A method for extracting data of geological mineral exploration

Abstract

The application provides a geological mineral exploration data extraction method, which comprises the following steps: defining an exploration accuracy standard and dividing an independent exploration unit, establishing a unified exploration reference coordinate system, in the hierarchical exploration process of preliminary exploration, detailed exploration and sampling exploration, synchronously preprocessing the data obtained in each stage and connecting the data to a three-dimensional geological model in stages. In the hierarchical exploration process, the data obtained in the stages of preliminary exploration, detailed exploration and sampling exploration are connected to the three-dimensional geological model in stages after preprocessing, and global error detection and model correction are simultaneously performed in each stage, so that the model can be continuously iteratively updated with subsequent high-precision data, the problem that the low-precision data in the early stage is solidified in the initial modeling stage and is transmitted in stages in the prior art is avoided, and the expression accuracy of the three-dimensional geological model on the spatial structure and attribute distribution of the real geological body is improved.

Description

Technical Field

[0001] This invention relates to the field of geological and mineral exploration technology, and in particular to a method for extracting data in geological and mineral exploration. Background Technology

[0002] Geological and mineral exploration is the foundation of mineral resource development and utilization. Its core lies in the accurate extraction of data on the spatial distribution, lithological structure, and related attributes of geological bodies to support mineralization prediction, resource assessment, and engineering construction decisions. With the development of digital exploration technology, combining hierarchical exploration processes with three-dimensional geological modeling has become a common technical approach in current geological and mineral exploration.

[0003] In existing technologies, geological and mineral exploration data extraction methods often employ a tiered process combining preliminary exploration, initial exploration, detailed exploration, and sampling exploration. A three-dimensional geological model is first constructed based on preliminary exploration data, and then the model is refined through subsequent sampling. For example, the publication number is... However, the above methods generally adopt a linear hierarchical process of "modeling first, then local correction". Due to the limited accuracy of the data obtained in the preliminary survey and initial exploration stages, the initial three-dimensional geological model built based on this data inevitably contains errors. These errors are easily solidified in the modeling stage and propagated step by step in the subsequent process. At the same time, subsequent corrections usually focus on local locations or single-point parameters, lacking a global coordination and feedback mechanism for the overall structural relationship of the model and multi-source data. It is difficult to balance the overall accuracy of exploration data and exploration efficiency under exploration conditions with complex geological structures or uneven distribution of anomalies. Therefore, a method for extracting data from geological and mineral exploration is proposed. Summary of the Invention

[0004] In view of this, the present invention provides a method for extracting data in geological and mineral exploration, in order to solve or alleviate the technical problems existing in the prior art, and at least provide a beneficial alternative.

[0005] The technical solution of this invention is implemented as follows: a method for extracting data in geological and mineral exploration, comprising the following steps: S1. Define the exploration accuracy standards for the exploration area, divide it into several independent exploration units, collect existing basic geological data for the area, and establish a unified exploration benchmark coordinate system based on the basic geological data to ensure the benchmark consistency of subsequent data acquisition, modeling and verification. S2. A hierarchical model of preliminary exploration, primary exploration, detailed exploration, and sampling exploration is adopted to carry out exploration work in each exploration unit in sequence. After each exploration stage is completed, the collected spatial location data of geological bodies, lithological structure data and related attribute data are preprocessed simultaneously to remove invalid data and noise data. S3. Based on the preprocessed data of the preliminary exploration, an initial three-dimensional geological model is constructed. After the completion of each stage of primary exploration, detailed exploration and sampling exploration, the preprocessed data of the corresponding stage is connected to the initial three-dimensional geological model. At the same time, global error detection is performed on the model to locate the error distribution area and error source. Combined with the high-precision data of subsequent stages, the overall structure and local parameters of the model are collaboratively corrected to realize the iterative update of the model. S4. After the last model iteration update is completed, target exploration data is extracted from the model. The extracted data is compared with the measured data by field sampling and measurement. After verifying that the exploration accuracy standard is met, the final exploration extraction data is output.

[0006] In a further preferred embodiment, the independent exploration unit determines the unit scale based on the exploration accuracy standard, and divides the exploration area with the unit boundary line, so that the geological body type and structural complexity within the same exploration unit meet the preset consistency requirements.

[0007] In a further preferred embodiment, the exploration reference coordinate system is established by setting up or calling up no less than three control points, and the basic geological data, preliminary exploration data, geophysical and geochemical data and borehole data are uniformly converted to the exploration reference coordinate system to form a common spatial reference frame.

[0008] More preferably, the preprocessing includes performing consistency checks on missing fields and duplicate records and removing invalid records; truncating or removing data that exceeds a preset physical reasonable range; and performing outlier suppression processing on the sampled sequence to obtain a stage-specific effective dataset.

[0009] More preferably, the preliminary survey is used to obtain surface topography, water system distribution, outcrop information and surface structural traces, and the preliminary survey data is used as surface constraint input for constructing the initial three-dimensional geological model.

[0010] More preferably, the global error detection includes spatially mapping the prediction results of the three-dimensional geological model to the effective dataset of the stage under the exploration reference coordinate system, and calculating at least one residual index among spatial location residual, stratigraphic interface residual, and attribute residual.

[0011] More preferably, an error distribution region is generated based on the residual index, wherein the error distribution region is a set of regions that satisfy the condition that the residual exceeds a preset threshold and is spatially connected and clustered.

[0012] More preferably, the error sources include at least two categories: coordinate registration deviation and insufficient sampling density. The error source category is output by determining the distribution difference of the residual in the neighborhood of the control point and the neighborhood of the non-control point, as well as the correlation of the residual with the change of sampling density.

[0013] More preferably, the collaborative correction includes prioritizing the use of high-precision data from subsequent stages to update the model structure or parameters within the error distribution region, and imposing change constraints on model parameters outside the error distribution region to ensure that their changes do not exceed a preset change threshold, so as to maintain the overall continuity of the model.

[0014] More preferably, the on-site sampling and measurement includes borehole sampling or in-situ testing, and the stratigraphic interface depth, lithological label, or physical property parameters obtained from the sampling and measurement are used as verification benchmarks; when the difference between the model-extracted data and the verification benchmarks meets the exploration accuracy standard, the final exploration and extraction data are output and stored.

[0015] The embodiments of the present invention have the following advantages due to the adoption of the above technical solutions: I. In the process of graded exploration, the data obtained from each stage of preliminary survey, primary exploration, detailed exploration and sampling exploration are preprocessed and then integrated into the three-dimensional geological model in stages. At each stage, global error detection and model correction are performed simultaneously, so that the model can be continuously iterated and updated as high-precision data is subsequently obtained. This avoids the problem in the prior art where low-precision data in the early stage is solidified and passed down level by level, thus improving the accuracy of the three-dimensional geological model in expressing the spatial structure and attribute distribution of the real geological body.

[0016] Second, in the process of model updating, this invention not only locates the error distribution area based on residual detection, but also further classifies and determines the source of error, and on this basis, performs collaborative correction on the overall structure and local parameters of the model. Compared with the existing technology that only corrects local positions or single-point parameters, this invention can concentrate correction resources on areas with structural deviation trends, while applying change constraints to non-error areas, thereby maintaining the overall continuity and structural rationality of the model while ensuring the effect of local correction.

[0017] Third, this invention establishes a closed-loop process for exploration data acquisition, model updating, and accuracy verification through error detection and feedback during the hierarchical exploration and modeling process. It can guide subsequent corrections based on model error distribution and data reliability, reducing the occurrence of invalid or repeated explorations. In exploration scenarios with complex geological structures or uneven distribution of anomalies, it can improve the overall efficiency of exploration work and reduce exploration costs and cycles while ensuring the accuracy of exploration data.

[0018] The above overview is for illustrative purposes only and is not intended to be limiting in any way. In addition to the illustrative aspects, embodiments, and features described above, further aspects, embodiments, and features of the invention will become readily apparent from the accompanying drawings and the following detailed description. Attached Figure Description

[0019] To more clearly illustrate the technical solutions in the embodiments of this application 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 of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0020] Figure 1 This is a flowchart of the steps of the present invention. Detailed Implementation

[0021] In the following description, only certain exemplary embodiments are briefly described. As those skilled in the art will recognize, the described embodiments can be modified in various ways without departing from the spirit or scope of the invention. Therefore, the drawings and description are considered to be exemplary in nature and not restrictive.

[0022] The embodiments of the present invention will now be described in detail with reference to the accompanying drawings.

[0023] like Figure 1 As shown in the figure, this invention provides a method for extracting data in geological and mineral exploration, the specific steps of which are as follows: S1. Determine accuracy standards, divide exploration units, and establish an exploration reference coordinate system. For the area to be explored, the exploration accuracy standards should be clearly defined based on the project objectives (such as mineralization prediction, resource estimation, or engineering construction design). The accuracy standards may include at least one or more of the following: spatial location error threshold, stratigraphic interface depth error threshold, attribute parameter error threshold, or comprehensive confidence threshold. Different levels can be set for different exploration units according to the differences in objectives, thereby providing a unified criterion for subsequent "whether the standard is met". The unit scale of independent exploration units is determined based on exploration accuracy standards, and the exploration area is divided by unit boundary lines. This ensures that the geological body types and structural complexity within the same exploration unit meet preset consistency requirements. Specifically, the unit scale can be set according to structural complexity, stratigraphic continuity, spatial distribution of mineralization anomalies, and the magnitude of surface geomorphological changes. When there are dense faults, rapid stratigraphic changes, or uneven distribution of anomalies within the region, the unit scale is reduced accordingly; when the stratigraphy within the region is continuous and the structure is relatively simple, the unit scale can be appropriately increased. Through this method, subsequent error detection and correction can be limited to spatially consistent units, reducing the risk of structural deviations caused by cross-geological unit modeling.

[0024] After the unit division is completed, the existing basic geological data of the area are collected. The basic geological data may include geological maps, stratigraphic columns, structural profiles, existing borehole data, existing geophysical and geochemical exploration results, remote sensing interpretation data, and previous engineering geological exploration records. A unified exploration benchmark coordinate system is established based on the basic geological data to ensure the benchmark consistency of subsequent data acquisition, modeling and verification. Preferably, the exploration benchmark coordinate system is established by setting up or calling up no less than three control points. The control points can be measurement control points, existing high-precision positioning benchmark points, or known points that have been verified. The basic geological data, preliminary exploration data, geophysical and geochemical data, and borehole data are uniformly converted to the exploration benchmark coordinate system to form a common spatial reference frame. Through the above-mentioned unified coordinate benchmark, the systematic registration error when multiple source data are superimposed can be reduced, laying the foundation for subsequent residual calculation and error source determination.

[0025] S2. Tiered exploration acquisition and stage data preprocessing Within the framework of independent exploration units, a hierarchical model of preliminary exploration, primary exploration, detailed exploration, and sampling exploration is adopted to conduct exploration work on each exploration unit in sequence. Each stage can be organized according to the strategy of "from coarse to fine, from surface to point": preliminary exploration is used to quickly establish surface constraints and overall understanding; primary exploration is used to obtain basic geological information over a large area; detailed exploration is used to increase the data density and identification accuracy of key parts; and sampling exploration is used to obtain highly reliable measured data that can be used as a basis for verification and calibration.

[0026] After each exploration phase is completed, the collected spatial location data, lithological structure data, and related attribute data of geological bodies are simultaneously preprocessed to remove invalid and noisy data, thereby obtaining a valid dataset for that phase. This preprocessing process preferably includes the following steps: (1) Consistency check: Perform consistency checks on missing fields and duplicate records, and remove invalid records that cannot be located to exploration units or cannot be mapped to the exploration reference coordinate system; (2) Reasonable range constraint: Threshold truncation or elimination is performed on data that exceeds the preset physical reasonable range, for example, attribute values ​​that are abnormal and do not conform to geological laws are eliminated; (3) Outlier suppression: Outlier suppression is performed on the sampled sequence to reduce the amplification effect of random noise or occasional interference on subsequent modeling and residual statistics.

[0027] The preprocessed effective datasets for each stage are uniformly represented in the exploration reference coordinate system to facilitate subsequent model integration, spatial correspondence, and error detection.

[0028] Among them, preliminary surveys are preferred for obtaining information such as surface topography, water system distribution, outcrop information and surface structural traces. The preliminary survey data is used as the surface constraint input for constructing the initial three-dimensional geological model. Specifically, surface constraints can be used to limit the surface boundary of the model, control the stratigraphic outcrop boundary, and provide a priori constraints for the initial geometric shape of fault or tectonic boundaries, thereby improving the structural rationality and interpretability of the initial model.

[0029] S3, Initial 3D Modeling, Global Error Detection, Error Source Determination and Collaborative Correction Iterative Update An initial 3D geological model is constructed based on the effective dataset from the preliminary survey and exploration. The initial model can adopt a data expression form suitable for expressing stratigraphic interfaces and structural relationships, such as a structural model based on stratigraphic interfaces, a volume model based on voxels / grids, or a combination of both. Regardless of the expression form adopted, the model should maintain spatial consistency in the exploration reference coordinate system and be able to support the access and updating of subsequent stage data.

[0030] After the completion of each stage of preliminary exploration, detailed exploration, and sampling exploration, the preprocessed data of the corresponding stage are integrated into the initial 3D geological model. Simultaneously, global error detection is performed on the model to locate the error distribution areas and sources. Then, combined with high-precision data from subsequent stages, the overall structure and local parameters of the model are collaboratively corrected, thereby achieving iterative updates of the model. Specifically, the preferred global error detection includes: Under the exploration reference coordinate system, the prediction results of the three-dimensional geological model are spatially correlated with the effective dataset of the stage, and at least one residual index among spatial location residual, stratigraphic interface residual and attribute residual is calculated.

[0031] Furthermore, an error distribution region is generated based on the residual index. The error distribution region is preferably defined as a set of regions where the residuals exceed a preset threshold and are spatially connected and clustered. When the residuals are not merely scattered points exceeding the limit, but form continuous or clustered areas exceeding the limit, they are identified as error distribution regions. This setting avoids over-correction of occasional outliers and concentrates correction resources on regions with structural deviation trends.

[0032] After locating the error distribution area, the source of the error is determined. The error sources preferably include at least two categories: coordinate registration deviation and insufficient sampling density. The error source category is output by determining the difference in the distribution of residuals in the neighborhood of control points and the neighborhood of non-control points, as well as the correlation between residuals and sampling density. When the residuals exhibit a systematic shift in the neighborhood of control points and differ from those in the neighborhood of non-control points, the error is more likely related to coordinate registration deviation. When the residual magnitude is correlated with sampling density and forms a connected cluster error region in the low sampling density area, the error is more likely related to insufficient sampling density.

[0033] During the collaborative correction phase, a strategy of "enhanced updates in the error zone and constrained changes in the non-error zone" is preferred: within the error distribution region, high-precision data from subsequent stages are prioritized for updating the model structure or parameters; simultaneously, change constraints are applied to model parameters outside the error distribution region to ensure that their changes do not exceed a preset change threshold, thus maintaining the overall continuity of the model. These change constraints can suppress unnecessary drift in the non-error zone and prevent non-physical abrupt changes in the global structure caused by local corrections, thereby achieving collaborative and stable updates of the overall structure and local parameters. By repeatedly executing the "access-detection-determination-correction" process after each stage, the model is continuously iterated and updated, ensuring that errors caused by low-precision data in the early stages are not solidified but are gradually weakened and corrected with the introduction of subsequent high-precision data.

[0034] S4. Target data extraction, on-site measurement and verification, and output storage After the final model iteration update is completed, target exploration data is extracted from the updated 3D geological model. The target exploration data can be determined according to the needs of the exploration task, such as the spatial boundary of the target geological body, the 3D morphology of the stratigraphic interface, the lithological distribution, the key physical property parameter field, or the distribution of mineralization-related attributes.

[0035] Subsequently, the extracted data is compared and verified with the measured data using on-site sampling and measurement. After verification that the data meets the exploration accuracy standards, the final exploration extracted data is output. On-site sampling and measurement preferably includes borehole sampling or in-situ testing, and the stratigraphic interface depth, lithological labels, or physical property parameters obtained from the sampling and measurement are used as verification benchmarks. When the difference between the model extracted data and the verification benchmark meets the exploration accuracy standards, the final exploration extracted data is output and stored. The comparison and verification can be performed by corresponding the model output with the measured benchmark in the exploration benchmark coordinate system and calculating the corresponding difference index. When the difference meets the exploration accuracy standards (e.g., spatial position error, interface depth error, or attribute error does not exceed the preset threshold), the extracted data is deemed to meet the standards, and the final exploration extracted data is output and stored in a preset data format for use in mineralization prediction, resource estimation, or engineering decision-making.

[0036] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any person skilled in the art can easily conceive of various variations or substitutions within the technical scope disclosed in the present invention, and these should all be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A method for extracting data in geological and mineral exploration, characterized in that, Includes the following steps: S1. Define the exploration accuracy standards for the exploration area, divide it into several independent exploration units, collect existing basic geological data for the area, and establish a unified exploration benchmark coordinate system based on the basic geological data to ensure the benchmark consistency of subsequent data acquisition, modeling and verification. S2. A hierarchical model of preliminary exploration, primary exploration, detailed exploration, and sampling exploration is adopted to carry out exploration work in each exploration unit in sequence. After each exploration stage is completed, the collected spatial location data of geological bodies, lithological structure data and related attribute data are preprocessed simultaneously to remove invalid data and noise data. S3. Based on the preprocessed data of the preliminary exploration, an initial three-dimensional geological model is constructed. After the completion of each stage of primary exploration, detailed exploration and sampling exploration, the preprocessed data of the corresponding stage is connected to the initial three-dimensional geological model. At the same time, global error detection is performed on the model to locate the error distribution area and error source. Combined with the high-precision data of subsequent stages, the overall structure and local parameters of the model are collaboratively corrected to achieve iterative update of the model. S4. After the last model iteration update is completed, target exploration data is extracted from the model. The extracted data is compared with the measured data by field sampling and measurement. After verifying that the exploration accuracy standard is met, the final exploration extraction data is output.

2. The method for extracting geological and mineral exploration data according to claim 1, characterized in that, The independent exploration unit determines the unit scale according to the exploration accuracy standard, and divides the exploration area with the unit boundary line so that the geological body type and structural complexity within the same exploration unit meet the preset consistency requirements.

3. The method for extracting geological and mineral exploration data according to claim 1, characterized in that, The exploration reference coordinate system is established by setting up or calling up no less than three control points, and basic geological data, preliminary exploration data, geophysical and geochemical data and borehole data are uniformly converted to the exploration reference coordinate system to form a common spatial reference frame.

4. The method for extracting geological and mineral exploration data according to claim 1, characterized in that, The preprocessing includes performing consistency checks on missing fields and duplicate records and removing invalid records; truncating or removing data that exceeds a preset physical reasonable range; and performing outlier suppression processing on the sampled sequence to obtain a stage-specific effective dataset.

5. The method for extracting geological and mineral exploration data according to claim 1, characterized in that, The preliminary survey is used to obtain surface topography, water system distribution, outcrop information and surface structural traces, and the preliminary survey data is used as the surface constraint input for constructing the initial three-dimensional geological model.

6. The method for extracting geological and mineral exploration data according to claim 1, characterized in that, The global error detection includes spatially mapping the prediction results of the three-dimensional geological model to the effective dataset of the stage under the exploration reference coordinate system, and calculating at least one residual index among spatial location residual, stratigraphic interface residual, and attribute residual.

7. The method for extracting geological and mineral exploration data according to claim 6, characterized in that, An error distribution region is generated based on the residual index. The error distribution region is a set of regions that satisfy the condition that the residual exceeds a preset threshold and is spatially connected and clustered.

8. The method for extracting geological and mineral exploration data according to claim 7, characterized in that, The error sources include at least two categories: coordinate registration deviation and insufficient sampling density. The error source category is output by judging the difference in the distribution of residuals in the neighborhood of control points and the neighborhood of non-control points, as well as the correlation of residuals with the change of sampling density.

9. The method for extracting geological and mineral exploration data according to claim 1, characterized in that, The collaborative correction includes prioritizing the use of high-precision data from subsequent stages to update the model structure or parameters within the error distribution region, and imposing change constraints on model parameters outside the error distribution region to ensure that the amount of change does not exceed a preset change threshold, so as to maintain the overall continuity of the model.

10. The method for extracting geological and mineral exploration data according to claim 1, characterized in that, The on-site sampling and measurement includes borehole sampling or in-situ testing, and the stratigraphic interface depth, lithological label or physical property parameters obtained from the sampling and measurement are used as verification benchmarks; when the difference between the model-extracted data and the verification benchmarks meets the exploration accuracy standard, the final exploration-extracted data is output and stored.

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