This paper deals with the dynamic availability of a subsea blowout preventer (BOP) with respect to regional and industrial requirements. The study aims to reduce the non-productive time on drilling rigs due to complex propagation of failures within the BOP and BOP control system. In this development, fault tree analysis updated with near real time failure database is implemented into operational decision-making process. First, the system is defined with specifications, boundaries and assumptions. Failure modes of each component are stated. The requirements on the BOP control system are determined with respect to API Standard 53. Fault trees are constructed to address each requirement, and cut sets are produced. For dynamic analysis, a database on BOP state and failure component is created using reports from drilling contractor and operator. Upon detection of a failure, the cut sets are updated. With this application, impact of newly discovered failure in combination with the existing set of failures over BOP availability and compliance is determined in a standardized manner allowing consistent and efficient judgment.

Presented in this paper is a model-based approach for performance and health monitoring of a double spool blowout preventer (BOP) pressure regulator. Governing equations of the pressure regulator are derived based on mathematical and functional relationships. The relationships are carried to a simulation environment. Same approach is followed to generate the model of an annular preventer control circuit from the hydraulic power unit to the preventer itself. The nominal performance the regulator during an annular preventer closing event and effects of internal leakages are shown via simulation. Model-based condition and performance monitoring techniques are developed to detect regulator internal leakages and regulator instabilities. The methods are demonstrated over a dataset obtained from a deepwater BOP. The results show that the leakage detection method can differentiate between a leaking and non-leaking regulator within the same BOP, and that regulator instabilities can be detected with the given sensor set and data acquisition capabilities.

Summary Presented here is a case study on the condition and performance monitoring (CPM) of a subsea blowout preventer (BOP) pipe ram. The proposed real-time CPM solution uses adaptive physics-based models that process sensor measurements at the point of origin (known as edge analytics). The adapted model coefficients are treated as a vector, the magnitude of which estimates the degree of health degradation and the phase of which identifies its source. The benefits of using an adaptive model-based approach over traditional machine-based learning and artificial-neural-networks solutions include zero algorithm-training times, broad applicability to BOPs, model modularity, and accurate health-degradation estimates. The proposed CPM methodology is validated on a BOP pipe ram using both operational and simulated data. A sensitivity study of the method to system uncertainty is also presented.

Presented is the performance analysis of annular blowout preventer (BOP) reciprocating elastomer hydraulic seals operating in subsea environments. The method is based on a systems-level model that combines the effects of friction, material mechanical properties of the seal, installation compression, subsea hydrostatic pressure, and control system dynamics into one model. The model is calibrated using data from tests conducted on the surface and then validated on subsea operational data. Through model simulations, it will be shown that insufficient installation squeeze of the seal in combination with low elasticity seal material results in cases where the seal does not leak at the surface but show substantial internal leakage in subsea conditions. Leakage is also observed under dynamic operation when the walls of the seal groove do not energize the seal. The proposed model-based analysis method in conjunction with surface level testing offers a new paradigm in evaluating reciprocating seal subsea performance a priori of subsea operation thereby avoiding costly downtimes and subsea failures.

Pumping unit efficiency is highly disturbed by the presence of gas influx reducing the productivity and inducing unpredictable system response due to the change of its intrinsic properties such as the natural frequency. A poor estimation of those properties may affect the on-field crew and system safety as well as the production rate. The purpose of this paper is to construct a hydromechanical model describing the coupled multiphase flow-pumping unit system dynamics and to develop a procedure to control the pumping speed for safety assurance and oil production maximization. A coupled mechanical-multiphase flow model capturing the interplay between the gas void fraction (GVF) and the driving harmonic force of the pumping unit is developed. Specifically, the predicted downhole pressure is used to determine the sucker rod effective load. Consequently, a reduced-order model, capturing the dynamics of the sucker rod, is used to estimate the saddle bearings axial displacements which are function of polished rod loading. An error-driven adaptation using the difference between presumed bearing displacement with known GVF and the predicted bearing displacement from the proposed multiphysics model is employed to estimate the unknown downhole GVF. The obtained results prove that the adaptation allows an accurate evaluation of the pumped fluid's GVF, thereby circumventing the need for a costly and inaccurate measurement of the two-phase flow gas fraction. Based on this estimation, a control strategy is then proposed to regulate the pump speed while avoiding the resonance frequency of the sucker-rod system.