Stochastic Time-Dependent Deterioration Models for Estimating Residual Service Life of Offshore Jacket-Type Platforms

This paper presents deterioration models for maintenance planning of offshore jacket platform based on two methods: i) stochastic Markov-chain based model and ii) stochastic-mechanistic deterioration models based on steel corrosion rates. Markov-chain models require the estimation of transition probability matrix (TPM), which is typically derived from the inspection data. The global structural health condition of the jacket is computed based on the condition of individual elements and their criticality in terms of failure consequence. The criticality factors are established based on nonlinear static redundancy analyses. This method can model deterioration when routine inspection records of jacket members are available. When there is scarcity of inspection records, stochastic-mechanistic deterioration modeling approach can be used. Monte-Carlo simulations with established corrosion wastage models are utilized to estimate the time-dependent deterioration of jacket legs, horizontal and diagonal bracings in splash and immersion zones. This method is proposed when there is scarcity of inspection records. The deterioration models are further utilized to predict the timing for Maintenance, Repair and Rehabilitation (MRR) actions, and estimate the residual service life of the jacket platform. This study demonstrates the application of the proposed deterioration modeling approaches with a case study of a typical 4-legged offshore jacket platform.

IN-PLACE ANALYSIS OF OFFSHORE JACKET PLATFORM FOR DIFFERENT WAVE DIRECTIONS

Offshore jacket platforms are subjected to variety of forces during their life period. To resists all kinds of forces, the structural elements should be designed properly to have safety and economy. In order to fulfil this purpose, the structure should be analyzed with great care. As the improvement of oil and gas moves into more profound water, in any case, taller stages with longer periods are fabricated that react all the more powerfully to extraordinary waves. Expectation of the dynamic reaction of such structures in extraordinary ocean states is in this way an essential plan thought. Standard waves have all their vitality lumped at a couple of particular frequencies and can, in this manner, cause wrong powerful enhancements, particularly if these frequencies happen to be near the regular frequencies of the structure. In any case, waves in the ocean are exceptionally sporadic and can be best depicted as directional range, which indicates the appropriation of wave vitality as for recurrence and heading, and is most appropriate for the examination of structure in recurrence space technique. For this situation the nonlinear drag is linearized and utilized in the Morison's condition. This guess is proper for the littler, operational sort waves considered in weariness counts, in light of the fact that the powers because of these waves are overwhelmed by the direct idleness part. Various kinds of investigations related with the coat stage ought to be performed to figure the reaction of the structure and measurement the components of the structure. Here an endeavor has been made to complete various examinations to comprehend the dynamic conduct of coat stages subject to different stacking conditions in various ecological conditions. Coat set up investigation was performed, both static and dynamic hypothetically fixed base stage. With the ongoing imaginative thoughts of investigation utilizing programming, it is presently simpler for the seaward architects to do disentangled and sensible assessment of the static operational and extreme point of confinement state qualities of format or coat stages, which are exposed to different ecological conditions. The essential auxiliary parts of coat type seaward structures including topsides, coat, heaps and the encompassing soil are viewed as utilizing SACS programming various types of investigations identified with coat stage according to API code prerequisite.