Leakage detection in underwater oil and natural gas pipelines using convolutional neural networks

Underwater oil and natural gas pipelines are an underwater transport infrastructure known to be reliable, fast, efficient, preferred for the transmission of energy far distances. The rapid continuous increase in demand due population growth, industrial developments, global growth requires economic environmental solutions safe control sources such as gas. These lines damaged their work corrosive ambient conditions, elements sudden change air water temperatures, tectonic activities, external blows caused by fishing equipment military exercises. Therefore, it is necessary determine damages without requiring more hardware, saving time, cost. In this study, were detected using convolutional neural networks detection performance artificial network was analyzed. with 97.63% accuracy. A controlled, sustainable model established prevent potential damage from becoming threat pollution living creatures ecosystem study.