Geological data analysis system and method

Abstract

The invention discloses a geological data analysis system and method, and relates to the technical field of earth science, and the system comprises a data obtaining module which is used for obtaining original geological detection data; the quality control module is used for identifying abnormal data in the original geological detection data by adopting a data verification method and deleting or correcting the abnormal data to obtain quality optimization data; and the data analysis module is used for performing statistical analysis and model construction based on the quality optimization data to obtain a statistical analysis result and an analysis model corresponding to the original geological detection data. The quality control module is arranged, the abnormal data in the geological detection data are identified by adopting a data verification method, and the abnormal data are deleted or corrected, so that the quality of the geological detection data is ensured, and the accuracy of a geological data analysis result is improved.

Description

Technical Field

[0001] This application relates to the field of earth science technology, and in particular to a geological data analysis system and method. Background Technology

[0002] Geological data analysis refers to the collection, organization, processing, analysis, and interpretation of geological data obtained from geological surveys using various methods such as mathematics, statistics, and computer science. Further processing of the analytical results of geological data can assist in the exploration of mineral resources, the prediction of geological hazards, and the testing of foundation stability in the early stages of engineering construction. Therefore, geological data analysis has wide applications in various fields.

[0003] Currently, geological testing data is analyzed using analytical systems. However, because geological testing data comes from a wide range of sources, including field sampling, instrumental measurements, and historical data, the quality of data from different sources varies significantly, leading to potential errors or incompleteness. Current geological data analysis systems only have algorithms for processing the input data; they can only process the input data and cannot guarantee its quality. If abnormal data exists in the input, the accuracy of the analysis results cannot be guaranteed. Summary of the Invention

[0004] The purpose of this application is to provide a geological data analysis system and method that can ensure the quality of geological testing data and improve the accuracy of geological data analysis results.

[0005] To achieve the above objectives, this application provides the following solution:

[0006] In a first aspect, this application provides a geological data analysis system, including:

[0007] The data acquisition module is used to acquire raw geological testing data;

[0008] The quality control module is used to identify abnormal data in the original geological detection data using data verification methods, and to delete or correct the abnormal data to obtain quality-optimized data.

[0009] The data analysis module is used to perform statistical analysis and model building based on the quality optimization data, so as to obtain the statistical analysis results and analysis models corresponding to the original geological detection data.

[0010] Secondly, this application provides a geological data analysis method, including:

[0011] The raw geological testing data is obtained using the data acquisition module;

[0012] A quality control module is used to identify abnormal data in the original geological detection data based on data verification methods, and the abnormal data is deleted or corrected to obtain quality-optimized data.

[0013] Based on the quality optimization data, the data analysis module performs statistical analysis and model construction to obtain the statistical analysis results and analysis model corresponding to the original geological detection data.

[0014] According to the specific embodiments provided in this application, the following technical effects are disclosed:

[0015] This application provides a geological data analysis system and method. By setting up a quality control module and using data verification methods to identify abnormal data in geological testing data, and deleting or correcting abnormal data, the quality of geological testing data is guaranteed and the accuracy of geological data analysis results is improved. By setting up a data analysis module, statistical analysis and model construction are performed on the quality-optimized geological testing data to obtain statistical analysis results and analysis models of the geological testing data, which can realize intuitive and visual display of geological testing data analysis results. Attached Figure Description

[0016] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the embodiments 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.

[0017] Figure 1 A schematic diagram of the functional modules of a geological data analysis system provided in an embodiment of this application;

[0018] Figure 2 A schematic diagram illustrating the specific operation of the data acquisition module provided in an embodiment of this application for cleaning, correcting and standardizing raw geological detection data;

[0019] Figure 3 A schematic diagram of the overall framework of a geological data analysis system provided in an embodiment of this application;

[0020] Figure 4 A schematic diagram illustrating the composition and connection relationship of the various data processing modules provided in an embodiment of this application;

[0021] Figure 5 This is a schematic diagram showing the connection relationship of a data storage module provided in an embodiment of this application;

[0022] Figure 6 This is a flowchart illustrating a geological data analysis method provided in one embodiment of this application.

[0023] Figure label:

[0024] 101-Data Acquisition Module, 102-Quality Control Module, 103-Data Analysis Module, 1021-Data Review Unit, 1022-Anomaly Handling Unit, 1023-Instrument Calibration Tracking Unit, 1031-Statistical Analysis Unit, 1032-Model Building Unit, 201-Data Storage Module, 202-Query Module, 203-Central Processing Unit. Detailed Implementation

[0025] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0026] To make the above-mentioned objectives, features and advantages of this application more apparent and understandable, the application will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0027] In one exemplary embodiment, such as Figure 1 As shown, a geological data analysis system is provided, including a data acquisition module 101, a quality control module 102, and a data analysis module 103. The data acquisition module 101 is used to acquire raw geological testing data. The quality control module 102 is used to identify abnormal data in the raw geological testing data using data verification methods, and to delete or correct the abnormal data to obtain quality-optimized data. The data analysis module 103 is used to perform statistical analysis and model construction based on the quality-optimized data to obtain the statistical analysis results and analysis model corresponding to the raw geological testing data.

[0028] In one example, the data acquisition module 101 is further configured to sequentially clean, correct, and standardize the raw geological detection data. For example... Figure 2 As shown, data cleaning performs preliminary cleaning of the original geological survey data. After removing obvious noise, the original geological survey data undergoes invalid data removal and duplicate data merging in sequence. Invalid data removal deletes data containing missing values; duplicate data merging merges data collected repeatedly. Data correction performs coordinate correction on the data obtained from the data cleaning step to ensure the accuracy of the coordinates. Data standardization uses the unified International System of Units (SI) to convert the corrected geological data to standard units and convert the data format for easier subsequent data analysis.

[0029] In one instance, the data validation method includes standard comparison and threshold verification. For example... Figure 3 As shown, the quality control module 102 includes a data review unit 1021 and an anomaly handling unit 1022.

[0030] The data review unit 1021 is used to sequentially perform standard comparisons and threshold reviews on the original geological testing data to identify abnormal data. The data review unit 1021 includes a standard comparison library and a data threshold library. The standard comparison library includes national standards, industry standards, local standards, and internal enterprise standards. The data threshold library includes the standard threshold ranges corresponding to the original geological testing data. The data review unit 1021 performs real-time review of the data based on the standard threshold ranges of the geological testing data and marks abnormal data. Further, the data review unit 1021 categorizes abnormal data into minor, moderate, and severe abnormalities based on the degree to which the abnormal data deviates from the standard threshold range. Using the above technical solution, the quality control module 102 can monitor the quality of the entire data analysis process, ensuring the accuracy of the data analysis.

[0031] An anomaly handling unit 1022 is used to delete or correct the abnormal data to obtain the quality-optimized data. In one example, the anomaly handling unit 1022 is also used to trace the source of the abnormal data to determine the cause of the anomaly. The anomaly handling unit 1022 includes an anomaly diagnosis subunit and an anomaly handling subunit. The anomaly diagnosis subunit receives the data review results from the data review unit 1021 and, in conjunction with the stored data in the data storage module 201, traces the root cause of the anomaly to determine the cause of the abnormal data. Based on the determination of the cause of the abnormal data, the anomaly handling subunit generates a targeted processing plan, deletes or corrects the abnormal data, and records the processing process. Furthermore, the processing of abnormal data by the anomaly handling subunit also includes re-detection and special annotation.

[0032] In one example, the data acquisition module 101 acquires the raw geological detection data through a data acquisition instrument. For example... Figure 3 As shown, the quality control module 102 also includes an instrument calibration tracking unit 1023. The instrument calibration tracking unit 1023 is connected to the data acquisition instrument and is used to monitor the calibration status and calibration validity period of the instrument. Real-time monitoring of the instrument's validity period allows for timely calibration of instruments nearing their calibration expiration date.

[0033] In another example, the quality control module 102 covers the entire process of geological testing data from input to output. The quality control module 102 allows for real-time monitoring of the entire process from input to output of analysis results. The data review unit 1021 performs real-time comparisons of the geological testing data against various built-in standard libraries to determine whether the data meets the standard requirements. Identifying and processing abnormal data before data analysis can avoid deviations in analysis results caused by geological testing data not meeting standards.

[0034] The statistical analysis results include descriptive statistics, visualized geological information, and correlation coefficients. The analytical models include geological structure models and geological data models. For example... Figure 3 As shown, the data analysis module 103 includes a statistical analysis unit 1031 and a model building unit 1032.

[0035] Among them, such as Figure 4 As shown, the statistical analysis unit 1031 is used to perform descriptive statistics calculation, spatial statistical analysis, and data correlation calculation based on the quality-optimized data, to obtain the values ​​of the descriptive statistics, the visualized geological information, and the correlation coefficients. Specifically, the descriptive statistics calculation step performs statistical calculations on the quality-optimized data, generating the mean, median, and standard deviation of the quality-optimized data, and plots the data distribution histogram and box plot based on the statistical calculation results. The spatial statistical analysis step uses Geographic Information System (GIS) technology, utilizing the geographic information in the quality-optimized data to perform spatial interpolation and spatial correlation analysis to visualize the geological information, thereby obtaining visualized geological information and studying the correlation between geological structures and data. The data correlation calculation step performs correlation calculations based on the quality-optimized data to obtain the correlation coefficients between each pair of quality-optimized data. Using the above technical solution, the data analysis module 103 can realize the analysis and processing of geological detection data.

[0036] like Figure 4 As shown, the model building unit 1032 is used to build the geological structure model and the geological data model based on the quality optimization data. The geological structure model constructs a geological concept model based on the quality optimization data; the geological data model constructs a mathematical model based on the quality optimization data. Using the above technical solution, the model building unit 1032 can build models based on the quality optimization data, facilitating subsequent observation and retrieval. Furthermore, the models can be used to predict geological phenomena, providing forward-looking support for geological decision-making.

[0037] In another example, such as Figure 3As shown, the geological data analysis system further includes a data storage module 201, a query module 202, and a central processing unit 203. The data storage module 201 is used for local and cloud storage of the raw geological detection data, the quality optimization data, the statistical analysis results, and the analysis model. The data acquisition module 101 inputs the acquired raw geological detection data into the data storage module 201 for backup. Furthermore, the data storage module 201 performs data overwrite backup of the entire geological data analysis process. The query module 202 receives user query commands and performs conditional filtering and visualization of the data stored in the data storage module based on the query commands. The central processing unit 203 sends control commands to the data acquisition module 101, the quality control module 102, and the data analysis module 103 to control each module to perform corresponding geological detection data processing and upload the geological data from each process to the data storage module 201.

[0038] In another example, such as Figure 5 As shown, the data storage module 201 includes a local database and a cloud database. The local database and the cloud database are interconnected. The local database is connected to the data acquisition module 101, the data review unit 1021, the anomaly handling unit 1022, the instrument calibration tracking unit 1023, the statistical analysis unit 1031, and the model building unit 1032, respectively, to store raw geological detection data and all intermediate data generated during data analysis in batches, thereby achieving precise data traceability in geological data analysis. Using the above technical solution, geological data from each stage of the data analysis process can be stored in batches using both the local and cloud databases.

[0039] like Figure 4 As shown, the query module 202 can perform conditional queries and chart queries. Conditional queries retrieve data based on criteria such as time and testing items; chart queries output the data or charts generated by the data analysis module 103, facilitating understanding of the geological conditions. Using the above technical solution, the query module 202 can visualize the analyzed data, allowing users to intuitively understand the geological situation.

[0040] In another exemplary embodiment, such as Figure 6 As shown, a geological data analysis method is provided, including the following steps 601 to 603. Wherein:

[0041] Step 601: Use the data acquisition module to acquire the original geological detection data.

[0042] Step 602: Using a quality control module, abnormal data in the original geological detection data are identified based on a data verification method, and the abnormal data is deleted or corrected to obtain quality-optimized data.

[0043] Step 603: Using the data analysis module, statistical analysis and model construction are performed on the quality optimization data to obtain the statistical analysis results and analysis model corresponding to the original geological detection data.

[0044] The beneficial effects of this application are as follows:

[0045] The geological data analysis system and method proposed in this application solve the problem of abnormal analysis results caused by the inability of existing geological detection data analysis systems to identify and analyze abnormal input data. Specifically:

[0046] 1. This application includes a quality control module covering the entire process of geological testing data from input to output. This module allows for real-time monitoring of the entire process, comparing data against built-in standard and threshold libraries. Before analysis, outlier data is removed to prevent deviations in analysis results caused by non-compliance with standards. Simultaneously, the quality control module monitors the calibration status of the acquisition instruments, ensuring the accuracy of the collected data. The data review unit within the quality control module reviews the data in real-time, quickly identifying data that significantly deviates from the normal range, providing a basis for further analysis of the causes of anomalies.

[0047] 2. This application incorporates a preprocessing step before analyzing geological testing data to preprocess the data and ensure the accuracy of the analysis results. The data analysis module is connected to the data storage module, and the local database in the data storage module communicates with the cloud database. Furthermore, the local database stores data in batches for each step of the data analysis process. This allows for precise data traceability at any time, enabling understanding of the data's origin, processing, and changes, facilitating data review and verification.

[0048] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of the relevant data must comply with relevant regulations.

[0049] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM).

[0050] The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, etc., and are not limited to these.

[0051] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0052] This document uses specific examples to illustrate the principles and implementation methods of this application. The descriptions of the above embodiments are only for the purpose of helping to understand the methods and core ideas of this application. Furthermore, those skilled in the art will recognize that, based on the ideas of this application, there will be changes in the specific implementation methods and application scope. Therefore, the content of this specification should not be construed as a limitation of this application.

Claims

1. A geologic data analysis system, characterized by, The geological data analysis system comprises: a data acquisition module for acquiring original geological detection data; a quality control module for identifying abnormal data in the original geological detection data by using a data verification method, and deleting or correcting the abnormal data to obtain quality-optimized data; a data analysis module for performing statistical analysis and model construction based on the quality-optimized data, respectively, to obtain statistical analysis results and analysis models corresponding to the original geological detection data.

2. The geologic data analysis system of claim 1, wherein, The geological data analysis system further comprises a data storage module for locally storing and cloud-storing the original geological detection data, the quality-optimized data, the statistical analysis results and the analysis models.

3. The geologic data analysis system of claim 2, wherein, The geological data analysis system further comprises a query module for receiving a query command of a user and performing conditional filtering and visual display on the data stored in the data storage module according to the query command.

4. The geologic data analysis system of claim 1, wherein, The data acquisition module is further configured to sequentially perform cleaning, correction and standardization processing on the original geological detection data.

5. The geologic data analysis system of claim 1, wherein, The data verification method comprises standard comparison and threshold review; The quality control module comprises: a data review unit for sequentially performing standard comparison and threshold review on the original geological detection data to identify the abnormal data; an abnormal data processing unit for deleting or correcting the abnormal data to obtain the quality-optimized data.

6. The geologic data analysis system of claim 5, wherein, The data review unit comprises a standard comparison library and a data threshold library; the standard comparison library comprises national standards, industry standards, local standards and enterprise internal standards; and the data threshold library comprises standard threshold ranges corresponding to the original geological detection data.

7. The geologic data analysis system of claim 5, wherein, The abnormal data processing unit is further configured to trace the abnormal data to determine abnormal reasons corresponding to the abnormal data.

8. The geologic data analysis system of claim 5, wherein, The data acquisition module acquires the original geological detection data by using a collection instrument; The quality control module further comprises an instrument calibration tracking unit for monitoring a calibration state and a calibration validity period of the collection instrument.

9. The geologic data analysis system of claim 1, wherein, The statistical analysis results comprise descriptive statistic values, visualized geological information and correlation coefficients; The analysis models comprise geological structure models and geological data models; The data analysis module comprises: a statistical analysis unit for performing descriptive statistic calculation, spatial statistical analysis and data correlation calculation based on the quality-optimized data to obtain the descriptive statistic values, the visualized geological information and the correlation coefficients; a model construction unit for constructing the geological structure models and the geological data models based on the quality-optimized data.

10. A method of geologic data analysis applied to the geologic data analysis system of any one of claims 1-9, characterized in that, The geological data analysis method comprises: acquiring original geological detection data by using a data acquisition module; identifying abnormal data in the original geological detection data by using a quality control module based on a data verification method, and deleting or correcting the abnormal data to obtain quality-optimized data; performing statistical analysis and model construction based on the quality-optimized data by using a data analysis module to obtain statistical analysis results and analysis models corresponding to the original geological detection data.

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