North Sea Chalk Reservoir – Seismic History Matching Workflow

This presentation outlines an integrated workflow that incorporates 4D seismic data into the North-Sea Chalk Reservoir history matching process. Successful application and associated benefits of the workflow process are also presented. A number of 4D seismic surveys have been acquired over this field between 1989 and 2008 and this data is becoming a quantitative tool for describing the spatial distribution of reservoir properties and compaction. The seismic monitoring data is used to optimize the waterflood by providing water movement insights and subsequently improve infill well placement. Reservoir depletion and water injection in this field lead to rock compaction and fluid substitution. These changes are revealed in space and time through 4D seismic differences. Inconsistencies between predicted 4D differences (calculated from reservoir model output) and actual 4D differences are therefore used to identify reservoir model shortcomings. This process is captured using the following workflow: prepare and upscale a geologic model; simulate fluid flow and associated rock-physics using a reservoir model; generate a synthetic 4D seismic response from fluid and rock-physics forecasts; and update the reservoir model to better match actual production data and 4D seismic observations. The above-mentioned Seismic History Matching (SHM) workflow employs rock-physics modeling to quantitatively constrain the reservoir model and develop a simulated 4D seismic response. Different parameterization techniques and seismic misfit formulations were validated and used to calibrate and update the reservoir model. This workflow updates the parameters in the closed loop system through minimization of a misfit function by using a customized Particle Swarm Optimization Algorithm. In summary, the Seismic History Matching workflow is a multi-disciplinary process that requires strong collaboration between geological, geomechanical, geophysical and reservoir engineering disciplines to optimize reservoir management.