Oil and gas exploration business process generation method and device

Abstract

This invention discloses a method and apparatus for generating oil and gas exploration business processes. The method includes: acquiring selection results of oil and gas exploration data and exploration business requirements; breaking down the exploration business requirements and identifying keywords; inputting the identified keywords sequentially into a text classification model and outputting classification results; searching a module library for modules whose keyword matching probability with the module name is greater than a preset probability based on the classification results; determining the input-output relationship of the modules; configuring parameters in the modules that are not pre-configured based on the selection results and exploration business requirements; and generating and displaying an oil and gas exploration business process based on the module's input-output relationship and the selected oil and gas exploration data, using the configured module as a node. This method can improve the generation efficiency of oil and gas exploration business processes and the accuracy of oil and gas exploration data processing, and can quickly respond to changes in exploration business requirements.

Description

Technical Field

[0001] This invention relates to the field of energy retail technology, and in particular to a method and apparatus for generating oil and gas exploration business processes. Background Technology

[0002] This section is intended to provide background or context for embodiments of the present invention. The description herein is not intended to imply that it is prior art simply because it is included in this section.

[0003] Oil and gas exploration is a highly complex and technology-intensive industry, involving a large amount of data processing, analysis, and decision-making. As the business processes of oil and gas companies become increasingly complex and diversified, effectively managing and optimizing these processes to improve overall operational efficiency, ensure business quality, and reduce operating costs has become a key issue.

[0004] Traditional oil and gas exploration business processes rely on manual operation and experience-based judgment, which is not only inefficient and costly in terms of process generation and management, but also difficult to adapt to rapidly changing environments and technological advancements. It is also difficult to respond quickly to changes in exploration business needs, resulting in low accuracy in oil and gas exploration data processing. Summary of the Invention

[0005] This invention provides a method for generating oil and gas exploration business processes to improve the efficiency of generating oil and gas exploration business processes and the accuracy of oil and gas exploration data processing, enabling rapid response to changes in exploration business needs. The method includes:

[0006] The system obtains the user's selection results from multiple oil and gas exploration business systems, as well as the user's input exploration business requirements, which are in the form of text data.

[0007] The exploration business requirements are broken down, and the keywords of the broken-down exploration business requirements are identified.

[0008] The identified keywords are sequentially input into a pre-trained text classification model, and the classification results are output. The text classification model is trained using historical oil and gas exploration data, a pre-established thesaurus for oil and gas exploration business, and module names in the module library. The classification result is the matching probability between keywords and module names.

[0009] Based on the classification results, modules with a keyword matching probability greater than a preset probability are searched in the module library; the modules include pre-configured parameters and non-pre-configured parameters;

[0010] Based on the order of keywords in the exploration business requirements, and / or the textual data between keywords in the exploration business requirements, determine the input-output relationship of the module;

[0011] Based on the selection results and exploration business requirements, configure the parameters that are not pre-configured in the module;

[0012] Using pre-configured modules as nodes, the system generates and displays oil and gas exploration business processes based on the module's input-output relationships and the selected oil and gas exploration data.

[0013] This invention also provides an oil and gas exploration business process generation device to improve the generation efficiency of oil and gas exploration business processes and the accuracy of oil and gas exploration data processing, enabling rapid response to changes in exploration business needs. The device includes:

[0014] The acquisition module is used to acquire the user's selection result from multiple oil and gas exploration business systems, as well as the exploration business requirements input by the user; the exploration business requirements are text data.

[0015] The splitting module is used to break down exploration business requirements and perform keyword recognition on the split exploration business requirements;

[0016] The classification module is used to input the identified keywords into a pre-trained text classification model and output the classification results. The text classification model is trained using historical oil and gas exploration data, a pre-established thesaurus for oil and gas exploration business, and module names in the module library. The classification result is the matching probability between the keyword and the module name.

[0017] The search module is used to search the module library for modules whose keyword matching probability with the module name is greater than a preset probability, based on the classification results; the module includes pre-configured parameters and non-pre-configured parameters;

[0018] The input-output relationship determination module is used to determine the input-output relationship of the module based on the order of keywords in the exploration business requirements and / or the text data between keywords in the exploration business requirements.

[0019] The parameter configuration module is used to configure parameters that are not pre-configured in the module according to the selection results and exploration business requirements;

[0020] The oil and gas exploration business process generation module is used to generate and display oil and gas exploration business processes based on the input and output relationships of modules with configured parameters and the selected oil and gas exploration data, using these modules as nodes.

[0021] Compared with existing oil and gas exploration business process generation technologies, this invention obtains the user's selection results from multiple oil and gas exploration business systems, as well as the user's input exploration business requirements; these requirements are textual data; the exploration business requirements are broken down, and keyword recognition is performed on the broken-down requirements; the identified keywords are sequentially input into a pre-trained text classification model, and the classification results are output; the text classification model is trained using historical oil and gas exploration data, a pre-established specialized thesaurus for the oil and gas exploration business field, and module names in a module library; the classification result is the matching probability between keywords and module names; based on the classification results, in The module library searches for modules whose keyword matching probability with module name is greater than a preset probability; the modules include pre-configured parameters and non-pre-configured parameters; the input-output relationship of the modules is determined based on the order of keywords in exploration business requirements, and / or the textual data between keywords in exploration business requirements; based on the selection results and exploration business requirements, the non-pre-configured parameters in the modules are configured; using the modules with configured parameters as nodes, an oil and gas exploration business process is generated and displayed based on the module's input-output relationship and the selected oil and gas exploration data, which can improve the generation efficiency of oil and gas exploration business processes and the accuracy of oil and gas exploration data processing, and can quickly respond to changes in exploration business requirements. Attached Figure Description

[0022] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort. In the drawings:

[0023] Figure 1 This is a flowchart of an oil and gas exploration business process generation method provided in an embodiment of the present invention;

[0024] Figure 2 A flowchart illustrating a specific example of an oil and gas exploration business process generation method provided in this embodiment of the invention;

[0025] Figure 3 This is a schematic diagram of an oil and gas exploration business process generation device provided in an embodiment of the present invention;

[0026] Figure 4 This is a schematic diagram of a specific example of an oil and gas exploration business process generation device provided in an embodiment of the present invention;

[0027] Figure 5This is a schematic diagram of a computer device provided in an embodiment of the present invention. Detailed Implementation

[0028] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the embodiments of the present invention will be further described in detail below with reference to the accompanying drawings. Here, the illustrative embodiments of the present invention and their descriptions are used to explain the present invention, but are not intended to limit the present invention.

[0029] The acquisition, storage, use, and processing of data in this application comply with relevant laws and regulations.

[0030] In this document, the term "and / or" merely describes a relationship, indicating that three relationships can exist. For example, A and / or B can represent three cases: A alone, A and B simultaneously, and B alone. Furthermore, the term "at least one" in this document means any combination of at least two of any one or more elements. For example, including at least one of A, B, and C can mean including any one or more elements selected from the set consisting of A, B, and C.

[0031] In the description of this specification, the terms "comprising," "including," "having," and "containing" are open-ended terms, meaning that they include but are not limited to. The terms "an embodiment," "a specific embodiment," "some embodiments," and "for example," etc., refer to specific features, structures, or characteristics described in connection with that embodiment or example that are included in at least one embodiment or example of this application. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, or characteristics described can be combined in any suitable manner in one or more embodiments or examples. The order of steps involved in the various embodiments is used to illustrate the implementation of this application, and the order of steps is not limited and can be adjusted appropriately as needed.

[0032] During digital transformation, business processes involve the flow and processing of large amounts of heterogeneous data. The data records of intermediate results, execution steps, and related nodes generated during the process from the initial state of oil and gas data to the final output are also crucial. However, existing process management systems generally lack effective data collection, analysis, and feedback mechanisms, making it impossible to track process status in real time, and even more difficult to provide detailed process records and quantitative evaluation indicators to support continuous process improvement and optimization.

[0033] With the development of artificial intelligence and big data technologies, the oil and gas exploration industry has an increasingly urgent need for tools that can automate and intelligently design processes, monitor execution, and evaluate performance. Therefore, a new technological solution is urgently needed that can build a complete system for collecting process events and node events on top of specific business operations in the oil and gas exploration industry, and combine this with data analysis algorithms to provide users with objective and accurate assessments of process completion quality, thereby helping oil and gas companies achieve efficient and flexible process management in a constantly changing business environment.

[0034] The embodiments of the present invention aim to enable the generated oil and gas exploration business process to respond quickly to changes in exploration needs, achieve rapid iteration and optimization of the process, and significantly improve the design and execution efficiency of the oil and gas exploration process.

[0035] Figure 1 This is a flowchart of a method for generating an oil and gas exploration business process provided in an embodiment of the present invention, such as... Figure 1 As shown, the method may include:

[0036] Step 101: Obtain the user's selection result from multiple oil and gas exploration business systems, as well as the exploration business requirements input by the user; the exploration business requirements are text data.

[0037] Step 102: Decompose the exploration business requirements and identify keywords in the decomposed exploration business requirements;

[0038] Step 103: Input the identified keywords into the pre-trained text classification model in sequence and output the classification results; the text classification model is trained using historical oil and gas exploration data, a pre-established specialized thesaurus for oil and gas exploration business, and module names in the module library; the classification result is the matching probability between keywords and module names.

[0039] Step 104: Based on the classification results, search the module library for modules whose keyword and module name have a matching probability greater than a preset probability; the modules include pre-configured parameters and non-pre-configured parameters;

[0040] Step 105: Determine the input-output relationship of the module based on the order of keywords in the exploration business requirements and / or the textual data between keywords in the exploration business requirements.

[0041] Step 106: Configure the parameters that are not pre-configured in the module according to the selection results and exploration business requirements;

[0042] Step 107: Using the module with configured parameters as a node, generate and display the oil and gas exploration business process based on the module's input-output relationship and the selected oil and gas exploration data.

[0043] Compared with existing oil and gas exploration business process generation technologies, the embodiments of this invention can improve the efficiency of oil and gas exploration business process generation and the accuracy of oil and gas exploration data processing, enabling rapid response to changes in exploration business needs. It meets the unique requirements of the oil and gas exploration field and enhances the professionalism and accuracy of data processing.

[0044] In one embodiment, the selection results of the user selecting oil and gas exploration data from multiple oil and gas exploration business systems according to the data index through a visual interface, as well as the exploration business requirements input by the user through the visual interface, can be obtained.

[0045] In one embodiment, a visual interface can be provided by the system. The oil and gas exploration business system may include: an exploration and production technology data management system, an oil, gas and water well production data management system, an oil and gas production Internet of Things system, etc.; the exploration business requirements can be input by the user through the visual interface, such as "importing seismic data, preprocessing the seismic data, and then interpreting the preprocessed seismic data." Through the visual interface, users can build and customize complex oil and gas exploration business process models in an intuitive and efficient way.

[0046] In one embodiment, the exploration business requirements are broken down and keyword recognition is performed on the broken-down exploration business requirements. This may include: breaking down the exploration business requirements according to preset identifiers to obtain multiple clauses; performing keyword recognition on each clause using a keyword recognition model to obtain keyword recognition results corresponding to each clause; the keyword recognition model is obtained by training a deep neural network model using the clauses obtained from breaking down historical exploration business requirements according to preset identifiers and a special terminology library for the oil and gas exploration business field.

[0047] In one embodiment, keyword recognition is performed on each clause using a keyword recognition model to obtain keyword recognition results corresponding to each clause. This may include: splitting each clause using a keyword recognition model to obtain multiple words corresponding to each clause; performing entity recognition on each word corresponding to each clause using a keyword recognition model to obtain entity names corresponding to each clause; extracting keyword features from the entity names corresponding to each clause using a keyword recognition model, and identifying keyword recognition results corresponding to each clause based on the extracted keyword features.

[0048] In this embodiment, step 102 breaks down the phrase "after importing seismic data, preprocess the seismic data, and then interpret the preprocessed seismic data." Specifically, the exploration business requirement can be broken down into multiple clauses according to preset identifiers. For example, if the user inputs the exploration business requirement through the visualization page as "after importing seismic data, preprocess the seismic data, and then interpret the preprocessed seismic data," the preset identifiers can be commas, periods, etc. Breaking down the exploration business requirement according to these preset identifiers results in the clauses "after importing seismic data," "preprocess the seismic data," "then," and "interpret the preprocessed seismic data." The word "then" has no specific meaning in the subsequent exploration business processing flow; therefore, the clauses can be filtered after obtaining them to get the desired clauses.

[0049] In this embodiment, a pre-trained segmentation model can be used to establish a specialized thesaurus for the oil and gas exploration business domain. This thesaurus can then be used to train the semantic segmentation model, generating a segmentation model. The segmented results can be "Import seismic data," "Preprocess seismic data," or "Interpret seismic data after preprocessing."

[0050] The specialized terminology database for the oil and gas exploration business can be updated in real time according to the technological advancements in the field, in order to adapt to the rapidly changing environment and technological progress.

[0051] Figure 2 A flowchart illustrating a specific example of an oil and gas exploration business process generation method provided in this embodiment of the invention, such as... Figure 2 As shown, in one embodiment, the oil and gas exploration business process generation method may further include:

[0052] Step 201: Obtain the historical exploration business requirements input by the user through the visual interface;

[0053] Step 202: According to the preset identifiers, the historical exploration business requirements are broken down into multiple clauses;

[0054] Step 203: Using multiple clauses obtained by breaking down historical exploration business requirements and a specialized thesaurus for the oil and gas exploration business field, a deep neural network model is trained to generate a keyword recognition model.

[0055] In this embodiment, keyword recognition can also be performed on each clause using a keyword recognition model to obtain the keyword recognition results corresponding to each clause. The keyword recognition model can be obtained by training a deep neural network model using clauses that have been split according to preset identifiers based on historical exploration business requirements and a specialized thesaurus for the oil and gas exploration business field. Figure 2The process shown can also utilize existing keyword recognition technology, which will not be elaborated here.

[0056] In one embodiment, the method for generating an oil and gas exploration business process may further include: obtaining the selection result of a user selecting historical oil and gas exploration data from multiple oil and gas exploration business systems through a visual interface in accordance with a data index; and training a classification model using historical oil and gas exploration data, a specialized thesaurus for the oil and gas exploration business field, and module names in a module library to generate a text classification model.

[0057] Before step 103, a text classification model is pre-trained. The identified keywords are sequentially input into the trained text classification model, and the classification result is output. The classification result represents the probability of matching the keyword with the module name. In step 103, inputting "preprocessing earthquake data" into the text classification model will result in a classification result with a 95% probability of matching the module name "earthquake data preprocessing".

[0058] In step 104, based on the classification results, modules whose names match keywords with a probability greater than a preset probability are searched in the module library. Modules include both pre-configured and unconfigured parameters. As mentioned above, the "Seismic Data Preprocessing" module can be searched in step 104. The module has its internal logic and some parameters pre-configured.

[0059] In step 105, the input-output relationship of each module is determined based on the order of keywords corresponding to the classification results in the business requirements and the textual data between the keywords. For example, it can be determined that a is the input of b based on a "import earthquake data" after b "preprocess earthquake data". Alternatively, it can be determined that a is the input of b based on the textual data "after" between a and b. If a and b are "simultaneously", then they have the same execution order in the business process. In this case, the judgment condition 1: "based on the textual data between the keywords" has a higher priority than the judgment condition 2: "the order of keywords corresponding to the classification results in the business requirements".

[0060] In step 106, configure the parameters that the module has not configured properly according to the selection result and business requirements. For example, if the selection result is "data from the earthquake data system", configure the data source path of the "earthquake data import" module to the earthquake data system according to the selection result "earthquake data import", or configure the data source path of the "earthquake data import" module to the earthquake data system according to the business requirements "import earthquake data".

[0061] In step 107, using the configured modules as nodes, an oil and gas exploration business process is generated and displayed based on the module's input-output relationships and the selected oil and gas exploration data. The system automatically drags business modules into a blank canvas to form business process nodes, connecting modules to create a complete data processing flow.

[0062] In one embodiment, the method for generating an oil and gas exploration business process may further include: integrating visualization function components and / or large-scale standalone software into a module library as modules; if the module with configured parameters is a visualization function component, the module with configured parameters acquires data in the oil and gas exploration business process by directly pushing the data; if the module with configured parameters is a large-scale standalone software, the module with configured parameters acquires data in the oil and gas exploration business process by processing and converting the data format according to the interface of the large-scale standalone software.

[0063] In this embodiment, when the process reaches a preset module node, a visualization component or a large monolithic software application is automatically instantiated. For visualization components, the process automatically pushes data that the component can respond to, based on the data previously selected by the user (since the visualization component conforms to application visualization assembly technology and uses the same data structure as the workflow, data can be pushed directly). For large monolithic software applications, since they have their own data backend and storage, data cannot be pushed directly. The process processes and converts the data format based on the capabilities of the data transmission system and methods between the cloud platform and exploration and development professional software before pushing it into the software. To meet the unique needs of the oil and gas exploration field, this embodiment integrates dedicated functional modules and professional software to improve the professionalism and accuracy of data processing.

[0064] In one embodiment, the oil and gas exploration business process generation method may further include: receiving operation instructions input by a user through a visual interface; the operation instructions include one or any combination of: dragging and dropping modules from a module library onto a work canvas to form process nodes, configuring parameters that are not pre-configured in the module, and configuring the input-output relationship of the module.

[0065] In this embodiment, a visual graphical interface and drag-and-drop operation allow users to intuitively and efficiently build and customize complex exploration workflow models. Users can drag the three business modules—"Seismic Data Import," "Seismic Data Preprocessing," and "Seismic Interpretation"—from the module library into a blank canvas using the graphical user interface, forming three business workflow nodes. Then, the user configures the data source path for the "Seismic Data Import" module and sets parameters such as processing range and processing accuracy for the "Seismic Data Preprocessing" module. Finally, the user connects the "Seismic Data Import" module to the "Seismic Data Preprocessing" module via a cable to ensure data flow continuity. Next, the user connects the "Seismic Data Preprocessing" module to the "Seismic Interpretation" module to form a complete data processing workflow, thus completing the configuration of the seismic interpretation business workflow model.

[0066] In actual workflow execution, the user selects the previously configured seismic interpretation workflow model to activate the workflow instance. The system automatically executes each module according to the pre-arranged workflow model. For example, after seismic data is imported, the system automatically starts the seismic data preprocessing module, and after processing, automatically transfers the data to the seismic interpretation module. During workflow execution, the system monitors the execution status of each module in real time, such as processing progress and data flow, and displays this information to the user through dynamic charts in a graphical interface. Simultaneously, the system records the execution details of each module, including processing time and data changes, and generates a detailed report after the workflow is completed for subsequent analysis and auditing. Through automated workflow execution and real-time monitoring, the efficiency of oil and gas exploration is optimized while ensuring data security and integrity.

[0067] The embodiments of the present invention can also provide automatic matching of business and process templates. For example, the configuration of the seismic interpretation business process model has been completed above. This configuration can be saved in the system. After the user selects data or enters business requirements, the seismic interpretation business process model can be automatically called without reconfiguration. That is, a correspondence and calling relationship between data type, business type and process model is formed.

[0068] If the selected module is a module integrated into a large monolithic software, a data format conversion module can be called before this module, with the configuration parameters being the existing data format and the data format required by the large monolithic software.

[0069] This invention provides an innovative process design and execution method for the oil and gas exploration industry. This method can be based on a system, hereinafter referred to as the Oil and Gas Exploration Business Process Generation System or simply the System. Through a visual graphical interface and drag-and-drop operation, users can intuitively and efficiently build and customize complex exploration process models. The system design needs to meet the specific requirements of the oil and gas exploration field, improving the professionalism and accuracy of data processing by integrating dedicated functional modules and professional software. Furthermore, the Oil and Gas Exploration Business Process Generation System can optimize the efficiency of oil and gas exploration work through automated process execution and real-time monitoring, while ensuring data security and integrity.

[0070] The oil and gas exploration business process generation system can accomplish the following:

[0071] 1. Graphical Interface Design:

[0072] (1.1) Develop and deploy an intuitive graphical user interface (GUI) specifically designed for the design and use of oil and gas exploration processes.

[0073] (1.2) Create a clear and easy-to-use work area or canvas environment to provide users with a blank space to visualize the construction process model.

[0074] 2. Establishing a drag-and-drop functional module library:

[0075] (2.1) The system provides a solidified library of built-in functional modules, including general functional modules such as actions, tasks, branches, and approvals in the general process engine, as well as customized functional modules such as data loading, data conversion, and data submission specifically for the oil and gas exploration business.

[0076] (2.2) In addition, the system also provides the ability to integrate visualization function components or large-scale standalone software for different business scenarios into the pre-built modules, such as seismic data processing tools, velocity field building tools, and large-scale standalone well logging processing and interpretation software.

[0077] (2.3) Through graphical interface interaction design, users can directly select functional modules by dragging and dropping them from the module library onto the work canvas to form process nodes.

[0078] It is important to note that components or software integrated into pre-built modules must conform to application visualization assembly technology or cloud-based exploration and development professional software integration framework technology.

[0079] 3. Customizable configuration of functional modules:

[0080] (3.1) Provide customizable parameter interfaces for each pre-set functional module to adapt to different oil and gas exploration scenarios and needs, and ensure that users can make detailed configurations according to actual business.

[0081] (3.2) Specific configurations include the following aspects: definition of conversion format of oil and gas data processing module, setting of filtering conditions, specific writing of oil and gas business decision-making logic rules, formulation of task distribution strategy, editing of notification information content and designation of its recipients, etc.

[0082] 4. Process Logic Arrangement:

[0083] (4.1) Guide users to connect the various functional nodes to each other by drawing lines on the canvas or using other graphical representation methods according to the actual oil and gas exploration business logic sequence, and clarify the input and output relationship.

[0084] (4.2) It supports flexible adjustment of node positions and redefinition of the connection relationship between nodes, thereby building a complete process model that adapts to complex application scenarios.

[0085] (4.3) During the process logic arrangement, ensure the correctness of the flow path and be able to verify in real time whether the process design meets the expected execution logic and feasibility requirements.

[0086] (4.4) This invention supports the integration of tools and software required in specific oil and gas exploration business areas into process nodes as pre-built modules within traditional process orchestration. Combined with built-in modules in the oil and gas exploration business area, this enables the online and process-oriented implementation of business functions.

[0087] 5. Process execution control:

[0088] (5.1) First, in the actual operation, the system performs orderly scheduling and flow management of oil and gas data according to the flowchart model pre-arranged by the user through the graphical interface and stored in the system database.

[0089] (5.2) Each node defined in the flowchart represents a specific functional module, such as data conversion, logical judgment, or task allocation. When oil and gas data enters a node, the system automatically triggers the corresponding functional module to execute according to the pre-set operation rules and parameters within that node.

[0090] (5.3) By precisely controlling the start and end conditions of each node and their interdependencies, the entire process is ensured to proceed accurately and without error in accordance with the design intent.

[0091] (5.4) The data loading module provides a visual interface, offering data display and selection functions based on the main object data index (e.g., seismic work area -> 3D seismic data volume -> 3D seismic horizon). Users can select data from within the system or from systems already integrated with the data ecosystem (e.g., data from the Exploration and Production Technology Data Management System (A1), Oil, Gas and Water Well Production Data Management System (A2), Oil and Gas Production IoT System (A3), etc.). Selected data is recorded in the workflow for use by subsequent nodes. Furthermore, only data references and pointers are recorded in the workflow to avoid large data transfers affecting the workflow's processing speed.

[0092] (5.5) When the process reaches a pre-defined module node, the system will automatically instantiate the visualization component or launch the monolithic large software. For visualization components, the process will automatically push data that the component can respond to for its use based on the data previously selected by the user (since the visualization component conforms to the application visualization assembly technology and uses the same data structure as the workflow, data can be pushed directly). For monolithic large software, since it has its own data backend and storage, data cannot be pushed directly. The process will process and convert the data format based on the capabilities of the data transmission system and methods between the cloud platform and the exploration and development professional software before pushing it into the software.

[0093] (5.6) When the pre-set module node completes execution, the process will automatically collect the data results produced by the visualization component and store them in the system, incorporating them into the process data. For large monolithic software that needs to display the built-in data submission module, the process will obtain the data results produced by this software based on the data transmission system and methods between the cloud platform and the exploration and development professional software, convert them into a unified data format, store them in the system, and simultaneously incorporate them into the process data.

[0094] (5.7) The data conversion module is used between nodes of two different large-scale single-unit software pre-built modules. Based on the data transmission system and methods between the cloud platform and exploration and development professional software, the system automatically obtains the data output of the previous node software and converts it into the data format used by the next node software before pushing it. This process only converts the data format and pushes the data from software to software; it does not store the data involved in the process in the system or within the workflow.

[0095] 6. Real-time process tracking:

[0096] (6.1) The present invention has specially developed a real-time process tracking module. This module uses advanced data capture technology to monitor and record the state changes and location migration of oil and gas data during the execution process in real time.

[0097] (6.2) This module can provide real-time feedback and intuitive display of the flow of oil and gas data between different nodes, including the current step, the list of completed steps, and their detailed flow timestamps and content descriptions.

[0098] (6.3) Through a highly interactive visual interface, it provides users with comprehensive and real-time process execution monitoring methods, effectively improving process management efficiency and transparency.

[0099] (6.4) Pre-defined module nodes that have already been executed can be executed repeatedly. If the output data changes after repeated execution (or the source data selected for data loading changes), the process will notify the operator of the next node after the data change, informing them of the content of the data change. Users can choose to re-execute the node to respond to the change.

[0100] 7. Process recording and result output:

[0101] (7.1) For each step of the execution process, the present invention constructs a comprehensive and detailed process recording and result output system, and adopts efficient data capture and storage technology to ensure the integrity and accuracy of the records.

[0102] (7.2) During the process, the system will record in detail the start and end times of each step, the specific execution details, as well as the various data results generated in the middle and the final result data.

[0103] (7.3) All these critical execution record information are securely and reliably stored inside the system to facilitate later process traceability analysis, audit review or optimization and improvement work, thereby ensuring the effectiveness and compliance of the whole process management.

[0104] The oil and gas exploration business process generation method of this invention is based on an oil and gas exploration business process generation system. This system uses an intuitive graphical user interface (GUI) to allow users to interactively design and select and configure functional modules through drag-and-drop, forming process nodes to construct complex process models. The oil and gas exploration business process generation system has a rich built-in library of functional modules, including modules specifically customized for the oil and gas exploration business field, such as data loading, data conversion, and data submission, as well as integrated professional components and software for seismic data processing and well logging interpretation. The system also achieves real-time process tracking, utilizing advanced data capture technology to monitor and record the state changes and location migrations of oil and gas data during the process execution, providing comprehensive and real-time process execution monitoring capabilities, effectively improving process management efficiency and transparency.

[0105] This invention also proposes an oil and gas exploration business process generation device, the principle of which is similar to the oil and gas exploration business process generation method, and will not be described in detail here.

[0106] Figure 3 This is a schematic diagram of an oil and gas exploration business process generation device provided in an embodiment of the present invention, such as... Figure 3 As shown, the oil and gas exploration business process generation device may include:

[0107] The acquisition module 301 is used to acquire the selection result of the user in selecting oil and gas exploration data from multiple oil and gas exploration business systems, as well as the exploration business requirements input by the user; the exploration business requirements are text data.

[0108] The splitting module 302 is used to split the exploration business requirements and perform keyword recognition on the split exploration business requirements;

[0109] The classification module 303 is used to input the identified keywords into a pre-trained text classification model and output the classification results. The text classification model is trained using historical oil and gas exploration data, a pre-established thesaurus for oil and gas exploration business, and module names in the module library. The classification result is the matching probability between the keyword and the module name.

[0110] Search module 304 is used to search the module library for modules whose keyword and module name have a matching probability greater than a preset probability, based on the classification results; the module includes pre-configured parameters and non-pre-configured parameters;

[0111] The input-output relationship determination module 305 is used to determine the input-output relationship of the module based on the order of keywords in the exploration business requirements and / or the text data between keywords in the exploration business requirements.

[0112] The parameter configuration module 306 is used to configure parameters that are not pre-configured in the module according to the selection results and exploration business requirements;

[0113] The oil and gas exploration business process generation module 307 is used to generate and display the oil and gas exploration business process based on the input and output relationship of the modules and the selected oil and gas exploration data, using the modules with configured parameters as nodes.

[0114] In one embodiment, the split module 302 is specifically used for:

[0115] The exploration business requirements are broken down into multiple clauses according to preset identifiers;

[0116] The keyword recognition model is used to identify keywords in each clause to obtain the keyword recognition results corresponding to each clause. The keyword recognition model is obtained by training a deep neural network model using clauses that are split according to preset identifiers of historical exploration business requirements and a special vocabulary library for oil and gas exploration business.

[0117] In one embodiment, the split module 302 is specifically used for:

[0118] Each clause is split using a keyword recognition model to obtain multiple words corresponding to each clause;

[0119] The keyword recognition model is used to identify the entities of each word corresponding to each clause, and the entity names corresponding to each clause are obtained.

[0120] The keyword recognition model extracts keyword features from the entity names corresponding to each clause, and identifies the keyword recognition results corresponding to each clause based on the extracted keyword features.

[0121] Figure 4 This is a schematic diagram of a specific example of an oil and gas exploration business process generation device provided in an embodiment of the present invention, such as... Figure 4 As shown, in one embodiment, the oil and gas exploration business process generation device further includes: a keyword recognition model training module 401, used for:

[0122] Obtain historical exploration business requirements input by users through a visual interface;

[0123] Based on preset identifiers, historical exploration business requirements are broken down into multiple clauses;

[0124] By using multiple clauses obtained from breaking down historical exploration business requirements and a specialized thesaurus for the oil and gas exploration business field, a deep neural network model is trained to generate a keyword recognition model.

[0125] In one embodiment, the oil and gas exploration business process generation device further includes: a text classification model training module, used for:

[0126] Obtain the selection results of users through a visual interface, selecting historical oil and gas exploration data from multiple oil and gas exploration business systems according to data indexing;

[0127] By utilizing historical oil and gas exploration data, a specialized thesaurus for the oil and gas exploration business, and module names from the module library, a classification model is trained to generate a text classification model.

[0128] In one embodiment, the oil and gas exploration business process generation device further includes: a format conversion module, used for:

[0129] Integrate visualization functional components and / or large monolithic software into a module library as modules;

[0130] If the module with configured parameters is a visualization function component, the module with configured parameters acquires data in the oil and gas exploration business process by directly pushing the data; if the module with configured parameters is a large-scale standalone software, the module with configured parameters acquires data in the oil and gas exploration business process by processing and converting the data format according to the interface of the large-scale standalone software.

[0131] In one embodiment, the oil and gas exploration business process generation device further includes: an operation module, used for:

[0132] Receive operation instructions input by the user through a visual interface; the operation instructions include one or any combination of the following: dragging and dropping modules from the module library onto the work canvas to form process nodes, configuring parameters that are not pre-configured in the module, and configuring the input and output relationships of the module.

[0133] Compared with existing oil and gas exploration business process generation technologies, this invention obtains the user's selection results from multiple oil and gas exploration business systems, as well as the user's input exploration business requirements; these requirements are textual data; the exploration business requirements are broken down, and keyword recognition is performed on the broken-down requirements; the identified keywords are sequentially input into a pre-trained text classification model, and the classification results are output; the text classification model is trained using historical oil and gas exploration data, a pre-established specialized thesaurus for the oil and gas exploration business field, and module names in a module library; the classification result is the matching probability between keywords and module names; based on the classification results, in The module library searches for modules whose keyword matching probability with module name is greater than a preset probability; the modules include pre-configured parameters and non-pre-configured parameters; the input-output relationship of the modules is determined based on the order of keywords in exploration business requirements, and / or the textual data between keywords in exploration business requirements; based on the selection results and exploration business requirements, the non-pre-configured parameters in the modules are configured; using the modules with configured parameters as nodes, an oil and gas exploration business process is generated and displayed based on the module's input-output relationship and the selected oil and gas exploration data, which can improve the generation efficiency of oil and gas exploration business processes and the accuracy of oil and gas exploration data processing, and can quickly respond to changes in exploration business requirements.

[0134] Through the embodiments of this invention, users can quickly respond to changes in exploration needs, achieve rapid iteration and optimization of processes, and significantly improve the design and execution efficiency of oil and gas exploration processes. Integrated professional software and functional modules will greatly improve the accuracy and depth of data processing, thereby providing more reliable support for exploration decisions. Real-time process tracking and data management functions enhance process transparency and traceability, making it easier to identify and resolve various problems in the process in a timely manner. Furthermore, a comprehensive process recording and result output system provides detailed data support for subsequent audits, reviews, and process optimization. Overall, this invention will drive the oil and gas exploration industry towards a more efficient and intelligent direction, while improving team collaboration efficiency and project management quality.

[0135] This invention also provides a computer device. Figure 5 This is a schematic diagram of a computer device in an embodiment of the present invention. The computer device 500 includes a memory 510, a processor 520, and a computer program 530 stored in the memory 510 and executable on the processor 520. When the processor 520 executes the computer program 530, it implements the above-mentioned oil and gas exploration business process generation method.

[0136] This invention also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described oil and gas exploration business process generation method.

[0137] This invention also provides a computer program product, which includes a computer program that, when executed by a processor, implements the above-described oil and gas exploration business process generation method.

[0138] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0139] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0140] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0141] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0142] The specific embodiments described above further illustrate the purpose, technical solution, and beneficial effects of the present invention. It should be understood that the above descriptions are merely specific embodiments of the present invention and are not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for generating an oil and gas exploration business process, characterized in that, include: Obtain the user's selection results from multiple oil and gas exploration business systems, as well as the exploration business requirements input by the user; The exploration business requirements are text data; The exploration business requirements are broken down, and the keywords of the broken-down exploration business requirements are identified. The identified keywords are sequentially input into a pre-trained text classification model, and the classification results are output. The text classification model is trained using historical oil and gas exploration data, a pre-established thesaurus for oil and gas exploration business, and module names in the module library. The classification result is the probability of matching keywords with module names; Based on the classification results, modules with a keyword matching probability greater than a preset probability are searched in the module library; the modules include pre-configured parameters and non-pre-configured parameters; Based on the order of keywords in the exploration business requirements, and / or the textual data between keywords in the exploration business requirements, determine the input-output relationship of the module; Based on the selection results and exploration business requirements, configure the parameters that are not pre-configured in the module; Using pre-configured modules as nodes, the system generates and displays oil and gas exploration business processes based on the module's input-output relationships and the selected oil and gas exploration data.

2. The method as described in claim 1, characterized in that, The exploration business requirements are broken down, and keyword identification is performed on the broken-down exploration business requirements, including: The exploration business requirements are broken down into multiple clauses according to preset identifiers; The keyword recognition model is used to identify keywords in each clause to obtain the keyword recognition results corresponding to each clause. The keyword recognition model is obtained by training a deep neural network model with clauses after splitting historical exploration business requirements according to preset identifiers and a special vocabulary library for oil and gas exploration business.

3. The method as described in claim 2, characterized in that, The keyword recognition model is used to identify keywords in each clause, and the keyword recognition results corresponding to each clause are obtained, including: Each clause is split using a keyword recognition model to obtain multiple words corresponding to each clause; The keyword recognition model is used to identify the entities of each word corresponding to each clause, and the entity names corresponding to each clause are obtained. The keyword recognition model extracts keyword features from the entity names corresponding to each clause, and identifies the keyword recognition results corresponding to each clause based on the extracted keyword features.

4. The method as described in claim 2, characterized in that, Also includes: Obtain historical exploration business requirements input by users through a visual interface; Based on preset identifiers, historical exploration business requirements are broken down into multiple clauses; By using multiple clauses obtained from breaking down historical exploration business requirements and a specialized thesaurus for the oil and gas exploration business field, a deep neural network model is trained to generate a keyword recognition model.

5. The method as described in claim 1, characterized in that, Also includes: Obtain the selection results of users through a visual interface, selecting historical oil and gas exploration data from multiple oil and gas exploration business systems according to data indexing; By utilizing historical oil and gas exploration data, a specialized thesaurus for the oil and gas exploration business, and module names from the module library, a classification model is trained to generate a text classification model.

6. The method as described in claim 1, characterized in that, Also includes: Integrate visualization functional components and / or large monolithic software into a module library as modules; If the module with configured parameters is a visualization function component, the module with configured parameters acquires data in the oil and gas exploration business process by directly pushing the data; if the module with configured parameters is a large-scale standalone software, the module with configured parameters acquires data in the oil and gas exploration business process by processing and converting the data format according to the interface of the large-scale standalone software.

7. The method as described in claim 1, characterized in that, Also includes: Receive operation instructions input by the user through a visual interface; the operation instructions include one or any combination of the following: dragging and dropping modules from the module library onto the work canvas to form process nodes, configuring parameters that are not pre-configured in the module, and configuring the input and output relationships of the module.

8. An oil and gas exploration business process generation device, characterized in that, include: The acquisition module is used to acquire the user's selection result from multiple oil and gas exploration business systems, as well as the exploration business requirements input by the user; the exploration business requirements are text data. The splitting module is used to break down exploration business requirements and perform keyword recognition on the split exploration business requirements; The classification module is used to input the identified keywords into a pre-trained text classification model and output the classification results. The text classification model is trained using historical oil and gas exploration data, a pre-established thesaurus specifically for the oil and gas exploration business, and module names from the module library. The classification result is the probability of matching keywords with module names; The search module is used to search the module library for modules whose keyword matching probability with the module name is greater than a preset probability, based on the classification results; the module includes pre-configured parameters and non-pre-configured parameters; The input-output relationship determination module is used to determine the input-output relationship of the module based on the order of keywords in the exploration business requirements and / or the text data between keywords in the exploration business requirements. The parameter configuration module is used to configure parameters that are not pre-configured in the module according to the selection results and exploration business requirements; The oil and gas exploration business process generation module is used to generate and display oil and gas exploration business processes based on the input and output relationships of modules with configured parameters and the selected oil and gas exploration data, using these modules as nodes.

9. A computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the method of any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, implements the method of any one of claims 1 to 7.

11. A computer program product, characterized in that, The computer program product includes a computer program that, when executed by a processor, implements the method of any one of claims 1 to 7.

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