| dc.description.abstract | The present project is focused on evaluating dual boosting (production with seabed boosting and electric submersible pumps, ESPs, simultaneously) as an alternative to improve total oil production rate of subsea fields. DualLift is a new field developing strategy proposed by OneSubsea/Schlumberger in recent years. The principal target of the method is deep and ultra-deep low GOR oil reservoirs (e.g.Gulf of Mexico) that have long transportation distances. The analysis was performed using coupled reservoir and production network models. Field production profiles were computed and analysed for four different cases:
No boosting, no ESP s, MPP
ESP s installed
MPP(Multiphase Booster)
DualLift system (ESP+MPP)
The report provides a short history of Electrical Submersible Pumps, Multiphase Boosters, the operating limits of the pumps and equipment.
The models to use in the study given by OneSubsea. In order to escape incompatibility and possible errors during running simulations, it decided to use the software supported by the one company (e.g.Schlumberger). Initially network model built in GAP (Petroleum Experts), afterwards it transferred into Pipesim. Reservoir model developed in ECLIPSE 100. Coupling reservoir and network implemented by Integrated Asset Modeler Avocet.
Also except four cases mentioned earlier, water injection case was added for comparison as the possible implementation method. Based on the economic calculation and total oil recovery factor, a number of injection wells and its best location analyzed by ECLIPSE 100. Network model built with installed water separator at the seabed, which separating water coming from production wells and re-injecting back into reservoir through injection well. Optimization study performed for standalone reservoir model using ECLIPSE 300 and for coupled reservoir and network models in IAM Avocet where field oil production total was an objective function, and the water injection rate is an objective parameter.
A simplified economic analysis performed using the computed production profiles and approximate cost values. | en |
