I compare three repeatability measures using the time lapse data from Sleipner CO2 storage project in offshore Norway. The three repeatability are NRMS, predictability, and cross-correlation coefficient. I first review the work of Kragh and Christie (2002) who used NRMS and predictability and created a random noise model to explain their relationship. Using the Sleipner dataset, I show an excellent fit to their theory. I then review the work of Coléou et al. (2013), who used NRMS and cross-correlation measures and introduced two new attributes: quality indicator (Q) and anomaly indicator (A). After discussing the relationship between predictability and cross-correlation I apply the Q and A attributes to the Sleipner dataset, showing how well the CO2 plume can be identified.
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SPE/AAPG/SEG Carbon, Capture, Utilization, and Storage Conference and Exhibition
March 11–13, 2024
Houston, Texas, USA
ISBN:
978-1-959025-62-7
Repeatability indicators in time lapse seismology and their application to the Sleipner CO2 storage project
Brian Russell
Brian Russell
GeoSoftware, Calgary
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Paper presented at the SPE/AAPG/SEG Carbon, Capture, Utilization, and Storage Conference and Exhibition, Houston, Texas, USA, March 2024.
Paper Number:
SPE-CCUS-2024-4012771
Published:
March 11 2024
Citation
Russell, Brian. "Repeatability indicators in time lapse seismology and their application to the Sleipner CO2 storage project." Paper presented at the SPE/AAPG/SEG Carbon, Capture, Utilization, and Storage Conference and Exhibition, Houston, Texas, USA, March 2024. doi: https://doi.org/10.15530/ccus-2024-4012771
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