Hydrocarbon recovery in clastic reservoirs depends essentially on the quality of our understanding of the precise architecture of sand bodies and intercalated shaly baffles and barriers. Various methods have been developed for enriching the fundamental data collection from outcrop analogues, including Terrestrial Laser Scanning digital photogrammetry, high-precision GPS survey, etc. The three-dimensional outcrop datasets collecting using these methods are critical for understanding the link between seismic-scale and well-scale data in the subsurface.
In this study, we illustrate a methodology for integrating 3D outcrop data, interpreting them, and using the interpretation, along with data integrated from traditional outcrop measurements, to produce a reservoir model of a fluvial sequence from the Escanilla Formation in the Ainsa sub-basin of northern Spain. The use of laser scanner outcrop capture techniques (LiDAR) provides a robust and flexible data set that can spatially constrain the modeling of observed features. The three-dimensional outcrop reconstruction, coupled with sequence stratigraphy concepts allows the morphology, size and distribution of key architectural elements to be modeled in subsurface reservoirs. Using streamline simulations, the different observed heterogeneity levels are tested, in order to sort and classify them according to their dynamic impact and stratigraphic position.
The reservoir model constructed from these data allows geologists and reservoir engineers to see the critical differences between real and modeled heterogeneities, and provides a mechanism for an improved understanding of modeling subsurface reservoirs.