Integrated Reservoir Modelling of the Alvheim Field

Abstract

Abstract The Alvheim field is located offshore Norway, with a small portion extending into the UK sector. The field is composed of several low relief hydrocarbon accumulations within the Palaeocene Heimdal Formation. Production started in 2008. Recently, a new integrated reservoir model of the Alvheim field was built with the following key objectives: Integrate all known data/constraints, simplify where reasonable, and establish workflows for continuous maintenance/improvement. The Alvheim field includes thin oil rim reservoirs with horizontal wells. The oil-water contact is varying, partly explained by aquifer depletion from nearby fields. Smaller sector models were constructed to test different alternatives for grid selection, saturation modelling, upscaling methods, initialisation methodology, aquifer modelling and lower completion (inflow control devices) modelling. The dynamic full field model is the main tool for production forecasting and should include all relevant constraints and optimisation aspects. The possibility to use active controls to honour the FPSO unit's swivel velocity constraints and to optimise gas lift were investigated. The studies showed that an orthogonal block centred grid was best for the dynamic full field model, giving a good representation of the horizontal wells and a very computationally efficient model. The static model grid was chosen to best honour the geological concepts and to be applicable in dynamic sector model studies. The varying hydrocarbon contacts were gridded as part of the saturation modelling in the static model and included in the upscaling to the full field dynamic model. Studies showed that the Heimdal aquifer model could be simplified and that the dynamic model could be initialised in 2008. The inflow control devices were found to impact the history match and have been implemented as part of the dynamic model. The active controls implemented in the dynamic full field model have simplified the forecast setup and has the ability to improve the forecast quality and the production optimisation. The new Alvheim model has proved to work well, and the established work flows are used for continuous model improvement.