LAPSE:2024.1941
Published Article

LAPSE:2024.1941
Construction Method and Practical Application of Oil and Gas Field Surface Engineering Case Database Based on Knowledge Graph
August 28, 2024
Abstract
To address the challenge of quickly and efficiently accessing relevant management experience for a wide range of ground engineering construction projects, supporting project management with information technology is crucial. This includes the establishment of a case database and an application platform for intelligent search and recommendations. The article leverages Optical Character Recognition (OCR) technology, knowledge graph technology, and Natural Language Processing (NLP) technology. It explores the mechanisms for classifying construction cases, methods for constructing a case database, structuring case data, intelligently retrieving and matching cases, and intelligent recommendation methods. This research forms a complete, feasible, and scalable method for deconstructing, storing, intelligently retrieving, and recommending construction cases, providing a theoretical basis for the establishment of a construction case database. It aims to meet the needs of digital project management and intelligent decision-making support in the oil and gas sector, thereby enhancing the efficiency and accuracy of project construction. This work offers a theoretical foundation for the development of an intelligent management platform for ground engineering projects in the oil and gas industry, supporting the sector’s digital transformation and intelligent development.
To address the challenge of quickly and efficiently accessing relevant management experience for a wide range of ground engineering construction projects, supporting project management with information technology is crucial. This includes the establishment of a case database and an application platform for intelligent search and recommendations. The article leverages Optical Character Recognition (OCR) technology, knowledge graph technology, and Natural Language Processing (NLP) technology. It explores the mechanisms for classifying construction cases, methods for constructing a case database, structuring case data, intelligently retrieving and matching cases, and intelligent recommendation methods. This research forms a complete, feasible, and scalable method for deconstructing, storing, intelligently retrieving, and recommending construction cases, providing a theoretical basis for the establishment of a construction case database. It aims to meet the needs of digital project management and intelligent decision-making support in the oil and gas sector, thereby enhancing the efficiency and accuracy of project construction. This work offers a theoretical foundation for the development of an intelligent management platform for ground engineering projects in the oil and gas industry, supporting the sector’s digital transformation and intelligent development.
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Keywords
decision-making assistance, engineering construction cases, intelligent push, intelligent retrieval, knowledge graph technology
Subject
Suggested Citation
Xia T, Dai Z, Zhang Y, Wang F, Zhang W, Xu L, Zhou D, Zhou J. Construction Method and Practical Application of Oil and Gas Field Surface Engineering Case Database Based on Knowledge Graph. (2024). LAPSE:2024.1941
Author Affiliations
Xia T: Natural Gas Gathering and Transmission Engineering Technology Research Institute, PetroChina Southwest Oil and Gas Field Company, Chengdu 610041, China
Dai Z: Natural Gas Gathering and Transmission Engineering Technology Research Institute, PetroChina Southwest Oil and Gas Field Company, Chengdu 610041, China
Zhang Y: Infrastructure Construction Engineering Department, PetroChina Southwest Oil and Gas Field Company, Chengdu 610066, China
Wang F: Natural Gas Gathering and Transmission Engineering Technology Research Institute, PetroChina Southwest Oil and Gas Field Company, Chengdu 610041, China
Zhang W: Natural Gas Gathering and Transmission Engineering Technology Research Institute, PetroChina Southwest Oil and Gas Field Company, Chengdu 610041, China
Xu L: Natural Gas Gathering and Transmission Engineering Technology Research Institute, PetroChina Southwest Oil and Gas Field Company, Chengdu 610041, China
Zhou D: School of Intelligent Manufacturing, Panzhihua College, Panzhihua 617000, China
Zhou J: Petroleum Engineering School, Southwest Petroleum University, Chengdu 610500, China
Dai Z: Natural Gas Gathering and Transmission Engineering Technology Research Institute, PetroChina Southwest Oil and Gas Field Company, Chengdu 610041, China
Zhang Y: Infrastructure Construction Engineering Department, PetroChina Southwest Oil and Gas Field Company, Chengdu 610066, China
Wang F: Natural Gas Gathering and Transmission Engineering Technology Research Institute, PetroChina Southwest Oil and Gas Field Company, Chengdu 610041, China
Zhang W: Natural Gas Gathering and Transmission Engineering Technology Research Institute, PetroChina Southwest Oil and Gas Field Company, Chengdu 610041, China
Xu L: Natural Gas Gathering and Transmission Engineering Technology Research Institute, PetroChina Southwest Oil and Gas Field Company, Chengdu 610041, China
Zhou D: School of Intelligent Manufacturing, Panzhihua College, Panzhihua 617000, China
Zhou J: Petroleum Engineering School, Southwest Petroleum University, Chengdu 610500, China
Journal Name
Processes
Volume
12
Issue
6
First Page
1088
Year
2024
Publication Date
2024-05-25
ISSN
2227-9717
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Original Submission
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PII: pr12061088, Publication Type: Journal Article
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LAPSE:2024.1941
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https://doi.org/10.3390/pr12061088
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[v1] (Original Submission)
Aug 28, 2024
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Aug 28, 2024
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