Abstract

We present the results of a rock physics driven workflow to analyze and steer a planned CO2 migration campaign, it combines a rock-physical seismic model, reservoir model and Bayesian scenario framework to assess monitoring configurations. The injection of CO2 into the subsurface requires a detailed understanding of the petrophysical properties and rock physical frame of the formation under stress. The underlying assumptions made for the unconsolidated high porosity formation have a significant impact on the expected seismic response. For a shallow aquifer pressure and saturation dependent elastic parameters are derived within a rock physical description. Distinguishing pressure and saturation related changes of the acoustic impedance is subject to the sensitivities of the properties used to derive the underlying seismic P- and S-velocities as well as densities. These uncertainties can induce a non-negligible variability in the footprint of a seismic image of the CO2 plume. The rock physics model is based on a solid frame consisting of quartz and clay and saturated with water and gas. The integrated workflow coupled with dynamic simulations provides a possibility to define and evaluate conformance measures during operation. Within this context the workflow is applied to the extended Svelvik CO2 field laboratory, which can be considered as a big sandbox model with capabilities for up-scaling to larger storage formations. An experimental design assessing the sensitivity of the information present for the site is translated into a scenario-based ensemble of dynamic models. Following, a practical quantitative workflow for a-priori assessment of monitoring strategies in probabilistic conformance verification is demonstrated. The results provide insight into the impact of different aspects of geophysical monitoring configurations (e.g., sparsity, noise levels, detection thresholds and timing) on the conformance verification accuracy.

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