Geologically-and structurally-based characterization of reservoir analogs using lidar-derived quantitative

Like many fields in earth sciences, petroleum geology is an area that requires high-quality spatial data. Recent advances in terrestrial light detection and ranging (LIDAR) technology and photogrammetry resulted in rapid expansion of capabili-ties in terms of accurate data collection, visualization and analysis, fueled by the need to resolve geometrical properties of smaller scale geologic features that affect fluid flow, such as shale drapes or fractures. The study of sedimentary rock out-crops are of particular interest as they can be used as analogs for similar petroleum reservoir rocks.

By harnessing recent developments in 3D digital imaging, this study ad-dresses: (1) characterization of shales and their impact on permeability anisotropy (𝑘𝑘𝑣𝑣𝑘𝑘ℎ⁄) in tidally-influenced fluvial deposits; (2) characterization of fracture at-tributes from 3D surface reconstructions; and (3) the utility of calibrated LIDAR intensity as a remote spectral sensor.

The Cretaceous Ferron Sandstone is an outcrop analog for fluvial–tidal sys-tems with primary reservoirs being tidally-influenced point bars. Detailed shale characteristics were measured to test the hypothetical relationships between dep-ositional environment and shale character and to use these observations to make geologically-based estimates of 𝑘𝑘𝑣𝑣𝑘𝑘ℎ⁄. Long, infrequent, and anisotropic shales vii were associated with braided setting, whereas short, abundant and equidimensional shales were common in meandering river deposits. Moreover, the unique character of each depositional unit was reflected in the estimated 𝑘𝑘𝑣𝑣𝑘𝑘ℎ⁄ distributions. More tidally-influenced reservoirs resulted in low 𝑘𝑘𝑣𝑣𝑘𝑘ℎ⁄ estimates (0.09), whereas 𝑘𝑘𝑣𝑣𝑘𝑘ℎ⁄ for reservoirs that contained predominantly fluvial facies was higher (0.17). 

The fracture system developed within the exposures of Mississippian Boone Formation was characterized using a hybrid approach, combining LIDAR-based digital outcrop models and georeferenced high-quality photomosaics. The results suggest that LIDAR, coupled with referenced gigapixel photomosaics provides an effective medium for fracture identification with the capacity of resolving fracture characteristics with sufficient fidelity, making it an attractive alternative for frac-ture modeling workflows.

Ability of LIDAR as a spectral sensor to detect grain size was tested with an experiment consisting of sandpapers. LIDAR intensity approximated target re-flectance after being calibrated. Fine-grained sandpapers were more reflective of the near-infrared wavelength of the LIDAR laser source. The close agreement be-tween LIDAR-generated and laboratory measured reflectance data signaled the potential of calibrated laser as a spectral tool for effective grain size determination.