Characterization of fluvial architectural elements using a three-dimensional outcrop data set: Escanilla braided system, South-Central Pyrenees, Spain

Abstract

Hydrocarbon recovery in clastic reservoirs depends essentially on how well we understand the precise architecture of sand bodies and intercalated shaly baffl es and barriers. Various methods have been developed for enriching the fundamental data collection from outcrop analogs; these include Terrestrial Laser Scanning (groundbased lidar), digital photogrammetry, highprecision GPS survey, etc. The three-dimensional outcrop data sets collected using these methods are critical for understanding the link between seismic-scale and well-scale data in the subsurface. This study illustrates a methodology for integrating three-dimensional outcrop data, interpreting that data, and integrating the resulting interpretations with data from traditional outcrop measurements. A reservoir model of a fl uvial sequence from the Escanilla Formation in the Ainsa Basin of northern Spain was produced using this methodology. Three-dimensional aerial photographs and laser scanner outcrop capture techniques provide a robust and fl exible data set that can spatially constrain the modeling of observed features. The three-dimensional outcrop reconstruction, coupled with sequence stratigraphy concepts, enables the morphology, size, and distribution of key architectural elements to be modeled in subsurface reservoirs. The reservoir model constructed from these data allows geologists and reservoir engineers to evaluate the critical differences between real and modeled heterogeneities and provides a mechanism for an improved understanding of modeling subsurface reservoirs.

Creating three-dimensional channel bodies in LiDAR-integrated outcrop characterization: A new approach for improved stratigraphic analysis

“…Guided by the norm that channel sand-body true width is always measured perpendicular to paleoflow direction, we performed channel sand-body width correction in the ArcMap interface. We targeted this dimensional correction to add more interpretation value to our results (e.g., Labourdette and Jones, 2007). Without sand-body width correction, dimensional analyses of channel sand bodies will likely be spurious.…”

“…Integration of light detection and ranging (LiDAR) technology into geological studies has been increasingly popular, with applications ranging from lava flow (e.g., Cashman et al, 2013) to fracture characterization (e.g., Olariu et al, 2008;Wilson et al, 2011) to sedimentologic-stratigraphic investigation (e.g., Bellian et al, 2005;Labourdette and Jones, 2007) to human habitat facilities (e.g., fault-scarp characterization beneath human civic facility; Engelkemeir and Khan, 2008). The ease of robust data collection using the LiDAR technology, in either completing field-data acquisition within a short time period or providing an alternative data resource where inaccessible terrain hinders direct field site investigation, has fueled the widespread use of LiDAR technology.…”

“…Thus far, use of LiDAR data in fluvial stratigraphic analysis includes: (1) spatial variability of facies in 3-D digital outcrop models (e.g., Bellian et al, 2005), (2) facies analysis and deterministic models for flow simulation (e.g., Labourdette and Jones, 2007), and (3) channel sand-body dimensional attributes (e.g., Fabuel-Perez et al, 2009;Rittersbacher et al, 2013Rittersbacher et al, , 2014. The creation of 3-D channel bodies using LiDAR data at a stratigraphic scale yields a spatio-temporal model of channelized sand bodies in a sedimentary basin and contributes significantly toward fluvial stratigraphic analysis on a range of time scales from short-(single to tens of thousands of years) to long-term (hundreds of thousands to millions of years).…”

Applications of digital outcrop models: two fluvial case studies from the Triassic Wolfville Fm., Canada and Oukaimeden Sandstone Fm., Morocco

“…Data in digital outcrop studies can be collected using several tools such as terrestrial or airborne scanning LiDAR and laser ranging as well as Real Time Kinematic (RTK) or Differential (D) GPS, high-resolution shallow seismic, Ground Penetrating Radar (GPR) and boreholes (Corbeanu et al 2001;Hodgetts et al 2004;Jones et al 2004;Verwer et al 2004a;Verwer et al 2004b;Labourdette and Jones 2007;Viseur et al 2007;Engelkemeir and Khan 2008;Jones et al 2008a;2008b;Fabuel-Perez et al 2009a;Verwer et al 2009a;. Valuable additional data (e.g.…”

“…The use of digital field techniques is becoming a more common tool to aid fieldwork and some powerful applications have been demonstrated in recent studies, for example in sedimentological and structural studies (Hodgetts et al 2004;Verwer et al 2004b;Adams et al 2005;Labourdette and Jones 2007;Phelps and Kerans 2007;Olariu et al 2008;Phelps et al 2008;Fabuel-Perez et al 2009a;Hodgetts 2009;Verwer et al 2009a;Verwer et al 2009b;Wilson et al 2009) as well as in earth surface process (Wawrzyniec et al 2007;McCormick et al 2008) and ichnology (Bates et al 2008). Work has further focussed on how the digital data can best be captured and visualized, and in quantifying uncertainties inherent in the datasets (Bond et al 2007;Enge et al 2007;Verwer et al 2007;Buckley et al 2008).…”