Elsevier, Tectonophysics, 1-2(361), p. 97-120
DOI: 10.1016/s0040-1951(02)00586-3
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The 3-D seismic tomographic data are used together with field, core and well log structural information to determine the detailed 3-D architecture of fault zones in a granitic massif of volume 500×575×168 m at Mina Ratones area in the Albalá Granitic Pluton. To facilitate the integration of the different data, geostatistical simulation algorithms are applied to interpolate the relatively sparse structural (hard) control data conditioned to abundant but indirect 3-D (soft) seismic tomographic data. To effectively integrate geologic and tomographic data, 3-D migration of the velocity model from the time domain into the depth domain was essential. The resulting 3-D model constitutes an image of the fault zone architecture within the granitic massif that honours hard and soft data and provides an evaluation of the spatial variability of structural heterogeneities based on the computation of 3-D experimental variograms of Fracture Index (fault intensity) data. This probabilistic quantitative 3-D model of spatially heterogeneous fault zones is suitable for subsequent fluid flow simulations. The modeled image of the 3-D fault distribution is consistent with the fault architecture in the Mina Ratones area, which basically consists of two families of subvertical structures with NNE–SSW and ENE–WSW trends that displaces the surfaces of low-angle faults (North Fault) and follows their seismically detected staircase geometry. These brittle structures cut two subvertical dykes (27 and 27′ Dykes) with a NNE–SSW to N–S trend. The faults present high FI (FI>12) adjacent bands of irregular geometry in detail that intersect in space delimiting rhombohedral blocks of relatively less fractured granite (FI<6). Both structural domains likely correspond with the protolith and the damaged zone/fault core in the widely accepted model for fault zone architecture. Therefore, the construction of 3-D grids of the FI in granitic areas affected by brittle tectonics permits the quantitative structural characterization of the rock massif.