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Towards Crustal Reservoir Flow Structure Modelling Through Interactive 3D Visualization of MEQ & MT Field Data

We seek to use modern 3D graphics visualization to enable human visual pattern recognition to assess reservoir structures manifested by in situ fracture systems. In situ flow structures of crustal reservoirs have hitherto been largely assumed to be tied to specific formations and essentially uniform within a given formation. However, neither working assumption has been particularly successful in guiding the drill bit to new active portions of a given geothermal field. A greater degree of in situ spatial flow complexity is hypothesized, and that complexity is almost certainly due to fracture-system control of reservoir fluid pathways. Four types of geophysical field data have demonstrated a close association with in situ fracture content: microseismic event locations, microseismic shear wave splitting density and alignment, magnetotelluric resistivity distributions and magnetotelluric polarization alignment. Visually combining any/all such geophysical field data 3D distributions would help reservoir operators to formulate more rational drilling assessments based on fracture content of the reservoir formations. To this end, we define the general 3D data visualization problem ( Rugis 2008) in an abstract way in which we map either a structured or unstructured finite discrete position mesh into 3D space and then assign scalar and/or vector data values, possibly time varying, to elements of that mesh. In practice, fracture-relevant geophysical data-sets can consist of point data (e.g., microseismic event locations and magnitudes), 2D mesh data (e.g., electrical conductivity data along multiple planar-cut grids) or volumetric data (e.g., tomographic treatments of shear-wave splitting data) and each of these data types can be assigned to an appropriately designed common mesh in a natural way. We present data treatments using a software toolset of complementary packages within a well-defined data interface to allow ready application to specific reservoir data sets, ultimately including 3D flow modelling. Data sets treated are synthetic microseismic event locations based on spatial correlations observed in geothermal field microseismic data (Section 2); synthetic porosity/fracturedensity distributions consistent with observed well-log spatial fluctuation statistics (Section 3); seismic wave speed distributions inferred from geothermal field microseismic event locations (Section 4); the spatial distribution of in situ fracture density from observation of seismic shear-wave splitting (Section 5); magnetotelluric survey inversions from forward modelled response curves for synthetic spatial distributions of fracture density fluctuations based on a generic geothermal low resistivity plume (Section 6).