Attenuation Characteristics of Ultrasonic Waves From Sonar Logging Tools in Salt Cavern Gas Storage
Year: 2024
Type: article
Abstract: The sonar detection of salt cavern gas storage (SCGS) has a low accuracy due to sound wave attenuation. To solve the problem, this paper analyzes the attenuation features of sound waves in SCGS, based on the mechanical wave equation and Urick sound wave attenuation theory, as well as expression of sound velocity in dilute solution and the general empirical formula of solution density. Specifically, three attenuation forms of sound waves in dilute solutions with different concentrations were studied, and a theoretical model for the total attenuation of sound waves in SCGS was established. The model was adopted to explore the effect of solution temperature and concentration on sound wave attenuation. The results yield some interesting findings. It is shown that the temperature has a small overall effect on the attenuation of sound waves. Also, the total attenuation coefficient of sound waves in suspensions with different concentrations increases with the frequency of the sound waves. Furthermore, when the frequency of the sound waves remains unchanged, the total attenuation coefficient increases with the concentration of the suspension. Finally, when the solution concentration is less than 10%, the total attenuation coefficient of the sound waves depends on scattering attenuation, and the sound wave attenuation is not greatly affected by the viscous attenuation and thermal attenuation. Four salt solutions were tested to verify the correctness of the theoretical research. The experimental results show that, in the SCGS environment, the salt solutions are ranked in a descending order of the influence over sonar detection accuracy starting from potassium chloride solution, via magnesium sulfates solution and calcium chloride solution to sodium chloride solution. The research provides a strong theoretical guidance for sonar detection of SCGS, and a powerful engineering reference for sonar detection in brine.
Authors: Hai-Yan Yang, Yu Wang, Sen-Lin Liu, Qing Tu, Gang Chen
Institutions: Xihua University, Chengdu Technological University
Language: English
Subfield: Mechanics of Materials
Field: Engineering
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W4406119577