Current practice of early leak detection methods for underground storage tanks

Abstract

This article aims to provide general review on current practice of leak detection methods of underground storage tanks (UST). Fuel (i.e. gasoline and diesel oil) leakage from UST can contaminate groundwater and drinking water with various hydrocarbon contaminants. These leaks create ponds of fuel that spill into the land and aquifers, polluting and seriously destroying habitats. Numerous efforts have been focused on the development of leak detection to the tanks. However, without the opportunity to conduct fault intensity calibration and estimate a product's lifetime, there is a lack of information provided to consider the condition of previous underlying leakage. As a result, it is too late whether the harm has already been done. There are methods of detection that have been studied for the past ten years. Many approaches have been practised to detect leakage. Specific sensing devices will combine with additional applications that analyse and interpret the data to detect storage tank leaks. Various methods will provide different results depending on the feature chosen. Some approaches will use machine learning to analyse the provided data and provide the best leak detection result. This paper will explore the best leak detection techniques to improve underground tanks' structural integrity. At the end, this paper will give some overview on current practice early detection methods on underground storage tanks for future research.