Distributed fibre optic sensing for production optimization

I løpet av det andre året fortsetter planlegging og konkretisering av eksperimentene. I samarbeid med industrideltakerne i prosjektet fastlegges oppsettet og testscenariene, som for eksempel væskesammensetning og strømningshastighet. Det er viktig at det vi studerer er relevant og nyttig for industrien. Selve gjennomføringen av eksperimentene ligger an til å finne sted i begynnelsen av 2022, og dette vil generere mye informasjon i form av målinger, som deretter skal analyseres videre i prosjektet.

The down-hole measurement of fluid flow is key to enabling operators to optimize production, improve reservoir management and maximise field recovery. The well environment is however harsh and can limit the operative life of conventional electronic down-hole gauges. In recent years fiber optic (FO) based measurement systems have been developed and well deployments have proven this technology to be inherently robust. FO sensing is able to deliver comprehensive well data which is on the verge of making a step change in well and reservoir monitoring capability. A unique ability of FO technology is that a single fibre can capture in real-time temperature variations and the acoustic noise field, from top to bottom of the well. An overall research challenge is to understand the flow generated acoustic events in the wellbore in order to understand the response of the fibre and perform high-fidelity data interpretation of real well FO surveys. This project is a national collaboration between organisations performing research within fiber optics, signal processing, flow modelling, machine learning and petroleum. The objective is to develop methods for analysing and processing distributed measurements to support the application of FO sensing technology in oil and gas wells. The planned work packages focus on; physical experiments, numerical acoustic modelling, machine learning and method integration in a transient well flow model used to analyse real well surveys. Development and testing of models will be performed in cooperation with the industry. The project will be executed by research partners NORCE, SINTEF, UiB and UiS. One PhD student will be educated at UiB and a post-doctoral research fellow will be appointed at UiS and collaborate with Northwestern University, Illinois. Scientific results obtained will be disseminated through PhD-dissertations, presentations at international conferences, proceedings and international journals and annual workshops.