Quite often main issues occurred in unmanned platform due to erosion on XTree. The frozen well intervention system is a typical remedial job to resolve this kind of problem, generating extremely high costs, between 3,5 MMUSD and 12 MMUSD per intervention. Eni conducts pipe erosion studies using a JIP with Tulsa University; however, no dedicated analysis were demanded on Xtree valves geometries. An R&D project was created to cover this gap, in order to replace the current corrective maintenance approach with a preventive one. A new erosion Prediction Model for XTree Valves, both subsea and surface in brown fields, was developed to increase wells life expectancy and maximize the assets integrity. In order to do such thing jointly with Politecnico di Milano University, there has been the development of the project by steps: first, the design of a fluid-dynamic model that analyzes the sand particle interaction with the Xtree valves components, and then an experimental laboratory set-ups design has been performed. Finally the validation of the prediction model with experimental results. The prediction model has been integrated in a tool that adds erosion alerts to Eni wells integrity dashboard and constitutes an upgrade to the internal wells control tool. The delivered software helps to plan the equipment maintenance activities, especially in brown fields, intensely reducing remedial jobs performed in emergency conditions. Moreover, the project achievements can also be extended for additional applications, such as: studies on new non-metallic materials characterization in harsh conditions, usage validation for valves/pipe coatings and supply additional information to support well completion design. Furthermore, the experimental set-ups are now available for erosion tests as asset Eni.

Enhanced erosion prediction for Xtree valves’ lifetime estimation

MALAVASI, STEFANO;MESSA, GIANANDREA VITTORIO
2017

Abstract

Quite often main issues occurred in unmanned platform due to erosion on XTree. The frozen well intervention system is a typical remedial job to resolve this kind of problem, generating extremely high costs, between 3,5 MMUSD and 12 MMUSD per intervention. Eni conducts pipe erosion studies using a JIP with Tulsa University; however, no dedicated analysis were demanded on Xtree valves geometries. An R&D project was created to cover this gap, in order to replace the current corrective maintenance approach with a preventive one. A new erosion Prediction Model for XTree Valves, both subsea and surface in brown fields, was developed to increase wells life expectancy and maximize the assets integrity. In order to do such thing jointly with Politecnico di Milano University, there has been the development of the project by steps: first, the design of a fluid-dynamic model that analyzes the sand particle interaction with the Xtree valves components, and then an experimental laboratory set-ups design has been performed. Finally the validation of the prediction model with experimental results. The prediction model has been integrated in a tool that adds erosion alerts to Eni wells integrity dashboard and constitutes an upgrade to the internal wells control tool. The delivered software helps to plan the equipment maintenance activities, especially in brown fields, intensely reducing remedial jobs performed in emergency conditions. Moreover, the project achievements can also be extended for additional applications, such as: studies on new non-metallic materials characterization in harsh conditions, usage validation for valves/pipe coatings and supply additional information to support well completion design. Furthermore, the experimental set-ups are now available for erosion tests as asset Eni.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11311/1031552
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