Hydroacoustic and geochemical traces of marine gas seepage in the North Sea

Methane is the second most important anthropogenic greenhouse gas on Earth and contributes considerably to global radiative forcing. The last IPCC assessment report 2007 assigns geological methane emissions as a significant source. This thesis therefore concentrates on the quantity and atmospheric implications of methane emissions from the seabed of the North Sea. Sampling of marine seepage is challenging compared to readily accessible terrestrial sites; thus marine seepage sites have scarcely been observed or even yet discovered. Moreover, in terms of atmospheric contribution, the fate of methane after ebullition into the water column is usually not considered. Hydroacoustic systems have proven to be very efficient remote sensing tools for gas seepage analysis even in water depth greater than 2000 m. Technical progress led to much higher remote sensing potential by means of modern multibeam applications for gas bubbles detection in the water column. However, to be effective, these novel multibeam systems require new methods for data analysis. This thesis firstly demonstrates the application of multibeam systems as efficient gas bubble remote sensing tools. Therefore an anthropogenic blowout site was mapped using a multibeam sonar. The advantage of multibeam technology compared to singlebeam is increased efficiency due to larger coverage than singlebeam systems, three dimensional plume mapping, and exact localization of gas sources. Moreover the deployment of the multibeam prototype GasQuant is examined, which is an adapted sounder specifically designed for in situ gas bubble detection. GasQuant was deployed for several days within a gas seep field in the Central North Sea (Tommeliten). Aside from minor system adaptations, major effort was spent to handle the non-standard large datasets by means of various data processing and visualization routines. Taking into account the surrounding tidal current flow field, unique data patterns were extracted to unambiguously detect gas bubbles in the water column. Thus, a total of 52 single seep holes were localized and characterized with respect to their tempo-spatial variability. Recently, water column scanning multibeam mapping systems entered the market. Due to their huge amount of data output, manual processing is no longer feasible. Thus, a generic algorithm for the detection of rising gas bubbles in multibeam data was developed that accounts for the current tidal flow field for detection issues (Appendix A). Incorporation of other disciplines such as geochemistry and oceanography allowed for a methane gas source strength estimate of the Tommeliten gas seepage field in the North Sea. Combined acoustic mapping and in situ sampling revealed a source strength of ~0.8-4.8*106 mol/yr – a considerable quantity compared to prominent gas seep sites around the world (e.g. ~1*106 mol/yr at Vodyanitskii mud volcano, Black Sea; 2.19*106 mol/yr at North Hydrate Ridge offshore Oregon). Obviously previous studies have underestimated the area of active venting at Tommeliten. By modeling gas bubble dissolution and geochemical sampling it was found that the majority of bubble-mediated methane at Tommeliten already dissolves in the ‘deep’ water between the 70 m release depth and 40 m. Thus the methane is trapped below the upper-well mixed summer layer, from which it would readily be degassed by air-sea exchange processes. Given the heavy storm activity during winter, research cruises into the North Sea preferentially take place during the summer, where low atmospheric outgassing/emissions from seabed methane is expected due to stratification. However, considering the distinct hydrographic seasonal cycle of the North Sea, quantitative transport of seepage methane into the atmosphere seems likely during winter after fall mixing. This seasonal bias is not only constrained to the study site, but relevant for the entire Central and Northern North Sea as well as many mid-latitude shallow shelf sea waters showing temporal stratification

Autonomous Exploration of Large-Scale Natural Environments

This thesis addresses issues which arise when using robotic platforms to explore large-scale, natural environments. Two main problems are identified: the volume of data collected by autonomous platforms and the complexity of planning surveys in large environments. Autonomous platforms are able to rapidly accumulate large data sets. The volume of data that must be processed is often too large for human experts to analyse exhaustively in a practical amount of time or in a cost-effective manner. This burden can create a bottleneck in the process of converting observations into scientifically relevant data. Although autonomous platforms can collect precisely navigated, high-resolution data, they are typically limited by finite battery capacities, data storage and computational resources. Deployments are also limited by project budgets and time frames. These constraints make it impractical to sample large environments exhaustively. To use the limited resources effectively, trajectories which maximise the amount of information gathered from the environment must be designed. This thesis addresses these problems. Three primary contributions are presented: a new classifier designed to accept probabilistic training targets rather than discrete training targets; a semi-autonomous pipeline for creating models of the environment; and an offline method for autonomously planning surveys. These contributions allow large data sets to be processed with minimal human intervention and promote efficient allocation of resources. In this thesis environmental models are established by learning the correlation between data extracted from a digital elevation model (DEM) of the seafloor and habitat categories derived from in-situ images. The DEM of the seafloor is collected using ship-borne multibeam sonar and the in-situ images are collected using an autonomous underwater vehicle (AUV). While the thesis specifically focuses on mapping and exploring marine habitats with an AUV, the research applies equally to other applications such as aerial and terrestrial environmental monitoring and planetary exploration

Desarrollo de un sistema electrónico para la captación de imágenes de un solo píxel mediante métodos acústicos

Treball final de Màster Universitari en Enginyeria Industrial. Codi: SJA020. Curs acadèmic: 2018/2019This project explains the implementation in an integrated and autonomous electronic device of an acoustic imaging system. The device belongs to the so called single pixel devices; that is to say, this device is able to reconstruct an image with spatial resolution using a single sensor or transducer. The key point of these techniques is the ability to modulate the source field and then recover the signal sequentially or by multiplexing in frequency (as it happens in this case). The image is finally reconstructed through a computational algorithm. All along this project you will be able to discover the physics equations underneath the problem, the image reconstruction algorithm and its behavior, and its implementation in a real system and environment, which is the main part of the project. Considerations and restrictions of applying a mathematical model to the real world will appear and constraint the solution, forcing to take decisions such as the components selection. Simulation results will be given and discussed, validating the reconstruction algorithm. Moreover, experimental measurements will be provided and will lead the discussion to potential mistakes and ways to improve the performance of the device

Change detection in combination with spatial models and its effectiveness on underwater scenarios

This thesis proposes a novel change detection approach for underwater scenarios and combines it with different especially developed spatial models, this allows accurate and spatially coherent detection of any moving objects with a static camera in arbitrary environments. To deal with the special problems of underwater imaging pre-segmentations based on the optical flow and other special adaptions were added to the change detection algorithm so that it can better handle typical underwater scenarios like a scene crowded by a whole fish swarm

Design and Implementation of Bio-inspired Underwater Electrosense

Underwater electrosense, manipulating underwater electric field for sensing purpose, is a growing technology bio-inspired by weakly electric fish that can navigate in dark or cluttered water. We studied its theoretical foundations and developed sophisticated sensing algorithms including some first-introduced techniques such as discrete dipole approximation (DDA) and convolutional neural networks (CNN), which were tested and validated by simulation and a planar sensor prototype. This work pave a solid way to applications on practical underwater robots

Engineering derivatives from biological systems for advanced aerospace applications

The present study consisted of a literature survey, a survey of researchers, and a workshop on bionics. These tasks produced an extensive annotated bibliography of bionics research (282 citations), a directory of bionics researchers, and a workshop report on specific bionics research topics applicable to space technology. These deliverables are included as Appendix A, Appendix B, and Section 5.0, respectively. To provide organization to this highly interdisciplinary field and to serve as a guide for interested researchers, we have also prepared a taxonomy or classification of the various subelements of natural engineering systems. Finally, we have synthesized the results of the various components of this study into a discussion of the most promising opportunities for accelerated research, seeking solutions which apply engineering principles from natural systems to advanced aerospace problems. A discussion of opportunities within the areas of materials, structures, sensors, information processing, robotics, autonomous systems, life support systems, and aeronautics is given. Following the conclusions are six discipline summaries that highlight the potential benefits of research in these areas for NASA's space technology programs

3D reconstruction and object recognition from 2D SONAR data

Accurate and meaningful representations of the environment are required for autonomy in underwater applications. Thanks to favourable propagation properties in water, acoustic sensors are commonly preferred to video cameras and lasers but do not provide direct 3D information. This thesis addresses the 3D reconstruction of underwater scenes from 2D imaging SONAR data as well as the recognition of objects of interest in the reconstructed scene. We present two 3D reconstruction methods and two model-based object recognition methods. We evaluate our algorithms on multiple scenarios including data gathered by an AUV. We show the ability to reconstruct underwater environments at centimetre-level accuracy using 2D SONARs of any aperture. We demonstrate the recognition of structures of interest on a medium-sized oil-field type environment providing accurate yet low memory footprint semantic world models. We conclude that accurate 3D semantic representations of partially-structured marine environments can be obtained from commonly embedded 2D SONARs, enabling online world modelling, relocalisation and model-based applications

Underwater Vehicles

For the latest twenty to thirty years, a significant number of AUVs has been created for the solving of wide spectrum of scientific and applied tasks of ocean development and research. For the short time period the AUVs have shown the efficiency at performance of complex search and inspection works and opened a number of new important applications. Initially the information about AUVs had mainly review-advertising character but now more attention is paid to practical achievements, problems and systems technologies. AUVs are losing their prototype status and have become a fully operational, reliable and effective tool and modern multi-purpose AUVs represent the new class of underwater robotic objects with inherent tasks and practical applications, particular features of technology, systems structure and functional properties