Logging report generation method and device, equipment and storage medium

Abstract

The invention discloses a logging report generation method and device, equipment and a storage medium. The method comprises the steps that multiple pieces of logging report field information configured by a user are acquired; based on the multiple pieces of logging report field information and a pre-trained language processing model, determining a field data query statement corresponding to each piece of logging report field information; querying field data corresponding to each piece of logging report field information from a pre-constructed logging database by executing the field data query statement; and based on the field data corresponding to each piece of logging report field information, generating a plurality of logging reports corresponding to the logging report field information. Through the technical scheme of the embodiment of the invention, dynamic configuration and automatic generation of the logging report are realized, so that the flexibility of the logging report is improved, and differential requirements of users are met.

Description

Technical Field

[0001] The present invention relates to the technical field of petroleum industry, and in particular to a method, device, equipment and storage medium for generating a logging report. Background Art

[0002] With the rapid development of the oil industry, logging reports are needed to more clearly display logging data. At present, specific report field data is usually obtained manually, and logging reports containing only specific fields are generated based on the obtained logging report field data. It can be seen that this report generation method is time-consuming and labor-intensive, and has poor flexibility and cannot meet the differentiated needs of users. Summary of the invention

[0003] The present invention provides a logging report generation method, device, equipment and storage medium to realize dynamic configuration and automatic generation of logging reports, thereby improving the flexibility of logging reports and meeting differentiated needs of users.

[0004] In a first aspect, an embodiment of the present invention provides a method for generating a logging report, comprising:

[0005] Get multiple logging report field information configured by the user;

[0006] Based on multiple logging report field information and a pre-trained language processing model, determine a field data query statement corresponding to each logging report field information;

[0007] By executing the field data query statement, the field data corresponding to each logging report field information is queried from the pre-built logging database;

[0008] Based on the field data corresponding to each logging report field information, a plurality of logging reports corresponding to the logging report field information are generated.

[0009] In a second aspect, an embodiment of the present invention further provides a mud logging report generating device, comprising:

[0010] A mud logging report field information acquisition module is used to acquire multiple mud logging report field information configured by the user;

[0011] A field data query statement determination module is used to determine the field data query statement corresponding to each logging report field information based on multiple logging report field information and a pre-trained language processing model;

[0012] A field data query module is used to query the field data corresponding to each logging report field information from a pre-built logging database by executing the field data query statement;

[0013] The mud logging report generation module is used to generate mud logging reports corresponding to multiple mud logging report field information based on the field data corresponding to each mud logging report field information.

[0014] In a third aspect, an embodiment of the present invention further provides an electronic device, the electronic device comprising: at least one processor; and

[0015] a memory communicatively connected to the at least one processor; wherein,

[0016] The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the mud logging report generation method provided in any embodiment of the present invention.

[0017] In a fourth aspect, an embodiment of the present invention further provides a computer-readable storage medium, wherein the computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to execute the logging report generation method provided by any embodiment of the present invention when executed.

[0018] The technical solution of the embodiment of the present invention obtains multiple logging report field information configured by the user, determines the field data query statement corresponding to each logging report field information based on the multiple logging report field information and the pre-trained language processing model, and automatically and quickly obtains the field data query statement corresponding to each logging report field information without manual intervention, which greatly shortens the logging report generation time. By executing the field data query statement, the field data corresponding to each logging report field information is queried from the pre-built logging database, and the automatic query of the field data corresponding to the logging report field information is realized, and the logging report field information can be flexibly changed to obtain the corresponding field data. Based on the field data corresponding to each logging report field information, multiple logging reports corresponding to the logging report field information are automatically generated. Thereby, the dynamic configuration and automatic generation of the logging report are realized, thereby improving the flexibility of the logging report and meeting the differentiated needs of users.

[0019] It should be understood that the contents described in this section are not intended to identify the key or important features of the embodiments of the present invention, nor are they intended to limit the scope of the present invention. Other features of the present invention will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings in the following description are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0021] Figure 1 is a flow chart of a method for generating a logging report according to the first embodiment of the present invention;

[0022] Figure 2 is a flow chart of a method for generating a logging report according to Embodiment 2 of the present invention;

[0023] Figure 3 It is a structural schematic diagram of a mud logging report generating device provided according to the third embodiment of the present invention;

[0024] Figure 4 The present invention is a schematic diagram of the structure of an electronic device for implementing the method for generating a mud logging report according to an embodiment of the present invention. DETAILED DESCRIPTION

[0025] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0026] It should be noted that the terms "target", "current", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0027] Embodiment 1

[0028] Figure 1 A flow chart of a method for determining reservoir sensitive parameters is provided for the first embodiment of the present invention. This embodiment can be applied to the generation of any logging report. Figure 1 As shown, the method can be executed by a mud logging report generating device, which can be implemented in the form of hardware and / or software, and can be configured in an electronic device. Figure 1 As shown, the method specifically comprises the following steps:

[0029] S110, obtaining multiple logging report field information configured by the user.

[0030] Among them, logging refers to the process of using rock and mineral analysis, geochemistry, geophysics and other methods to observe, collect, collect, record and analyze the information of wellbore return such as solid, liquid and gas during the drilling process, so as to establish logging geological profiles, discover oil and gas displays, evaluate oil and gas layers, and provide drilling information services for petroleum projects (investors, drilling projects, other projects). Logging report refers to a report based on the information of wellbore return such as solid, liquid and gas during the logging process. The logging report field information may refer to the field information that needs to be included in the generated logging report. For example, the logging data can be abstracted into attribute field information (i.e., concepts) one by one, so as to obtain the desired logging data based on each field information. For example, the logging report field information may include operation type, achievement description, establishment time, achievement query, data source, remarks, etc.

[0031] Specifically, the user can configure the field information to be included in the mud logging report to be generated based on his own needs on the configuration interface, thereby obtaining multiple mud logging report field information configured by the user, and realizing dynamic configuration of the mud logging report.

[0032] S120: Based on multiple mud logging report field information and a pre-trained language processing model, determine a field data query statement corresponding to each mud logging report field information.

[0033] Among them, the language processing model can be any neural network model that is pre-trained based on sample data and is used to convert field information into query statements. For example, the language processing model can be obtained by pre-training a large language model based on sample report field information and field data query statement labels corresponding to the sample report field information. Among them, a large language model (LLM) refers to a pre-trained model obtained by training on a large amount of language sample data. For example, a large language model can refer to a GPT (Generative Pre-Trained Transformer) model or a BERT (Bidirectional Encoder Representation from Transformers) model. By training sentence conversion based on a large language model, the model training speed and language processing accuracy can be improved.

[0034] The field data query statement may refer to an execution statement for querying the logging data corresponding to the report field information. For example, the field data query statement may refer to a structured query language (SQL) query statement.

[0035] Specifically, using the pre-trained language processing model, language processing and sentence conversion can be performed on multiple logging report field information, and the field data query sentence corresponding to each logging report field information can be automatically and quickly obtained without human intervention, so as to improve the speed of generating logging reports.

[0036] As an optional embodiment, S120 may include: inputting each logging report field information into a pre-trained language processing model for language processing and sentence conversion; and obtaining a field data query sentence corresponding to each logging report field information based on the output of the language processing model.

[0037] Specifically, when there is only one kind of logging database and all logging report field information is stored in this kind of logging database, each logging report field information can be directly input into a pre-trained language processing model, and features of the input logging report field information are extracted in the language processing model. Based on the extracted field feature information, corresponding field data query statements are generated, and the generated field data query statements are output, so as to quickly obtain the field data query statements corresponding to each logging report field information in this kind of logging database.

[0038] As another optional embodiment, S120 may include: obtaining the logging database type information corresponding to each logging report field information; inputting each logging report field information and the corresponding logging database type information into a pre-trained language processing model for language processing and statement conversion; based on the output of the language processing model, obtaining the field data query statement corresponding to each logging report field information, and the field data query statement conforms to the query syntax of the corresponding logging database type.

[0039] Specifically, when there are multiple types of logging databases, and different types of report field information are respectively stored in corresponding types of logging databases, each logging report field information and the corresponding logging database type information can be input into a pre-trained language processing model, and features of each logging report field information are extracted in the language processing model. Based on the extracted field feature information, a field data query statement under the input database type is generated, and the generated field data query statement is output, so as to quickly obtain a field data query statement that conforms to the corresponding logging database type.

[0040] S130, querying the field data corresponding to each logging report field information from the pre-built logging database by executing the field data query statement.

[0041] The logging database may refer to a database for storing logging data, and the number of databases may be one or more, for example, the logging database may be DB2, MS SQL, Oracle, Infomix, etc. The field data may be specific logging data corresponding to each logging report field information, that is, field attribute value.

[0042] Specifically, all logging databases for storing logging data can be pre-constructed. If there is only one logging database, then by executing the field data query statement corresponding to each logging report field information, the logging data corresponding to each logging report field information can be queried from the logging database, and the logging data can be determined as the corresponding field data. If there are at least two logging databases, then by executing the field data query statement corresponding to each logging report field information, the logging data corresponding to each logging report field information can be queried from the logging database corresponding to the logging report field information type, and the logging data can be determined as the corresponding field data.

[0043] Exemplarily, the construction process of the logging database may include: conceptually abstracting the logging report requirements and establishing a logging conceptual model; performing relational transformation on the logging conceptual model and determining a logging logical model; storing the logging logical model in a physical structure to obtain a logging database, and storing the collected original logging data in the logging database.

[0044] The mud logging conceptual model may refer to a corresponding relationship model between mud logging report requirements and concepts. For example, the mud logging conceptual model may refer to an entity relationship model ER model. The mud logging logical model may refer to a relationship model between mud logging data concepts and mud logging data. For example, the mud logging logical model may refer to a logical data model.

[0045] Specifically, based on all logging report requirements, report requirements with the same characteristics are classified and conceptually abstracted to establish a logging conceptual model. The logging conceptual model is transformed in relation to transform the concepts of logging data and the connections between logging data into logical descriptions of logging data, and the logging logical model is determined. Physical structure design is performed based on the logging logical model, and a physical structure that best suits the application environment is selected for the logging logical model, so that the designed physical database occupies less storage space and the operation of the database has the highest possible operating speed. The logging logical model is stored in a physical structure, and a query index is designed to form a database model to obtain a logging database. The logical description of the data is transformed into technical specifications for storing and retrieving data through the physical design of the database, and the collected original logging data is stored in the logging database. It is ensured that the database can provide sufficiently good performance and that the integrity, security and recoverability of the database are guaranteed.

[0046] S140 . Generate multiple mud logging reports corresponding to mud logging report field information based on the field data corresponding to each mud logging report field information.

[0047] Specifically, each logging report field information and the field data corresponding to each logging report field information are configured according to a preset fixed logging report format to generate multiple logging reports corresponding to the logging report field information.

[0048] The technical solution of the embodiment of the present invention obtains multiple logging report field information configured by the user; based on the multiple logging report field information and the pre-trained language processing model, the field data query statement corresponding to each logging report field information is determined to automatically and quickly obtain the field data query statement corresponding to each logging report field information, without manual intervention, which greatly shortens the logging report generation time. By executing the field data query statement, the field data corresponding to each logging report field information is queried from the pre-built logging database, and the automatic query of the field data corresponding to the logging report field information is realized, and the logging report field information can be flexibly changed to obtain the corresponding field data. Based on the field data corresponding to each logging report field information, multiple logging reports corresponding to the logging report field information are automatically generated. This realizes the dynamic configuration and automatic generation of logging reports, thereby improving the flexibility of logging reports and meeting the differentiated needs of users.

[0049] On the basis of the above scheme, after S140, it also includes: obtaining the sharer information configured by the user and the access permission information corresponding to the sharer information; based on the sharer information and the corresponding access permission information, sharing the generated logging report, so that the sharer can access the logging report based on the corresponding access permission information.

[0050] The user-configured sharer information may refer to other user information set by the user with access rights to the logging report. The access rights information may refer to information that the user restricts or allows the sharer to access certain information items or certain control items according to the identity of the sharer.

[0051] Specifically, the access permission information corresponding to the sharer information is determined based on the sharer information configured by the user, and the generated mud logging report is shared with the sharer based on the sharer information and the corresponding access permission information, and the sharer accesses the mud logging report based on the corresponding access permission information. Flexible management of mud logging report permissions is achieved, and data access and modification can be controlled according to the permissions of different users, further meeting the differentiated needs of users for mud logging reports.

[0052] Embodiment 2

[0053] Figure 2This is a flow chart of a method for generating a mud logging report provided in the second embodiment of the present invention. Based on the above embodiments, this embodiment optimizes the step of "generating mud logging reports corresponding to multiple mud logging report field information based on the field data corresponding to each mud logging report field information". The explanations of the terms that are the same or corresponding to the above embodiments are not repeated here.

[0054] See also Figure 2 Another logging report generation method provided in this embodiment specifically includes the following steps:

[0055] S210, obtaining multiple logging report field information configured by the user.

[0056] S220: Based on multiple mud logging report field information and a pre-trained language processing model, determine a field data query statement corresponding to each mud logging report field information.

[0057] S230: Query the field data corresponding to each logging report field information from the pre-built logging database by executing the field data query statement.

[0058] S240: Obtaining the logging report format information configured by the user.

[0059] The logging report format information may refer to the layout position information of each logging report field information.

[0060] Specifically, the user can configure the layout position information of each logging report field information in the logging report to be generated based on his own needs on the configuration interface, thereby obtaining the logging report format information configured by the user, and realizing the personalized configuration of the logging report.

[0061] S250: Generate a mud logging report that complies with the mud logging report format information based on the field data corresponding to each mud logging report field information and the mud logging report format information.

[0062] Specifically, according to the configured logging report format information, the field data corresponding to each logging report field information is filled in to generate a logging report that conforms to the logging report format information, thereby realizing dynamic configuration of the report format, further improving the flexibility of logging report generation, and meeting users' differentiated and personalized needs for logging reports.

[0063] The technical solution of the embodiment of the present invention obtains the logging report format information configured by the user, generates a logging report that conforms to the logging report format information based on the field data corresponding to each logging report field information and the logging report format information, thereby realizing flexible and changeable logging report generation, and further meeting the differentiated report needs and personalized report needs of different users.

[0064] Embodiment 3

[0065] Figure 3 This is a schematic diagram of the structure of a logging report generation device provided in the third embodiment of the present invention. Figure 3 As shown, the device includes: a logging report field information acquisition module 310, a field data query statement determination module 320, a field data query module 330 and a logging report generation module 340.

[0066] The mud logging report field information acquisition module 310 is used to acquire multiple mud logging report field information configured by the user;

[0067] A field data query statement determination module 320 is used to determine a field data query statement corresponding to each logging report field information based on multiple logging report field information and a pre-trained language processing model;

[0068] The field data query module 330 is used to query the field data corresponding to each logging report field information from the pre-built logging database by executing the field data query statement;

[0069] The mud logging report generation module 340 is used to generate mud logging reports corresponding to multiple mud logging report field information based on the field data corresponding to each mud logging report field information.

[0070] The technical solution of this embodiment obtains multiple logging report field information configured by the user; based on the multiple logging report field information and the pre-trained language processing model, the field data query statement corresponding to each logging report field information is determined to automatically and quickly obtain the field data query statement corresponding to each logging report field information, without manual intervention, which greatly shortens the logging report generation time. By executing the field data query statement, the field data corresponding to each logging report field information is queried from the pre-built logging database, and the automatic query of the field data corresponding to the logging report field information is realized, and the logging report field information can be flexibly changed to obtain the corresponding field data. Based on the field data corresponding to each logging report field information, multiple logging reports corresponding to the logging report field information are automatically generated. This realizes the dynamic configuration and automatic generation of logging reports, thereby improving the flexibility of logging reports and meeting the differentiated needs of users.

[0071] Optionally, the field data query statement determination module 320 is specifically used to: input each logging report field information into a pre-trained language processing model for language processing and statement conversion; based on the output of the language processing model, obtain the field data query statement corresponding to each logging report field information.

[0072] Optionally, the field data query statement determination module 320 is further specifically used to: obtain the logging database type information corresponding to each logging report field information; input each logging report field information and the corresponding logging database type information into a pre-trained language processing model for language processing and statement conversion; based on the output of the language processing model, obtain the field data query statement corresponding to each logging report field information, and the field data query statement conforms to the query syntax of the corresponding logging database type.

[0073] Optionally, the logging report generation module 340 is specifically used to: obtain logging report format information configured by the user; and generate a logging report that complies with the logging report format information based on field data corresponding to each logging report field information and the logging report format information.

[0074] Optionally, the logging database construction module is specifically used to: perform conceptual abstraction on the logging report requirements and establish a logging conceptual model; perform relational transformation on the logging conceptual model and determine a logging logical model; perform physical structure storage on the logging logical model to obtain a logging database, and store the collected original logging data in the logging database.

[0075] Optionally, the device further comprises:

[0076] An access right information acquisition unit, configured to acquire user-configured sharer information and access right information corresponding to the sharer information after generating multiple logging reports corresponding to the logging report field information based on the field data corresponding to each logging report field information;

[0077] The mud logging report access unit is used to share the generated mud logging report based on the sharer information and the corresponding access permission information, so that the sharer can access the mud logging report based on the corresponding access permission information.

[0078] Optionally, the language processing model is obtained by training a large language model in advance based on sample report field information and field data query statement labels corresponding to the sample report field information.

[0079] The Internet of Vehicles data synchronization device provided in the embodiment of the present invention can execute the Internet of Vehicles data synchronization method provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the execution method.

[0080] Figure 4A schematic diagram of the structure of an electronic device 12 that can be used to implement an embodiment of the present invention is shown. The electronic device is intended to represent various forms of digital computers, such as desktop computers, workstations, servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processing, smart phones, wearable devices (such as helmets, glasses, watches, etc.) and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present invention described and / or required herein.

[0081] like Figure 4 As shown, the electronic device 12 is in the form of a general purpose computing device. The components of the electronic device 12 may include, but are not limited to: one or more processors or processing units 16, a system memory 28, and a bus 18 that connects various system components (including the system memory 28 and the processing unit 16).

[0082] Bus 18 represents one or more of several types of bus structures, including a memory bus or memory controller, a peripheral bus, an accelerated graphics port, a processor or a local bus using any of a variety of bus architectures. By way of example, these architectures include, but are not limited to, an Industry Standard Architecture (ISA) bus, a Micro Channel Architecture (MAC) bus, an Enhanced ISA bus, a Video Electronics Standards Association (VESA) local bus, and a Peripheral Component Interconnect (PCI) bus.

[0083] The electronic device 12 typically includes a variety of computer system readable media. These media can be any available media that can be accessed by the electronic device 12, including volatile and non-volatile media, removable and non-removable media.

[0084] The system memory 28 may include computer system readable media in the form of volatile memory, such as random access memory (RAM) 30 and / or cache memory 32. The electronic device 12 may further include other removable / non-removable, volatile / non-volatile computer system storage media. By way of example only, the storage system 34 may be used to read and write non-removable, non-volatile magnetic media ( Figure 4 not shown, usually called a "hard drive"). Although Figure 4Not shown in the figure, a disk drive for reading and writing to a removable non-volatile disk (e.g., a "floppy disk"), and an optical disk drive for reading and writing to a removable non-volatile optical disk (e.g., a CD-ROM, a DVD-ROM, or other optical media) may be provided. In these cases, each drive may be connected to the bus 18 via one or more data medium interfaces. The system memory 28 may include at least one program product having a set (e.g., at least one) of program modules that are configured to perform the functions of the various embodiments of the present invention.

[0085] A program / utility 40 having a set (at least one) of program modules 42 may be stored, for example, in system memory 28, such program modules 42 including, but not limited to, an operating system, one or more application programs, other program modules, and program data, each of which or some combination may include an implementation of a network environment. Program modules 42 generally perform the functions and / or methods of the embodiments described herein.

[0086] The electronic device 12 may also communicate with one or more external devices 14 (e.g., keyboards, pointing devices, displays 24, etc.), may also communicate with one or more devices that enable a user to interact with the electronic device 12, and / or may communicate with any device that enables the electronic device 12 to communicate with one or more other computing devices (e.g., network cards, modems, etc.). Such communication may be performed via an input / output (I / O) interface 22. Furthermore, the electronic device 12 may also communicate with one or more networks (e.g., local area networks (LANs), wide area networks (WANs), and / or public networks, such as the Internet) via a network adapter 20. As shown, the network adapter 20 communicates with other modules of the electronic device 12 via a bus 18. It should be understood that, although not shown in the figure, other hardware and / or software modules may be used in conjunction with the electronic device 12, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems.

[0087] The processing unit 16 executes various functional applications and data processing by running the program stored in the system memory 28, for example, implementing a logging report generation method provided in the embodiment of the present invention, the method comprising:

[0088] Get multiple logging report field information configured by the user;

[0089] Based on multiple logging report field information and a pre-trained language processing model, determine a field data query statement corresponding to each logging report field information;

[0090] By executing the field data query statement, the field data corresponding to each logging report field information is queried from the pre-built logging database;

[0091] Based on the field data corresponding to each logging report field information, a plurality of logging reports corresponding to the logging report field information are generated.

[0092] Of course, those skilled in the art can understand that the processor can also implement the technical solution of the logging report generation method provided by any embodiment of the present invention.

[0093] This embodiment provides a computer-readable storage medium, on which a computer program is stored. When the program is executed by a processor, the steps of the method for generating a mud logging report provided in any embodiment of the present invention are implemented. The method includes:

[0094] Get multiple logging report field information configured by the user;

[0095] Based on multiple logging report field information and a pre-trained language processing model, determine a field data query statement corresponding to each logging report field information;

[0096] By executing the field data query statement, the field data corresponding to each logging report field information is queried from the pre-built logging database;

[0097] Based on the field data corresponding to each logging report field information, a plurality of logging reports corresponding to the logging report field information are generated.

[0098] The computer storage medium of the embodiment of the present invention can adopt any combination of one or more computer-readable media. The computer-readable medium can be a computer-readable signal medium or a computer-readable storage medium. The computer-readable storage medium can be, for example, but not limited to: an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples (non-exhaustive list) of computer-readable storage media include: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In this document, a computer-readable storage medium can be any tangible medium containing or storing a program, which can be used by an instruction execution system, device or device or used in combination with it.

[0099] Computer-readable signal media may include data signals propagated in baseband or as part of a carrier wave, which carry computer-readable program code. Such propagated data signals may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. Computer-readable signal media may also be any computer-readable medium other than a computer-readable storage medium, which may send, propagate, or transmit a program for use by or in conjunction with an instruction execution system, apparatus, or device.

[0100] The program code embodied on the computer readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.

[0101] Computer program code for performing the operations of the present invention may be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, C++, and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0102] It should be understood by those skilled in the art that the modules or steps of the present invention described above can be implemented by a general-purpose computing device, they can be concentrated on a single computing device, or distributed on a network composed of multiple computing devices, optionally, they can be implemented by a program code executable by a computer device, so that they can be stored in a storage device and executed by the computing device, or they can be made into individual integrated circuit modules, or multiple modules or steps therein can be made into a single integrated circuit module for implementation. Thus, the present invention is not limited to any specific combination of hardware and software.

[0103] Note that the above are only preferred embodiments of the present invention and the technical principles used. Those skilled in the art will understand that the present invention is not limited to the specific embodiments described herein, and that various obvious changes, readjustments and substitutions can be made by those skilled in the art without departing from the scope of protection of the present invention. Therefore, although the present invention has been described in more detail through the above embodiments, the present invention is not limited to the above embodiments, and may include more other equivalent embodiments without departing from the concept of the present invention, and the scope of the present invention is determined by the scope of the appended claims.

Claims

1. A method for generating a logging report, characterized in that: include: Get multiple logging report field information configured by the user; Based on multiple logging report field information and a pre-trained language processing model, determine a field data query statement corresponding to each logging report field information; By executing the field data query statement, the field data corresponding to each logging report field information is queried from the pre-built logging database; Based on the field data corresponding to each logging report field information, a plurality of logging reports corresponding to the logging report field information are generated.

2. The method according to claim 1, characterized in that: Based on multiple logging report field information and a pre-trained language processing model, a field data query statement corresponding to each logging report field information is determined, including: Input each logging report field information into a pre-trained language processing model for language processing and sentence conversion; Based on the output of the language processing model, a field data query statement corresponding to each logging report field information is obtained.

3. The method according to claim 1, characterized in that Based on multiple logging report field information and a pre-trained language processing model, a field data query statement corresponding to each logging report field information is determined, including: Get the logging database type information corresponding to each logging report field information; Input each logging report field information and corresponding logging database type information into a pre-trained language processing model for language processing and sentence conversion; Based on the output of the language processing model, a field data query statement corresponding to each mud logging report field information is obtained, and the field data query statement conforms to the query syntax of the corresponding mud logging database type.

4. The method according to claim 1, characterized in that: Based on the field data corresponding to each logging report field information, multiple logging reports corresponding to the logging report field information are generated, including: Get the logging report format information configured by the user; Based on the field data corresponding to each logging report field information and the logging report format information, a logging report conforming to the logging report format information is generated.

5. The method according to claim 1, characterized in that The construction process of the logging database includes: Carry out conceptual abstraction of mud logging report requirements and establish mud logging conceptual model; Performing relational transformation on the mud logging conceptual model to determine a mud logging logical model; The logging logic model is physically stored to obtain a logging database, and the collected original logging data is stored in the logging database.

6. The method according to claim 1, characterized in that After generating multiple logging reports corresponding to the logging report field information based on the field data corresponding to each logging report field information, the method further includes: Obtaining the sharer information configured by the user and the access permission information corresponding to the sharer information; Based on the sharer information and corresponding access permission information, the generated mud logging report is shared, so that the sharer can access the mud logging report based on the corresponding access permission information.

7. The method according to any one of claims 1 to 6, characterized in that: The language processing model is obtained by training a large language model in advance based on sample report field information and field data query statement labels corresponding to the sample report field information.

8. A mud logging report generating device, characterized in that: include: A mud logging report field information acquisition module is used to acquire multiple mud logging report field information configured by the user; A field data query statement determination module is used to determine the field data query statement corresponding to each logging report field information based on multiple logging report field information and a pre-trained language processing model; A field data query module is used to query the field data corresponding to each logging report field information from a pre-built logging database by executing the field data query statement; The mud logging report generation module is used to generate mud logging reports corresponding to multiple mud logging report field information based on the field data corresponding to each mud logging report field information.

9. An electronic device, characterized in that: The electronic device comprises: at least one processor; and a memory communicatively connected to the at least one processor; wherein, The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the mud logging report generating method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the method for generating a mud logging report according to any one of claims 1 to 7 when executed.

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