PetroKG: Construction and Application of Knowledge Graph in Upstream Area of PetroChina  

作　　者：Xiang-Guang Zhou Ren-Bin Gong Fu-Geng Shi Zhe-Feng Wang 

机构地区：[1]PetroChina Research Institute of Petroleum Exploration and Development,Beijing 100083,China [2]Huawei Technologies,Hangzhou 310007,China

出　　处：《Journal of Computer Science & Technology》2020年第2期368-378,共11页计算机科学技术学报（英文版）

摘　　要：There is a large amount of heterogeneous data distributed in various sources in the upstream of PetroChina. These data can be valuable assets if we can fully use them. Meanwhile, the knowledge graph, as a new emerging technique, provides a way to integrate multi-source heterogeneous data. In this paper, we present one application of the knowledge graph in the upstream of PetroChina. Specifically, we first construct a knowledge graph from both structured and unstructured data with multiple NLP (natural language progressing) methods. Then, we introduce two typical knowledge graph powered applications and show the benefit that the knowledge graph brings to these applications:compared with the traditional machine learning approach, the well log interpretation method powered by knowledge graph shows more than 7.69% improvement of accuracy.

关 键 词：KNOWLEDGE GRAPH NATURAL LANGUAGE processing oil and gas industry 

分 类 号：TP39[自动化与计算机技术—计算机应用技术]