Using Distributed Fibre Optic Sensing to Recover Well Integrity and Restore Production

Subject North Sea oil producing well has developed sustained casing pressure in the A-annulus, resulted in well being shut-in for around 3 years. Several attempts were made to understand the source of the tubing-to-annulus communication, however remediation actions based on the conventional intervention techniques were not successful, leak location was not isolated and sustained annular pressure remained. This resulted in deferral of oil production and costs incurred due to unsuccessful intervention and remediation techniques. As the well was already equipped with the permanent fibre optic cable for the communication with the downhole pressure gauge, an alternative opportunity was taken to detect leak location by repurposing the cable for the use of Distributed Acoustic Sensing (DAS) technology along with latest pattern recognition techniques. This approach is based on decoupling of fluid movement signature from the background noise and use pattern recognition algorithms to construct fluid flow logs across entire length of the fibre, displaying character and evolution of fluid noise through depth and time. Performed acquisition program allowed to activate the leak, presence of which was clearly visible on the wellhead and A-annulus pressure data. DAS-based acoustic flow logs allowed to clearly identify the exact location of the leak points and additionally provided an understanding to the reasons of failure of remediation methods based on the interpretation of conventional tool results. Remediation strategy based on the insights provided by DAS succeeded to isolate leak points with no further pressure build-up observed in the A-annulus. As a result, operator was able to return to production the well that has been shut-in for three years. This allowed to reinstate 1mbod in production, restore well primary barriers and reduce operational spend through cancellation of further well interventions. This technology offers a new method of acoustic data processing on DAS that extracts valuable insights to identify the source of fluid flow and flow pathways, providing an ability of capturing events behind multiple casing strings.