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Automatic Early Detection System of Hydrate Formation in Gas Plumes Based on Cognitive Models. P. 195–203

Версия для печати

Section: Geosciences

UDC

532.546

Authors

Marina Yu. Prakhova*, Andrey N. Krasnov*, Elena A. Khoroshavina*
*Ufa State Petroleum Technological University (Republic of Bashkortostan, Ufa, Russian Federation)

Abstract

The hydrate formation in wells and gas plumes in the development of gas fields is a serious problem. This problem is especially acute in the fields located in the Arctic zone, due to the specific conditions of their operation: low temperatures, laying of plumes in permafrost, etc. The resulting hydrates can lead to emergencies. The non-hydrate operation regime in the Arctic zone is practically impossible; therefore, operative diagnosis of the emergence of hydrate formation is an actual task that can be solved by developing automatic early detection systems. The article considers the main factors affecting the hydrate formation process. The relationship between them can not be described analytically; in addition, we have insufficient quantitative information about these factors. The authors propose to construct detection systems using cognitive maps. The control actions in the developed system are formed on the basis of the results of online measurements of the thermobaric conditions at the beginning and the end of the plume, ambient temperature and dew point temperature of the water, as well as the mass flow rate of the well, gas composition and density, presented by the oilfield technological service. We use the theoretical hydrate formation temperature as a basic criterion for diagnosing the beginning of the hydrate formation process. This parameter is significantly influenced by the change of the gas heat transfer coefficient in the plume to the environment, and a number of other factors (presence of abrasive particles and moisture in the gas, soil condition and terrain relief, availability and condition of snow cover, etc.). As an example, we propose a deterministic cognitive model for correcting the heat transfer coefficient, the use of which makes it possible to calculate the theoretical hydrate formation temperature more accurately and, consequently, to increase the accuracy of methanol dosing.

Keywords

gas plume, gas hydrate, hydrate formation condition, hydrate inhibitor injectability, methanol, cognitive map, gas heat transfer coefficient
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