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CN-122021576-A - Oil gas production data intelligent meter reading method based on large model and coding model

CN122021576ACN 122021576 ACN122021576 ACN 122021576ACN-122021576-A

Abstract

The invention relates to an oil gas production data intelligent meter reading method of a large model and a coding model, which comprises the steps of receiving a source table transmitted by a user and used for recording oil gas production data, acquiring template selection information input by the user, extracting information of a header field in the source table, determining a form of a target template table to be converted by the source table according to the template selection information input by the user, extracting information of the header field of the target template table and drop-down frame configuration, matching the header field of the source table with the header field of the target template table based on the large model, establishing a mapping relation, and utilizing the coding model to migrate data content of all columns of oil gas production data under the header field of the source table to a corresponding position of the target template table according to the drop-down frame configuration contained in the target template table based on the mapping relation.

Inventors

  • JIANG BIN
  • SHI YINLIANG
  • DONG YINTAO
  • LI ZHUOYANG
  • Bian Qingyu

Assignees

  • 中国海洋石油集团有限公司
  • 中海油研究总院有限责任公司

Dates

Publication Date
20260512
Application Date
20260115

Claims (8)

  1. 1. An intelligent meter reading method for oil gas production data of a large model and a coding model is characterized by comprising the following steps: step (1), receiving a source form which is transmitted by a user and is used for recording oil and gas production data, and acquiring template selection information input by the user; Analyzing the source table, and extracting information of a header field in the source table; Step (3), determining the form of a target template form to be converted by the source form according to template selection information input by a user, and extracting the information of the header field of the target template form and the configuration of a drop-down frame; step (4), based on the large model, matching the header field of the source form with the header field of the target template form, and establishing a mapping relation; And (5) based on the mapping relation, migrating the data content of each column of oil gas production data under the table head field in the source table to the corresponding position of the target template table by utilizing the coding model according to the drop-down frame configuration contained in the target template table.
  2. 2. The method according to claim 1, wherein in the step (2), comprising: Reading a table file of a source table uploaded by a user based on a client, and identifying the position of a table head row of the source table file; And processing the merging cells in the multi-level header to generate a complete level header name.
  3. 3. The method according to claim 2, wherein in the step (3), comprising: determining the form of a target template form to be converted of a source form according to template selection information input by a user, reading a form file of the corresponding target template form, and identifying the position of a header line in the form file; processing the merging unit cells in the multi-level header to generate a complete level header name; the extraction template table is provided with a field of a drop-down box and an option list thereof.
  4. 4. A method according to claim 3, characterized in that in said step (4) it comprises: constructing a structured prompt word according to the header matching requirement of the source form and the target template form; calling a large model, extracting and analyzing a returned result; and extracting and checking the dictionary objects of the matching results, and generating a header mapping dictionary of the source table and the target template table.
  5. 5. The method according to claim 4, wherein in the step (5), during the data content migration process, for the fields with the drop-down frame configuration constraints in the target template table, a hybrid matching strategy is adopted to convert and migrate the data content in the corresponding column of the source table, and for the fields without the drop-down frame configuration constraints in the target template table, directly migrate the data content in the corresponding column of the source table.
  6. 6. An oil gas production data intelligent meter reading system of a large model and a coding model is characterized by comprising: a form uploading module for receiving a source form which is transmitted by a user and is used for recording oil and gas production data, The template selection module is used for acquiring template selection information input by a user; the source table analysis module is used for analyzing the source table and extracting the information of the header field in the source table; the template analysis model is used for determining the form of a target template form to be converted by the source form according to template selection information input by a user, and extracting the information of the header field of the target template form and the configuration of a drop-down frame; the header matching module is used for matching the header fields of the source form with the header fields of the target template form based on the large model, and establishing a mapping relation; And the data filling module is used for migrating the data content of each column of oil gas production data under the header field in the source table to the corresponding position of the target template table according to the drop-down frame configuration contained in the target template table by utilizing the coding model based on the mapping relation.
  7. 7. A computer storage medium, characterized in that a computer program is stored, which computer program, when being executed by a processor, implements the method of any of claims 1 to 5.
  8. 8. A computer device comprising a memory storing a computer program and a processor executing the computer program to implement the method of any one of claims 1 to 5.

Description

Oil gas production data intelligent meter reading method based on large model and coding model Technical Field The invention relates to the technical field of oil gas production, in particular to an intelligent meter reading method for oil gas production data based on a large model and a coding model. Background With the continuous progress of technology, oil and gas exploration and development is accelerating to digital transformation. However, the technical evolution also brings new challenges that the oil and gas production data generated by the upstream business has wide sources and various formats. The data tables adopted by different operation units and different periods are quite different in structure and standard, and the data importing efficiency is seriously hindered. The currently commonly adopted fixed template importing mode requires business personnel to manually arrange data strictly according to a preset format, has strict requirements on field sequence, naming standards, dictionary values and the like, is complex in operation and low in fault tolerance, and also has high manual cleaning cost and difficult improvement of efficiency. Disclosure of Invention Aiming at the problems, the invention aims to provide an oil gas production data intelligent meter reading method based on a large model and a coding model, which can automatically identify the header mapping relation between a source table and a standard template, intelligently analyze and match semantic content containing drop-down frame options, realize automatic data migration among tables of different formats, shorten the data import time of a user and greatly improve the efficiency and accuracy of data processing. In order to achieve the above purpose, the present invention adopts the following technical scheme: In a first aspect, the application provides an intelligent meter reading method for oil gas production data of a large model and a coding model, comprising the following steps: step (1), receiving a source form which is transmitted by a user and is used for recording oil and gas production data, and acquiring template selection information input by the user; Analyzing the source table, and extracting information of a header field in the source table; Step (3), determining the form of a target template form to be converted by the source form according to template selection information input by a user, and extracting the information of the header field of the target template form and the configuration of a drop-down frame; step (4), based on the large model, matching the header field of the source form with the header field of the target template form, and establishing a mapping relation; And (5) based on the mapping relation, migrating the data content of each column of oil gas production data under the table head field in the source table to the corresponding position of the target template table by utilizing the coding model according to the drop-down frame configuration contained in the target template table. In one implementation, in the step (2), it includes: Reading a table file of a source table uploaded by a user based on a client, and identifying the position of a table head row of the source table file; And processing the merging cells in the multi-level header to generate a complete level header name. In one implementation, the step (3) includes: determining the form of a target template form to be converted of a source form according to template selection information input by a user, reading a form file of the corresponding target template form, and identifying the position of a header line in the form file; processing the merging unit cells in the multi-level header to generate a complete level header name; the extraction template table is provided with a field of a drop-down box and an option list thereof. In one implementation, in the step (4), it includes: constructing a structured prompt word according to the header matching requirement of the source form and the target template form; calling a large model, extracting and analyzing a returned result; and extracting and checking the dictionary objects of the matching results, and generating a header mapping dictionary of the source table and the target template table. In the step (5), in the process of data content migration, a mixed matching strategy is adopted for fields with drop-down frame configuration constraints in the target template table, so that data content in a corresponding column of the source table is converted and migrated, and for fields without drop-down frame configuration constraints in the target template table, data content in a corresponding column of the source table is directly migrated. Due to the adoption of the technical scheme, the invention has the following advantages: According to the technical scheme, intelligent matching of the header fields can be automatically completed according to the standard template form selected by th