[1]尚福华,徐凡钧,曹茂俊.测井处理解释领域知识图谱构建方法研究[J].计算机技术与发展,2022,32(12):206-212.[doi:10. 3969 / j. issn. 1673-629X. 2022. 12. 031]
　SHANG Fu-hua,XU Fan-jun,CAO Mao-jun.Research on Knowledge Graph Construction for Logging Process and Interpretation Domain[J].,2022,32(12):206-212.[doi:10. 3969 / j. issn. 1673-629X. 2022. 12. 031]
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测井处理解释领域知识图谱构建方法研究()
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《计算机技术与发展》[ISSN:1006-6977/CN:61-1281/TN]

卷:
32
期数:
2022年12期
页码:
206-212
栏目:
新型计算应用系统
出版日期:
2022-12-10

文章信息/Info

Title:
Research on Knowledge Graph Construction for Logging Process and Interpretation Domain
文章编号:
1673-629X(2022)12-0206-07
作者:
尚福华; 徐凡钧; 曹茂俊
东北石油大学 计算机与信息技术学院,黑龙江 大庆 163318
Author(s):
SHANG Fu-hua; XU Fan-jun; CAO Mao-jun
School of Computer and Information Technology,Northeast Petroleum University,Daqing 163318,China
关键词:
测井处理解释; 测井领域知识; 知识图谱; 知识抽取; 图数据库
Keywords:
logging process and interpretation; logging domain knowledge; knowledge graph; knowledge extraction; graph database
分类号:
TP301
DOI:
10. 3969 / j. issn. 1673-629X. 2022. 12. 031
摘要:
为了解决测井处理解释领域数据存储分散、信息共享困难和数据间缺乏良好管理与组织的问题,进一步提高测井解释知识的利用率和共享程度,在研究测井处理解释业务流程基础上引入知识图谱技术,提出了一种测井处理解释领域知识图谱的构建方法。 以测井处理解释为核心,结合测井解释领域知识特点,重点对测井处理解释的业务流程进行研究分析。 以知识图谱的构建为主体,通过知识抽取、知识融合和知识推理等技术,将测井处理解释领域中分散、隐形、不规范状态的大量知识和经验进行梳理,构建了测井处理解释领域知识图谱。 并采用混合构建方式,结合信息抽取和知识融合等关键技术完成了测井处理解释领域知识图谱的构建,在 Neo4j 图数据库中进行存储并对其进行可视化展示。 该方法将知识图谱与测井处理解释流程紧密联系,为测井处理解释领域知识图谱构建提供了一种新思路。
Abstract:
In order to solve the problems of scattered data storage,difficulty in information sharing and lack of good management and organization between data in the field of logging processing and interpretation,and further improve the utilization rate and sharing degree oflogging interpretation knowledge,we introduce knowledge graph technology based on study of the business process of logging processingand interpretation and propose a method for constructing knowledge graph in the field of logging processing and interpretation. Takinglogging processing and interpretation as the core,combined with the characteristics of knowledge in the field of logging interpretation,wefocus on the research and analysis of the business process of logging processing and interpretation. With the construction of knowledgegraph as the main body,using knowledge extraction,knowledge fusion and knowledge reasoning and other related technologies,a largeamount of knowledge and experience of scattered,invisible and irregular states in the interpretation field are sorted out,and a knowledgegraph of logging processing and interpretation field is constructed. The construction of the knowledge graph in the field of loggingprocessing and interpretation is completed by the hybrid construction method, combined with key technologies such as knowledgeextraction and knowledge fusion,which are stored in the Neo4j graph database and displayed visually. This method closely links theknowledge graph with the logging processing and interpretation process,and provides a new idea for the construction of knowledge graphsin the field of logging processing and interpretation.

相似文献/References:

[1]尚福华,卢玉莹,曹茂俊.基于改进 LSTM 神经网络的测井曲线重构方法[J].计算机技术与发展,2022,32(06):198.[doi:10. 3969 / j. issn. 1673-629X. 2022. 06. 033]
　SHANG Fu-hua,LU Yu-ying,CAO Mao-jun.Well Logging Curve Reconstruction Method Based on Improved LSTM Neural Network[J].,2022,32(12):198.[doi:10. 3969 / j. issn. 1673-629X. 2022. 06. 033]

更新日期/Last Update: 2022-12-10