DOI: 10.3390/jmse11122275 ISSN: 2077-1312

CO2 Injection Monitoring: Enhancing Time-Lapse Seismic Inversion for Injected Volume Estimation in the Utsira Formation, Sleipner Field, North Sea

Doyin Pelemo-Daniels, Basil O. Nwafor, Robert R. Stewart
  • Ocean Engineering
  • Water Science and Technology
  • Civil and Structural Engineering

This article presents an in-depth study of CO2 injection monitoring in the Sleipner Field, focusing on the Utsira Formation. The research leverages advanced time-lapse inversion techniques and 4D seismic data analysis to enhance the accuracy of volume estimations and provide a comprehensive understanding of the dynamic behavior of the injected CO2 plume. The analysis encompasses cross correlation, time shift, predictability, and other key elements to yield robust insights into the reservoir’s response to CO2 injection. Cross-correlation analysis results of 60% to 100% outside the injection zone and less than 50% within the injection zone reveal a distinct dissimilarity between the injection and non-injection zones, emphasizing phase, time, and frequency content changes due to CO2 injection. Time shifts are meticulously calibrated globally on a trace-by-trace basis, to account for shallow statics and velocity changes, improving the overall alignment of seismic data. Predictability analysis results of 0 to 0.34 within the injection zone and 0.45 to 0.96 at the background further reinforce the findings, highlighting high predictability values in areas untouched by production and markedly lower values within the injection zone. These results provide a measure of the reliability of the seismic data and its ability to reflect the subtle changes occurring in the reservoir. Crucially, the time-lapse inversion process excels in capturing the evolving state of the CO2 plume within the Utsira Formation. The seismic data reveals the migration and expansion of the plume over time and the dynamic nature of the reservoir’s response to CO2 injection. Integrating various data facets reduces non-uniqueness in inversion results, allowing for more precise volume estimations.

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