Title: A mechanistic model development to overcome the challenges of subsea fluid sampling

Authors: Nimi Abili; Fuat Kara

Addresses: Department of Offshore and Ocean Technology, School of Applied Science, Cranfield University, Cranfield, MK43 0AL Bedfordshire, UK ' Department of Offshore and Ocean Technology, School of Applied Science, Cranfield University, Cranfield, MK43 0AL Bedfordshire, UK

Abstract: Extracting fluid samples from actual flow stream being measured subsea is one of the operational requirements for obtaining sustained accurate measurement for calibration of a subsea multiphase flow meter (MPFM). Samples collected from topside facilities do not represent the fluid being measured due to chemical injection downstream the meter and possible liquid separation/hold-up. However, the issue of subsea intervention and transportation of fluid samples present another challenge with significant cost impact and risk to the subsea environment. To overcome these challenges, a virtual compositional fluid tracking model has been developed as an optimal solution in bridging the gaps in subsea fluid sampling. The virtual model is developed with a compositional fluid tracking module, capturing the essential building blocks of the Subsea Production System (SPS). Results from the mechanistic model demonstrates the capability in improving understanding of well flow stream, taking into considerations the variations in fluid compositions in real time, and calculating the physical properties in view of matching the hydrocarbons compositions to enable a proactive and cost effective fluid sampling operations. This has also enabled the development of advanced operations monitoring, as operational conditions - we cannot control - changes over the field life.

Keywords: transient flow modelling; multiphase flow modelling; compositional fluid tracking; subsea MPFM; subsea fluid sampling; multiphase flow meters; well flow stream; optimal solution; analytical techniques; advanced operations monitoring; applications; mechanistic modelling; hydrocarbons.

DOI: 10.1504/IJMOM.2013.058335

International Journal of Modelling in Operations Management, 2013 Vol.3 No.3/4, pp.267 - 281

Received: 08 Mar 2013
Accepted: 26 Aug 2013
Published online: 29 Jan 2014 *

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