Abstract:
The U.S. outer continental shelf is a major source of energy for the United States. The rapid growth of oil and gas production in the Gulf of Mexico increases the risk of underwater oil spills at greater water depths and drilling wells. These hydrocarbons leakages can be caused by either natural events, such as seeping from fissures in the ocean seabed, or by anthropogenic accidents, such as leaking from broken wellheads and pipelines. In order to improve safety and reduce the environmental risks of offshore oil and gas operations, the Bureau of Safety and Environmental Enforcement (BSEE) recommended the use of real-time monitoring. An early warning system for detecting, locating, and characterizing hydrocarbon leakages is essential for preventing the next oil spill as well as for seafloor hydrocarbon seepage detection. Existing monitoring techniques have significant limitations and cannot achieve real-time monitoring. This project launches an effort to develop a functional real-time monitoring system that uses passive acoustic technologies to detect, locate, and characterize undersea hydrocarbon leakages over large areas in a cost-effective manner.
In an oil spill event, the leaked hydrocarbon is injected into seawater with huge amounts of discharge at high speeds. With mixed natural gases and oils, this hydrocarbon leakage creates underwater sound through two major mechanisms: shearing and turbulence by a streaming jet of oil droplets and gas bubbles, and bubble oscillation and collapse. These acoustic emissions can be recorded by hydrophones in the water column at far distances. They will be characterized and differentiated from other underwater noises through their unique frequency spectrum, evolution and transportation processes and leaking positions, and further, be utilized to detect and position the leakage locations.
With the objective of leakage detection and localization, our approach consisted of recording and modeling the acoustic signals induced by the oil spill and implementing advanced signal processing and triangulation localization techniques with a hydrophone network.
Tasks of this project were:
1. Conduct a laboratory study to simulate hydrocarbon leakages and their induced sound under controlled conditions, and to establish the correlation between frequency spectra and leakage properties, such as oil-jet intensities and speeds, bubble radii and distributions, and crack sizes.
2. Implement and develop acoustic bubble modeling for estimating features and strength of the oil leakage.
3. Develop a set of advanced signal processing and triangulation algorithms for leakage detection and localization.
The experimental data have been collected in a water tank in the building of the National Center for Physical Acoustics, the University of Mississippi from 2018-2020, including hydrophone recorded underwater sounds generated by oil leakage bubbles under different testing conditions, such as pressures, flow rates, jet velocities, and crack sizes, and movies of oil leakages. Two types of oil leakages (a few bubbles and constant flow bubbles) were tested to simulate oil seepages either from seafloors or from oil well and pipeline breaches. Two types of gases were investigated (nitrogen and methane). These data were analyzed for acoustic bubble modeling, oil leakage characterization, and localization.
This dataset contains data for oil leakage source localization. Two localization algorithms were developed: TDOA-based and SpectraRatio-based algorithms. The folders of the dataset are described as follows:
• the folders of “Signals” contain raw underwater sounds data used for localization
• the folders of “Results” contain the results of true and predicted oil leakage source positions
More details of this dataset can be found in the corresponding ReadMe files in each folder.
Suggested Citation:
Cao, Lei and Xyang Xing. 2021. Passive acoustic technology to detect, locate, and characterize undersea hydrocarbon leaks. Distributed by: GRIIDC, Harte Research Institute, Texas A&M University–Corpus Christi. doi:10.7266/4S9EBZKX
Data Parameters and Units:
Headers include: Sources (S1, S2, S3, S4); Signal Type (Electric/Bubble); True Location (cm); Estimated Location (cm) (LLSE/NLS); and RMSE (cm) (LLSE/NLS).
Methods:
The experimental data have been collected in a water tank in the building of the National Center for Physical Acoustics, the University of Mississippi from 2018-2020, including hydrophone recorded underwater sounds generated by oil leakage bubbles under different testing conditions, such as pressures, flow rates, jet velocities, and crack sizes, and movies of oil leakages. Two types of oil leakages (a few bubbles and constant flow bubbles) were tested to simulate oil seepages either from seafloors or from oil well and pipeline breaches. Two types of gases were investigated (nitrogen and methane). These data were analyzed for localization.
This dataset contains data for oil leakage source localization. Two localization algorithms were developed: TDOA-based and SpectraRatio-based algorithms.
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