Drilling sampling task sheet generation method and system based on intelligent optimization, and medium

Abstract

The present application relates to the technical field of intelligent management of geotechnical engineering geological exploration, and proposes a drilling sampling task sheet generation method based on intelligent optimization, which is applied to a computer system and includes the following steps: constructing a geological exploration resource library and a drilling sampling task sheet template library; collecting and analyzing user input requirements; using a knowledge graph for semantic understanding and requirement analysis, identifying key parameters and mapping them to preset standard specifications, and simultaneously obtaining matching sampling requirements from the geological exploration resource library based on the mapping relationship; automatically adjusting parameter values through a rule engine to generate parameter configuration suggestions; automatically generating a preliminary draft of the task sheet; and generating a drilling sampling task sheet that meets the requirements of accurate specification adaptation, intelligent parameters and dynamic template adjustment. The present application improves the accuracy and efficiency of generating drilling sampling task sheets for geotechnical engineering geological exploration.

Description

Technical Field

[0001] This invention relates to the field of intelligent management technology for geotechnical engineering geological exploration, specifically to a method, system, and medium for generating borehole sampling task sheets based on intelligent optimization. Background Technology

[0002] Drilling sampling involves obtaining samples of rock, soil, and water during the drilling process. These samples are then used for testing or inspection to acquire quantitative indicators required for engineering design. It is a crucial part of engineering surveying, and therefore, engineering surveying standards have clear regulations regarding drilling sampling, which must be strictly followed. The type and quantity of samples are not only influenced by engineering surveying standards but also closely related to site geological conditions, with numerous influencing factors. In practice, professionals need to consult a considerable amount of data when preparing sampling task sheets, resulting in low efficiency. Furthermore, in engineering practice, the number of boreholes may be increased or decreased during implementation, and discrepancies may arise between actual site conditions and pre-predicted results. Both of these situations may necessitate adjustments to sampling requirements and the re-preparation of drilling sampling task sheets. Manual operations are prone to errors due to forgetfulness and tedious procedures, leading to serious non-compliant final results. Using drilling sampling requirements as a "resource library," intelligently obtaining drilling sampling types and quantity indicators through software, and being able to quickly adjust to changes in conditions and automatically generate drilling sampling task sheets is a long-awaited solution in production, but no successful implementation has been achieved to date. Summary of the Invention

[0003] In view of this, it is necessary to address the shortcomings and deficiencies in existing technologies by proposing a method, system, and medium for generating borehole sampling task sheets based on intelligent optimization, thereby improving the accuracy and efficiency of generating borehole sampling task sheets for geotechnical engineering geological exploration.

[0004] To achieve the above objectives, the present invention adopts the following technical solution:

[0005] This invention proposes a method for generating borehole sampling task sheets based on intelligent optimization, comprising:

[0006] A geological exploration resource database and a borehole sampling task book template database are constructed. The geological exploration resource database includes a relational database and an entity relationship data package. The relational database is used to store structured form data. The entity relationship data package includes entity relationships constructed from a knowledge graph regarding exploration specifications, engineering grades, stratigraphic lithology, and sampling parameters. The borehole sampling task book template database supports custom formats and content, stores data by industry category, and can automatically adjust field layout and required fields.

[0007] Collect and parse user-inputted requirements information, including geological conditions, exploration targets, and parameter requirements;

[0008] Using knowledge graphs for semantic understanding and requirement analysis, key parameters are identified and mapped to preset standard specifications. At the same time, based on this mapping relationship, matching sampling requirements are obtained from the geological exploration resource database.

[0009] Based on historical data and best practices, the rule engine automatically adjusts parameter values ​​and generates parameter configuration suggestions.

[0010] Call the template in the borehole sampling task book template library that is adapted to the current project scenario, dynamically adjust the task book template format, and automatically fill the optimized parameter configuration and the obtained sampling requirements into the dynamic template to generate the first draft of the task book.

[0011] Automatically generate borehole sampling task sheets that meet the requirements of accurate standard adaptation, intelligent parameter control, and dynamic template adjustment.

[0012] This invention further proposes a method for generating borehole sampling task sheets based on intelligent optimization, applied to a computer system. The method includes:

[0013] S100, Receive engineering requirement information input by the user, the engineering requirement information including geological conditions and exploration targets and parameter requirements;

[0014] S200, Construct a geological exploration resource database; the geological exploration resource database includes a relational database and an entity association data package; the relational database is used to store structured form data; the entity association data package includes entity associations constructed from a knowledge graph regarding exploration specifications, engineering grades, stratigraphy, and sampling parameters;

[0015] S300, Establish a drilling sampling task template library for intelligent adaptation; the drilling sampling task template library is used to support custom formats and content, store them according to industry categories and can automatically adjust field layout and required fields;

[0016] S400: Use the knowledge graph in the geological exploration resource database to perform semantic understanding and requirement analysis on the engineering requirement information, identify key parameters and map the key parameters to preset standard specifications;

[0017] S500 calls the rule engine, which automatically adjusts the sampling-related parameter values ​​based on the key parameters and mapping results obtained from the parsing, combined with historical engineering data and best practices. At the same time, it obtains matching sampling requirements from the geological exploration resource library based on the basic information of the project and the geological conditions in the requirements.

[0018] S600 automatically fills the optimized parameters and obtained sampling requirements into the dynamic template adapted in the borehole sampling task book template library through the entity association mapping relationship of the knowledge graph, and generates the initial draft of the task book.

[0019] The S700, through a B / S or C / S architecture of a computer system, supports the viewing, editing, and distribution of task books, and realizes data traceability and closed-loop updates of the geological exploration resource database.

[0020] This invention further proposes a system constructed using the method described above, comprising the following components:

[0021] The data processing unit is used to collect and parse demand information;

[0022] The intelligent optimization unit is used to optimize parameters based on knowledge graphs and rule engines.

[0023] The template management unit is used to dynamically adjust the format of the task book template.

[0024] The generation and output unit is used to generate and output standardized task book documents with one click.

[0025] The present invention further proposes a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the steps of the intelligent optimization-based borehole sampling task book generation method described above.

[0026] The beneficial effects of this invention are as follows:

[0027] This invention improves the accuracy and efficiency of generating borehole sampling task sheets for geotechnical engineering geological exploration; it also solves the problems of low efficiency and easy omissions in traditional manual query specifications, and can be dynamically configured to significantly improve the flexibility and maintainability of the geological exploration resource database. Attached Figure Description

[0028] Figure 1 This is a flowchart illustrating the intelligent optimization-based borehole sampling task book generation method according to Embodiment 2 of the present invention.

[0029] Figure 2 This is a schematic diagram of some form fields in the geological exploration resource database involved in Embodiment 3 of the present invention;

[0030] Figure 3 This is a schematic diagram of the borehole sampling task template according to Embodiment 3 of the present invention;

[0031] Figure 4 This is a schematic diagram of a borehole sampling task book generated by referencing geological exploration resource database form data based on basic engineering information and inferred geological conditions, as described in Embodiment 3 of the present invention.

[0032] Figure 5 This is a schematic diagram of a software system architecture built using a drilling sampling task book generation method based on intelligent optimization, as described in Embodiment 3 of the present invention. Detailed Implementation

[0033] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be further described clearly and completely below in conjunction with the embodiments of this invention. It should be noted that the described embodiments are merely some embodiments of this invention, and not all embodiments. All other embodiments obtained by those skilled in the art based on the embodiments of this invention without creative effort are within the scope of protection of this invention.

[0034] As used in this specification and the following claims, the words “a,” “an,” and “the” have the meaning of plural reference unless the context clearly indicates otherwise. Furthermore, as used in the description herein, unless the context clearly indicates otherwise, “in” has the meaning of both “in…” and “on…”.

[0035] The following is a detailed description of embodiments of the invention depicted in the accompanying drawings. The embodiments are detailed in order to clearly convey the invention. However, the amount of detail provided is not intended to limit the contemplative variations of the embodiments; rather, it is intended to cover all modifications, equivalents, and substitutions falling within the spirit and scope of the invention as defined by the appended claims.

[0036] In the following description, numerous specific details are set forth in order to provide a thorough understanding of embodiments of the invention. It will be apparent to those skilled in the art that embodiments of the invention may be practiced without some of these specific details.

[0037] Example 1

[0038] This embodiment proposes a method for generating borehole sampling task sheets based on intelligent optimization, including:

[0039] A geological exploration resource database and a borehole sampling task book template database are constructed. The geological exploration resource database includes a relational database and an entity relationship data package. The relational database is used to store structured form data. The entity relationship data package includes entity relationships constructed from a knowledge graph regarding exploration specifications, engineering grades, stratigraphic lithology, and sampling parameters. The borehole sampling task book template database supports custom formats and content, stores data by industry category, and can automatically adjust field layout and required fields.

[0040] Collect and parse user-inputted requirements information, including geological conditions, exploration targets, and parameter requirements;

[0041] Using knowledge graphs for semantic understanding and requirement analysis, key parameters are identified and mapped to preset standard specifications. At the same time, based on this mapping relationship, matching sampling requirements are obtained from the geological exploration resource database.

[0042] Based on historical data and best practices, the rule engine automatically adjusts parameter values ​​and generates parameter configuration suggestions.

[0043] Call the template in the borehole sampling task book template library that is adapted to the current project scenario, dynamically adjust the task book template format, and automatically fill the optimized parameter configuration and the obtained sampling requirements into the dynamic template to generate the first draft of the task book.

[0044] Automatically generate borehole sampling task sheets that meet the requirements of accurate standard adaptation, intelligent parameter control, and dynamic template adjustment.

[0045] In some embodiments, the key parameters are indexed by basic engineering information (type and scale, etc.) combined with inferred geological conditions (strata lithology and groundwater level).

[0046] In some embodiments, the parameter configuration recommendations are specifically the sampling parameter range values ​​given in the exploration specifications; specifically, the parameter configuration recommendations are the sampling parameter "range values" given in the exploration specifications, so it is necessary to give an accurate fixed value within this "range value" based on historical experience.

[0047] In some embodiments, the rule engine is optimized to automatically generate parameter configuration suggestions based on geological conditions, exploration objectives, and parameter requirements, and is also used to issue warnings for outliers or parameters that do not meet standards, and provide correction suggestions.

[0048] In some embodiments, the operation of the rules engine is optimized based on the following data sources:

[0049] Historical exploration data;

[0050] Industry standards and specifications;

[0051] User-defined parameters.

[0052] In some optimized embodiments, the method further includes the following steps:

[0053] It provides version management functions and a user interface; the version management function is used to support historical record queries and version rollback; the user interface is used to input requirement information and view the generated task book documents.

[0054] Example 2

[0055] like Figure 2 As shown:

[0056] This embodiment proposes a method for generating borehole sampling task sheets based on intelligent optimization, applied to a computer system. The method includes:

[0057] S100, Receive engineering requirement information input by the user, the engineering requirement information including geological conditions and exploration targets and parameter requirements;

[0058] S200, Construct a geological exploration resource database; the geological exploration resource database includes a relational database and an entity association data package; the relational database is used to store structured form data; the entity association data package includes entity associations constructed from a knowledge graph regarding exploration specifications, engineering grades, stratigraphy, and sampling parameters;

[0059] S300, Establish a drilling sampling task template library for intelligent adaptation; the drilling sampling task template library is used to support custom formats and content, store them according to industry categories and can automatically adjust field layout and required fields;

[0060] S400: Use the knowledge graph in the geological exploration resource database to perform semantic understanding and requirement analysis on the engineering requirement information, identify key parameters and map the key parameters to preset standard specifications;

[0061] S500 calls the rule engine, which automatically adjusts the sampling-related parameter values ​​based on the key parameters and mapping results obtained from the parsing, combined with historical engineering data and best practices. At the same time, it obtains matching sampling requirements from the geological exploration resource library based on the basic information of the project and the geological conditions in the requirements.

[0062] S600 automatically fills the optimized parameters and obtained sampling requirements into the dynamic template adapted in the borehole sampling task book template library through the entity association mapping relationship of the knowledge graph, and generates the initial draft of the task book.

[0063] The S700, through a B / S or C / S architecture of a computer system, supports the viewing, editing, and distribution of task books, and realizes data traceability and closed-loop updates of the geological exploration resource database.

[0064] Specifically, the intelligent optimization-based borehole sampling task book generation method of this embodiment uses a relational database to build a universal geological exploration resource library. It uses forms to record the requirements of different industry exploration specifications for borehole sampling under different engineering conditions, which can be directly used for subsequent borehole sampling task book generation. This solves the problems of low efficiency and easy omission in traditional manual specification query. The dynamic configuration significantly improves the flexibility and maintainability of the geological exploration resource library.

[0065] In some embodiments, the geological exploration resource database in S200 is optimized to be a geological exploration resource database with a dual storage architecture of "relational database + knowledge graph"; the relational database is also used to record borehole sampling parameters for different engineering levels and exploration stages in different exploration specifications; the borehole sampling parameters include sampling type, quantity, vertical spacing and depth.

[0066] In some embodiments, optimized, in S200, the borehole sampling task template library includes a basic information layer and a sampling requirements layer; the basic information layer includes fixed fields: industry type and engineering level; the sampling requirements layer includes blank units classified by sampling type that belong to dynamic fields; the borehole sampling task template library is also used to record sampling requirements for various types of samples, customize text format and content addition permissions, and support the interface for linkage with system engineering data.

[0067] In some embodiments, the key parameters are optimized in S400 by indexing basic engineering information (type and scale, etc.) in conjunction with inferred geological conditions (strata lithology and groundwater level).

[0068] In some embodiments, the matching sampling requirement is specifically a range of sampling parameters generated after indexing from the geological exploration resource database to the specified exploration specification. Specifically, the matching sampling requirement is a "range value" of sampling parameters given after indexing from the geological exploration resource database to the specific exploration specification. Therefore, it is necessary to provide an accurate value within this "range value" based on historical experience.

[0069] In some embodiments, in S500, the requirements recorded in the borehole sampling form are retrieved from the geological exploration resource database by indexing basic engineering information including type and scale, combined with inferred geological conditions including stratigraphic lithology and groundwater level.

[0070] In some embodiments, in S600, the initial draft of the task book is automatically filled in: based on the entity relationship mapping of the knowledge graph, the query results of the resource library are filled into the corresponding blank cells of the template, thereby intelligently generating the sampling task book for the corresponding borehole.

[0071] In some optimized embodiments, the knowledge graph includes exploration specifications, engineering grade, stratigraphic lithology, borehole sampling parameters, and ternary relationships; the ternary relationships are the relationship between specifications applicable to engineering grade, engineering grade sampling dependent on stratigraphic lithology, and the corresponding sampling parameters of stratigraphic lithology; the borehole sampling parameters include four parameters: sampling type, quantity, vertical spacing, and depth.

[0072] In some embodiments, the geological exploration resource database has a built-in standard association mapping table. This table is used to achieve automatic conversion of terms and parameter adaptation between different standards, and supports incremental updates during version iterations. It is also used for dynamic configuration: that is, it allows borehole sampling personnel with configuration permissions to customize new standards, add information fields, and combine and adjust parameter ranges.

[0073] In some embodiments, the dynamic template in S600 includes a basic information layer, a sampling requirement layer, and an attachment association layer; the basic information layer is used to fix the industry type; the sampling requirement layer automatically matches the corresponding parameters based on the preset sampling type; and the attachment association layer is used to link the unstructured data of the three-dimensional geological model.

[0074] In some embodiments, the borehole sampling task template library is categorized and stored according to the engineering level and exploration stage of different industries. This is used to support the automatic matching of the optimal template from the geological exploration resource library and the acquisition of the requirements in the borehole sampling form based on basic engineering information including type and scale, as well as inferred geological conditions including stratigraphic lithology and groundwater level.

[0075] In some optimized embodiments, the process of inferring geological conditions is as follows: the lithological distribution of the strata at the location of the borehole is obtained based on the guide hole information of the three-dimensional geological model of the site; the guide hole information is a virtual hole at any location of the three-dimensional geological model.

[0076] In some embodiments, the computer system preferably includes the following modules:

[0077] The data acquisition module is used to collect and parse user input information.

[0078] The knowledge graph parsing module is used for semantic understanding and requirement analysis.

[0079] The parameter optimization module is used to automatically adjust parameter values ​​based on historical data and best practices.

[0080] The template management module is used to dynamically adjust the format of task book templates;

[0081] The task book generation module is used to automatically generate drilling sampling task books that meet the requirements of accurate specification adaptation, intelligent parameter optimization, and dynamic template adjustment.

[0082] In some embodiments, the parameter optimization module further includes a rule engine submodule and an anomaly detection submodule;

[0083] The rules engine submodule is used to generate parameter configuration suggestions based on geological conditions, exploration objectives, and parameter requirements;

[0084] The anomaly detection submodule is used to issue warnings for abnormal values ​​or parameters that do not meet the standards, and to provide correction suggestions.

[0085] In some embodiments, the template management module further includes a content replacement submodule and a content generation submodule;

[0086] The content replacement submodule is used to automatically replace fixed content and formatting in the template;

[0087] The content generation submodule is used to generate new template content based on optimized parameters and integrate it into existing templates.

[0088] In some embodiments, the task specification generation module is further optimized to output a standardized task specification document, including safety precautions and emergency measures.

[0089] In some embodiments, the task book generation module is further optimized to provide version management functions, supporting historical record queries and version rollback.

[0090] In some embodiments, the system further includes a data storage module for storing historical data, parameter configuration suggestions, and generated task sheets.

[0091] In some embodiments, the knowledge graph parsing module further optimizes the extraction of key parameters through semantic analysis and maps the key parameters to preset standard specifications.

[0092] In some embodiments, the rule engine module further optimizes the process by generating parameter configuration suggestions based on historical data and best practices, issuing warnings for outliers or parameters that do not meet standards, and providing correction suggestions.

[0093] Example 3

[0094] Example 3 is a further optimized design of Example 2;

[0095] like Figures 2-5 As shown:

[0096] This embodiment proposes a method for generating borehole sampling task sheets based on intelligent optimization, including:

[0097] In S200, in this embodiment, as Figure 2The geological exploration resource database forms shown here use the standard "Code for Geotechnical Engineering Investigation" (GB 50021) as the reference. Extracted fields include project type, exploration stage, stratigraphic lithology, and corresponding combinations of different sampling types such as borehole sampling quantity, vertical sampling spacing, and sampling depth (generally range values). Sampling types include disturbed soil samples, undisturbed soil samples, rock samples, and water samples. The industry type is "construction engineering," the project type is "building construction and pile foundation," the exploration stage is "preliminary exploration," and the stratigraphic lithology includes special soils such as soft soil and expansive soil. Personnel with configuration permissions can customize and add new standards and information fields such as borehole sampling, and assign range values ​​to fields such as borehole sampling quantity. They can also freely combine, delete, and adjust configured items.

[0098] In S200, such as Figure 3 As shown, the borehole sampling task book template was compiled using the document processing software WPS. The task book template is divided into two parts. The first part contains the basic information of the project, such as industry type, project type, project location, and exploration stage. The blank fields are automatically obtained and filled based on the relevant settings of the borehole sampling personnel. The second part contains the sampling type, sampling quantity, vertical sampling spacing, and sampling depth under specific strata and lithology. The blank fields are automatically filled based on the form information fields obtained from the geological resource database and combined with the specific strata and lithology.

[0099] In S500, the industry type is construction engineering, the project type is building construction and pile foundation, the estimated pile diameter is d=0.8m, the exploration stage is detailed exploration stage, and the stratigraphic lithology information, based on regional geological survey data and surrounding small-scale geological exploration data, is inferred as follows: Stratum 1 is silty clay, estimated thickness 2m; Stratum 2 is silty clay, belonging to soft soil, estimated thickness 5m; Stratum 3 is residual sandy clay, estimated thickness 4m; Stratum 4 is completely weathered granite, estimated thickness 2m; Stratum 5 is strongly weathered granite, estimated thickness 4m. Stratum 5 is initially selected as the bearing layer, i.e., the pile foundation is a rock-socketed pile. The estimated depth of the groundwater level is 8m, which is within the exploration depth range, therefore water samples need to be considered. Based on the above information, the requirements recorded in the borehole sampling form are retrieved from the geological exploration resource database.

[0100] In S600, such as Figure 4 As shown, the requirements recorded in the borehole sampling form are retrieved from the geological exploration resource database and combined with the stratigraphic lithology, groundwater level information and basic project information. The information is then automatically filled into the corresponding blank cells in the configured borehole sampling task book template according to the corresponding relationship, thereby intelligently generating the sampling task book for the corresponding borehole.

[0101] In the S700, the system adopts a B / S or C / S architecture. The geological exploration resource library and borehole sampling task template are deployed on the server, supporting cross-platform deployment on multiple operating systems such as Windows, Linux, and domestic IT innovation. The geological exploration resource library can be directly configured online by accessing the server through the B-end (web terminal) or C-end (client terminal). The borehole sampling task template is first edited locally and then uploaded to the server through the B-end (web terminal) or C-end (client terminal).

[0102] Specifically, the instructions required to generate a borehole sampling task book can be sent via a web page or a client. These instructions include setting the industry type, engineering type, and engineering exploration stage of the specific project; entering stratigraphic lithology and groundwater level information; retrieving relevant form information from the geological resource database and automatically filling it into the borehole sampling task book template; and viewing and editing the generated results on the web page or client. After confirming that there are no errors, designated borehole sampling personnel can be selected for distribution. The designated borehole sampling personnel can view the distributed content on the web page or client.

[0103] In some optimized embodiments, the requirements recorded in the borehole sampling form are retrieved from the geological exploration resource database using basic project information (type and scale, etc.) and inferred geological conditions (strata lithology and groundwater level) as an index.

[0104] Geological conditions are inferred based on the guide hole (a virtual hole at any position in the three-dimensional geological model) of the site to obtain the approximate distribution of strata lithology at the borehole location.

[0105] Specifically, the method in this embodiment constructs an intelligent decision-making system in the field of geological exploration: it achieves intelligent parameter prediction by integrating multi-source geological data with AI models, rather than passively recording data; it designs professional algorithms such as standard conflict adaptation and interval value optimization, and has the ability to make proactive decisions.

[0106] In some embodiments, the method of this embodiment, when applied in a specific engineering project, will automatically fill the data obtained from the resource library into the corresponding blank cells in the pre-prepared borehole sampling task book template, thereby intelligently generating the corresponding borehole sampling task book.

[0107] The reserved blank cells can record all sampling requirements for all types of samples (such as disturbed soil samples, undisturbed soil samples, rock samples, and water samples), such as the number of samples, vertical spacing of samples, and sampling depth; they can also record basic information such as the industry type, engineering level, project location, and exploration stage of a specific project as preliminary content.

[0108] The generation process includes a conflict detection mechanism. When different standards conflict on the same parameter, they are automatically adapted according to priority rules (national standards > industry standards > local standards). The priority can be customized by authorized personnel based on the specific characteristics of the project. When the data in the resource library is an interval value, the value is selected according to the rules optimized by the machine learning model. The model is trained and generated based on historical project compliance data and survey efficiency indicators. It can be dynamically adjusted according to the project risk level (the upper limit is taken for high-risk projects, the average value is taken for conventional projects, and the lower limit is taken for low-risk projects).

[0109] In some embodiments, the method of this embodiment adds a smart template adaptation function to the template compilation based on the document processing software. The template can automatically adjust the field layout and required fields according to the project type, thus breaking through the static limitations of traditional template compilation.

[0110] In some specific embodiments, the system designed by the method of this embodiment adopts a B / S or C / S architecture, wherein the resource library and templates are deployed on the server side, the instructions required to generate the borehole sampling task book are sent through the web or client side, and the generated results can be viewed, edited and distributed on the web or client side; the geological exploration resource library and the borehole sampling task book template are both deployed on the server side, supporting cross-platform deployment on multiple operating systems such as Windows, Linux and domestic IT innovation; the system supports access to the resource library and templates from the web or client side through API interface, supports multi-member sharing and hierarchical permission management; the system adopts caching preheating technology to improve the access speed of high-frequency standard data, introduces data compression algorithms to reduce transmission bandwidth occupation, and designs a breakpoint resume mechanism to ensure stable uploading of large file templates.

[0111] The intelligent agent involved in the method / system of this invention achieves the core value of exploration technology, such as "precise adaptation of standards, intelligent optimization of parameters, dynamic adjustment of templates, and one-click generation of task sheets," through the collaboration of "knowledge graph + rule engine."

[0112] The method / system of the present invention also has the following advantages:

[0113] More targeted: Focusing on a single key link of drilling and sampling, solving "operational" problems on the front line of production, rather than at the "analysis" level of problems;

[0114] Superior compliance: Through multi-standard conflict handling and intelligent range value selection, the task book is ensured to be 100% compliant with industry standards, avoiding human error;

[0115] Greater flexibility: Supports dynamic updates of standards and customizable template adjustments to adapt to the personalized needs of different industries and project types;

[0116] The efficiency improvement is more significant: the time from "manually reviewing specifications → compiling task book" is shortened to within 10 minutes of "inputting information → generating task book", and it also supports rapid adjustments after changes in geological conditions during construction.

[0117] Example 4

[0118] Example 4 is a further optimized design of Example 2;

[0119] The intelligent optimization-based borehole sampling task book generation method in this embodiment involves five key steps during execution: First, a universal geological exploration resource database is constructed using a relational database, and forms are used to record the borehole sampling requirements under different engineering conditions in different industry exploration specifications; second, a borehole sampling task book template is prepared, with blank cells reserved in the template to record the sampling requirements for various types of samples; third, in specific engineering applications, borehole data is retrieved from the geological exploration resource database using basic project information (type and scale, etc.) combined with inferred geological conditions (strata lithology and groundwater level) as an index. The requirements recorded in the sampling form; fourth, the data obtained from the resource library, combined with stratigraphic lithology and groundwater information, are automatically filled into the blank cells corresponding to the pre-prepared borehole sampling task book template to intelligently generate the borehole sampling task book; fifth, the above steps are implemented through a software system, which adopts a B / S or C / S architecture, in which the resource library and template are deployed on the server, and the instructions required to generate the borehole sampling task book are sent through the web or client, and the generated results can be viewed, edited and distributed on the web or client.

[0120] Specifically, the intelligent optimization-based borehole sampling task book generation method of this embodiment includes:

[0121] A geological exploration resource database with a dual storage architecture of "relational database + knowledge graph" is constructed: the relational database stores structured forms and records the borehole sampling parameters (sampling type, quantity, vertical spacing, depth) for different engineering levels and exploration stages in different exploration specifications; the knowledge graph stores the entity-relationship-attribute association relationship of "exploration specification-engineering level-stratum lithology-sampling parameters".

[0122] As a preferred option, the survey specifications include national general specifications, such as the "Code for Geotechnical Engineering Survey" (GB 50021), industry-specific specifications for various sectors, such as the "Code for Geological Survey of Highway Engineering" (JTG C20), the "Code for Geological Survey of Railway Engineering" (TB 10012), the "Code for Geological Survey of Water Conservancy and Hydropower Engineering" (GB 50487), the "Code for Geotechnical Engineering Survey of Thermal Power Plants" (GB / T 51031), and local specifications, such as the "Code for Geotechnical Engineering Survey of Urban Rail Transit in Zhejiang Province" (DB33 / T 1126) and the "Code for Survey of Expressways in Loess Areas" (DB62 / T 2993), etc.

[0123] As a preferred option, the borehole sampling form includes four parameters: sampling type, sampling quantity, vertical sampling spacing, and sampling depth. Sampling types include disturbed soil samples, undisturbed soil samples, rock samples, and water samples. The borehole sampling quantity, vertical sampling spacing, and sampling depth are generally range values.

[0124] As a preferred method, the borehole sampling form records the changes in sampling quantity, vertical spacing, and sampling depth under different sampling types, depending on six main influencing factors: industry type, project type, engineering exploration stage, exploration area, stratigraphic lithology, and groundwater level. Industry types include power, water conservancy, construction, etc., with different geological exploration specifications corresponding to different industry types. Project types include pile foundations, slopes, and caverns. Specific values ​​for exploration stages include preliminary exploration, detailed exploration, and construction exploration. Stratigraphic lithology includes collapsible soil, red clay, permafrost, expansive soil, saline soil, weathered rock, residual soil, and contaminated soil, among other special soil types. Groundwater level is mainly considered when it is higher than the exploration depth; if it is higher, water sampling should be considered. The exploration area is positively correlated with the sampling quantity; that is, the larger the area, the more samples are taken. Some geological exploration specifications have regulations corresponding to the exploration area.

[0125] As a preferred feature, this geological exploration resource database supports dynamic configuration. Drilling and sampling personnel with configuration permissions can customize and add new specifications and information fields such as borehole sampling type, and combine them. They can also assign range values ​​to parameters such as borehole sampling quantity, vertical sampling spacing, and sampling depth. They can freely combine, delete, and adjust the configured items. The resource database has a built-in specification association mapping table to realize automatic terminology conversion and parameter adaptation between different specifications. It supports incremental updates when specification versions are iterated, avoiding full reconstruction.

[0126] As a second aspect of the present invention, the present invention provides a template for creating a borehole sampling task book, which can then be directly called from a geological resource database to fill in blank data and generate a borehole sampling task book containing basic information about the specific project. The process can be summarized as follows:

[0127] Build an intelligently adaptable borehole sampling task template library: The template includes a basic information layer (fixed fields: industry type, project level, etc.) and a sampling requirements layer (dynamic fields: blank cells classified by sampling type) to record the sampling requirements of various types of samples. The template library is stored in categories according to "industry type" and can automatically adjust the field layout and required fields according to the project type. It has custom text format and content addition permissions and supports the interface for linkage with system engineering data.

[0128] Preferably, the document processing software can be the Office suite, WPS, etc., and the template text format can be .docx, .doc, .rtf, .pdf, etc.

[0129] As a preferred option, a borehole sampling task template is prepared in advance using document processing software. The template has reserved blank cells that can record all sampling requirements for all types of samples (such as disturbed soil samples, undisturbed soil samples, rock samples, and water samples), such as the number of samples, vertical spacing of samples, and sampling depth. It can also record basic information such as the industry type, project type, project location, and exploration stage of the specific project as preliminary content.

[0130] As a preferred option, this borehole sampling task template supports dynamic configuration. Borehole sampling tasks with configuration permissions, in addition to including basic project information, sampling type, and sampling requirements such as sampling quantity, vertical spacing, and sampling depth in blank cells, can also customize other text formats, such as font style and size, paragraph spacing, and freely add other text content, such as titles. The template supports intelligent adaptation, which can automatically adjust the field layout and required fields according to the project type, and reserves an interface for linkage with system engineering data.

[0131] As a third aspect of the present invention, the present invention provides a method for querying a geological exploration resource database based on basic engineering information and inferred geological conditions to obtain the requirements recorded in the borehole sampling form. The process can be summarized as follows:

[0132] In specific engineering applications, the requirements recorded in the borehole sampling form are obtained from the geological exploration resource database by using basic project information (type and scale, etc.) and inferred geological conditions (strata lithology and groundwater level) as an index.

[0133] As a preferred option, basic project information includes industry type, project type, project exploration stage, and exploration area area; stratigraphic and lithological information includes stratigraphic sequence and average stratigraphic thickness; and groundwater refers to the absolute elevation of groundwater and its relative depth to the exploration area.

[0134] As a preferred option, stratigraphic lithology and groundwater level information can first be obtained from large-scale stratigraphic data in regional geological survey data. If there are available engineering data around the exploration area, they should be obtained first from these engineering data. When data is lacking, query interfaces for DeepSeek and OpenAI models have been built, which can automatically search and obtain data based on the location information of the engineering area.

[0135] As a preferred option, the requirements recorded in the borehole sampling form are obtained from the geological exploration resource database based on the basic project information, including industry type, project type, project exploration stage, exploration area, and inferred stratigraphic lithology and groundwater level information.

[0136] The data obtained from the geological exploration resource database will be automatically filled into the corresponding blank cells in the pre-prepared borehole sampling task book template, thereby intelligently generating the corresponding borehole sampling task book.

[0137] As a preferred method, the data is automatically entered into the borehole sampling task template based on the query data, sampling type, and sampling requirements, such as the correspondence between sampling quantity, vertical sampling spacing, and sampling depth.

[0138] As a preferred option, when the sampling requirement obtained from the geological exploration resource database is an interval value, the deterministic value entered is optimized by a machine learning model. The model is generated based on historical engineering compliance data and exploration efficiency indicators, and is optimized using a gradient descent algorithm. It can be dynamically adjusted according to the engineering risk level (the upper limit value is taken for high-risk projects, the average value is taken for conventional projects, and the lower limit value is taken for low-risk projects).

[0139] Preferably, the generated borehole sampling task sheet text format can be .docx, .doc, .rtf, .pdf, etc.

[0140] As a fourth aspect of the present invention, the present invention provides a method for implementing the above steps using a software system architecture such as B / S or C / S architecture, some of which can be summarized as follows:

[0141] Implemented through a software system, the system adopts a B / S or C / S architecture. The geological exploration resource library and templates are deployed on the server. The instructions required to generate the borehole sampling task book are sent through a web page or client. The generated results can be viewed, edited, and distributed on the web page or client.

[0142] As a preferred option, both the geological exploration resource database and the borehole sampling task template are deployed on the S (server) side, supporting cross-platform deployment on multiple operating systems such as Windows, Linux, and domestically developed IT applications;

[0143] Preferably, the system supports access to the geological exploration resource database and borehole sampling task book template from either a B-end (web-based) or C-end (client-based) via an API interface, and supports sharing among multiple members. Appropriate member configuration permissions can be set for the geological exploration resource database and borehole sampling task book template. Borehole sampling personnel with configuration permissions for the geological exploration resource database can perform dynamic configuration operations on the database, while those with configuration permissions for the borehole sampling task book template can dynamically configure the template and upload it to the S (server) end. Other borehole sampling personnel can only view and access the template.

[0144] Preferably, the instructions required to generate the borehole sampling task book are sent via a web page or client. The instructions include setting the industry type, engineering type, engineering exploration stage, and exploration area of ​​the specific project; manually entering the lithology and groundwater level information; automatically searching for and obtaining the lithology and groundwater level information using the query interface of DeepSeek and OpenAI models; and previewing and editing the generated borehole sampling task book.

[0145] Furthermore, the generated borehole sampling task sheets can be viewed and edited on a web page or client, and can be quickly distributed online by designated borehole sampling personnel. Personnel receiving the distribution message can view it on the web page or client. A load balancing module is deployed on the server side to support concurrent task processing for multiple projects. The system has a fault tolerance mechanism, automatically switching to a backup node when a temporary server failure occurs. Caching and preheating technology is used to improve the access speed of high-frequency standard data, data compression algorithms are introduced to reduce transmission bandwidth consumption, and a breakpoint resume mechanism is designed to ensure stable uploading of large file templates.

[0146] Example 5

[0147] This embodiment proposes a system built using the method described in any one of the technical solutions of any of the embodiments 1-4. The system includes the following components:

[0148] The data processing unit is used to collect and parse demand information;

[0149] The intelligent optimization unit is used to optimize parameters based on knowledge graphs and rule engines.

[0150] The template management unit is used to dynamically adjust the format of the task book template.

[0151] The generation and output unit is used to generate and output standardized task book documents with one click.

[0152] In some embodiments, the intelligent optimization unit is optimized to include a parameter configuration subunit and an exception handling subunit:

[0153] The parameter configuration subunit is used to generate parameter configuration suggestions based on geological conditions and exploration objectives.

[0154] The exception handling subunit is used to detect and correct parameters that do not meet the standards.

[0155] In some embodiments, the template management unit is optimized to include a content replacement subunit and a content generation subunit;

[0156] The content replacement sub-unit is used to automatically replace fixed content and formatting in the template;

[0157] The content generation subunit is used to generate new template content based on the optimized parameters and integrate it into the existing template.

[0158] In some embodiments, the generation and output unit is further configured to output a standardized task specification document, including safety precautions and emergency measures.

[0159] In some embodiments, the generation and output unit is further configured to provide version management functionality, supporting historical record queries and version rollback.

[0160] Example 6

[0161] This embodiment proposes a computer-readable storage medium storing a computer program. When the computer program is executed by a processor, it implements the steps of the intelligent optimization-based borehole sampling task book generation method as described in any one of the technical solutions of any one of the embodiments 1-4.

[0162] The processor can have various specific implementations. For example, it may include one or more combinations of a central processing unit (CPU), GPU, NPU, TPU, or DPU, etc., and this application embodiment does not impose specific limitations. The processor can also be a single-core processor or a multi-core processor. The processor can be a combination of a CPU and hardware chips. The aforementioned hardware chips can be application-specific integrated circuits (ASICs), programmable logic devices (PLDs), or combinations thereof. The aforementioned PLDs can be complex programmable logic devices (CPLDs), field-programmable gate arrays (FPGAs), generic array logic (GALs), or any combination thereof. The processor can also be implemented using logic devices with built-in processing logic, such as FPGAs or digital signal processors (DSPs).

[0163] The storage medium described in this embodiment can be volatile memory or non-volatile memory, or both. The non-volatile memory can be read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), or flash memory. The volatile memory can be random access memory (RAM), which is used as an external cache. By way of example, but not limitation, many forms of RAM are available, such as static random access memory (SRAM), dynamic random access memory (DRAM), synchronous dynamic random access memory (SDRAM), double data rate synchronous dynamic random access memory (DDR SDRAM), enhanced synchronous dynamic random access memory (ESDRAM), synchronous linked dynamic random access memory (SLDRAM), and direct rambus RAM (DRRAM).

[0164] Embodiments of the present invention include various steps, which will be described below. These steps may be performed by hardware components or may be contained in machine-executable instructions, which may be used by a general-purpose or special-purpose processor programmed with the instructions to perform these steps. Alternatively, the steps may be performed by a combination of hardware, software, and firmware and / or by a human operator. The processor involved in the embodiments of this application may be a chip. For example, it may be a field-programmable gate array (FPGA), an application-specific integrated circuit (ASIC), a system-on-chip (SoC), a central processing unit (CPU), a network processor (NP), a digital signal processor (DSP), a microcontroller unit (MCU), a programmable logic device (PLD), or other integrated chips.

[0165] Furthermore, the present invention can be implemented using hardware, software, firmware, middleware, microcode, hardware description languages, or any combination thereof. When implemented in software, firmware, middleware, or microcode, program code or code segments (e.g., a computer program product) that perform the necessary tasks can be stored in a machine-readable medium. The processor can perform the necessary tasks. In the above embodiments, it can be implemented wholly or partially using software, hardware, firmware, or any combination thereof. When implemented using a software program, it can be implemented wholly or partially in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, all or part of the flow or function described in the embodiments of this application is generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another via wired (e.g., coaxial cable, fiber optic, Digital Subscriber Line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium that a computer can access, or it can include one or more data storage devices such as servers or data centers that can be integrated with media. The available medium can be magnetic media (e.g., floppy disks, hard disks, magnetic tapes), optical media (e.g., DVDs), or semiconductor media (e.g., solid-state drives (SSDs)).

[0166] The system, device, and storage medium in this invention are based on multiple aspects of the same inventive concept as the method in the foregoing embodiments. The implementation process of the method has been described in detail above, so those skilled in the art can clearly understand the structure and implementation process of the system, device, and storage medium in this embodiment based on the foregoing description. For the sake of brevity, it will not be described again here.

[0167] The present invention can also provide some of the systems depicted in the figures in various configurations. In some embodiments, the system can be configured as a distributed system, wherein one or more components of the system are distributed across one or more networks of a cloud computing system.

[0168] 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 method for generating borehole sampling task sheets based on intelligent optimization, characterized in that, include: A geological exploration resource database and a borehole sampling task book template database are constructed. The geological exploration resource database includes a relational database and an entity relationship data package. The relational database is used to store structured form data. The entity relationship data package includes entity relationships constructed from a knowledge graph regarding exploration specifications, engineering grades, stratigraphic lithology, and sampling parameters. The borehole sampling task book template database supports custom formats and content, stores data by industry category, and can automatically adjust field layout and required fields. Collect and parse user-inputted requirements information, including geological conditions, exploration targets, and parameter requirements; Using knowledge graphs for semantic understanding and requirement analysis, key parameters are identified and mapped to preset standard specifications. At the same time, based on this mapping relationship, matching sampling requirements are obtained from the geological exploration resource database. Based on historical data and best practices, the rule engine automatically adjusts parameter values ​​and generates parameter configuration suggestions. Call the template in the borehole sampling task book template library that is adapted to the current project scenario, dynamically adjust the task book template format, and automatically fill the optimized parameter configuration and the obtained sampling requirements into the dynamic template to generate the first draft of the task book. Automatically generate borehole sampling task sheets that meet the requirements of accurate standard adaptation, intelligent parameter control, and dynamic template adjustment.

2. The method according to claim 1, characterized in that, The key parameters are indexed by basic engineering information and inferred geological conditions; The parameter configuration recommendations are based on the sampling parameter range values ​​given in the exploration specifications; The rule engine is used to automatically generate parameter configuration suggestions based on geological conditions, exploration targets and parameter requirements. It is also used to issue warnings for outliers or parameters that do not meet the standards and to provide correction suggestions. The rules engine operates based on the following data sources: Historical exploration data; Industry standards and specifications; User-defined parameters.

3. The method according to claim 1, characterized in that, The method also includes the following steps: It provides version management functions and a user interface; the version management function is used to support historical record queries and version rollback; the user interface is used to input requirement information and view the generated task book documents.

4. A method for generating borehole sampling task sheets based on intelligent optimization, applied in a computer system, characterized in that, The method includes: S100, Receive engineering requirement information input by the user, the engineering requirement information including geological conditions and exploration targets and parameter requirements; S200, Construct a geological exploration resource database; the geological exploration resource database includes a relational database and an entity association data package; the relational database is used to store structured form data; the entity association data package includes entity associations constructed from a knowledge graph regarding exploration specifications, engineering grades, stratigraphy, and sampling parameters; S300, Establish a drilling sampling task template library for intelligent adaptation; the drilling sampling task template library is used to support custom formats and content, store them according to industry categories and can automatically adjust field layout and required fields; S400: Use the knowledge graph in the geological exploration resource database to perform semantic understanding and requirement analysis on the engineering requirement information, identify key parameters and map the key parameters to preset standard specifications; S500 calls the rule engine, which automatically adjusts the sampling-related parameter values ​​based on the key parameters and mapping results obtained from the parsing, combined with historical engineering data and best practices. At the same time, it obtains matching sampling requirements from the geological exploration resource library based on the basic information of the project and the geological conditions in the requirements. S600 automatically fills the optimized parameters and obtained sampling requirements into the dynamic template adapted in the borehole sampling task book template library through the entity association mapping relationship of the knowledge graph, and generates the initial draft of the task book. The S700, through a B / S or C / S architecture of a computer system, supports the viewing, editing, and distribution of task books, and realizes data traceability and closed-loop updates of the geological exploration resource database.

5. The method according to claim 4, characterized in that, In S200, the geological exploration resource database is a geological exploration resource database with a dual storage architecture of "relational database + knowledge graph"; the relational database is also used to record borehole sampling parameters for different engineering levels and exploration stages in different exploration specifications; the borehole sampling parameters include sampling type, quantity, vertical spacing and depth; In S200, the borehole sampling task template library includes a basic information layer and a sampling requirement layer; the basic information layer includes fixed fields: industry type and engineering level; the sampling requirement layer includes blank units classified by sampling type, which are dynamic fields; the borehole sampling task template library is also used to record the sampling requirements of various types of samples, customize text format and content addition permissions, and support the interface for linkage with system engineering data; In S400, the key parameters are indexed by basic engineering information and inferred geological conditions; In S500, the requirements recorded in the borehole sampling form are obtained from the geological exploration resource database by using basic engineering information including type and scale, combined with inferred geological conditions including stratigraphic lithology and groundwater level as an index. In S500, the matching sampling requirement is the range of sampling parameters generated after indexing from the geological exploration resource database to the specified exploration specification; In S600, the initial draft of the task book is automatically generated: based on the entity relationship mapping of the knowledge graph, the query results of the resource library are filled into the corresponding blank cells of the template, thereby intelligently generating the sampling task book for the corresponding borehole.

6. The method according to claim 4, characterized in that, The knowledge graph includes exploration specifications, engineering grade, stratigraphic lithology, borehole sampling parameters, and ternary relationships. The ternary relationships are the relationship between the specifications applicable to the engineering grade, the engineering grade sampling depending on the stratigraphic lithology, and the corresponding sampling parameters of the stratigraphic lithology. The borehole sampling parameters include four parameters: sampling type, quantity, vertical spacing, and depth. The geological exploration resource database has a built-in standard association mapping table, which is used to realize the automatic conversion of terms and parameter adaptation between different standards, and supports incremental updates during version iteration. It is also used for dynamic configuration: that is, it allows borehole sampling personnel with configuration permissions to customize new standards, add information fields, and combine and adjust parameter ranges.

7. The method according to claim 4, characterized in that, In S600, the dynamic template includes a basic information layer, a sampling requirement layer, and an attachment association layer; the basic information layer is used to fix the industry type; the sampling requirement layer automatically matches the corresponding parameters based on the preset sampling type; the attachment association layer is used to link the unstructured data of the three-dimensional geological model; The borehole sampling task template library is classified and stored according to the engineering level and exploration stage of different industries. It is used to support the automatic matching of the optimal template from the geological exploration resource library and the acquisition of the requirements in the borehole sampling form based on basic engineering information including type and scale, as well as the inferred geological conditions including stratigraphic lithology and groundwater level. The process of inferring geological conditions is as follows: based on the guide hole information of the three-dimensional geological model of the site, the distribution of strata and lithology at the location of the borehole is obtained; the guide hole information is a virtual hole at any location in the three-dimensional geological model.

8. The method according to any one of claims 4-7, characterized in that, The computer system includes the following modules: The data acquisition module is used to collect and parse user input information. The knowledge graph parsing module is used for semantic understanding and requirement analysis. The parameter optimization module is used to automatically adjust parameter values ​​based on historical data and best practices. The template management module is used to dynamically adjust the format of task book templates; The task book generation module is used to automatically generate drilling sampling task books that meet the requirements of accurate specification adaptation, intelligent parameter optimization, and dynamic template adjustment.

9. A system constructed by the method described in any one of claims 1-3, characterized in that, Includes the following components: The data processing unit is used to collect and parse demand information; The intelligent optimization unit is used to optimize parameters based on knowledge graphs and rule engines. The template management unit is used to dynamically adjust the format of the task book template. The generation and output unit is used to generate and output standardized task book documents with one click.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by the processor, it implements the steps of the intelligent optimization-based borehole sampling task book generation method as described in any one of claims 1-7.

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