8.3.4 Monitoring the injection process
Time lapse seismic data - The major success of the SACS project has been the demonstration that conventional, time-lapse, p-wave seismic data can be a successful monitoring tool for CO2 injected into a saline aquifer (Eiken et al. 2000). Even with the CO2 in a supercritical, rather than a gaseous, state it has been shown that CO2 accumulations with a thickness as low as about a metre can be detected - far below the conventional seismic resolution limit of approximately 7 m. Even these thin accumulations cause significant, observable and measurable changes in the seismic signal, both in amplitude and in travel time (Figure 23a).
It is exactly this major effect on the time lapse seismic signal of relatively thin CO2 accumulations that has built confidence that any major leakage into the overlying caprock succession would have been detected. So far, no changes in the overburden have been observed in the Sleipner, implying that there are no leakages from the Utsira formation.
The time lapse seismic data have provided insights into the geometrical distribution of the injected CO2 at different time steps and show the different migration pathways (Figures 23b and 22c). Due to the lower density of CO2 with respect to the formation water, buoyancy is the dominant physical process governing the migration. The seismic data have revealed at least temporary barriers (very thin shale layers) to vertical migration of the CO2 that could not be resolved on the pre-injection baseline data alone. Due to the pronounced effect of the CO2 on the amplitude of the time lapse seismic signal these barriers have been mapped locally, markedly increasing the understanding of the CO2 migration within the reservoir. At various
locations chimneys have been observed where CO2 passes through the thin shale layers (Figure 23b). The presence of thin shale layers has radically affected the CO2 distribution in the reservoir, with CO2 migrating laterally for several hundred metres beneath the intra- reservoir shales (Fig. 23c). It the longer term, this dissemination of CO2 throughout the
reservoir thickness (rather than just being concentrated at the top) may allow more efficient dissolution of CO2 and effectively increase the reservoir capacity (Torp and Gale, 2003). Interpretation of the post-stack seismic data has provided much of the information required to characterise the “CO2 bubble” including mapping the different CO2 levels and quantifying the amount of CO2 at each level (Fig. 24).
Quantitative interpretation of the time lapse seismic data is necessarily linked both to the choice of an appropriate rock physics model, i.e. Gassmann (1951) and also to assumptions on saturation ranges and temperatures. By making these assumptions, a mass balance can be attempted by comparing the actual injected quantity of CO2 with the seismically derived quantity. Such an analysis has the potential to confirm (as a first order approximation) whether all of the CO2 is imaged by the time lapse seismic data. A reasonable match between the reservoir simulation model and the seismic data is required to gain insight in the predictive power of the reservoir simulation.
8.3.4 Monitoring the injection process
Time lapse seismic data - The major success of the SACS project has been the demonstration that conventional, time-lapse, p-wave seismic data can be a successful monitoring tool for CO2 injected into a saline aquifer (Eiken et al. 2000). Even with the CO2 in a supercritical, rather than a gaseous, state it has been shown that CO2 accumulations with a thickness as low as about a metre can be detected - far below the conventional seismic resolution limit of approximately 7 m. Even these thin accumulations cause significant, observable and measurable changes in the seismic signal, both in amplitude and in travel time (Figure 23a).
It is exactly this major effect on the time lapse seismic signal of relatively thin CO2 accumulations that has built confidence that any major leakage into the overlying caprock succession would have been detected. So far, no changes in the overburden have been observed in the Sleipner, implying that there are no leakages from the Utsira formation.
The time lapse seismic data have provided insights into the geometrical distribution of the injected CO2 at different time steps and show the different migration pathways (Figures 23b and 22c). Due to the lower density of CO2 with respect to the formation water, buoyancy is the dominant physical process governing the migration. The seismic data have revealed at least temporary barriers (very thin shale layers) to vertical migration of the CO2 that could not be resolved on the pre-injection baseline data alone. Due to the pronounced effect of the CO2 on the amplitude of the time lapse seismic signal these barriers have been mapped locally, markedly increasing the understanding of the CO2 migration within the reservoir. At various
locations chimneys have been observed where CO2 passes through the thin shale layers (Figure 23b). The presence of thin shale layers has radically affected the CO2 distribution in the reservoir, with CO2 migrating laterally for several hundred metres beneath the intra- reservoir shales (Fig. 23c). It the longer term, this dissemination of CO2 throughout the
reservoir thickness (rather than just being concentrated at the top) may allow more efficient dissolution of CO2 and effectively increase the reservoir capacity (Torp and Gale, 2003). Interpretation of the post-stack seismic data has provided much of the information required to characterise the “CO2 bubble” including mapping the different CO2 levels and quantifying the amount of CO2 at each level (Fig. 24).
Quantitative interpretation of the time lapse seismic data is necessarily linked both to the choice of an appropriate rock physics model, i.e. Gassmann (1951) and also to assumptions on saturation ranges and temperatures. By making these assumptions, a mass balance can be attempted by comparing the actual injected quantity of CO2 with the seismically derived quantity. Such an analysis has the potential to confirm (as a first order approximation) whether all of the CO2 is imaged by the time lapse seismic data. A reasonable match between the reservoir simulation model and the seismic data is required to gain insight in the predictive power of the reservoir simulation.
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