| PetroKG: Construction and Application of Knowledge Graph in Upstream Area of PetroChina |
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| 作者姓名： | Xiang-Guang Zhou Ren-Bin Gong Fu-Geng Shi Zhe-Feng Wang |
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| 作者单位： | PetroChina Research Institute of Petroleum Exploration and Development;Huawei Technologies |
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| 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.
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| 关 键 词： | KNOWLEDGE GRAPH natural LANGUAGE processing oil and gas INDUSTRY |
| 收稿时间： | 2019-08-20 |
PetroKG: Construction and Application of Knowledge Graph in Upstream Area of PetroChina |
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| Xiang-Guang Zhou,Ren-Bin Gong,Fu-Geng Shi,Zhe-Feng Wang.PetroKG: Construction and Application of Knowledge Graph in Upstream Area of PetroChina[J].Journal of Computer Science and Technology,2020,35(2):368-378. |
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| Authors: | Xiang-Guang Zhou Ren-Bin Gong Fu-Geng Shi Zhe-Feng Wang |
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| Affiliation: | 1.PetroChina Research Institute of Petroleum Exploration and Development, Beijing 100083, China;2.Huawei Technologies, Hangzhou 310007, China |
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| Abstract: | 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. |
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| Keywords: | knowledge graph natural language processing oil and gas industry |
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