prediction system based on multi-source information data analysis, including: the copper mine target area prediction method based on multi-source information data analysis comprises a processor, a machine-readable storage medium for storing machine-executable instructions of the processor, wherein the processor is configured to execute the copper mine target area prediction method based on multi-source information data analysis by executing the machine-executable instructions. In yet another aspect, embodiments of the present invention further provide a computer program product including machine-executable instructions stored in a computer-readable storage medium, from which a processor of a computer device reads the machine-executable instructions, the processor executing the machine-executable instructions, causing the computer device to perform the copper mine target prediction method based on multi-source information data analysis described above. Based on the above aspects, through collecting the multi-source copper mine related basic information which is easy to acquire in a target area, covering the surface rock outcrop record, soil element content data, area gravity observation data, remote sensing image characteristic data, geological structure mapping data and the like, integrati