The Riserless Well Intervention (RLWI) system that performs complex offshore oil well Plugging and Abandonment (P&A) operations is a typical Multi-Mission Phased-Mission System (MM-PMS), which requires multiple missions to be completed within a phase. P&A processes involve complex operations and equipment that can contaminate local marine ecosystems if they fail. Therefore, it is necessary to evaluate the reliability of the RLWI system. This paper proposes a dynamic reliability evaluation model for analyzing the RLWI MM-PMS. The GO model of the phase operation process and the Fault Tree (FT) model used to analyze the failure of each mission were established, and a Dynamic Bayesian Network (DBN) model based on the GO model and the FT model was developed for reliability evaluation. The established model can analyze the changes in the reliability of the RLWI MM-PMS more comprehensively, and can also clarify the importance of different missions and different system components. In addition, considering the impact of the marine environment on operators, the Standardized Plant Analysis Risk-Human (SPAR-H) reliability analysis is used for quantification. These findings can guide the improvement of the reliability of the RLWI system and the success rate of P&A operations.

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The lifting and sinking motion generated by the drilling platform causes large fluctuations in the suspension tension of the large hook, which affects the stability of the drilling pressure acting on the rock at the bottom of the well, greatly reduces the efficiency of drilling and decreases the service life of the drill bit and the drill column under the action of cyclically varying loads, causing an increase in the overall drilling cost. In order to avoid the above situation, a nonlinear model of a semi-active lift-sink compensation system is designed and a method to improve the compensation efficiency of the system is proposed. Firstly, the relevant physical model of the hydraulic system is established, and then its simulation model is built according to the working principle of the semi-active lift and sink compensation system. Then the effects of different factors are added to the simulation model of semi-active lifting and sinking compensation, and finally the effects of different factors on the compensation efficiency of the active lifting and sinking system are compared. The simulation results show that a regular sinusoidal wave with a peak value of 6.5 m and a period of 10 s as the ship's lifting and sinking displacement input will reduce the compensation efficiency of the semi-active lifting and sinking compensation system, while the smaller the stiffness of the wire rope, the better the compensation effect of the drill column and the higher the compensation accuracy. The proposed method can effectively improve the compensation efficiency of semi-active lifting and sinking compensation system.

In order to solve the separation efficiency problem of the vertical centrifuge. First, understand the working principle and dynamic theory of the centrifuge, preliminarily design the technical parameters from the experience and experimental data of the prototype, solid works model, specify the overall structure scheme, and complete the virtual assembly. Secondly, the work performance is verified. The production capacity is calculated with power to meet the design requirements. Then, to verify the design strength and deformation meet the design requirements. Then, the finite element numerical analysis of the internal flow field. The FLUENT software is used to analyze the internal flow field velocity distribution and the turbulent kinetic energy of the centrifuge. Finally, a solid phase distribution rule analysis was performed to investigate the effect of particle diameter size on the separation performance at a suitable particle volume fraction.

The simulation and control of the severe slugging flow in the subsea multiphase pipeline is the focus of research in the production and exploitation of oil companies. Severe slug flow results in severe fluctuations of pressure and flow rate at both the wells end and the receiving host processing facilities, causing safety and shutdown risks. To prevent the severe slugging flow regime in multiphase transport pipelines, an ODE model is established by using the mass conservation law for individual phases in the pipeline and the riser sections. Then, the proposed model is compared to the results from the OLGA simulation. A comparative study of different slugging flow control solutions is conducted. Extended Kalman Filter (EKF), Back Propagation Neural Network (BPNN) and EKF&BPNN are used for state estimation and combined with PI controller. The EKF and BPNN are good nonlinear filters. However, when the nominal choke opening is increased, they work unsatisfying. The EKF&BPNN observer shows slightly better results than EKF and BPNN when the system has high input disturbance.