Outcrop analogues: the good, the bad and the ugly. Journal of Mediterranean Earth Sciences

The amount of subsurface data available to characterize subsurface reservoirs and de-risk uncertainty at different scale of observation represents one of the main challenges in exploration and production. A sound-outcrop-based conceptual depositional model is key to reducing such uncertainties (Martinius, 2017; Rossi et al., 2017). Ancient and present-day analogues are extensively used to provide valuable information on geobody size, geometry and internal characterization representing a valuable tool in improving understanding of subsurface reservoir (Chiarella et al., 2012; Chiarella et al., 2016; Telesca et al., this volume). Analogue data can be classified in four key types: (i) soft data, which include information about the facies and their lateral and vertical relationship; (ii) hard data, which describe the dimensions and geometry of the geobody; (iii) training images, which record the dimensions, proportions and spatial relationship; and (iv) analogue production data, which provide data from direct subsurface production analogues (Howell et al., 2014). An important aspect that needs to be considered is the areal coverage of the outcrop in comparison with the subsurface reservoir - the typical size for an oil field is between 2 and 20 km, and wells are usually spaced from a few hundred metres to a few kilometres apart. Consequently despite the plethora of high-quality outcrops around the world, there are only a limited number that are large enough to make them suitable for the collection of data at a scale that is really suitable to understand reservoir geometries at a field or even interwell spacing (Howell et al., 2014). At the same time, for the few outcrops that are large enough to overcome the size of the typical oil field (e.g. Book Cliff and Karoo Basin) the identification of which part of the depositional system best represents the studied reservoir can be challenging. Therefore, not all analogues provide valuable information for reservoir characterisation. A step towards improving the applicability of outcrop analogues to subsurface case studies, has been the advent of Virtual Outcrop studies with the development of LiDAR and photogrammetric based acquisition systems. This has improved our ability to generate “reservoir models” of the outcrops, which can be flow simulated closing the loop between the outcrop and the subsurface (e.g. Enge and Howell, 2010; Fig. 1). Further, the generation of synthetic seismic data from outcrops (e.g. Bakke et al., 2008) has also helped to close the gap between the outcrop analogue and the subsurface dataset. However, it is important to note that no two systems are identical and therefore the ‘perfect’ analogue does not exist. What we strive for is to combine studies from several partial analogues and to improve the conceptual geological model. In that respect, it is important to have clear in mind the purpose and scale of your study in order to select the appropriate analogues to incorporate.