Tectonic architectures span at least 12 orders of magnitude from individual microstructures to lithospheric plates. Traditional paper-based geological mapping and fieldwork techniques have not been able to accurately capture the geospatial properties of mesoscale (10-2 102 m) features in surface outcrops. In addition, geophysical imaging of the subsurface is poor at these length scales. This lack of fine-scale spatial precision has meant that the superbly detailed lithological units and structures we see in surface outcrops have not been integrated directly into predictive numerical and analogue models. As a result, models created to simulate the spatial heterogeneity that we see at the mesoscale are currently not well calibrated to natural datasets. It is therefore difficult to even partially confirmat predictive, three dimensional (3D) models at this scale. This creates significant problems for industrial users interested in the extraction or storage of fluids in subsurface reservoirs, since accurate predictions of these processes rely critically on a complete 3D understanding of the subsurface mesoscale geology.
New digital data capture methods can now provide photorealistic, spatially precise and geometrically accurate 3D Virtual Outcrops Models of geological exposures. Terrestrial laser scanners and Real Time Kinematic (RTK) GPS units are the principal tools used for capture of surface outcrop data. Automatic data collection involves scanning the outcrop surface with a laser to capture the topography with a cm-spaced grid of spatial coordinates in x, y and z. Using built-in digital cameras, the most recent laser scanners collect registered photographs that allow the software to colour the points to match the outcrop, and produce a photo-realistic 3D image. Laser scanning produces large volumes of data rapidly (up to 12,000 points per second), but the range of attributes is limited, and it works best on cliff sections or in mines and quarries where the scanner can be placed directly in front of the outcrop. With RTK GPS data collection, any measurable attribute (surface dip, strike, lithology) can be recorded together with the spatial coordinates at a user-controlled sample spacing down to c. 5 cm. The efficiency of data collection is determined by the speed at which the attribute is measured, but this is unlikely to be faster than 1 per second. As the method is GPS-based, it works best on sub-horizontal outcrop surfaces with an unobstructed view of the sky. Photographs can be draped onto the topographic surfaces created using RTK GPS, allowing the surface geology to be analysed in detail within an immersive 3D visualisation environment. An additional advantage is that these outcrop-scale data can be easily integrated into a single standardised database, e.g. a 3D Geographical Information System (GIS) and combined with other geological or geophysical datasets collected across a range of scales.
The key advantage over traditional structural mapping is that every structure is precisely located in space. Our examples show how digital datasets provide a 3D geological model that can be used to calibrate mesoscale numerical and analogue models in the same way that geophysical datasets (seismic reflection, gravity and magnetics) are used to constrain lithosphere geodynamic and basin models. The fundamental challenge for these new methods will be to deliver improved fine-scale geological constraint on predictive geomechanical models, allowing fine-tuning of sub-seismic resolution structure in oil reservoirs models.