An integrated methodology is proposed to quantitatively evaluate interwell connectivity by uniting available data from the production and seismic domains, while simultaneously honouring reservoir geology. The Capacitance Model approach for interwell evaluation is selected initially to obtain prior understanding using well production and injection fluctuations. Then, to make proper use of 4D seismic data, we extend the newly developed “well2seis” technique to further predict the well-to-reservoir connectivity by correlating multiple seismic monitor surveys to the well behaviour data. Based on the prior information provided by the Capacitance Model, appropriate wells are selected to provide robust 4D seismic correlation. The final result is generated as a 3D attribute volume, which directly reveals spatial patterns of reservoir connectivity. The proposed methodology is firstly tested on a synthetic case, where it is shown that the well2seis correlation attribute can correctly identify key reservoir flow barriers and conduits. When applied to observed data from the Norne field, the pressure diffusion and fluid flow pathways from injectors to producers are detected, which are consistent with bottom-hole pressure measurements and observed sea water production breakthrough. We also discover a key fault barrier which was not considered in the reservoir model previously and successfully improves the history matching quality. The understanding of the reservoir connectivity is significantly improved compared to using conventional methods or the 4D seismic method independently.
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- School of Energy, Geoscience, Infrastructure and Society, Institute for GeoEnergy Engineering - Research Fellow
- School of Energy, Geoscience, Infrastructure and Society - Research Fellow
Person: Research Assistant/Fellow
- School of Energy, Geoscience, Infrastructure and Society, Institute for GeoEnergy Engineering - Professor
- School of Energy, Geoscience, Infrastructure and Society - Professor
Person: Academic (Research & Teaching)