CREATING 2-D AND 3-D DIGITAL MODELS OF LITHOLOGIC HETEROGENEITY FOR HYDROLOGIC INVESTIGATIONS IN THE BASIN AND RANGE/RIO GRANDE RIFT BASINS (Invited Presentation)

Numerical hydrologic models require the definition of horizontal hydraulic conductivity throughout the model volume for each model unit of interest. In many instances, geologic heterogeneity is known to, or can be assumed to, influence groundwater movement. Thus, it is useful to develop a spatially distributed array of geologic properties, such as lithology, that can be a starting point for the estimation of hydraulic properties. Sedimentary deposits in extensional and rift basin settings tend to be difficult to characterize in three dimensions due to spatially varying facies patterns, active tectonism which influence facies patterns, lack of deep well data and age control, and complex interfingering with rift-related volcanic units. Two examples are presented for using geologic data to create deterministic, data-driven 2-D and 3-D spatial arrays to describe the heterogeneity of the geologic system.

In Rio Grande rift basins of southernmost New Mexico, a digital 3-D geologic framework model was constructed by combining faults, elevation of the tops of stratigraphic units, and boundary lines depicting the subsurface extent of each unit. For basin-filling Santa Fe Group rocks, 2-D lithofacies-based zones were derived from lithofacies assemblages shown on previously published cross sections; 2-D zones of river channel deposits were based on interpretation of soil survey data. These zones were then imprinted on the 3-D geologic framework model for each unit. In the composite extensional and strike-slip Amargosa basin in southern Nevada and eastern California, lithologic data from 505 boreholes were reduced to a limited suite of descriptors based on geologic knowledge of the basin; the data were then distributed in three-dimensional space using 3-D interpolation methods. Lithologic units were grouped into interpreted genetic classes, such as playa or alluvial fan, to create a three-dimensional model of the interpreted facies data. The lithologic and interpreted facies models compare favorably to resistivity, aeromagnetic, and geologic map data, lending confidence to the interpretation. However, both approaches are fundamentally limited by the undersampling of the subsurface in comparison with information that is obtained from surface geologic mapping.