Cognitive model application for automatic system of methanol supply to flowlines

Innovations and Prospects of Development of Mining Machinery and Electrical Engineering

矿业工程;电工学

Prakhova, M. Yu^1 ; Khoroshavina, E.A.^1 ; Krasnov, A.N.^1 ; Zakirnichnaya, M.M.^1

Ufa State Petroleum Technological University, 1, Kosmonavtov Av., Ufa

450062, Russia^1

关键词: Automatic systems;    Central processing facilities;    Current parameters;    Gas-condensate fields;    Natural gas extraction;    Production fields;    Real time analysis;    Temperature and pressures;   

Others  :  https://iopscience.iop.org/article/10.1088/1755-1315/87/5/052023/pdf
DOI  :  10.1088/1755-1315/87/5/052023

来源: IOP

【 摘 要 】

The main problem during natural gas extraction is hydrating risk. The hydrates could be formed at every stage of extraction: from gas foundation to Central Processing Facility (CPF). The hydrating is quite unwanted process, because it decreases the efficiency of field operations and causes accidents. The process operating procedure of any production field provides some measures to prevent hydrating. Mostly different hydrate growth inhibitors are used to prevent hydrating, for example methanol or water-methanol solution. At this time the most important problem is evaluation of the optimal methanol flow rate or water-methanol solution concentration for current conditions. The cognitive model application for hydrating diagnosis is discussed in the article. It is based on real time analysis of head temperature and pressure, temperature and pressure in the entrance of the CPF and ambient temperature. In this case, current parameters and their dynamic are analyzed. The hydrating conditions are diagnosed by the algorithm, offered in this article. This algorithm includes the results of temperature and pressure dynamic analysis and the cognitive model, based on expert knowledge. This system was tested in the Yamburg gas condensate field. These tests approved real methanol saving.