Oil spill detection using optical sensors: a multi-temporal approach

Oil pollution is one of the most destructive consequences due to human activities in the marine environment. Oil wastes come from many sources and take decades to be disposed of. Satellite based remote sensing systems can be implemented into a surveillance and monitoring network. In this study, a multi-temporal approach to the oil spill detection problem is investigated. Change Detection (CD) analysis was applied to MODIS/Terra and Aqua and OLI/Landsat 8 images of several reported oil spill events, characterized by different geographic location, sea conditions, source and extension of the spill. Toward the development of an automatic detection algorithm, a Change Vector Analysis (CVA) technique was implemented to carry out the comparison between the current image of the area of interest and a dataset of reference image, statistically analyzed to reduce the sea spectral variability between different dates. The proposed approach highlights the optical sensors’ capabilities in detecting oil spills at sea. The effectiveness of different sensors’ resolution towards the detection of spills of different size, and the relevance of the sensors’ revisiting time to track and monitor the evolution of the event is also investigated

SMART-DETECT: AN IOT BASED MONITORING SYSTEM FOR OIL LEAK DETECTION

In the past couple of years, the oil and gas industry is aiming to reduce it’s day-to-day costs due to reasons such as reduction in oil prices, mass overproduction and so on. This has the Oil and Gas industries aiming for innovative ways to reduce costs and minimize nonproductive time. In order to accomplish this goal, oil companies need to improve and control measurements with more reliable but relatively cheaper systems. One of the methods is using Internet-of-Things (IoT) based monitoring systems which can help in remote monitoring. IoT is offering better solutions for oil and gas companies to reduce potential failures and downtime by achieving a better and faster method to acquire information efficiently. A real-time stream of data can minimize the need for human intervention in the oil field in case of a catastrophe by reducing the risk of a hazard, saving time, and increasing the environmental pollution control. IoT can be a vital transformation for the Oil and Gas industry. The aim of this thesis is to validate and prove that IoT solutions can be feasible in the oil industry specifically in the pipe leak detection solution ,by building a prototype that operates on low power communication protocol (LoRa®) and conducting experimental procedures on an actual pipe using water instead of oil due to practical difficulty of using oil for the experiment