SpiDeR –Spill Detection and Recognition system for ROV operations

P. Pocwiardowski
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Abstract

The paper presents the outline of the Spill Detection and Recognition system – SpiDeR and its application to underwater oil and gas detection, classification and source characterization demonstrated in the remote-sensing survey of Mississippi Canyon area in the Gulf of Mexico founded by BSEE in 2017. The main objective of the operation was to deploy sensor package from a remotely-operated vehicle (ROV) to survey, detect, and map the location(s) of hydrocarbon emissions that are responsible for the surface oil spill and sheen footprint in the Mississippi Canyon Area. The objectives have been accomplished by conducting a multi-day, three-part survey mapping the area of interest, generation of georeferenced charts and 3D visualizations with detected oil active spills, all supported by a ROV intervention outfitted with oil spill detection and recognition system SpiDeR. SpiDeR is a modular sensor suite capable of detecting, recognizing the source and classifying the hydrocarbon underwater leaks. The sensor suit with selectable configuration can be installed on any type of ROV vehicle and interfaces to the ROV with a single cable conducting the power and data. The presented here and used during the mission complete sensor suite consist of two 3D, broad band, electronically scanning multibeam sonar systems NORBIT WBMS STX, one Forward Looking Sonar NORBIT WBMS FLS, fluorescent oil classifier LIF – Laser Induced Fluorescence detection unit and the video camera with lights. The most useful capability of the SpiDeR is the ability to generate 3D imagery (georeferenced bathymetry) even when the ROV is not moving. That combined with time gives 4D observable capabilities of the oil spill. The 4D capabilities have been proven useful during the u-bathymetry part in Phase 2 and forward-looking 3D in Phase 3 of this mission. The system has been deployed from the ROV in the area where it has been known for the last decade that the leak of hydrocarbons is coming from. The real task at hand was to recognize the leak source and that source contain hydrocarbons and accurately document the source location and provide measurable documentation of its character.
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SpiDeR—用于ROV作业的泄漏检测和识别系统
本文介绍了BSEE于2017年在墨西哥湾密西西比峡谷地区的遥感调查中建立的泄漏检测和识别系统- SpiDeR及其在水下油气检测、分类和来源表征中的应用。此次作业的主要目的是部署远程操作车辆(ROV)的传感器包,以调查、检测和绘制碳氢化合物排放的位置,这些碳氢化合物排放是造成密西西比峡谷地区地表溢油和油迹的原因。通过进行为期多天、分三部分的调查,绘制出感兴趣的区域,生成地理参考图表,并对检测到的石油活跃泄漏进行3D可视化,所有这些都由配备溢油检测和识别系统SpiDeR的ROV干预提供支持。SpiDeR是一种模块化传感器套件,能够检测、识别水下碳氢化合物泄漏的来源并对其进行分类。该传感器套装具有可选配置,可安装在任何类型的ROV车辆上,并通过单根电缆与ROV连接,传输电源和数据。在任务中使用的完整传感器组件包括两个3D,宽带,电子扫描多波束声纳系统NORBIT WBMS STX,一个前视声纳NORBIT WBMS FLS,荧光油分类器LIF -激光诱导荧光探测单元和带灯的摄像机。SpiDeR最有用的能力是即使ROV不移动也能生成3D图像(地理参考测深)。这与时间相结合,提供了石油泄漏的4D可观测能力。在第二阶段的u-测深部分和第三阶段的前瞻性3D部分,4D功能已经被证明是有用的。该系统已从ROV部署在过去十年中已知的碳氢化合物泄漏区域。当前的真正任务是识别泄漏源以及泄漏源中含有的碳氢化合物,并准确记录泄漏源位置,并提供可测量的泄漏特征文件。
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