Real-time natural gas leak detection of offshore platforms using optical gas imaging and faster R-CNN approach

Real-time natural gas leak detection of offshore platforms using optical gas imaging and faster R-CNN approach

Natural gas

Leak detection

Offshore oil well production

Gases

Arctic engineering

Offshore oil wells

Drilling platforms

Infrared imaging

This study aims to introduce the integrated approach, namely the integration of the Faster R-CNN technique and Optical gas imaging (OGI) for real-time natural gas leak detection of offshore platforms. OGI is used to record large number of leak videos which are essential to develop the desirable Faster R-CNN model. Due to the fact that the natural gas leak incidents are rare on the offshore platforms, it is difficult to record large number of the real-world leak videos by using the OGI. This study firstly proposes the strategy to simulate the OGI by the CFD tool. The proposed strategy could generate large number of virtual infrared images. Based on the infrared images, the Faster R-CNN approach is trained and its performance is tested. A case study of deep-water drilling platform is conducted. The results demonstrate the feasibility of the proposed strategy as well as the competing performance of the Faster R-CNN approach for the real-time automatic natural gas leak detection of offshore platforms. Copyright 2020 ASME

Ocean, Offshore and Arctic Engineering Division

1

Shi, Jihao

Chen, Guoming

Zhu, Yuan

ASME 2020 39th International Conference on Ocean, Offshore and Arctic Engineering, OMAE 2020, August 3, 2020 - August 7, 2020

2020

conferencePaper

10.1115/OMAE2020-19080

http://dx.doi.org/10.1115/OMAE2020-19080