Overcome Structural Challenges and Enabling Focused Seismic CCS Monitoring: the North Sea Leman Field Example

Presented at EAGE GET 2024, 5th EAGE Global energy Transition Conference & Exhibition, Rotterdam, November 2024 by Amandine Festucci

Written by Amandine Festucci¹, Marta Puig², Chris Furby², Henry Morris³, Victoria Brun¹, Elodie Morgan¹, ¹SpotLight ,²Perenco ,³Carbon Catalyst

Introduction: The Poseidon project is a carbon storage project in the Leman gas field offshore UK in production since the sixties. This licence will be the first CO2 injection in the UK with several challenges regarding the Monitoring Measurement and Verification (MMV) plan. As part of the monitoring technologies for the Pilot injection, the focused seismic solution will be implemented at the end of 2024. This active seismic solution detects changes in specific subsurface areas, called Spots, using only one source and one receiver per spot (Al Khatib et al, 2021). Legacy seismic data such as 3D seismic, velocity model and raw seismic gather are at the core of this focused seismic monitoring analysis. Two advantages of the spot seismic concerns the spot location accuracy and the optimum location for source and receiver. Depending on the field geology, Common Mid-Point (CMP) and model-based approaches will present limitations. Few hundred meters differences in X, Y locations have been observed for several spots on the Leman gas field when comparing CMP. Aside of ray path propagations in the subsurface, signal to noise ratio is also paramount with such a light amount of seismic data and legacy data are key to ensure the best seismic quality possible. To determine each source and receiver location, a demigration is performed followed by an optimum selection. This paper is demonstrating the importance of using such algorithms and not the CMP assumption, even in non-complex geological context on two practical examples. The impact of geological dips added with the streamer data orientation highlight the errors made when using this assumption. Also, by capitalizing on the legacy data, this technology ensures that the quality of the acquired trace will be optimal for CO2 detection.

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