JCSE, vol. 20, no. 3, pp.216-229, September, 2026

DOI: http://dx.doi.org/10.5626/JCSE.2026.20.3.216

Optimization Research on Fusion between 3D Models Based on Graph Neural Network Algorithms and Entire Lifecycle Management Data of Offshore Oil Engineering Equipment

Wei Li, Yaofei Qi, Ruiyun Zhao, Gang Zhao, Xiuling Zhang, and Zhi’ang Li
Offshore Oil Engineering Co., Ltd., Tianjin, China Business-Intelligence of Oriental Nations Corporation Ltd., Beijing, China

Abstract: Three-dimensional (3D) model data is a crucial foundation for realizing the full lifecycle management of marine oil and gas equipment, making its data quality particularly important. To improve the data quality of marine oil and gas equipment during the design and production stages, this study first designed a full lifecycle management system. Addressing the lack of detailed 3D models in this system, a 3D model mesh reconstruction method for the full lifecycle management of marine oil and gas equipment was designed based on graph neural networks (GNN) and attention mechanisms. Performance comparison analysis of this method with other algorithms showed that its average chamfer distance was 2.09 and its average F1-score was 96.87, with an mIoU of 97.16% and an average SSIM of 0.981, both superior to the compared algorithms. Application effect analysis of the 3D reconstruction method revealed that the reconstructed 3D model of marine oil and gas equipment was rich in detail and had clear contours, achieving similarity rates of 96.8%?98.6% across different equipment components. Subsequently, the application effect analysis of the proposed marine oil and gas equipment lifecycle management system showed that the system effectively represented the 3D model of marine oil and gas equipment. These results demonstrated that the proposed marine oil and gas equipment lifecycle management system and 3D model reconstruction method were effective and have good practical value. They provided new technical means for data fusion and optimization of marine oil and gas equipment and also provided a theoretical basis for data quality optimization in the full lifecycle management of marine oil and gas equipment.

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