During exploitation underwater locations of oil and gas pipelines, regular technical inspections are required to monitor the condition of the pipe body and its supports. The technology of underwater pipeline survey using side-scan sonar (SSS) is characterized by a high degree of automation, information, efficiency and low labor costs compared to traditional methods based on the use of underwater vehicles or divers.

Often underwater pipelines are laid directly on the bottom or in shallow trenches. The impact of currents can lead to erosion of the bottom and the formation of large areas of sagging of the pipeline, which can cause unacceptable transverse loads on the pipe body. Therefore, the operation of such pipelines requires regular technical inspections. Such a survey can be carried out either visually with the help of an underwater vehicle or diver, or with the help of SSS.

In pipeline design and construction, the ability of SSS to give a very detailed bottom relief picture as well as to detect obstacles is used in determining the optimal path of the underwater pipeline. Since turbid water is transparent to the acoustic signal, SSS is also effective in the construction of underwater pipelines and offshore oil platforms.

Automated interpretation of the SSS image to determine pipeline sagging areas is a great advantage of acoustic imaging, greatly improving the efficiency of pipeline monitoring. Unlike the interpretation by the geophysicist operator, this interpretation does not suffer from lapses in attention and a decline in performance at night. It relies on formalized criteria, with SW developers preferring to rely on methods of mathematical statistics and probability theory to quantify system performance. However, human interpretation relies on a broader context. This allows you to recognize the situation associated with possible expensive activities for the descent of the underwater vehicle and the mobilization of the repair team, and focus on such areas. Automatic interpretation is used as a data filter, where human attention is drawn to areas where the probability of detection of sagging is high enough. The filtering algorithms are based on robust statistics tracking of more than 30 different variables describing the pipeline condition. Other image processing techniques are also used. For example, a reflection of the high intensity casting a deep acoustic shadow is tracked to the prediction of the position of the pipe. This method is irreplaceable in the case when the pipe in the underwater area is buried under the ground in places, and in places comes to the surface of the bottom.

At the same time, of course, such automation has a number of limitations. The first is the flat bottom assumption typical of all SSS. If the pipe is laid in a hollow with inclined walls, then the acoustic shadow, cast by it on the inclined wall of the hollow, and the strong reflection of the signal from this wall, will not make it possible to estimate its height and sagging. The second limitation is the unreliable interpretation of images of pipes with a diameter of less than 15 cm, which cause difficulties even for humans. The higher the operating frequency of SSS, the higher the resolution and image quality. Therefore, for small diameter pipes, high-frequency SSS variants should be considered, with an operating frequency of more than 250 kHz.

SSS have recently become a widely demanded hydrographic equipment. The implementation of such systems will allow to fulfill inspection of underwater sections of pipelines better and faster, which will undoubtedly have a positive impact on their safety and operational efficiency.