Abstract: As a complex system engineering, open-pit mining has many business categories, complex system structure and complex information logic relationship. In the process of intelligent upgrading and transformation of open-pit mines, many bottleneck problems such as unclear business information logic, unclear production factors, and difficult to implement information application scenarios are unavoidable. Therefore, in order to comprehensively analyze the correlation relation of open-pit mine engineering information and scientifically grasp the production factors of open-pit mine, a method of engineering information logical relation representation based on knowledge graph technology is studied and proposed. Taking Heidaigou open-pit coal mine as the research object and perforating and blasting links (perforation links and blasting links) as the research case, this paper first proposes the idea of constructing knowledge graph framework based on the graph theory, and introduces the core elements, construction process and key technologies of knowledge graph by constructing the information knowledge graph of perforating and blasting links of open-pit mine. The characteristics of engineering information structure and the difficulties of using high value data in the process of open-pit mining are systematically analyzed. Secondly, the simulation and deduction idea of the whole process of perforation and explosion engineering business is proposed, the business types and information correlation of perforation and explosion engineering are sorted out, the ontology structure system of perforation and explosion engineering information is improved, and a knowledge retrieval method of production information based on Cypher language is proposed based on computer science theory. The precise query and retrieval of knowledge of “business relationship, data logic, function realization” of engineering information knowledge in penetration and explosion link is realized. Finally, this paper briefly describes the knowledge graph construction methods and theoretical models such as knowledge acquisition, knowledge fusion and knowledge storage, and proposes an open-pit mine information knowledge inference model through the local feature extraction, feature integration, feature matching and other standardized operations of mine production knowledge, which realizes the knowledge search and knowledge inference of the open-pit mine puncture engineering information. It provides an effective and scientific decision for the production information management and resource integration allocation in the process of intelligent upgrading and transformation of open-pit mines.