Slug initiation and prediction using high accuracy methods - applications with field data - Kalogerakos, Stamatis (Cranfield University, 2011)
The sponsoring company of the project is BP. The framework within which the research is placed is that of the Transient Multiphase Flow Programme (TMF-4), a consortium of companies that are interested in phenomena related to ﬂow of liquids and gases, in particular with relevance to oil, water and air. The deliverables agreed for the project were: • validating EMAPS through simulations of known problems and experimental and ﬁeld data concerning slug ﬂow • introducing numerical enhancements to EMAPS • decreasing computation times in EMAPS • using multi-dimensional methods to investigate slug ﬂow The outcome of the current project has been a combination of new product development (1D multiphase code EMAPS) and a methodological innovation (use of 2D CFD for channel simulations of slugs). These are: • New computing framework composed of: – Upgraded version of 1D code EMAPS – Numerical enhancements with velocity proﬁle coeﬃcients – Validation with wave growth problem – Parallelisation of all models and sources in EMAPS – Testing suite for all sequential and parallel cases – Versioning control (SVN) and automatic testing upon code submission. • Use of 2D CFD VOF for channel simulation with: – Special initialisation techniques to allow transient simulations – Validation with wave growth problem – Mathematical perturbation analysis – Simulations of 92 experimental slug ﬂow cases The cost of uptake of the above tools is relatively small compared to the beneﬁts that are expected to follow, regarding predictions of hydrodynamic slugging. Depending on the timescales involved, it is also possible to use external consultancies in order to implement the solutions proposed, as these are software based and their uptake could be carried out in a small time-frame. Moreover it may not be necessary to build a parallel hardware infrastructure as it is now possible to have easy access to large parallel clusters and pay rates depending on use.