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Chapter 5: Underground geological storage 229 significant discrepancies. Most discrepancies could be traced to differences in fluid property descriptions, such as fluid densities and viscosities and mutual solubility of CO2 and water. The study concluded that ‘although code development work undoubtedly must continue . . . codes are available now that can model the complex phenomena accompanying geological storage of CO2 in a robust manner and with quantitatively similar results’ (Pruess et al., 2004). directly validated on a field scale because these reactions may take hundreds to thousands of years. However, the simulation of important mechanisms, such as the convective mixing of dissolved CO2, can be tested by comparison to laboratory analogues (Ennis-King and Paterson, 2003). Another possible route is to match simulations to the geochemical changes that have occurred in appropriate natural underground accumulations of CO2, such as the precipitation of carbonate minerals, since these provide evidence for the slow processes that affect the long-term distribution of CO2 (Johnson et al., 2005). It is also important to have reliable and accurate data regarding the thermophysical properties of CO2 and mixtures of CO2 with methane, water and potential contaminants such as H2S and SO2. Similarly, it is important to have data on relative permeability and capillary pressure under drainage and imbibition conditions. Code comparison studies show that the largest discrepancies between different simulators can be traced to uncertainties in these parameters (Pruess et al., 2004). For sites where few, if any, CO2-water-rock interactions occur, reactive chemical transport modelling may not be needed and simpler simulations that consider only CO2-water reactions will suffice. 5.4.3 Examples of storage site characterization and performance prediction Following are examples and lessons learned from two case studies of characterization of a CO2 storage site: one of an actual operating CO2 storage site (Sleipner Gas Field in the North Sea) and the other of a potential or theoretical site (Petrel Sub-basin offshore northwest Australia). A common theme throughout these studies is the integration and multidisciplinary approach required to adequately document and monitor any injection site. There are lessons to be learned from these studies, because they have identified issues that in hindsight should be examined prior to any CO2 injection. 5.4.3.1 Sleipner Studies of the Sleipner CO2 Injection Project (Box 5.1) highlighted the advantages of detailed knowledge of the reservoir stratigraphy (Chadwick et al., 2003). After the initial CO2 injection, small layers of low-permeability sediments within the saline formation interval and sandy lenses near the base of the seal were clearly seen to be exercising an important control on the distribution of CO2 within the reservoir rock (Figure 5.16a,b). Time-lapse three-dimensional seismic imaging of the developing CO2 plume also identified the need for precision depth mapping of the bottom of the caprock interval. At Sleipner, the top of the reservoir is almost flat at a regional scale. Hence, any subtle variance in the actual versus predicted depth could substantially affect migration patterns and rate. Identification and mapping of a sand lens above what was initially interpreted as the top of the reservoir resulted in a significant change to the predicted migration direction of the CO2 (Figure 5.16a,b). These results show the benefit of repeated three-dimensional seismic monitoring and integration of monitoring results into Another, similar intercomparison study was conducted for simulation of storage of CO2 in coal beds, considering both pure CO2 injection and injection of flue gases (Law et al., 2003). Again, there was good agreement between the simulation results from different codes. Code intercomparisons are useful for checking mathematical methods and numerical approximations and to provide insight into relevant phenomena by using the different descriptions of the physics (or chemistry) implemented. However, establishing the realism and accuracy of physical and chemical process models is a more demanding task, one that requires carefully controlled and monitored field and laboratory experiments. Only after simulation models have been shown to be capable of adequately representing real-world observations can they be relied upon for engineering design and analysis. Methods for calibrating models to complex engineered subsurface systems are available, but validating them requires field testing that is time consuming and expensive. The principal difficulty is that the complex geological models on which the simulation models are based are subject to considerable uncertainties, resulting both from uncertainties in data interpretation and, in some cases, sparse data sets. Measurements taken at wells provide information on rock and fluid properties at that location, but statistical techniques must be used to estimate properties away from the wells. When simulating a field in which injection or production is already occurring, a standard approach in the oil and gas industry is to adjust some parameters of the geological model to match selected field observations. This does not prove that the model is correct, but it does provide additional constraints on the model parameters. In the case of saline formation storage, history matching is generally not feasible for constraining uncertainties, due to a lack of underground data for comparison. Systematic parameter variation routines and statistical functions should be included in future coupled simulators to allow uncertainty estimates for numerical reservoir simulation results. Field tests of CO2 injection are under way or planned in several countries and these tests provide opportunities to validate simulation models. For example, in Statoil’s Sleipner project, simulation results have been matched to information on the distribution of CO2 in the subsurface, based on the interpretation of repeat three-dimensional seismic surveys (Lindeberg et al., 2001; van der Meer et al., 2001; see also Section 5.4.3. At the Weyburn project in Canada, repeat seismic surveys and water chemistry sampling provide information on CO2 distribution that can likewise be used to adjust the simulation models (Moberg et al., 2003; White et al., 2004). Predictions of the long-term distribution of injected CO2, including the effects of geochemical reactions, cannot bePDF Image | CARBON DIOXIDE CAPTURE AND STORAGE
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