Thèse de Doctorat
DOI
https://doi.org/10.11606/T.3.2018.tde-16072018-091052
Document
Auteur
Nom complet
Ivanilto Andreolli
Unité de l'USP
Domain de Connaissance
Date de Soutenance
Editeur
São Paulo, 2018
Directeur
Jury
Baliño, Jorge Luis (Président)
Castro, Marcelo Souza de
Gioria, Rafael dos Santos
Schettini, Edith Beatriz Camaño
Silveira Neto, Aristeu da
Titre en portugais
Mots-clés en portugais
Dinâmica dos fluídos
Escoamento multifásico
Petrologia (Produção)
Sistemas lineares
Resumé en portugais
Titre en anglais
Linear stability applied to multiphase oil flow.
Mots-clés en anglais
Flexible pipes (Stability)
Fluid dynamics
Linear systems
Multiphase flow
Petrology (Production)
Resumé en anglais
This work presents a linear stability analysis for a flowline-riser system. The model considers continuity equations for the liquid and gas phases, and a momentum equation for the mixture that accounts for friction effects. The water-oil mixture is modeled as being homogeneous. The void fraction is determined by using the drift-flux model based on several drift correlations. For stratified flow, the void fraction is expressed by the local equilibrium model of Taitel and Dukler (1976). Fluid characterization uses a black-oil model that considers mass transfer between the oil and gas flows as a function of the local pressure and temperature conditions. In the proposed approach with distributed parameters, several geometries with variable discretization can be considered, such as catenary and lazy wave risers. To perform the linear stability analysis, the equations of the model are linearized around the stationary state and discretized using the finite difference method, implemented using custom-written code in Matlab. From the linearized system, the stability of the steady state is evaluated by computing the roots of the characteristic polynomial equation of the eigenvalues and eigenvectors problem. Convergence of the numerical model is evaluated and stability maps for several oil production systems were presented. Numerical results were compared with the actual measurements of oil production systems. The model converged in all cases tested and presented an excellent agreement with field data.

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Date de Publication
2018-07-24

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