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A pipeline burst or rupture causing a leak may significantly impact the environment and the reputation of the company operating the pipeline This paper introduces an advanced deep learning framework that uses continuous wavelet transform (cwt) images for precise detection of such. In recent years, oil and gas pipelines are expected to be equipped with leak detection systems for monitoring the operations and detecting the leaks.

Pipeline methane leaks also pose safety risks due to the possibility of fires or explosions caused by ignition of the natural gas, which can cause significant harm to people and property Detecting pipeline leaks is an essential factor in maintaining the integrity of fluid transport systems Ensuring reliable pipeline integrity and pipeline leak detection can be done easily and remotely with the right technology.

This chart outlines the primary challenges faced in pipeline leak detection, their impacts, and potential strategies to mitigate these issues.

The key to the successful operation of pipeline leak detection systems is management commitment that assures the allocation of sufficient resources to the ongoing maintenance of leak detection systems and their supporting components Every pipeline operator should consider a role for a leak detection champion who understands how their system works, continually monitors its performance, and. This systematic review analysed the various principles and approaches of pipeline leakage detection and monitoring Furthermore, relevant standard, taxonomy of different methods of monitoring, and leakage detection of oil and gas in pipelines were discussed

Their merits, performance and limitations were also discussed.

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