SUPPORT TOOLS FOR KNOWLEDGE REPOSITORIES IN COMPUTER SYSTEMS OF THE OIL AND GAS INDUSTRY

Abstract

This study examines modern approaches and technologies in the field of creating and managing IT-supported knowledge repositories in the oil and gas industry. The text provides a detailed analysis of the role of information technology in forming effective knowledge management systems that are aimed at enhancing competitiveness and optimizing work processes at enterprises in the oil and gas sector. Particular attention is given to the use of artificial intelligence, machine learning, and other advanced IT solutions for analyzing large volumes of data, automating information processes, and improving decision making. The authors argue that effective knowledge management is critically important for ensuring sustainable development and adapting to changing market conditions in the oil and gas industry. A methodology is presented for creating and using corporate knowledge repositories based on textual components of corporate knowledge, i.e., all types of economically valuable documents in the form of technical reports, internal documentation, and normative regulatory documents. In this case, it is justified that the creation of effectively used corporate knowledge repositories can be achieved by translating original documents into some type of conceptual meta-level format. The resulting meta-documents can be stored in a knowledge repository (knowledge base) and considering the role of enhanced document models, all traditional information search functions (search, retrieval, and response generation) can be directly performed on them. In such a case, it becomes possible to use textual corporate knowledge according to the specific characteristics of their own value, as demonstrated in the general architecture of a prototype system that will be implemented to create and use the knowledge repository of meta-documents by PJSC Ukrnafta with more detailed information about the fundamental blocks of the prototype. Translating user queries into the format of a formal language for knowledge representation will allow generating a query system aimed at confirming their relevance and highlighting the main elements of the content.