2 research outputs found

    Development and Validation of a Simplified Transient Two-Phase Flow Model for Any Pipe Inclination

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    This study describes the development and validation of an improved simplified model for transient two-phase flow for any pipe inclination. The simplified model proposed has been validated with field-scale test well and laboratorial data, and also compared to the state-of-the-art commercial simulator for transient two-phase flow in pipes. The results of the simplified model showed an agreement within the range of ±30% for the holdup predictions for 65% of the scenarios, and an agreement within the range of ±30% for the pressure predictions for 82% of the scenarios considered in this work. In the oil and gas industry, transient two-phase flow is present in many production and drilling operations, such as in well unloading, well control, and managed pressure drilling. There are many commercial transient multiphase flow simulators available, which use complex numerical procedures to describe multiphase flow in pipes and estimate variables of interest, such as pressure, temperature, phase fractions, and flow regimes discretized in space and time. Many of the transient flow scenarios encountered in the industry are considered slow transients and a rigorous transient simulator may not be necessary in these cases. With a few simplifications of the fundamentals equations, less complex models can be deployed in such cases without significantly compromising the accuracy of the results. With this consideration, and taking the fact that acquiring a license of a commercial software can be prohibitive for small operators and consulting companies, an easy-to-use and open source simulator was implemented based on the simplified transient model discussed in this work

    OPTIMIZATION OF STEEL CATENARY RISERS USING BIOINSPIRED ALGORITHMS

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    The design of a riser is very time consuming, since a large number of parameters (e.g.: thickness, top angle, and material properties) are involved and tight safety requirements must be met. This leads to the study of tools, such as optimization algorithms, that can speed up the process of elaborating a feasible riser project for certain conditions. Considering that some of the parameters in the design of a riser can assume a discrete set of values, the utilization of mathematical programming algorithms becomes unfeasible. It is then necessary to use metaheuristic algorithms, such as Genetic Algorithm and Particle Swarm Optimization.In this context, this paper presents a study on the application of bio-inspired algorithms,including GA and PSO, to the design optimization of steel catenary risers. The problem consists of finding the riser material and wall thickness that minimize the cost to fabricate a viable riser, in conformance with the requirements of technical standards. The main hypotheses that were adopted are presented, along with the description of the methodology employed. The results show that a significant reduction in riser cost is achieved when the riser is divided in multiple segments with different thickness and material. The efficiency of the utilized algorithms in finding an optimum riser design for the specified conditions is onfirmed by the obtained numerical results
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