Uncertainties in reservoir geometry are significant if the injection is into a reservoir with gentle dips and only minor topography at its top (as at Sleipner), therefore, very detailed depth mapping is required (Figure 20c). This will permit accurate definition of the structure of the top surface to allow the prediction of the overall migration direction and evaluation of the location and volume of any structurally defined traps along the migration paths. This was done using a 3D seismic data around the injection site. Moreover, it requires velocity control from nearby boreholes to effectively minimise uncertainties in depth conversion.
Although significant faulting has not been identified so far in the Sleipner CO2 repository, in the general case it is important to identify and map any faults in the reservoir and caprock, and to make some assessment of fault sealing capacity (e.g. by empirical fault gouge shale ratio estimation), so as to be able to detect and assess possible reservoir compartmentalization and/or the potential for fault-related leakage.
Knowledge of reservoir properties, such as porosity and permeability, is required to quantify potential storage capacity and likely migration paths and rates. To determine these properties, core material from the reservoir close to the injection was used. Core and cuttings material from additional wells will further improve characterisation, particularly if vertical and lateral reservoir inhomogeneity is suspected. Determinations from material in the likely CO2 migration pathway, i.e. the top of the reservoir, are of particular importance. Analysis of the reservoir properties was supplemented by mineralogical analysis using XRD (x-ray diffraction) and geophysical logs such as γ-ray and sonic logs. The geophysical log data were used to extrapolate the physical property from the coring point(s) from wells at least as far from the injection point as the predicted CO2 migration (Figure 21). In regional terms the fairly sparse cover of wells appears sufficient to characterise the reservoir adequately in terms of broad stratigraphy and storage capacity (Table 5).
Assessment of the total reservoir storage potential (Effective Storage Capacity) is desirable, so that a proper injection strategy can be devised. This entails determination of the internal stratigraphy of the reservoir. At Sleipner, the presence of thin shale beds is radically affecting CO2 distribution in the reservoir, with CO2 migrating laterally for several hundred metres beneath intra-reservoir shales (see below). It is likely that in 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 well above the minimum value defined by the volume of the top reservoir traps. None of these thin shale beds were clearly resolved on the seismic data (not even on the 3D data) and require geophysical well logs for their identification (even utilising log data, the thinner shales are below the thickness resolution limit).
Uncertainties in reservoir geometry are significant if the injection is into a reservoir with gentle dips and only minor topography at its top (as at Sleipner), therefore, very detailed depth mapping is required (Figure 20c). This will permit accurate definition of the structure of the top surface to allow the prediction of the overall migration direction and evaluation of the location and volume of any structurally defined traps along the migration paths. This was done using a 3D seismic data around the injection site. Moreover, it requires velocity control from nearby boreholes to effectively minimise uncertainties in depth conversion.
Although significant faulting has not been identified so far in the Sleipner CO2 repository, in the general case it is important to identify and map any faults in the reservoir and caprock, and to make some assessment of fault sealing capacity (e.g. by empirical fault gouge shale ratio estimation), so as to be able to detect and assess possible reservoir compartmentalization and/or the potential for fault-related leakage.
Knowledge of reservoir properties, such as porosity and permeability, is required to quantify potential storage capacity and likely migration paths and rates. To determine these properties, core material from the reservoir close to the injection was used. Core and cuttings material from additional wells will further improve characterisation, particularly if vertical and lateral reservoir inhomogeneity is suspected. Determinations from material in the likely CO2 migration pathway, i.e. the top of the reservoir, are of particular importance. Analysis of the reservoir properties was supplemented by mineralogical analysis using XRD (x-ray diffraction) and geophysical logs such as γ-ray and sonic logs. The geophysical log data were used to extrapolate the physical property from the coring point(s) from wells at least as far from the injection point as the predicted CO2 migration (Figure 21). In regional terms the fairly sparse cover of wells appears sufficient to characterise the reservoir adequately in terms of broad stratigraphy and storage capacity (Table 5).
Assessment of the total reservoir storage potential (Effective Storage Capacity) is desirable, so that a proper injection strategy can be devised. This entails determination of the internal stratigraphy of the reservoir. At Sleipner, the presence of thin shale beds is radically affecting CO2 distribution in the reservoir, with CO2 migrating laterally for several hundred metres beneath intra-reservoir shales (see below). It is likely that in 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 well above the minimum value defined by the volume of the top reservoir traps. None of these thin shale beds were clearly resolved on the seismic data (not even on the 3D data) and require geophysical well logs for their identification (even utilising log data, the thinner shales are below the thickness resolution limit).
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