A method and system for modeling processing of multi-source wellbore data

Abstract

The application provides a modeling processing method and system for multi-source wellbore data, the method designs a standard template covering multi-type wellbore data extraction requirements of the standard template according to data characteristics of associated multi-source wellbore data and applied modeling data conditions, extracts wellbore source data from a multi-source database according to the required modeling data conditions, stores the wellbore source data into the standard template, verifies the integrity and validity of the data in each sub-template according to the preset modeling conditions and overcomes the abnormality, finally converts the source data meeting the conditions to obtain a plurality of wellbore numerical model module data structure files, and integrates to obtain an overall wellbore numerical model. By adopting the scheme, the problems of a complicated processing process, insufficient accuracy and long time consumption in the prior art are overcome, the data template considering data properties and application modeling conditions is organically combined with the data processing technology, the whole-process data rapid integration is realized, the accuracy and matching degree of the related data in the wellbore modeling are ensured, and the timeliness is improved.

Description

Technical Field

[0001] This invention relates to the field of multi-source data modeling technology for oil and gas reservoir wellbore, and in particular to a modeling method and system for multi-source wellbore data. Background Technology

[0002] With the continuous development and integration of computer engineering, mathematical modeling, and oil production engineering, wellbore modeling technology has seen some development and application, mainly concentrated in the field of wellbore digitization and visualization during the drilling process, reflected in the integration of wellbore models and geological information. The main function of wellbore digitization technology is to utilize the latest engineering geology, environmental technology, computer science, and modern information to acquire and organize various static and dynamic information obtained during drilling, logging, well logging, testing, oil and gas testing, well completion operations, and oil and water well production operations. It also uses wellbore digitization technology to digitally simulate data on geological environment, drilling equipment, wellbore trajectory, reservoir properties, and other objects, based on traditional data analysis, processing, and interpretation methods. However, current technologies only digitize or visualize wellbore-related data, which is structurally insufficient for users. Therefore, it is necessary to utilize wellbore modeling technology to better conduct research on the characteristics of vertical multiphase flow in wellbore and flow safety assurance, while also providing a model basis for optimizing wellbore lifting operating procedures.

[0003] Currently, mainstream wellbore modeling software (such as Prosper and PIPESIM) mainly includes single-well basic information, wellbore high-pressure properties, pump parameters, geothermal gradient, IPR parameters, tubing structure, well trajectory, etc., and relies primarily on interface-based input. However, wellbore models involve a large number of wells, well types, modules, and parameters, requiring a high level of expertise and software operation skills from wellbore modelers. Existing technologies have cumbersome data preparation and processing processes, long modeling cycles, and low efficiency, making it difficult to reliably and efficiently support reservoir development projects and failing to meet implementation requirements.

[0004] The information disclosed in the background section of this invention is intended only to enhance the understanding of the general background of this invention, and should not be construed as an admission or in any way implying that such information constitutes prior art known to those skilled in the art. Summary of the Invention

[0005] To address the above problems, the present invention provides a modeling processing method for multi-source wellbore data. In one embodiment, the method includes:

[0006] The template design process integrates the steps of designing a standard template that covers the comprehensive extraction requirements of wellbore data based on the data characteristics of all associated multi-source wellbore data and the modeling data conditions of all applications. The standard template includes multiple sub-templates, each sub-template corresponding to a type of modeling data condition, and each sub-template contains different well type data templates, including data templates for pumping unit wells, electric pump wells, jet pump wells, and water injection wells.

[0007] The multi-source data extraction steps involve extracting corresponding wellbore source data from independent or integrated multi-source databases based on the required modeling data conditions, and storing the data in the corresponding sub-templates of the standard template in combination with well type information to achieve targeted data fusion.

[0008] The data verification steps involve verifying the completeness and validity of the data in the corresponding sub-templates of the standard template based on the required wellbore modeling conditions list. If the data does not meet the requirements, the multi-source data extraction steps are repeated until all the required data meet the requirements.

[0009] The wellbore modeling steps involve synchronously inputting the source data that has passed verification in the standard template into a matching wellbore numerical model professional platform, converting it into several categories of multi-module wellbore numerical model data structure files, and integrating them to obtain the overall wellbore numerical model.

[0010] As a further improvement of the present invention, the method further includes:

[0011] The model verification process involves performing calculations on the obtained overall wellbore numerical model using preset test data. The integrity and validity of the data structure files of each module are verified based on the calculation process and results. If the set requirements are not met, the wellbore modeling process is repeated until all the data structure files of each module meet the requirements.

[0012] Furthermore, in one embodiment, during the wellbore modeling step, the source data is synchronously input into a matching wellbore numerical model professional platform through an interface or path corresponding to the application modeling conditions.

[0013] Specifically, in one embodiment, in the integrated template design step, different well type data templates are set to include different data storage areas, which respectively store data objects of different data source fields and data types. The data source fields are set according to the source category fields of the source data, including different wellbore data fields corresponding to a certain well type.

[0014] As a specific improvement of the present invention, in the multi-source data extraction step, the extracted source data is stored in the well-shaped data template of the corresponding sub-module using the data category keywords or fields as indexes.

[0015] On the other hand, in a preferred embodiment, when different modeling data conditions require the extraction of the same source data, the data is extracted independently and stored in a matching well-type data template according to an organization format that matches the modeling data conditions.

[0016] Preferably, in one embodiment, in the data verification step, the integrity and validity of the data in each sub-template of the standard template are verified according to the corresponding modeling data conditions. If both requirements are met, the verification is determined to be passed; otherwise, all data corresponding to the current modeling conditions that have not passed the verification are re-extracted.

[0017] Furthermore, in one embodiment, the wellbore modeling step includes:

[0018] Based on the wellbore modeling requirements, the corresponding high-pressure physical properties, pump parameters, geothermal gradient, IPR parameters, tubing structure, and well trajectory data are extracted from the wellbore data standard template using the well number field as the label. Six types of data structure files are generated and integrated to obtain the wellbore numerical model corresponding to the current well number field.

[0019] Multiple wellbore numerical models are integrated based on the well type field to construct an overall wellbore numerical model.

[0020] Based on other aspects of the methods described in any one or more of the foregoing embodiments, the present invention also provides a storage medium storing program code that can implement the methods described in any one or more of the foregoing embodiments.

[0021] Based on the application aspects of the methods described in any one or more of the above embodiments, the present invention also provides a modeling processing system for multi-source wellbore data, which performs the methods described in any one or more of the above embodiments.

[0022] Compared with the closest prior art, the present invention also has the following beneficial effects:

[0023] This invention provides a modeling processing method and system for multi-source wellbore data. The method designs a standard template that comprehensively covers the extraction requirements of wellbore data from different well types, based on the data characteristics of all associated multi-source wellbore data and all modeling data conditions applied. Based on this, wellbore source data is extracted from independent or integrated multi-source databases according to the required modeling data conditions and stored in the corresponding sub-templates within the standard template. This organically combines data templates that consider both data attributes and application modeling conditions with data processing technology, achieving rapid data integration throughout the entire process. It ensures that the format and content of the extracted and stored source data correspond to the application modeling requirements, achieving targeted and systematic data extraction and fusion. While controlling the amount of operational data, it ensures the correlation between the data processing results and the modeling processing requirements.

[0024] In addition, the present invention also verifies the integrity and validity of the data in each sub-template according to the preset modeling conditions. Only after the conditions are met is the source data applied to the conversion of wellbore data structure files and integrated modeling tasks. This avoids the situation where the data processing results are not complete or unusable due to errors or anomalies in the extraction or storage process, further improving the accuracy of the data processing results and reliably realizing the rapid modeling processing of wellbore data based on template data integration.

[0025] Other features and advantages of the invention will be set forth in the description which follows, and will be apparent in part from the description, or may be learned by practicing the invention. The objects and other advantages of the invention may be realized and obtained by means of the structures particularly pointed out in the description, claims, and drawings. Attached Figure Description

[0026] The accompanying drawings are provided to further illustrate the invention and form part of the specification. They are used in conjunction with the embodiments of the invention to explain the invention and do not constitute a limitation thereof. In the drawings:

[0027] Figure 1 This is a schematic flowchart of a modeling method for multi-source wellbore data provided in an embodiment of the present invention;

[0028] Figure 2 This is a schematic diagram of the data source standard template for the modeling processing method for multi-source wellbore data provided in the embodiments of the present invention;

[0029] Figure 3 This is a detailed flowchart of the data integration and modeling operation process of the modeling processing method for multi-source wellbore data provided in another embodiment of the present invention;

[0030] Figure 4 This is a schematic diagram of the data extraction process of the modeling processing method for multi-source wellbore data provided in the embodiments of the present invention;

[0031] Figure 5 This is an example of creating a well model based on reading data from the well number in the modeling processing method for multi-source wellbore data provided in the embodiments of the present invention;

[0032] Figure 6 This is an example of extracting data, modeling, and updating model structure file data in a modeling processing method for multi-source wellbore data provided in an embodiment of the present invention;

[0033] Figure 7 This is an example of the wellbore data model integration data file result of the modeling processing method for multi-source wellbore data provided in the embodiments of the present invention;

[0034] Figure 8This is a schematic diagram of the structure of a modeling system for multi-source wellbore data provided in an embodiment of the present invention.

[0035] Figure 9 This is a schematic diagram of the functional structure of a modeling system for multi-source wellbore data provided in an embodiment of the present invention. Detailed Implementation

[0036] The embodiments of the present invention will be described in detail below with reference to the accompanying drawings and examples. Those skilled in the art will then fully understand how the present invention uses technical means to solve technical problems and achieve technical effects, and will be able to implement the present invention specifically based on the above-described implementation process. It should be noted that, as long as there is no conflict, the various embodiments and features of the present invention can be combined with each other, and the resulting technical solutions are all within the protection scope of the present invention.

[0037] Although the flowchart describes the operations as sequential processes, many of these operations can be performed in parallel, concurrently, or simultaneously. The order of the operations can be rearranged. A process can terminate when its operation is complete, but it may also have additional steps not included in the diagram. A process can correspond to a method, function, procedure, subroutine, subroutine, etc.

[0038] Computer equipment includes user equipment and network equipment. User equipment or clients include, but are not limited to, computers, smartphones, PDAs, etc.; network equipment includes, but is not limited to, a single network server, a server group consisting of multiple network servers, or a cloud based on cloud computing consisting of a large number of computers or network servers. Computer equipment can operate independently to implement this invention, or it can connect to a network and implement this invention through interaction with other computer equipment in the network. The network in which the computer equipment is located includes, but is not limited to, the Internet, wide area network, metropolitan area network, local area network, VPN network, etc.

[0039] The terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the exemplary embodiments. Unless the context clearly indicates otherwise, the singular forms “a” and “an” as used herein are also intended to include the plural. It should also be understood that the terms “comprising” and / or “including” as used herein specify the presence of the stated features, integers, steps, operations, units, and / or components, without excluding the presence or addition of one or more other features, integers, steps, operations, units, components, and / or combinations thereof.

[0040] With the continuous development and integration of disciplines such as computer engineering, mathematical modeling and oil production engineering, wellbore modeling technology has been developed and applied to a certain extent, but it is mainly concentrated in the field of wellbore digitization and visualization during the drilling process, which is reflected in the integration of wellbore models and geological information.

[0041] The main function of wellbore digitization technology is to utilize the latest engineering geology, environmental technology, computer science, and modern information to acquire and organize various static and dynamic information obtained during drilling, logging, well logging, testing, oil and gas testing, well completion operations, and oil and water well production operations. It also digitally simulates data on geological environment, drilling equipment, wellbore trajectory, and reservoir properties, building upon traditional data analysis, processing, and interpretation methods. However, current technologies only digitize or visualize wellbore-related data, which lacks sufficient structural information for users. Therefore, it is necessary to utilize wellbore modeling technology to better conduct research on the characteristics of vertical multiphase flow in wellbore and flow safety assurance, while also providing a model foundation for optimizing wellbore lifting operating procedures.

[0042] Currently, mainstream wellbore modeling software (such as Prosper and PIPESIM) mainly includes single-well basic information, wellbore high-pressure properties, pump parameters, geothermal gradient, IPR parameters, tubing structure, well trajectory, etc., and relies primarily on interface-based input. However, wellbore models involve a large number of wells, well types, modules, and parameters, requiring a high level of expertise and software operation skills from wellbore modelers. Existing technologies have cumbersome data preparation and processing processes, long modeling cycles, and low efficiency, making it difficult to reliably and efficiently support reservoir development projects and failing to meet implementation requirements.

[0043] Research methods for integrating distributed heterogeneous information resources include federated database methods, data warehouse methods, virtual database methods, virtual data methods, distributed component integration methods, direct database access interface methods, grid-based methods, ontology-based methods, WebService-based methods, and extensible markup language methods. Among these, federated database technology was proposed to achieve interoperability between multiple independently operating databases. Independently operating database systems are usually called unit database systems, and a federated database system is a collection of cooperative yet independent unit database systems that integrate unit database systems to varying degrees. The fundamental characteristic of data warehousing is the physical storage of data. The construction of a data warehouse is achieved through the process of cleaning, transforming, integrating, loading, and periodically refreshing data from multiple data sources, storing it within a unified data model. A typical data warehouse includes metadata, data sources, data transformation tools, data collections, and data query and analysis tools. Data integration based on virtual data centers refers to the integration, transparent access, and transparent management of heterogeneous data based on a virtual data center data integration model. It allows unified access to structured, semi-structured, and unstructured data, with the access method independent of the data source. Distributed component integration transforms data access into independent distributed objects through encapsulation. It acts as a data access proxy between the data accessor and the data source, handling data source access operations and ultimately integrating heterogeneous data. Direct database access interface methods are relatively simple; different programming languages ​​have their own database access interfaces, through which the programming language executes SQL statements for database management. Methods based on grids, XML, ontology, and Web Services utilize extensible markup languages, offering advantages such as cross-language compatibility, cross-platform compatibility, extensibility, high efficiency, and separation of display and content.

[0044] Existing data processing methods primarily focus on information technology and digitalization, with limited integration with numerical technology applications in oil and gas field development. They also have stringent data access requirements, typically employing a method of backing up the entire data and then extracting the necessary data for computation. This approach is cumbersome, time-consuming, and labor-intensive, and the matching degree between the extracted data and the computational applications is difficult to guarantee. Therefore, there is an urgent need for data integration in reservoir and production engineering data management. This involves merging data objects from multiple relatively independent data sources and recombining them into a new, organic whole, thereby providing orderly and accurate support for the construction of wellbore data models.

[0045] Based on the above requirements, the purpose of this invention is to achieve rapid construction of wellbore data models using an indirect data integration method based on data templates. Firstly, it establishes standard data templates for wellbore models, providing a medium for extracting a large amount of multi-source key "core data" for wellbore modeling. Secondly, it extracts the "core data" required for wellbore modeling from various databases into standard data templates, laying the foundation for multi-source data integration and sharing in wellbore models and subsequent rapid numerical simulations. Through the conversion between template-standardized data and wellbore models, it enables rapid batch modeling and updating of wellbore numerical models, shortening the data preparation and processing cycle, improving wellbore modeling efficiency, and enabling non-professionals or those unfamiliar with the software to quickly build wellbore models.

[0046] The implementation idea of ​​this invention is as follows: (1) Establish a standard template for wellbore data based on the characteristics of the input data structure of the wellbore modeling software used (see example). Figure 1 This provides a medium for converting wellbore data into models;

[0047] (2) Manually input or automatically extract the well number of a single well based on the data source. Create standard data template tables for each of the four types of single wells, namely pumping well, electric pump well, jet pump well and water injection well, based on the well number. Automatically load the six types of source data, namely well high pressure properties, pump parameters, geothermal gradient, IPR parameters, tubing structure and well trajectory, into the data template to achieve the standard integration of key data of each well.

[0048] (3) Automatically create batch numerical models of wellbore for each well based on the data template table for each well;

[0049] (4) Based on the wellbore source database, automatically read and batch update one or more data items, regenerate the wellbore numerical model, and check the integrity and accuracy of the model file.

[0050] The following describes the detailed flow of the method according to an embodiment of the present invention with reference to the accompanying drawings, the steps of which can be executed in a computer system containing, for example, a set of computer-executable instructions. Although the logical order of the steps is shown in the flowchart, in some cases, the steps shown or described may be performed in a different order than that shown here.

[0051] Example 1

[0052] Figure 1 This diagram illustrates a flowchart of a modeling method for multi-source wellbore data provided in Embodiment 1 of the present invention. Figure 1 As can be seen, the method includes the following steps.

[0053] The template design process integrates the steps of designing a standard template that covers the comprehensive extraction requirements of wellbore data based on the data characteristics of all associated multi-source wellbore data and the modeling data conditions of all applications. The standard template includes multiple sub-templates, each sub-template corresponding to a type of modeling data condition, and each sub-template contains different well type data templates, including data templates for pumping unit wells, electric pump wells, jet pump wells, and water injection wells.

[0054] The multi-source data extraction steps involve extracting corresponding wellbore source data from independent or integrated multi-source databases based on the required modeling data conditions, and storing the data in the corresponding sub-templates of the standard template in combination with well type information to achieve targeted data fusion.

[0055] The data verification steps involve verifying the completeness and validity of the data in the corresponding sub-templates of the standard template based on the required wellbore modeling conditions list. If the data does not meet the requirements, the multi-source data extraction steps are repeated until all the required data meet the requirements.

[0056] The wellbore modeling steps involve synchronously inputting the source data that has passed verification in the standard template into a matching wellbore numerical model professional platform, converting it into several categories of multi-module wellbore numerical model data structure files, and integrating them to obtain the overall wellbore numerical model.

[0057] Based on the implementation logic of the above embodiments, the data integration technology of this invention, based on data templates, uses a large amount of multi-source data related to wellbore as a foundation, wellbore professional modeling data as a requirement, and standard templates for multi-source wellbore modeling data as a medium for data conversion and storage. This achieves data integration from a large amount of repetitive and invalid source data to a small amount of unique and valid "core data." Furthermore, by integrating the conversion between template-standardized data and wellbore numerical models, it enables rapid modeling and integration of different types of wellbore numerical models, shortening the data preparation and processing cycle, improving numerical modeling efficiency, and enabling non-professionals or those unfamiliar with the software to quickly perform modeling.

[0058] Researchers considered that professional wellbore numerical modeling platforms might experience execution errors during identification and conversion, leading to data omissions or anomalies that could affect the accuracy of modeling results. Therefore, in a preferred embodiment, the method of this invention further includes a model verification step: for the integrated overall wellbore numerical model, calculations are performed based on preset test data. The integrity and validity of the data structure files of each module are verified according to the model's calculation process and results. If the set requirements are not met, the wellbore modeling steps are re-executed until all module data structure files meet the requirements. In practical applications, a set time period or a set scale of test data can be selected to perform wellbore model numerical calculations to detect whether there are normal calculation measures and results. Alternatively, the model calculation results can be compared and analyzed with actual wellbore data, and combined with set error threshold constraints to determine whether the integrity and validity of the data structure files of each module in the current tested model can meet the implementation requirements.

[0059] The key aspect of this solution lies in the standardized integration of multi-source wellbore data and the conversion of the integrated standard source data into a wellbore numerical model module data structure file for integration. First, a standard and universal wellbore data template is established. Based on the characteristics of the input file data structure of the wellbore numerical simulator used, this invention establishes a standard template for wellbore data integration. This template extracts various types of source data to achieve standardized integration of key data, specifically refining and storing the source data into "core data" applicable to the target modeling task within the data template, and defining how to apply this data to construct the wellbore data model. To ensure the bidirectional adaptability of the established data template to the source data and the applied modeling conditions, in one embodiment, the integration template design step includes different data storage areas for different well types, corresponding to data objects with different data source fields and data types. The data source fields are set according to the source category fields of the source data, including different wellbore data fields corresponding to a specific well type.

[0060] In practical applications, database template tables can be created in the well type data templates of each sub-template based on the characteristics of the input file data structure of the wellbore numerical simulator used. See the example below. Figure 2 This is used to store various wellbore data extracted from the source data. In the example diagram, Figure 2 This example shows a standard template for wellbore data. After the database template table is created, you can also set keywords or field indexes for the table to speed up data retrieval.

[0061] Furthermore, the required wellbore source data is extracted through a multi-source data extraction step. Based on one or more modeling data conditions required for wellbore modeling, the corresponding wellbore source data is extracted from independent or integrated multi-source databases and stored in the corresponding well type data template in the standard template, thereby achieving targeted data fusion.

[0062] In one embodiment, in the multi-source data extraction step, after extracting the corresponding wellbore source data from an independent or overall multi-source database, a preprocessing operation is performed, including identifying and filtering out duplicate and invalid data in the extracted target source data.

[0063] Furthermore, the extracted and preprocessed source data is stored in the corresponding well-shaped data template using its data category keywords or fields as indexes.

[0064] In practical applications, data access interfaces or paths are established to extract large-scale multi-source data. Based on the keywords or fields corresponding to the application modeling requirements in the database template, the required data from the multi-source data is identified and extracted. This extracted data is then assigned to the database template for storage, thereby achieving rapid integration of core data in the early stages of the wellbore modeling process. The flowchart illustrating the operational principle of the data integration process is shown below. Figure 3 As shown, the data extraction process is as follows: Figure 4 As shown.

[0065] In addition, the researchers considered that when there are multiple formats of modeling data requirements, there may be situations where different modeling tasks need to reuse the same source data. However, the requirements for the organization format of the source data may be different in different modeling tasks. Therefore, in order to more accurately ensure the matching of the extracted source data with the requirements, in one embodiment, in the multi-source data extraction step, for the case where different modeling data conditions require the extraction of the same source data, the data is extracted independently and stored in the matching well-shaped data template according to the organization format that matches the modeling data conditions.

[0066] Based on the operating principles described in the above embodiments, and considering the requirements for establishing a wellbore numerical model and the characteristics of multi-source databases in oilfield development, this invention organically combines data templates with data processing technology to achieve rapid data integration throughout the entire process. This invention fully utilizes the standardization features of oilfield development and the indexing and storage technology of databases. It not only enables standardized and efficient data integration and storage but also simplifies and speeds up the data preprocessing process in wellbore model establishment, laying a data standard foundation for subsequent rapid wellbore modeling and fitting. This allows non-professionals or those unfamiliar with the software to quickly perform wellbore modeling.

[0067] Furthermore, in order to avoid abnormalities during the extraction or transmission process that could lead to discrepancies between the extraction results and the extraction conditions, a data verification step is used to verify whether the data in the corresponding sub-template of the standard template meets the requirements based on the preset modeling condition list after extraction and storage or before application to the target modeling operation.

[0068] Specifically, in one embodiment, in the data verification step, the integrity and validity of the data in each sub-template of the standard template are verified according to the corresponding modeling data conditions. If both meet the requirements, the verification is determined to be passed. Otherwise, all data corresponding to the current modeling conditions that have not passed the verification are re-extracted to ensure that the extraction results are accurately matched with the application modeling conditions, and to avoid discovering anomalies only when the data is put into application, which would affect the application efficiency.

[0069] After ensuring the integrity and validity of the data, it is transmitted to the corresponding wellbore data modeling platform through the data output steps according to the interface or path corresponding to the application modeling conditions, and then applied to subsequent modeling operations or calculations.

[0070] In practical applications, in one embodiment, during the wellbore modeling step, the source data is synchronously input into the matching wellbore numerical model professional platform through an interface or path corresponding to the application modeling conditions; optionally, after the corresponding source data is input into the wellbore numerical model professional platform, the data content of the current batch in the data standard template is cleared.

[0071] Alternatively, this invention can now be implemented via software programming, and the process can be described as follows:

[0072] (1) Data integration: Generate and initialize various data standard templates for wellbore, read key data from multiple source databases to achieve data integration, and establish a wellbore numerical model template database; among them, create and initialize four types of wellbore data standard templates for pumping wells, electric pump wells, jet pump wells and water injection wells, manually input or automatically extract single well numbers according to data sources, read multiple source databases according to well numbers and batch establish the above four types of single wellbore standard data template tables according to well numbers.

[0073] (2) Data conversion: The six types of source data, namely, high pressure properties of wellbore, pump parameters, geothermal gradient, IPR parameters, tubing structure, and well trajectory, are automatically loaded into the data template to establish a wellbore template data integration model for pumping wells, electric pump wells, jet pump wells and water injection wells.

[0074] (3) Batch modeling: Based on the integrated model of each well template data, call the wellbore modeling software to automatically create the numerical model of each wellbore in batches, and check the integrity and accuracy of such model files.

[0075] (4) Batch update: Based on actual update needs, update the six types of source data in the wellbore, including high pressure properties, pump parameters, geothermal gradient, IPR parameters, tubing structure, and well trajectory, and remodel the wellbore.

[0076] (5) If data or modules are missing or data updates are incorrect, rerun the wellbore data file module construction and update.

[0077] (6) End and output the final wellbore numerical model result file.

[0078] Furthermore, in one embodiment, the wellbore modeling step includes:

[0079] Based on the wellbore modeling requirements, the corresponding high-pressure physical properties, pump parameters, geothermal gradient, IPR parameters, tubing structure, and well trajectory data are extracted from the wellbore data standard template using the well number field as the label. Six types of data structure files are generated and integrated to obtain the wellbore numerical model corresponding to the current well number field.

[0080] Then, based on the well type field, multiple wellbore numerical models are integrated to construct an overall wellbore numerical model.

[0081] Implementation Case:

[0082] Specifically, the method proposed in this invention is used to implement rapid wellbore modeling in high water-cut blocks. Rapid wellbore modeling and updating based on data templates includes data template generation, multi-source data conversion, modular and batch construction of data models and wellbore models, and wellbore model updating. This rapid wellbore modeling and updating method can provide data, templates, and model foundations for subsequent rapid wellbore fitting. Examples of rapid wellbore modeling implementation are shown in Table 1 and... Figure 5 As shown in Table 1 (taking a jet pump well as an example), a multi-source data table template for the wellbore is first established. This template includes six types of data: high-pressure properties of the wellbore, pump parameters, geothermal gradient, IPR parameters, tubing structure, and well trajectory. Then, this invention is used to generate six types of modular data models and a wellbore model based on the well number conversion. Figure 5 and Figure 6 As shown. Next, update the wellbore numerical model and check its integrity and validity, generating the wellbore lifting data file (e.g., Figure 7 (As shown) is used for vertical pipe flow simulation in wellbore.

[0083] Table 1. Wellbore Multi-Source Data Template (Jet Pump Well)

[0084]

[0085] This invention, based on the characteristics of multi-source databases in oilfield development and the establishment of wellbore numerical models, organically combines data processing, data conversion, and model building technologies to achieve rapid wellbore modeling based on template data integration. Using multi-source wellbore data as a foundation, professional platform data files as a reference, and standard templates and files as the medium for data storage, integration, and conversion, it enables the rapid generation and integration of the eight structural module files of the wellbore numerical model. This invention fully utilizes the standardization of oilfield development and the structural and indexing characteristics of wellbore numerical model files, achieving rapid integration of multi-source data and making the cumbersome preprocessing process of wellbore numerical models faster and more efficient. It also lays a standard data and model foundation for subsequent rapid fitting of the wellbore numerical model.

[0086] For the foregoing method embodiments, in order to simplify the description, they are all described as a series of actions. However, those skilled in the art should understand that the present invention is not limited to the described order of actions, because according to the present invention, some steps can be performed in other orders or simultaneously. Furthermore, those skilled in the art should also understand that the embodiments described in the specification are preferred embodiments, and the actions and modules involved are not necessarily essential to the present invention.

[0087] It should be noted that, in other embodiments of the present invention, the method can also combine one or more of the above embodiments to obtain a new multi-source wellbore data fusion processing method to optimize the management of wellbore data.

[0088] It should be noted that, based on the methods in any one or more embodiments of the present invention described above, the present invention also provides a storage medium storing program code that can implement the methods described in any one or more embodiments, and when the code is executed by the operating system, it can implement the modeling processing method for multi-source wellbore data as described above.

[0089] Example 2

[0090] The methods described in detail in the above-disclosed embodiments of the present invention can be implemented using various forms of devices or systems. Therefore, based on other aspects of the methods described in any one or more of the above embodiments, the present invention also provides a modeling processing system for multi-source wellbore data. This system is used to execute the modeling processing method for multi-source wellbore data described in any one or more of the above embodiments. Specific embodiments are given below for detailed description.

[0091] Specifically, Figure 8 The diagram shows a schematic representation of the structure of a modeling system for multi-source wellbore data provided in an embodiment of the present invention. Figure 8 As shown, the system includes:

[0092] The integrated template design module is configured to design a standard template that covers the comprehensive extraction requirements of wellbore data based on the data characteristics of all associated multi-source wellbore data and all modeling data conditions of the application. The standard template includes multiple sub-templates, each sub-template corresponding to a type of modeling data condition, and each sub-template contains different well type data templates, including data templates for pumping unit wells, electric pump wells, jet pump wells, and water injection wells.

[0093] The multi-source data extraction module is configured to extract corresponding wellbore source data from independent or overall multi-source databases based on the required modeling data conditions, and store it in the corresponding sub-template in the standard template in combination with well type information, thereby achieving targeted data fusion.

[0094] The data verification module is configured to verify whether the integrity and validity of the data in the corresponding sub-template of the standard template meet the requirements based on the list of wellbore modeling conditions. If not, the multi-source data extraction steps are re-executed until all the required data meet the requirements.

[0095] The wellbore modeling module is configured to synchronously input the source data that has passed verification in the standard template into a matching wellbore numerical model professional platform, convert it into several categories of multi-mode wellbore numerical model module data structure files, and integrate them to obtain the overall wellbore numerical model.

[0096] The wellbore modeling module is the core component, responsible for converting wellbore models and managing structure files. After inputting and integrating the key data required for the wellbore numerical model from multiple source databases, the module converts the data into multiple structure files for the wellbore numerical model. These include the generation and integration of six data structure file modules: wellbore high-pressure properties, pump parameters, geothermal gradient, IPR parameters, tubing structure, and well trajectory. It also handles the batch construction of four types of wellbore model files: pumping unit wells, electric pump wells, jet pump wells, and water injection wells. Before this module executes, a series of model preprocessing logics generate four types of data templates with data items for pumping unit wells, electric pump wells, jet pump wells, and water injection wells. These templates include various wellbore data templates and data files. After the model is integrated, a model post-processing module performs verification: storing and displaying the well template data, wellbore models, and files in the output files, and evaluating the completeness and validity of the batch-generated data models and wellbore models. The connection principle of each module in the system is as follows: Figure 9 As shown.

[0097] The user interface module enables the human-computer interaction of the invention. Through this module, users can open, set, read, input, and generate data parameters, operating parameters, and data files for standard data templates. It also displays and enables the reading, storage, and conversion of multi-source wellbore data, as well as the batch construction and updating of single-well data models and numerical models. This facilitates the subsequent reading and conversion of key data required from multi-source databases to wellbore numerical models.

[0098] Furthermore, in a preferred embodiment, the system further includes a model verification module, which is configured to perform calculations based on the integrated overall wellbore numerical model using preset test data, and verify the integrity and validity of the data structure files of each module according to the calculation process and results of the model. If the set requirements are not met, the wellbore modeling operation is re-executed until all the data structure files of each module meet the requirements.

[0099] In one optional embodiment, the wellbore modeling module is configured to synchronously input source data into a matching wellbore numerical model professional platform through an interface or path corresponding to the application modeling conditions.

[0100] Furthermore, in one embodiment, the integrated template design module is configured to: set different well type data templates to include different data storage areas, which respectively store data objects of different data source fields and data types. The data source fields are set according to the source category fields of the source data, including different wellbore data fields corresponding to a certain well type.

[0101] Furthermore, to achieve the most comprehensive acquisition and fusion management of the required source data, this invention provides a multi-source data extraction module, which realizes the aggregation and retrieval of as many multi-source databases as possible. Preferably, in one embodiment, the multi-source data extraction module is configured to extract the corresponding wellbore source data from independent or integrated multi-source databases, and then perform preprocessing operations, including identifying and filtering out duplicate and invalid data in the extracted target source data.

[0102] Furthermore, in one embodiment, the multi-source data extraction module is further configured to store the extracted and preprocessed source data in the corresponding well-shaped data template, using its data category keywords or fields as indexes.

[0103] In cases where different modeling data conditions require the extraction of the same source data, the multi-source data extraction module extracts and stores the data independently into the matching well-type data template.

[0104] In an optional embodiment, the data verification module is configured to: verify the integrity and validity of the data in each sub-template of the standard template according to the corresponding modeling data conditions; if both requirements are met, the verification is deemed successful; otherwise, all data corresponding to the current modeling conditions that failed the verification are re-extracted. Through the data verification module's post-extraction processing, the module can identify and display the data content corresponding to the data template in the pre-output file and evaluate the integrity and validity of the extracted source data.

[0105] In practical applications, in one embodiment, the wellbore modeling module is configured to perform the following operations:

[0106] Based on the wellbore modeling requirements, the corresponding high-pressure physical properties, pump parameters, geothermal gradient, IPR parameters, tubing structure, and well trajectory data are extracted from the wellbore data standard template using the well number field as the label. Six types of data structure files are generated and integrated to obtain the wellbore numerical model corresponding to the current well number field.

[0107] Multiple wellbore numerical models are integrated based on the well type field to construct an overall wellbore numerical model.

[0108] In the modeling system for multi-source wellbore data provided in this embodiment of the invention, each module or unit structure can operate independently or in combination according to actual extraction and modeling needs to achieve the corresponding technical effects.

[0109] It should be understood that the embodiments disclosed herein are not limited to the specific structures, processing steps, or materials disclosed herein, but should be extended to equivalent substitutions of these features as understood by those skilled in the art. It should also be understood that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting.

[0110] The phrase "an embodiment" in the specification means that a specific feature, structure, or characteristic described in connection with the embodiment is included in at least one embodiment of the invention. Therefore, the phrase "an embodiment" appearing in various places throughout the specification does not necessarily refer to the same embodiment.

[0111] While the embodiments disclosed in this invention are as described above, the content is merely for the purpose of facilitating understanding of the invention and is not intended to limit the invention. Any person skilled in the art to which this invention pertains may make any modifications and variations in form and detail of the implementation without departing from the spirit and scope disclosed herein; however, the scope of patent protection for this invention shall still be determined by the scope defined in the appended claims.

Claims

1. A modeling method for multi-source wellbore data, characterized in that, The method includes: The template design process integrates the steps of designing a standard template that covers the comprehensive extraction requirements of wellbore data based on the data characteristics of all associated multi-source wellbore data and the modeling data conditions of all applications. The standard template includes multiple sub-templates, each sub-template corresponding to a type of modeling data condition, and each sub-template contains different well type data templates, including data templates for pumping unit wells, electric pump wells, jet pump wells, and water injection wells. The multi-source data extraction steps involve extracting corresponding wellbore source data from independent or integrated multi-source databases based on the required modeling data conditions, and storing the data in the corresponding sub-templates of the standard template in combination with well type information to achieve targeted data fusion. The data verification steps involve verifying the completeness and validity of the data in the corresponding sub-templates of the standard template based on the required wellbore modeling conditions list. If the data does not meet the requirements, the multi-source data extraction steps are repeated until all the required data meet the requirements. The wellbore modeling steps are as follows: For the source data that has passed verification in the standard template, it is synchronously input into the matching wellbore numerical model professional platform, converted into several categories of multi-module wellbore numerical model data structure files, and integrated to obtain the overall wellbore numerical model. In the wellbore modeling step, after the corresponding source data is input into the wellbore numerical model professional platform, clear the data content of the current batch in the data standard template; In the multi-source data extraction step, after extracting the corresponding wellbore source data from independent or overall multi-source databases, preprocessing operations are performed, including identifying and filtering out duplicate and invalid data in the extracted target source data. For cases where the same source data needs to be extracted under different modeling data conditions, the data is extracted independently and stored in the matching well data template according to the organization format that matches the modeling data conditions. The method further includes: The model verification process involves performing calculations on the obtained overall wellbore numerical model using preset test data. The integrity and validity of the data structure files of each module are verified based on the calculation process and results. If the set requirements are not met, the wellbore modeling process is repeated until all the data structure files of each module meet the requirements.

2. The method according to claim 1, characterized in that, In the wellbore modeling step, the source data is synchronously input into the matching wellbore numerical model professional platform through the interface or path corresponding to the application modeling conditions.

3. The method according to claim 1, characterized in that, In the integrated template design step, different well type data templates are set to include different data storage areas, which respectively store data objects of different data source fields and data types. The data source fields are set according to the source category fields of the source data, including different wellbore data fields corresponding to a certain well type.

4. The method according to claim 1 or 2, characterized in that, In the multi-source data extraction step, the extracted source data is stored in the well-shaped data template of the corresponding sub-module using the data category keywords or fields as indexes.

5. The method according to claim 1, characterized in that, In the data verification step, the integrity and validity of the data in each sub-template of the standard template are verified according to the corresponding modeling data conditions. If both requirements are met, the verification is determined to be passed. Otherwise, all data corresponding to the current modeling conditions that failed the verification are re-extracted.

6. The method according to claim 1, characterized in that, The wellbore modeling process includes: Based on the wellbore modeling requirements, the corresponding high-pressure physical properties, pump parameters, geothermal gradient, IPR parameters, tubing structure, and well trajectory data are extracted from the wellbore data standard template using the well number field as the label. Six types of data structure files are generated and integrated to obtain the wellbore numerical model corresponding to the current well number field. Multiple wellbore numerical models are integrated based on the well type field to construct an overall wellbore numerical model.

7. A storage medium, characterized in that, The storage medium stores program code capable of implementing the method as described in any one of claims 1 to 6.

8. A modeling system for multi-source wellbore data, characterized in that, The system performs the method as described in any one of claims 1 to 6.

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