An Experimental Setup to Measure Argon Leak Rate Through Barriers for Static and Rotational Motion

Abstract

As a greenhouse gas, methane significantly impacts global warming and air pollution. Oil and gas production, crude oil transportation, refining, and natural gas processing, transportation, and distribution are considered the main sources of methane emission in the oil and gas industry. Specifically, valves, joints, and moving parts where barriers were used have a magnificent role in methane emission. To address this problem, International Standard Organization(ISO) through ISO 15848 suggested that the oil and gas industry test the fugitive emission on their products with helium as a testing gas. Although, helium is an inert gas and its specifications make it an ideal gas for emission tests in the oil and gas industry, difficulty in production, transportation, high price, and global helium shortage lead us to find an alternative material. In this study, a setup was built to test argon emission in 25C, 121C, and 204C and pressure ranges of 600, 2250, 3750, 6750, and 10,000 psi on v-rings for static and rotational shafts with 2 rpm and 10 rpm. Experimental results were used to generate a machine learning model. Finally, a general polynomial formula was presented based on the machine learning model for static and rotational shafts with 2 rpm and 10 rpm. Results show the impact of temperature and rotational shaft’s speed on leak rate is significant. This study’s results apply to the valve, compressors, and any dynamic seal test process. Generally, the applications of this study can be to reduce the cost of the production and leak rate tests in rotational equipment design for the oil and gas industry.