Can acoustic emissions be used to size bubbles seeping from a sediment bed?

A noise robust sparse time-frequency representation method for measuring underwater gas leakage rate

Passive acoustic monitors analyze sound signals emitted by seafloor gas bubbles to measure leakage rates. In scenarios with low-flux gas leaks, individual bubble sounds are typically non-overlapping. Measurement methods for these bubble streams aim to estimate the frequency peak of each bubble sound, which correlates with the bubble's size. However, the presence of ocean ambient noise poses challenges to accurately estimating these frequency peaks, thereby affecting the measurement of gas leakage rates in shallow sea environments using passive acoustic monitors. To address this issue, we propose a robust measurement method that includes a noise-robust sparse time-frequency representation algorithm and an adaptive thresholding approach for detecting bubble frequencies. We demonstrate the effectiveness of our proposed method using experimental data augmented with ocean ambient noise and ship-transit noise recorded from a bay area.

Monitoring underwater volcano degassing using fiber-optic sensing

Continuous monitoring of volcanic gas emissions is crucial for understanding volcanic activity and potential eruptions. However, emissions of volcanic gases underwater are infrequently studied or quantified. This study explores the potential of Distributed Acoustic Sensing (DAS) technology to monitor underwater volcanic degassing. DAS converts fiber-optic cables into high-resolution vibration recording arrays, providing measurements at unprecedented spatio-temporal resolution. We conducted an experiment at Laacher See volcano in Germany, immersing a fiber-optic cable in the lake and interrogating it with a DAS system. We detected and analyzed numerous acoustic signals that we associated with bubble emissions in different lake areas. Three types of text-book bubbles exhibiting characteristic waveforms are all found from our detections, indicating different nucleation processes and bubble sizes. Using clustering algorithms, we classified bubble events into four distinct clusters based on their temporal and spectral characteristics. The temporal distribution of the events provided insights into the evolution of gas seepage patterns. This technology has the potential to revolutionize underwater degassing monitoring and provide valuable information for studying volcanic processes and estimating gas emissions. Furthermore, DAS can be applied to other applications, such as monitoring underwater carbon capture and storage operations or methane leaks associated with climate change.

Gas Migration Episodes Observed During Peridotite Alteration in the Samail Ophiolite, Oman

Serpentinization and carbonation of mantle rocks (peridotite alteration) are fundamentally important processes for a spectrum of geoscience topics, including arc volcanism, earthquake processes, chemosynthetic biological communities, and carbon sequestration. Data from a hydrophone array deployed in the Multi-Borehole Observatory (MBO) of the Oman Drilling Project demonstrates that free gas generated by peridotite alteration and/or microbial activity migrates through the formation in discrete bursts of activity. We detected several, minutes-long, swarms of gas discharge into Hole BA1B of the MBO over the course of a 9 month observation interval. The episodic nature of the migration events indicates that free gas accumulates in the permeable flow network, is pressurized, and discharges rapidly into the borehole when a critical pressure, likely associated with a capillary barrier at a flow constriction, is reached. Our observations reveal a dynamic mode of fluid migration during serpentinization, and highlight the important role that free gas can play in modulating pore pressure, fluid flow, and alteration kinetics during peridotite weathering.

Methods of acoustic gas flux inversion-Investigation into the initial amplitude of bubble excitation

Passive acoustic inversion techniques for measuring gas flux into the water column have the potential to be a powerful tool for the long-term monitoring and quantification of natural marine seeps and anthropogenic emissions. Prior inversion techniques have had limited precision due to lack of constraints on the initial amplitude of a bubble's excitation following its release into the water column ( _R). _R is determined by observing the acoustic signal of bubbles released from sediment in a controlled experiment and its use is demonstrated by quantifying the flux from a volcanic CO₂ seep offshore Panarea (Italy), improving the precision by 78%.

Analysis of sound pressure levels generated by nozzle-emitted large bubbles

The sound radiated by newly formed bubbles can be used to determine their properties. However, details of the fluid dynamics driving the acoustic emission remain unclear. A neck-collapsing model has been proposed to explain the sound generation at bubble pinch-off. The model uses a forcing function which drives the Rayleigh-Plesset equation and is linked to the bubble acoustic pressure. Here, the model is tested on bubbles of diameter up to 7 mm generated in distilled water, tap water, and alcohol-water solution. The model works well for bubbles less than 2.2 mm radius but the error increases up to 71% for larger diameters.

The influence of water hardness perturbations on bubble departure dynamics

The influence of small changes to water hardness on the nonlinear behaviour of liquid penetration into a capillary and the resulting air pressure fluctuations during air bubble formation are examined in this paper. Experiments were undertaken in which bubbles were generated both in water having a surface tensile force of σ = 72.2 mN/m and in an aqueous solution of calcium carbonate having a surface tensile force of σ = 75.4 mN/m, each contained in a glass capillary with an internal diameter of 1 mm. It is shown that both the maximum value of liquid penetration into the capillary and bubble growth time are affected by perturbations to the water hardness. The time it takes for the bubble to depart the capillary was estimated using the following nonlinear data analysis methods: time delay (τ), attractor reconstructions, correlation dimension (D), and largest Lyapunov exponent (λ). All estimates demonstrate that the pressure fluctuations in the c–c aqueous solutions and extent of liquid solution penetration into the capillary during the time between subsequent bubble departures behave chaotically. Furthermore, this work demonstrates that the dynamics of bubble formation along with the bubble waiting time are very sensitive to small perturbation in the physical properties of the liquid, and this sensitivity has a significant effect on the observed chaotic behaviour.

Extraction of bubble size and number data from an acoustically-excited bubble chain

The passive-acoustic measurement of bubbly flows could potentially deliver data useful to many industrial and environmental applications. However, acoustic interactions between bubbles complicate interpretations of measured frequencies in terms of the bubble sizes that are of practical interest. Experiments were undertaken on the emissions of a bubble chain when a just-formed bubble at one end of the chain created a sound pulse. This is an idealised paradigm for many applications. The chain was a one-dimensional line of bubbles fixed with known bubble sizes and inter-bubble spacings. Frequencies naturally emitted by the chain were measured for various bubble sizes and spacings, including cases such that the bubbles were close to touching. Semi-empirical fits were found relating the bubble size and number to the lowest and highest-measurable peak frequencies. It was found that all data collapsed onto two curves, one for the lowest-peak and one for the highest-peak frequency. This was confirmed by running numerical simulations for wider ranges of parameters than available experimentally. The results suggest that for a bubble chain, measurements of two peak frequencies could be used to determine the bubble size and also the number of interacting bubbles.