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Software outlines for decisions making support in oil and gas engineering

Chesanovskyy Mykola, Kravtsiv Kostiantyn, Protsiuk Volodymyr, Poteriailo Liudmyla

Zeszyty Naukowe. Organizacja i Zarządzanie / Politechnika Śląska

2021

z. 151

81--99

Purpose: The aim of this study is to develop an architecture of enterprise solutions that allow real-time (or simulated) extraction, storage and analysis of parameterized data from high- resolution sensors to more accurately predict the potential course of technological processes in the industry and solving of related logistics tasks. Design/methodology/approach: The development of an integration architecture based on appropriate Web tools for viewing and collaborating on corporate information of the oil and gas industry will allow full operational decision-making on this basis, guided by the values of relevant controlled parameters and imposed on them and the process as a whole relevant constraints in general are the methodological grounds of the research from the theoretical and subject domain scope. The functionality of the artificial intelligence system should be reduced to sending signals to the controller in order to modify the controlled parameters through the appropriate instructions. At the theoretical level, measurement, interpretation and control will take place either on the surface, or on the bore, or in both places at the same time. Findings: There were explored software outlines for making possible the creation of the desired findings for new and better business processes and technological innovations in the domestic gas and oil industries based on intelligent information solutions. As proposed in this study, optimal flexibility and forward performance will only be achieved through the use of the cloud as a platform for tomorrow's technological challenges in the oil and gas industry. Originality/value: The newly developed focus on novel class of increasing domestic business efficiency will generally encourage oil and gas companies to develop their information architecture in the direction of knowledge-based systems and solutions, especially when controlling the drilling of oil and gas wells in terms of incomplete, inaccurate and poorly structured information from sensors.