A.A. Lyubitskiy. SIMULATION MODEL OF SOUND BACKSCATTERING IN GAS FLARES

https://doi.org/10.15407/gpimo2022.04.053

A.A. Lyubitskiy, Researcher, Senior member IEEE
e-mail: a.lubitckiy@gmail.com
ORCID 0000-0001-7375-1364
O.Ya. Usikov Institute for Radiophysics and Electronics of NAS of Ukraine
12, Proskura Str. , Kharkiv, 61085, Ukraine

A.V. Omelchenko, Candidate of Technical Sciences, Associate Professor
e-mail: omela5656@gmail.com
ORCID 0000-0002-2338-6706
Kharkiv National University of Radio Electronics
14, Nauky Ave., Kharkiv, 61166, Ukraine

SIMULATION MODEL OF SOUND BACKSCATTERING IN GAS FLARES AND EVALUATION OF THE POTENTIAL ACCURACY OF DETERMINING SEEP COORDINATES BY SPLIT-BEAM ECHOSOUNDERS

A simulation model of sound backscattering in gas flares is presented, designed to solve direct and inverse problems of acoustic sensing of flares using the simulation (computer) modeling method. The model is based on the concept of the discrete character of sound scattering in a gas plume, according to which the received echo signal is the sum of elementary signals, backward-scattered bubbles that form the flare. At the same time, the model of sound reverberation in a gas flare is considered as a temporary random process in the absence of multiple scattering effects. The model takes into account the distributions of gas bubbles by sizes and rise velocities, as well as the evolution of bubbles and their gas exchange with the marine environment during ascent. Based on this, the potential accuracy of deter- mining the coordinates of gaseous sources (seeps) by a split-beam echo sounder was estimated by simulation modeling. It has been established that the main parameters that determine the RMS (root- mean-square deviations) of the estimates from the actual coordinates are the transverse size of the flare near the bottom, the SNR (signal-to-noise ratio), and the volume of echo signal samples. Dependences of the RMS on the determining parameters are obtained.

Keywords: gas flares, acoustic sensing, backscattering of sound, simulation modeling.

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