The acquisition of representative subsea fluid sampling from offshore field development asset is crucial for the correct evaluation of oil reserves and for the design of subsea production facilities. Due to rising operational expenditures, operators and manufacturers have been working hard to provide systems to enable cost effective subsea fluid sampling solutions. To achieve this, any system has to collect sufficient sample volumes to ensure statistically valid characterisation of the sampled fluids. In executing the research project, various subsea sampling methods used in the offshore industry were examined and ranked using multi criteria decision making; a solution using a remote operated vehicle was selected as the preferred method, to compliment the subsea multiphase flowmeter capability, used to provide well diagnostics to measure individual phases – oil, gas, and water. A mechanistic (compositional fluid tracking) model is employed, using the fluid properties that are equivalent to the production flow stream being measured, to predict reliable reservoir fluid characteristics on the subsea production system. This is applicable even under conditions where significant variations in the reservoir fluid composition occur in transient production operations. The model also adds value in the decision to employ subsea processing in managing water breakthrough as the field matures. This can be achieved through efficient processing of the fluid with separation and boosting delivered to the topside facilities or for water re-injection to the reservoir. The combination of multiphase flowmeter, remote operated vehicle deployed fluid sampling and the mechanistic model provides a balanced approach to reservoir performance monitoring. Therefore, regular and systematic field tailored application of subsea fluid sampling should provide detailed understanding on formation fluid, a basis for accurate prediction of reservoir fluid characteristic, to maximize well production in offshore field development.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:687773 |
| Date | January 2015 |
| Creators | Abili, Nimi Inko |
| Contributors | Athanasios, Kolios |
| Publisher | Cranfield University |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | http://dspace.lib.cranfield.ac.uk/handle/1826/10017 |
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