Acoustic and optical determination of bubble size distributions – Quantification of seabed gas emissions

Li, Jianghui; White, P.R.; Roche, Ben; Bull, Jonathan M.; Leighton, Timothy G.; Davis, J.W.; Fone, Joseph

doi:10.1016/j.ijggc.2021.103313

Cited by 28 publications

(13 citation statements)

References 42 publications

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“…Chronological metadata series were used to analyze the magnitude modulation along time and thus provide a relative estimation of the flares flow rate changes. For weaker and intermittent or impulsive energy events, once visually recognized, the relative segments were analyzed using a shorttime Fourier transform and a threshold algorithm was implemented following Peregrine, 1994 andLi et al, 2021 in order to identify and count bubbles events, obtaining a bubble size distribution for each deployment. The power spectrum analysis, performed on the acoustic records, revealed that the areas surrounding the observatory deployment sites radiated significant acoustic energy at a wide frequency band, apart from the ones of the typical ambient noise, as depicted by Figure 3, where PSD representative of the entire month of June is shown.…”

Section: Spectral Data Extrapolationmentioning

confidence: 99%

“…A time-frequency approach to discriminate between bubble sound emission and noise can be implemented. We took into account what was already proposed and successfully used by Li et al (2021) and implemented a single bubble identification method based upon bubble characteristics recognition, that includes pulsation time interval, frequency bandwidth and energy strength. As the signature of a bubble is a transient event with an exponentially decaying coda, each discrete time series of the acquired acoustic record was firstly divided into 75% overlapping segments, where the length of each one was chosen in order to approximately match the average duration of the bubble signature and simultaneously guarantee a suitable frequency resolution.…”

Section: Acoustical Bubble Identification and Thresholding Algorithmmentioning

confidence: 99%

“…As a rough generalization, the value holds up to within about 50% of its surface value down to a depth of about 100 m. Having Q expressed, it is possible to roughly estimate the typical duration in ∼5ms for methane bubbles having resonance frequency centered at 1 kHz at a depth of 120 m. Thus, once Fourier parameters were determined, the thresholding technique was applied in order to identify spectral peaks above a certain energy threshold Th E . After the peaks have been identified, all adjacent peaks were collected in a vector, and the difference between the minimum and the maximum frequency constituting the vector were compared with a bandwidth threshold Th band (detailed algorithm conceptualization can be found in Li et al, 2021). If the resulting difference exceeds the bandwidth threshold, the sound event is recognised as a bubble signal, excluded otherwise.…”

Section: Acoustical Bubble Identification and Thresholding Algorithmmentioning

confidence: 99%

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Black Sea Methane Flares From the Seafloor: Tracking Outgassing by Using Passive Acoustics

et al. 2021

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The Black Sea bottom is well known to be earth’s largest anaerobic methane source, hosting a huge amount of cold seeps releasing significant volumes of methane of both thermogenic and biogenic origin. Taking into account the well-known effects of methane concerning global warming, including the warming up of the oceans, an effective monitoring of its output from the Black Sea is nowadays an essential target for interdisciplinary studies. We discuss the results achieved during monitoring campaigns aimed to detect and track methane flares from the seafloor of the Romanian sector of the Black Sea, in order to better constrain the possible mechanisms responsible for its injection from the marine sediments, through the water column, into the atmosphere. In the mainframe of the ENVRI-Plus project, we deployed a multidisciplinary seafloor observatory for short, mid and long time monitoring and collected samples of the water column. The multidisciplinary seafloor observatory was equipped with probes for passive acoustic signals, dissolved CH4 and chemical-physical parameters. The collected data showed a high concentration of dissolved methane up to values of 5.8 micromol/L. Passive acoustics data in the frequencies range 40–2,500 Hz allow us to discriminate different degassing mechanisms and degassing styles. The acoustic energy associated with gas bubbling is interpreted as a consequence of the gas dynamics along the water column while the acoustic range 2–20 Hz reveals vibration mechanisms generated by gas dynamic’s along the cracks and inside the sediments.

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Section: Spectral Data Extrapolationmentioning

confidence: 99%

Section: Acoustical Bubble Identification and Thresholding Algorithmmentioning

confidence: 99%

Section: Acoustical Bubble Identification and Thresholding Algorithmmentioning

confidence: 99%

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Black Sea Methane Flares From the Seafloor: Tracking Outgassing by Using Passive Acoustics

et al. 2021

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“…Passive acoustic sensors, or hydrophones, can be used to detect the presence of bubbles based on their acoustic emissions [18]. Several studies demonstrate the capability to quantify bubble seepage using passive acoustic sensors [38,39], although further studies are encouraged to investigate the accuracy of these estimates. The detection range depends on the background noise level, leak rate, and sensitivity of the sensor.…”

Section: Acoustic Sensorsmentioning

confidence: 99%

Marine Monitoring for Offshore Geological Carbon Storage—A Review of Strategies, Technologies and Trends

et al. 2021

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Carbon capture and storage (CCS) could significantly contribute to reducing greenhouse gas emissions and reaching international climate goals. In this process, CO2 is captured and injected into geological formations for permanent storage. The injected plume and its migration within the reservoir is carefully monitored, using geophysical methods. While it is considered unlikely that the injected CO2 should escape the reservoir and reach the marine environment, marine monitoring is required to verify that there are no indications of leakage, and to detect and quantify leakage if it should occur. Marine monitoring is challenging because of the considerable area to be covered, the limited spatial and temporal extent of a potential leakage event, and the considerable natural variability in the marine environment. In this review, we summarize marine monitoring strategies developed to ensure adequate monitoring of the marine environment without introducing prohibitive costs. We also provide an overview of the many different technologies applicable to different aspects of marine monitoring of geologically stored carbon. Finally, we identify remaining knowledge gaps and indicate expected directions for future research.

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“…Rodrigues and Rubio [9] classified them into intrusive and nonintrusive methods. The intrusive methods include electroresistivity [43][44][45][46], ultrasound reflection [47][48][49][50][51], and optical techniques [52][53][54][55][56][57][58], which inevitably cause instrumented interference on bubble samples. In comparison to those approaches, the imaging technique as a nonintrusive method has been primarily adopted for both academic and industry bubble size measurement due to lower cost and ease of operation [5,9,15,16,28,30,59].…”

Section: Introductionmentioning

confidence: 99%

Applying Imaging Technique to Investigate Effects of Solute Concentrations and Gas Injection Rates on Gas Bubble Generation

Yan

Cheng

et al. 2022

Geofluids

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This work investigated the bubble size variation under various aqueous conditions, including saline and surfactant solutions, with different gas injection rates using a commercial bubble analyzer. The results show that salt and surfactant can minimize bubble size with increasing solute concentration, and the surfactant outperforms salt. In addition, the critical coalescence concentrations (CCC) of salt and surfactant could be determined at 20 g/l and 20 mg/l, respectively, over which bubble mean size cannot be further reduced. On the other hand, the gas injection rate, compared to the solute concentration, has minor effects on bubble size variation. Nonetheless, there is a critical coalescence injection rate (CCIR) of 30 ml/min for surfactant solution, over which the standard deviation of the bubble size distribution (BSD) cannot be further increased. In principle, this work improves the accuracy and efficiency of the bubble analyzer. It also presents a sound understanding of two influential factors rather than a single-factor controlling bubble size. Most importantly, it is the first time to observe and propose the concept of CCIR to describe how the gas injection rate influences the standard deviation of BSD. Based on those results and findings, it is able to conclude that bubble size control, whose mechanism has been previously identified as the bubble collision and coalescence rather than the surface tension of water solutions, is actually dominated by not only the solute concentration but also the gas injection rate when a porous air sparger is used to generate bubbles. It is expected that this work could contribute to laboratory modeling bubbly flow in a porous medium in order to bring more insights into the mechanism of soil gas leaking through soil strata.

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Acoustic and optical determination of bubble size distributions – Quantification of seabed gas emissions

Cited by 28 publications

References 42 publications

Black Sea Methane Flares From the Seafloor: Tracking Outgassing by Using Passive Acoustics

Black Sea Methane Flares From the Seafloor: Tracking Outgassing by Using Passive Acoustics

Marine Monitoring for Offshore Geological Carbon Storage—A Review of Strategies, Technologies and Trends

Applying Imaging Technique to Investigate Effects of Solute Concentrations and Gas Injection Rates on Gas Bubble Generation

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