DARTS—Drone and Artificial Intelligence Reconsolidated Technological Solution for Increasing the Oil and Gas Pipeline Resilience

Premkumar Ravishankar; Seokyon Hwang; Jing Zhang; Ibrahim X. Khalilullah; Berna Eren-Tokgoz

doi:10.1007/s13753-022-00439-w

Volume 13 Issue 5

Oct. 2022

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Premkumar Ravishankar, Seokyon Hwang, Jing Zhang, Ibrahim X. Khalilullah, Berna Eren-Tokgoz. DARTS—Drone and Artificial Intelligence Reconsolidated Technological Solution for Increasing the Oil and Gas Pipeline Resilience[J]. International Journal of Disaster Risk Science, 2022, 13(5): 810-821. doi: 10.1007/s13753-022-00439-w

Citation:

Premkumar Ravishankar, Seokyon Hwang, Jing Zhang, Ibrahim X. Khalilullah, Berna Eren-Tokgoz. DARTS—Drone and Artificial Intelligence Reconsolidated Technological Solution for Increasing the Oil and Gas Pipeline Resilience[J]. International Journal of Disaster Risk Science, 2022, 13(5): 810-821. doi: 10.1007/s13753-022-00439-w

Citation:

Premkumar Ravishankar, Seokyon Hwang, Jing Zhang, Ibrahim X. Khalilullah, Berna Eren-Tokgoz. DARTS—Drone and Artificial Intelligence Reconsolidated Technological Solution for Increasing the Oil and Gas Pipeline Resilience[J]. International Journal of Disaster Risk Science, 2022, 13(5): 810-821. doi: 10.1007/s13753-022-00439-w

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DARTS—Drone and Artificial Intelligence Reconsolidated Technological Solution for Increasing the Oil and Gas Pipeline Resilience

doi: 10.1007/s13753-022-00439-w

1. Department of Industrial and Systems Engineering, Lamar University, Beaumont, TX, 77710, USA;
2. Construction Management Program, Lamar University, Beaumont, TX, 77710, USA;
3. Department of Computer Science, Lamar University, Beaumont, TX, 77710, USA

Funds:

This project was partially supported by the Center for Midstream and Management Science at Lamar University, Beaumont, Texas, USA.

Available Online: 2022-11-01

Abstract

Abstract

The need for safe operation and effective maintenance of pipelines grows as oil and gas demand rises. Thereby, it is increasingly imperative to monitor and inspect the pipeline system, detect causes contributing to developing pipeline damage, and perform preventive maintenance in a timely manner. Currently, pipeline inspection is performed at pre-determined intervals of several months, which is not sufficiently robust in terms of timeliness. This research proposes a drone and artificial intelligence reconsolidated technological solution (DARTS) by integrating drone technology and deep learning technique. This solution is aimed to detect the targeted potential root problems-pipes out of alignment and deterioration of pipe support system-that can cause critical pipeline failures and predict the progress of the detected problems by collecting and analyzing image data periodically. The test results show that DARTS can be effectively used to support decision making for preventive pipeline maintenance to increase pipeline system safety and resilience.
- Artificial intelligence,
- Asset management,
- Drone application,
- Midstream industry,
- Pipeline resilience,
- Predictive maintenance

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References(41)

References

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