Data twinning method and system for positioning and predicting hidden phosphorite

Abstract

The invention is suitable for the technical field of hidden phosphorite positioning prediction, and provides a data twinning method and system for hidden phosphorite positioning prediction. The method comprises the following steps: acquiring basic geological data, geophysical observation data and geochemical anomaly data, and performing spatial unification and standardization processing; constructing a three-dimensional structure twinborn model; determining a phosphorite prediction space, and screening a plurality of space units; calculating a comprehensive mineralization probability index of the plurality of space units, and selecting a high-level target region range; and correcting and optimizing the three-dimensional structure twin model. According to the method, acquisition of multi-source data, space unification and standardization, construction of a three-dimensional structure twin model of a target area, screening of a plurality of space units, integration of mineralization probability indexes, selection of a high-level target area range and no dependence on experience judgment of geological personnel can be carried out, and a standardized and replicable positioning prediction process can be formed.

Description

Technical Field

[0001] This invention belongs to the field of concealed phosphate mine location prediction technology, and particularly relates to a data twin method and system for concealed phosphate mine location prediction. Background Technology

[0002] Existing methods for probing concealed phosphate deposits mostly rely on the experience and judgment of geologists. Different technicians have different understandings of the same data, making it difficult to form a standardized and replicable location and prediction process. Summary of the Invention

[0003] The purpose of this invention is to provide a data twin method and system for predicting the location of concealed phosphate mines, aiming to solve the technical problems existing in the prior art mentioned in the background.

[0004] The embodiments of the present invention are implemented as follows: A data twinning method for predicting the location of concealed phosphate deposits, the method specifically includes the following steps: Acquire basic geological data, geophysical observation data, and geochemical anomaly data of the target area, and perform spatial unification and standardization processing on the multi-source data to obtain multi-source standard data; Based on the multi-source standard data, a three-dimensional structural twin model of the target region is constructed; Resistivity distribution analysis was performed on the three-dimensional structural twin model to identify low-resistivity anomaly layers, determine the phosphate rock prediction space, and select multiple spatial units from the phosphate rock prediction space. Overlap analysis of F and Sr elemental combination anomalies was performed to calculate the comprehensive mineralization probability index of multiple spatial units and select the high-level target area range of concealed phosphate deposits. Receive drilling radioactive logging data, perform measured deviation analysis according to the high-level target area range, and correct and optimize the three-dimensional structural twin model.

[0005] As a further limitation of the technical solution of this invention, the steps of acquiring basic geological data, geophysical observation data, and geochemical anomaly data of the target area, and performing spatial unification and standardization processing of multi-source data to obtain multi-source standard data specifically include the following steps: Determine the target area for the location prediction of concealed phosphate mines; Collect basic geological data of the target area, including stratigraphic age, stratigraphic assemblage, structural type and sedimentary facies distribution information; Access geophysical observation data of the target area, including audio magnetotelluric data and borehole spontaneous combustion gamma logging data; The geochemical anomaly data of the target area is obtained, which is the indicative elemental anomaly information of concealed phosphate deposits extracted from the imported stream sediment measurement results. The basic geological data, the geophysical observation data, and the geochemical anomaly data are subjected to coordinate unification, scale normalization, and attribute standardization to obtain multi-source standard data.

[0006] As a further limitation of the technical solution of this invention embodiment, the step of constructing a three-dimensional structural twin model of the target region based on the multi-source standard data specifically includes the following steps: Obtain standard sedimentary features from the multi-source standard data, and reconstruct the carbonate platform tidal flat sedimentary system in virtual space; Based on the carbonate platform tidal flat sedimentary system, a three-dimensional structural twin model of the phosphorus-bearing strata in the target area was constructed, using each lithological segment of the Meishucun Formation as the basic unit.

[0007] As a further limitation of the technical solution of this invention, the step of performing resistivity distribution analysis on the three-dimensional structural twin model, identifying low-resistivity anomaly layers, determining the phosphate rock prediction space, and selecting multiple spatial units from the phosphate rock prediction space specifically includes the following steps: Resistivity distribution analysis was performed on the three-dimensional structural twin model to identify continuous and stable low-resistivity anomaly layers; The depth range with the highest mineralization probability is set below the low-resistivity anomaly layer to determine the phosphate prediction space of concealed phosphate deposits. Multiple spatial units are selected from the predicted phosphate rock space.

[0008] As a further limitation of the technical solution of this invention, the step of performing overlapping analysis of F and Sr elemental combination anomalies, calculating the comprehensive mineralization probability index of multiple spatial units, and selecting the high-level target area range of concealed phosphate deposits specifically includes the following steps: The F and Sr elements are combined and abnormally projected into the three-dimensional structural twin model, and multiple overlapping units are selected from the multiple spatial units. Based on the multi-source standard data, relevant factor data of multiple overlapping units are extracted; Based on the relevant factor data, calculate the comprehensive mineralization probability index of the multiple overlapping units; Based on multiple comprehensive mineralization probability indices, the high-level target area range of concealed phosphate deposits is selected.

[0009] As a further limitation of the technical solution of this embodiment of the invention, the calculation formulas for the plurality of comprehensive mineralization probability indices are as follows: ; in, Representing the One overlapping unit, For the first The comprehensive mineralization probability index of overlapping units. For the first The sedimentary facies favorability factor of each overlapping unit For the first Geophysical response factors of overlapping units, For the first Geochemical anomaly factors of overlapping units, , and These are preset weight values.

[0010] As a further limitation of the technical solution of this invention, the steps of receiving drilling radioactive logging data, performing measured deviation analysis according to the high-level target area, and correcting and optimizing the three-dimensional structural twin model specifically include the following steps: Receive drilling radioactive logging data; Based on the drilling radiometric logging data, a measured deviation analysis was performed on the high-level target area, and the measured deviation results were recorded. Based on the measured deviation results, adjust the sedimentary phase boundary, physical property parameters, and weight allocation; The three-dimensional structural twin model was corrected and optimized according to the adjusted sedimentary facies boundaries, physical property parameters, and weight allocation.

[0011] A data twin system for predicting the location of concealed phosphate deposits, the system comprising a data acquisition and processing module, a three-dimensional twin processing module, a spatial unit screening module, a target area selection module, and a measured deviation analysis module, wherein: The data acquisition and processing module is used to acquire basic geological data, geophysical observation data and geochemical anomaly data of the target area, and to perform spatial unification and standardization processing of multi-source data to obtain multi-source standard data. The three-dimensional twin processing module is used to construct a three-dimensional structural twin model of the target region based on the multi-source standard data. The spatial unit screening module is used to perform resistivity distribution analysis on the three-dimensional structural twin model, identify low-resistivity anomaly layers, determine the phosphate rock prediction space, and screen multiple spatial units from the phosphate rock prediction space. The target area selection module is used to perform overlap analysis of F and Sr element combination anomalies, calculate the comprehensive mineralization probability index of multiple spatial units, and select the high-level target area range of concealed phosphate deposits. The measured deviation analysis module is used to receive drilling radioactive logging data, perform measured deviation analysis according to the high-level target area range, and correct and optimize the three-dimensional structural twin model.

[0012] As a further limitation of the technical solution of this embodiment of the invention, the data acquisition and processing module specifically includes: The target area determination unit is used to determine the target area for the location prediction of concealed phosphate mines. The basic geological data acquisition unit is used to acquire basic geological data of the target area, including stratigraphic age, stratigraphic assemblage, structural type and sedimentary facies distribution information; A geophysical observation data access unit is used to access geophysical observation data of the target area, including audio magnetotelluric sounding data and borehole spontaneous combustion gamma logging data. The geochemical anomaly data acquisition unit is used to acquire geochemical anomaly data of the target area. The geochemical anomaly data is the indicative element anomaly information of concealed phosphate rock extracted from the imported stream sediment measurement results. The unification and standardization processing unit is used to perform coordinate unification, scale normalization, and attribute standardization processing on the basic geological data, the geophysical observation data, and the geochemical anomaly data to obtain multi-source standard data.

[0013] As a further limitation of the technical solution of this embodiment of the invention, the target area selection module specifically includes: An anomaly projection filtering unit is used to project the combination of F and Sr elements anomaly into the three-dimensional structural twin model, and to filter multiple overlapping units from multiple spatial units. The factor data extraction unit is used to extract relevant factor data of multiple overlapping units based on the multi-source standard data. The comprehensive mineralization probability index calculation unit is used to calculate the comprehensive mineralization probability index of multiple overlapping units based on the relevant factor data. The target area selection unit is used to select a high-level target area range for concealed phosphate deposits based on multiple comprehensive mineralization probability indices.

[0014] Compared with the prior art, the beneficial effects of the present invention are: This invention acquires basic geological data, geophysical observation data, and geochemical anomaly data, and performs spatial unification and standardization processing; constructs a three-dimensional structural twin model; determines the prediction space for phosphate deposits and selects multiple spatial units; calculates the comprehensive mineralization probability index of multiple spatial units and selects a high-level target area; and corrects and optimizes the three-dimensional structural twin model. It can acquire, spatially unify, and standardize multi-source data, construct a three-dimensional structural twin model of the target area, select multiple spatial units, calculate the comprehensive mineralization probability index, and select a high-level target area. It does not rely on the experience and judgment of geological personnel and can form a standardized and replicable location prediction process. Attached Figure Description

[0015] Figure 1 A flowchart of a data twinning method for predicting the location of concealed phosphate mines provided in an embodiment of the present invention is shown. Figure 2 The following is an application architecture diagram of the data twin system for locating and predicting concealed phosphate mines provided in an embodiment of the present invention. Detailed Implementation

[0016] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0017] Understandably, most current methods for probing concealed phosphate deposits rely on the experience and judgment of geological personnel. Different technicians may have different understandings of the same data, making it difficult to form a standardized and replicable positioning and prediction process.

[0018] To address the aforementioned issues, this invention discloses a data twin method and system for predicting the location of concealed phosphate deposits. This method acquires basic geological data, geophysical observation data, and geochemical anomaly data of the target area, and performs spatial unification and standardization processing on the multi-source data to obtain multi-source standard data. Based on the multi-source standard data, a three-dimensional structural twin model of the target area is constructed. Resistivity distribution analysis is performed on the three-dimensional structural twin model to identify low-resistivity anomaly layers, determine the phosphate deposit prediction space, and select multiple spatial units from the phosphate deposit prediction space. Overlap analysis of F and Sr elemental combination anomalies is conducted to calculate the comprehensive mineralization probability index of multiple spatial units, selecting the high-level target area range for concealed phosphate deposits. Drilling radioactive logging data is received, and measured deviation analysis is performed according to the high-level target area range, and the three-dimensional structural twin model is corrected and optimized. This method enables the acquisition, spatial unification and standardization of multi-source data, the construction of a three-dimensional structural twin model of the target area, the selection of multiple spatial units, the calculation of the comprehensive mineralization probability index, and the selection of the high-level target area range. It eliminates reliance on the experience and judgment of geological personnel, forming a standardized and replicable location prediction process.

[0019] Specifically, Figure 1 A flowchart of a data twin method for predicting the location of concealed phosphate mines, provided by an embodiment of the present invention, is shown.

[0020] In a preferred embodiment of the present invention, a data twinning method for predicting the location of concealed phosphate mines specifically includes the following steps: Step S101: Obtain basic geological data, geophysical observation data and geochemical anomaly data of the target area, and perform spatial unification and standardization processing on the multi-source data to obtain multi-source standard data.

[0021] In this embodiment of the invention, the target area for locating and predicting concealed phosphate deposits is first determined. Then, basic geological data such as stratigraphic age, stratigraphic combination, structural type, and sedimentary facies distribution information of the target area are collected. The distribution range of the Lower Cambrian Meishucun Formation, anticline structures, and ancient depression basins closely related to concealed phosphate deposits is identified. At the same time, geophysical observation data such as audio-frequency magnetotelluric data and borehole spontaneous combustion gamma logging data of the target area are accessed. The apparent resistivity and radioactivity response at different measurement points and depths are uniformly encoded. Furthermore, the indicative elemental anomaly information of concealed phosphate deposits is extracted from the imported stream sediment measurement results, and the correspondence between anomaly intensity and spatial location is established to obtain geochemical anomaly data of the target area. Afterward, the basic geological data, geophysical observation data, and geochemical anomaly data are subjected to coordinate unification, scale normalization, and attribute standardization processing to obtain multi-source standard data.

[0022] Specifically, in another preferred embodiment provided by the present invention, the steps of acquiring basic geological data, geophysical observation data, and geochemical anomaly data of the target area, and performing spatial unification and standardization processing on the multi-source data to obtain multi-source standard data specifically include the following steps: Determine the target area for the location prediction of concealed phosphate mines; Collect basic geological data of the target area, including stratigraphic age, stratigraphic assemblage, structural type and sedimentary facies distribution information; Access geophysical observation data of the target area, including audio magnetotelluric data and borehole spontaneous combustion gamma logging data; The geochemical anomaly data of the target area is obtained, which is the indicative elemental anomaly information of concealed phosphate deposits extracted from the imported stream sediment measurement results. The basic geological data, the geophysical observation data, and the geochemical anomaly data are subjected to coordinate unification, scale normalization, and attribute standardization to obtain multi-source standard data.

[0023] Furthermore, the data twinning method for predicting the location of concealed phosphate deposits also includes the following steps: Step S102: Construct a three-dimensional structural twin model of the target region based on the multi-source standard data.

[0024] In this embodiment of the invention, standard sedimentary features are obtained from multi-source standard data. Then, based on the standard sedimentary features, the carbonate platform tidal flat sedimentary system of the target area is reconstructed in virtual space, with a focus on strengthening the spatial expression of favorable mineralized microfacies such as high-energy subtidal flats and intertidal shoals. Subsequently, based on the carbonate platform tidal flat sedimentary system, a three-dimensional structural twin model of the phosphorus-bearing strata in the target area is constructed using each lithological segment of the Meishucun Formation as the basic unit. The continuity, thickness variation and burial depth characteristics of the main ore-bearing strata in space are clarified, and measured data are obtained. Based on the measured data, resistivity and radioactivity parameters are assigned to the three-dimensional structural twin model, so that the three-dimensional structural twin model has the same physical property response as the real strata in virtual space.

[0025] Specifically, in another preferred embodiment provided by the present invention, the step of constructing a three-dimensional structural twin model of the target region based on the multi-source standard data specifically includes the following steps: Obtain standard sedimentary features from the multi-source standard data, and reconstruct the carbonate platform tidal flat sedimentary system in virtual space; Based on the carbonate platform tidal flat sedimentary system, a three-dimensional structural twin model of the phosphorus-bearing strata in the target area was constructed, using each lithological segment of the Meishucun Formation as the basic unit.

[0026] Furthermore, the data twinning method for predicting the location of concealed phosphate deposits also includes the following steps: Step S103: Perform resistivity distribution analysis on the three-dimensional structural twin model, identify low-resistivity anomaly layers, determine the phosphate rock prediction space, and select multiple spatial units from the phosphate rock prediction space.

[0027] In this embodiment of the invention, resistivity distribution analysis is performed on a three-dimensional structural twin model to identify a continuous and stable low-resistivity anomaly layer. Then, the depth range with the highest mineralization probability is set below the low-resistivity anomaly layer to determine the phosphate prediction space of the concealed phosphate deposit. Based on multi-source standard data, multiple spatial units are selected from the phosphate prediction space.

[0028] Specifically, in another preferred embodiment provided by the present invention, the process of performing resistivity distribution analysis on the three-dimensional structural twin model, identifying low-resistivity anomaly layers, determining the phosphate ore prediction space, and screening multiple spatial units that conform to the ore-forming radioactive response law in combination with radioactive parameters specifically includes the following steps: Resistivity distribution analysis was performed on the three-dimensional structural twin model to identify continuous and stable low-resistivity anomaly layers; The depth range with the highest mineralization probability is set below the low-resistivity anomaly layer to determine the phosphate prediction space of concealed phosphate deposits. Multiple spatial units are selected from the predicted phosphate rock space.

[0029] Furthermore, the data twinning method for predicting the location of concealed phosphate deposits also includes the following steps: Step S104: Perform an overlap analysis of F and Sr element combination anomalies, calculate the comprehensive mineralization probability index of multiple spatial units, and select the high-level target area range of concealed phosphate deposits.

[0030] In this embodiment of the invention, by projecting the F and Sr elemental anomalies into a three-dimensional structural twin model and performing spatial overlap analysis with low resistivity anomalies and favorable sedimentary facies, multiple spatially overlapping units are selected from multiple spatial units. Then, based on multi-source standard data, relevant factor data of these overlapping units are extracted. Subsequently, based on the relevant factor data, a comprehensive mineralization probability index of the multiple overlapping units is calculated. By comparing and analyzing these comprehensive mineralization probability indices, a high-level target area for concealed phosphate deposits is selected. Specifically, the calculation formula for the multiple comprehensive mineralization probability indices is as follows: ; in, Representing the One overlapping unit, For the first The comprehensive mineralization probability index of overlapping units. For the first The sedimentary facies favorability factor of each overlapping unit For the first Geophysical response factors of overlapping units, For the first Geochemical anomaly factors of overlapping units, , and These are preset weight values.

[0031] It is understandable that the sedimentary facies favorability factor is related to the high values ​​of high-energy subtidal flats and intertidal shoals; the geophysical response factor is related to the matching degree of low resistivity and radioactive anomalies; and the geochemical anomaly factor is related to the anomaly intensity of F and Sr.

[0032] Specifically, in another preferred embodiment provided by the present invention, the step of performing overlap analysis of F and Sr elemental combination anomalies, calculating the comprehensive mineralization probability index of multiple spatial units, and selecting the high-level target area range of concealed phosphate deposits specifically includes the following steps: The F and Sr elements are combined and abnormally projected into the three-dimensional structural twin model, and multiple overlapping units are selected from the multiple spatial units. Based on the multi-source standard data, relevant factor data of multiple overlapping units are extracted; Based on the relevant factor data, calculate the comprehensive mineralization probability index of the multiple overlapping units; Based on multiple comprehensive mineralization probability indices, the high-level target area range of concealed phosphate deposits is selected.

[0033] Furthermore, the data twinning method for predicting the location of concealed phosphate deposits also includes the following steps: Step S105: Receive drilling radioactive logging data, perform measured deviation analysis according to the high-level target area range, and correct and optimize the three-dimensional structural twin model.

[0034] In this embodiment of the invention, drilling radiometric logging data of the target area is automatically received. Based on the drilling radiometric logging data, the measured deviation of the high-level target area is analyzed, and the measured deviation results are recorded. Then, according to the measured deviation results, the sedimentary facies boundary, physical property parameters and weight allocation are adjusted. Then, according to the adjusted sedimentary facies boundary, physical property parameters and weight allocation, the three-dimensional structural twin model is corrected and optimized, so that the three-dimensional structural twin model gradually approaches the real geological conditions and continuously improves the accuracy of the location prediction of concealed phosphate deposits.

[0035] Specifically, in another preferred embodiment provided by the present invention, the steps of receiving drilling radioactive logging data, performing measured deviation analysis according to the high-level target area range, and correcting and optimizing the three-dimensional structural twin model specifically include the following steps: Receive drilling radioactive logging data; Based on the drilling radiometric logging data, a measured deviation analysis was performed on the high-level target area, and the measured deviation results were recorded. Based on the measured deviation results, adjust the sedimentary phase boundary, physical property parameters, and weight allocation; The three-dimensional structural twin model was corrected and optimized according to the adjusted sedimentary facies boundaries, physical property parameters, and weight allocation.

[0036] Furthermore, Figure 2 The following is an application architecture diagram of the data twin system for locating and predicting concealed phosphate mines provided in an embodiment of the present invention.

[0037] Specifically, in another preferred embodiment of the present invention, a data twin system for predicting the location of concealed phosphate mines includes: The data acquisition and processing module 101 is used to acquire basic geological data, geophysical observation data and geochemical anomaly data of the target area, and to perform spatial unification and standardization processing of multi-source data to obtain multi-source standard data.

[0038] In this embodiment of the invention, the data acquisition and processing module 101 first determines the target area for the location prediction of concealed phosphate deposits, and then collects basic geological data such as stratigraphic age, stratigraphic combination, structural type, and sedimentary facies distribution information of the target area. It focuses on identifying the distribution range of the Lower Cambrian Meishucun Formation, anticline structures, and ancient depression basins closely related to concealed phosphate deposits. At the same time, it accesses geophysical observation data such as audio-frequency magnetotelluric data and borehole spontaneous combustion gamma logging data of the target area, and uniformly encodes the apparent resistivity and radioactivity response at different measurement points and depths. Furthermore, it extracts the indicative elemental anomaly information of concealed phosphate deposits from the imported stream sediment measurement results, establishes the correspondence between anomaly intensity and spatial location, and obtains geochemical anomaly data of the target area. Then, it performs coordinate unification, scale normalization, and attribute standardization processing on the basic geological data, geophysical observation data, and geochemical anomaly data to obtain multi-source standard data.

[0039] Specifically, in another preferred embodiment provided by the present invention, the data acquisition and processing module 101 specifically includes: The target area determination unit is used to determine the target area for the location prediction of concealed phosphate mines. The basic geological data acquisition unit is used to acquire basic geological data of the target area, including stratigraphic age, stratigraphic assemblage, structural type and sedimentary facies distribution information; A geophysical observation data access unit is used to access geophysical observation data of the target area, including audio magnetotelluric sounding data and borehole spontaneous combustion gamma logging data. The geochemical anomaly data acquisition unit is used to acquire geochemical anomaly data of the target area. The geochemical anomaly data is the indicative element anomaly information of concealed phosphate rock extracted from the imported stream sediment measurement results. The unification and standardization processing unit is used to perform coordinate unification, scale normalization, and attribute standardization processing on the basic geological data, the geophysical observation data, and the geochemical anomaly data to obtain multi-source standard data.

[0040] Furthermore, the data twin system for predicting the location of concealed phosphate deposits also includes: The three-dimensional twin processing module 102 is used to construct a three-dimensional structural twin model of the target region based on the multi-source standard data.

[0041] In this embodiment of the invention, the three-dimensional twin processing module 102 acquires standard sedimentary features from multi-source standard data, and then reconstructs the carbonate platform tidal flat sedimentary system of the target area in virtual space according to the standard sedimentary features, and focuses on strengthening the spatial expression of favorable mineralized microfacies such as high-energy subtidal flats and intertidal shoals. Then, based on the carbonate platform tidal flat sedimentary system, and using each lithological section of the Meishucun Formation as the basic unit, a three-dimensional structural twin model of the phosphorus-bearing strata in the target area is constructed to clarify the spatial continuity, thickness variation and burial depth characteristics of the main ore-bearing strata, and to acquire measured data. Based on the measured data, resistivity and radioactivity parameters are assigned to the three-dimensional structural twin model, so that the three-dimensional structural twin model has the same physical property response as the real strata in virtual space.

[0042] The spatial unit screening module 103 is used to perform resistivity distribution analysis on the three-dimensional structural twin model, identify low-resistivity anomaly layers, determine the phosphate rock prediction space, and screen multiple spatial units from the phosphate rock prediction space.

[0043] In this embodiment of the invention, the spatial unit screening module 103 analyzes the resistivity distribution of the three-dimensional structural twin model to identify a continuous and stable low-resistivity anomaly layer. Then, it sets the depth range with the highest mineralization probability below the low-resistivity anomaly layer to determine the phosphate prediction space of the concealed phosphate deposit. Based on multi-source standard data, it screens multiple spatial units from the phosphate prediction space.

[0044] The target area selection module 104 is used to perform overlap analysis of F and Sr element combination anomalies, calculate the comprehensive mineralization probability index of multiple spatial units, and select the high-level target area range of concealed phosphate deposits.

[0045] In this embodiment of the invention, the target area selection module 104 projects the F and Sr element combination anomaly onto a three-dimensional structural twin model, performs spatial overlap analysis with low resistivity anomalies and favorable sedimentary facies, and then filters multiple spatially overlapping units from multiple spatial units. Based on multi-source standard data, it extracts relevant factor data for these overlapping units. Then, based on the relevant factor data, it calculates the comprehensive mineralization probability index of the multiple overlapping units. By comparing and analyzing these comprehensive mineralization probability indices, it selects the high-level target area range for concealed phosphate deposits. Specifically, the calculation formula for the multiple comprehensive mineralization probability indices is as follows: ; in, Representing the One overlapping unit, For the first The comprehensive mineralization probability index of overlapping units. For the first The sedimentary facies favorability factor of each overlapping unit For the first Geophysical response factors of overlapping units, For the first Geochemical anomaly factors of overlapping units, , and These are preset weight values.

[0046] Specifically, in another preferred embodiment provided by the present invention, the target area selection module 104 specifically includes: An anomaly projection filtering unit is used to project the combination of F and Sr elements anomaly into the three-dimensional structural twin model, and to filter multiple overlapping units from multiple spatial units. The factor data extraction unit is used to extract relevant factor data of multiple overlapping units based on the multi-source standard data. The comprehensive mineralization probability index calculation unit is used to calculate the comprehensive mineralization probability index of multiple overlapping units based on the relevant factor data. The target area selection unit is used to select a high-level target area range for concealed phosphate deposits based on multiple comprehensive mineralization probability indices.

[0047] Furthermore, the data twin system for predicting the location of concealed phosphate deposits also includes: The measured deviation analysis module 105 is used to receive drilling radioactive logging data, perform measured deviation analysis according to the high-level target area range, and correct and optimize the three-dimensional structural twin model.

[0048] In this embodiment of the invention, the measured deviation analysis module 105 automatically receives drilling radiometric logging data of the target area, performs measured deviation analysis on the high-level target area based on the drilling radiometric logging data, records the measured deviation results, and then adjusts the sedimentary facies boundary, physical property parameters and weight allocation according to the measured deviation results. Then, according to the adjusted sedimentary facies boundary, physical property parameters and weight allocation, the three-dimensional structural twin model is corrected and optimized, so that the three-dimensional structural twin model gradually approaches the real geological conditions and continuously improves the accuracy of hidden phosphate mine location prediction.

[0049] The embodiments described above are merely illustrative of several implementations of the present invention, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of the present invention. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of the present invention, and these modifications and improvements all fall within the scope of protection of the present invention. Therefore, the scope of protection of this patent should be determined by the appended claims.

Claims

1. A data twinning method for predicting the location of concealed phosphate mines, characterized in that, The method specifically includes the following steps: Acquire basic geological data, geophysical observation data, and geochemical anomaly data of the target area, and perform spatial unification and standardization processing on the multi-source data to obtain multi-source standard data; Based on the multi-source standard data, a three-dimensional structural twin model of the target region is constructed; Resistivity distribution analysis was performed on the three-dimensional structural twin model to identify low-resistivity anomaly layers, determine the phosphate rock prediction space, and select multiple spatial units from the phosphate rock prediction space. Overlap analysis of F and Sr elemental combination anomalies was performed to calculate the comprehensive mineralization probability index of multiple spatial units and select the high-level target area range of concealed phosphate deposits. Receive drilling radioactive logging data, perform measured deviation analysis according to the high-level target area range, and correct and optimize the three-dimensional structural twin model.

2. The data twinning method for predicting the location of concealed phosphate mines according to claim 1, characterized in that, The acquisition of basic geological data, geophysical observation data, and geochemical anomaly data of the target area, and the spatial unification and standardization processing of multi-source data to obtain multi-source standard data specifically includes the following steps: Determine the target area for the location prediction of concealed phosphate mines; Collect basic geological data of the target area, including stratigraphic age, stratigraphic assemblage, structural type and sedimentary facies distribution information; Access geophysical observation data of the target area, including audio magnetotelluric data and borehole spontaneous combustion gamma logging data; The geochemical anomaly data of the target area is obtained, which is the indicative elemental anomaly information of concealed phosphate deposits extracted from the imported stream sediment measurement results. The basic geological data, the geophysical observation data, and the geochemical anomaly data are subjected to coordinate unification, scale normalization, and attribute standardization to obtain multi-source standard data.

3. The data twinning method for predicting the location of concealed phosphate mines according to claim 1, characterized in that, The process of constructing a three-dimensional structural twin model of the target region based on the multi-source standard data specifically includes the following steps: Obtain standard sedimentary features from the multi-source standard data, and reconstruct the carbonate platform tidal flat sedimentary system in virtual space; Based on the carbonate platform tidal flat sedimentary system, a three-dimensional structural twin model of the phosphorus-bearing strata in the target area was constructed, using each lithological segment of the Meishucun Formation as the basic unit.

4. The data twinning method for predicting the location of concealed phosphate mines according to claim 1, characterized in that, The process of performing resistivity distribution analysis on the three-dimensional structural twin model, identifying low-resistivity anomaly layers, determining the phosphate rock prediction space, and selecting multiple spatial units from the phosphate rock prediction space specifically includes the following steps: Resistivity distribution analysis was performed on the three-dimensional structural twin model to identify continuous and stable low-resistivity anomaly layers; The depth range with the highest mineralization probability is set below the low-resistivity anomaly layer to determine the phosphate prediction space of concealed phosphate deposits. Multiple spatial units are selected from the predicted phosphate rock space.

5. The data twinning method for predicting the location of concealed phosphate mines according to claim 1, characterized in that, The process of performing overlapping analysis of F and Sr elemental anomalies, calculating the comprehensive mineralization probability index of multiple spatial units, and selecting the high-level target area range of concealed phosphate deposits specifically includes the following steps: The F and Sr elements are combined and abnormally projected into the three-dimensional structural twin model, and multiple overlapping units are selected from the multiple spatial units. Based on the multi-source standard data, relevant factor data of multiple overlapping units are extracted; Based on the relevant factor data, calculate the comprehensive mineralization probability index of the multiple overlapping units; Based on multiple comprehensive mineralization probability indices, the high-level target area range of concealed phosphate deposits is selected.

6. The data twinning method for predicting the location of concealed phosphate mines according to claim 5, characterized in that, The formulas for calculating the multiple comprehensive mineralization probability indices are as follows: ； in, Representing the One overlapping unit, For the first The comprehensive mineralization probability index of overlapping units. For the first The sedimentary facies favorability factor of each overlapping unit For the first Geophysical response factors of overlapping units, For the first Geochemical anomaly factors of overlapping units, , and These are preset weight values.

7. The data twinning method for predicting the location of concealed phosphate mines according to claim 1, characterized in that, The process of receiving radioactive logging data from drilling, performing measured deviation analysis according to the high-level target area, and correcting and optimizing the three-dimensional structural twin model specifically includes the following steps: Receive drilling radioactive logging data; Based on the drilling radiometric logging data, a measured deviation analysis was performed on the high-level target area, and the measured deviation results were recorded. Based on the measured deviation results, adjust the sedimentary phase boundary, physical property parameters, and weight allocation; The three-dimensional structural twin model was corrected and optimized according to the adjusted sedimentary facies boundaries, physical property parameters, and weight allocation.

8. A data twin system for predicting the location of concealed phosphate mines, characterized in that, The system includes a data acquisition and processing module, a 3D twin processing module, a spatial unit filtering module, a target area selection module, and a measured deviation analysis module, wherein: The data acquisition and processing module is used to acquire basic geological data, geophysical observation data and geochemical anomaly data of the target area, and to perform spatial unification and standardization processing of multi-source data to obtain multi-source standard data. The three-dimensional twin processing module is used to construct a three-dimensional structural twin model of the target region based on the multi-source standard data. The spatial unit screening module is used to perform resistivity distribution analysis on the three-dimensional structural twin model, identify low-resistivity anomaly layers, determine the phosphate rock prediction space, and screen multiple spatial units from the phosphate rock prediction space. The target area selection module is used to perform overlap analysis of F and Sr element combination anomalies, calculate the comprehensive mineralization probability index of multiple spatial units, and select the high-level target area range of concealed phosphate deposits. The measured deviation analysis module is used to receive drilling radioactive logging data, perform measured deviation analysis according to the high-level target area range, and correct and optimize the three-dimensional structural twin model.

9. The data twin system for predicting the location of concealed phosphate mines according to claim 8, characterized in that, The data acquisition and processing module specifically includes: The target area determination unit is used to determine the target area for the location prediction of concealed phosphate mines. The basic geological data acquisition unit is used to acquire basic geological data of the target area, including stratigraphic age, stratigraphic assemblage, structural type and sedimentary facies distribution information; A geophysical observation data access unit is used to access geophysical observation data of the target area, including audio magnetotelluric sounding data and borehole spontaneous combustion gamma logging data. The geochemical anomaly data acquisition unit is used to acquire geochemical anomaly data of the target area. The geochemical anomaly data is the indicative element anomaly information of concealed phosphate rock extracted from the imported stream sediment measurement results. The unification and standardization processing unit is used to perform coordinate unification, scale normalization, and attribute standardization processing on the basic geological data, the geophysical observation data, and the geochemical anomaly data to obtain multi-source standard data.

10. The data twin system for predicting the location of concealed phosphate mines according to claim 8, characterized in that, The target area selection module specifically includes: An anomaly projection filtering unit is used to project the combination of F and Sr elements anomaly into the three-dimensional structural twin model, and to filter multiple overlapping units from multiple spatial units. The factor data extraction unit is used to extract relevant factor data of multiple overlapping units based on the multi-source standard data. The comprehensive mineralization probability index calculation unit is used to calculate the comprehensive mineralization probability index of multiple overlapping units based on the relevant factor data. The target area selection unit is used to select a high-level target area range for concealed phosphate deposits based on multiple comprehensive mineralization probability indices.

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