Oil pipeline leak detection and location using double sensors pressure gradient method
Jian Feng, Zhang Hua-guang
Abstract
Jian Feng, Zhang Hua-guang
Abstract
The monitoring of oil pipeline is an important task for economical and safe operation, loss prevention and environmental protection from crude oil emission. A leak detection of oil pipeline, therefore, plays a key role in the overall integrity monitoring for a pipeline system. Especially for a long pipeline operated alongside of dense cropland, a leak detection system is an indispensable condition to allow its construction. In this paper, a leak detection and location approach based on double sensors pressure gradient method is proposed. An industrial application to a long oil pipeline is also illustrated. The result of application supports the effectiveness of the proposed method.
OpenAlex reports 29 citations for this work. Citation counts describe recorded attention and do not establish research quality.
A contribution statement is not available in the OpenAlex record.
Method details are not available in the OpenAlex metadata.
Findings are not separately available in the OpenAlex metadata.
Limitations are not available in the OpenAlex metadata.
Application details are not available in the OpenAlex metadata.
The monitoring of oil pipeline is an important task for economical and safe operation, loss prevention and environmental protection from crude oil emission. A leak detection of oil pipeline, therefore, plays a key role in the overall integrity monitoring for a pipeline system. Especially for a long pipeline operated alongside of dense cropland, a leak detection system is an indispensable condition to allow its construction. In this paper, a leak detection and location approach based on double sensors pressure gradient method is proposed. An industrial application to a long oil pipeline is also illustrated. The result of application supports the effectiveness of the proposed method.
Key concepts: Pipeline (software), Leak, Pipeline transport, Leak detection, Petroleum engineering, Computer science, Key (lock), Crude oil