Basic Research Needs for Geosciences - Energetics Meetings and ...

GRAND CHALLENGE:INTEGRATED CHARACTERIZATION, MODELING, AND MONITORING OF GEOLOGIC SYSTEMSmanner. These limitations are compounded by constraints in available computational resources.Even with anticipated advancements in modeling theory, numerical methods, and computationalcapabilities, practical limitations in modeling the complex systems of interest in the geosciencesare likely to remain.Current modeling practices decouple both scales and physics, and integrate data, in an ad hocmanner. A rigorous paradigm for treating these problems in the geosciences is missing. This iscritical because incorrect treatment may lead to a gross accumulation of errors due to strongnonlinear couplings. Such strong nonlinearities are frequently encountered in multiphase flow(including partially saturated flow in the vadose zone), reactive transport, and geomechanics,although the spatial and temporal scales at which these processes need to be resolved aredifferent. There is a clear and urgent need to resolve these highly nonlinearly coupled processesin a way that preserves a theoretical and practical understanding of modeling and discretizationerrors. The scientific challenge is to determine the optimal level of modeling detail required toanswer specific questions with minimum violation of underlying physics and chemistry. Modelerror is thereby constrained, enabling models to provide an adequate representation of observedsystem behavior. One way to explore what levels of geologic detail are optimal is to work withmodels that are rich in details. Such geologic modeling is a challenge in itself, and is addressedin the next section.Geologic process models of subsurface structure and heterogeneityLarge-scale injection of fluids into the subsurface will drive a major new research agendafocused at understanding geological architecture and geomechanics at spatial scales ranging fromthe radius of the wellbore to the scale of basin-wide aquifers. At the local scale, the research willbe driven by concerns about injectivity of the fluids, its subsequent near-field migration path, andpotential fluid trapping mechanisms. At the large scale, the research will need to extend theprinciples of basin analysis that have evolved in the oil industry and academia over the past fewdecades (e.g., sequence stratigraphy, deep basin fluid circulation, 3D basin modeling).Substantial uncertainty is inherent in defining variable spatial patterns in rock properties atrelevant scales. This uncertainty can be reduced through collection of additional data and newmeasurement technologies, but it can almost never be eliminated. Subsurface scientists havemade important strides in dealing with uncertainty through the use of stochastic (geostatistical)descriptions of subsurface heterogeneity (e.g., Deutsch and Journel 1998; Carle et al. 1998;Figure 28). The stochastic methods suffer, however, from limitations in their ability to includecertain geologic structures (e.g., meandering patterns, faults, and permeability heterogeneity) thatcan be crucially important in mass transport analyses (e.g., Western et al. 2001; de Marsily et al.2005; Zinn and Harvey 2003). For example, the two spatial patterns in Figure 29 have the sameprobability densities and omnidirectional variograms, yet their connectivity is much different.Such spatial organization arises from the geological processes that laid down or modified therocks, and will ultimately be best incorporated through a new generation of stochastic orstochastic-deterministic methods that account for the geologic processes themselves (de Marsilyet al. 2005). Relatively new geostatistical approaches, such as the transition probability Markovchain approach (Figure 28 and Carle and Fogg 1997; Carle et al. 1998) and multiple-pointBasic Research Needs for Geosciences: Facilitating 21 st Century Energy Systems 81