To meet the requirements of riser safety monitoring in offshore oil fields, a new Fiber Bragg Grating (FBG)-based bundle-structure riser stress monitoring sensor has been developed. In cooperation with many departments, a 49-day marine test in water depths of 1365 m and 1252 m was completed on the “HYSY-981” ocean oil drilling platform. No welding and pasting were used when the sensor was installed on risers. Therefore, the installation is convenient, reliable and harmless to risers. The continuous, reasonable, time-consistent data obtained indicates that the sensor worked normally under water. In all detailed working conditions, the test results show that the sensor can do well in reflecting stresses and bending moments both in and in magnitude. The measured maximum stress is 132.7 MPa, which is below the allowable stress. In drilling and testing conditions, the average riser stress was 86.6 MPa, which is within the range of the China National Offshore Oil Corporation (CNOOC) mechanical simulation results.

In the mid 2012, three deep water exploration wells have been accomplished in the South China Sea by CNOOC as the operator employing the deep water drilling unit HYSY981, which symbolizes the epoch of deep water drilling of CNOOC. By reviewing the history of deep water drilling implemented by CNOOC and its partners, this paper put forward the key challenges of deep water drilling in South China Sea, such as typhoon, soliton, gas hydrates and so on. Potential solutions to these challenges are discussed in the paper, aiming at drilling safety. Firstly, this paper focuses on the strategy of the typhoon resistance for the new building deep water drilling unit (DWDU) HYSY981. On which the preliminary research results are given in the paper. The typhoon resistance solution is drawn up in combination with the platform dynamic analysis and operational mode that have been performed to demonstrate its feasibility. Secondly, the paper shows solutions to the soliton for deep water drilling in the South China Sea. And finally, the recommendation to deal with the risk of hydrate formation in deep water drilling is summarized.

The fatigue reliability assessment of deepwater risers plays an important role in the safety of oil and gas development. Physical-based models are widely used in riser fatigue reliability analyses. However, these models present some disadvantages in riser fatigue reliability analyses, such as low computational efficiency and the inability to introduce inspection data. An improved fatigue reliability analysis method was proposed to conduct the fatigue reliability assessment of deepwater risers. The data-driven models were established based on response surface methods to replace the original physical-based models. They are more efficient than the physics-based model, because a large number of complex numerical and iterative solutions are avoided in fatigue reliability analysis. The annual crack growth model of the riser based on fracture mechanics was established by considering the crack inspection data as a factor, and the crack growth dynamic Bayesian network was established to evaluate and update the fatigue reliability of the riser. The performance of the proposed method was demonstrated by applying the method to a case. Results showed that the data-driven models could be used to analyze riser fatigue accurately, and the crack growth model could be performed to analyze riser fatigue reliability efficiently. The crack inspection results update the random parameters distribution and the fatigue reliability of deepwater risers by Bayesian inference. The accuracy and efficiency of fatigue analysis of deepwater risers can be improved using the proposed method.

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