From outcrop to reservoir simulation model: Workfl ow and procedures Håvard D. Enge* Department of Earth Science, University of Bergen, Post box 7800, N-5020 Bergen, Norway, and Centre for Integrated Petroleum Research, University of Bergen, Post box 7800, N-5020 Bergen, Norway Simon J. Buckley Centre for Integrated Petroleum Research, University of Bergen, Post box 7800, N-5020 Bergen, Norway Atle Rotevatn Department of Earth Science, University of Bergen, Post box 7800, N-5020 Bergen, Norway, and Centre for Integrated Petroleum Research, University of Bergen, Post box 7800, N-5020 Bergen, Norway John A. Howell Centre for Integrated Petroleum Research, University of Bergen, Post box 7800, N-5020 Bergen, Norway ABSTRACT titative data on body geometry, and dynamic software; and (3) other applications of the col- investigation involves the simulation of fl uid lected data and the virtual outcrop. Since the pio- Advances in data capture and computer fl ow through the analog model. neering work of Bellian et al. (2005), there has technology have made possible the collection The work presented in this study dem- been a rapid increase in the application of lidar of three-dimensional, high-resolution, digital onstrates the utility of lidar as a data col- to the study and characterization of geological geological data from outcrop analogs. This lection technique for the building of more outcrops. Numerous groups are now working paper presents new methodologies for the accurate outcrop-based geocellular models. with such data, although, to date, no systematic acquisition and utilization of three-dimen- The aim of this publication is to present the methodologies for the collection, processing, sional information generated by ground- fi rst documentation of a complete workfl ow and utilization of these data have been published based laser scanning (lidar) of outcrops. A that extends from outcrop selection to model (e.g., Adams et al., 2007; Aiken, 2006; Deveu- complete workfl ow is documented—from investigation through the presentation of two gle et al., 2007; Enge et al., 2007; Enge et al., outcrop selection through data collection, worked data sets. 2006; Howell et al., 2007; Howell et al., 2006; processing and building of virtual outcrops— Jones et al., 2007; Lee et al., 2007; Martinsen et to geological interpretation and the building Keywords: outcrop analogs, laser methods, Pyr- al., 2007; Monsen, 2006; Oftedal et al., 2007; of geocellular models using an industry-stan- enees, sandstone, deltas, clinoforms, Canyonlands Olariu et al., 2005; Pedersen et al., 2007; Thur- dard, reservoir-modeling software. Data sets National Park, grabens, ramps, fault blocks, reser- mond, 2006). This paper documents a complete from the Roda Sandstone in the Spanish voir, modeling, analog simulation, fl uid. workfl ow, from outcrop selection through data Pyrenees and the Grabens region of Canyon- collection, processing, and interpretation, to the lands National Park, Utah, USA, are used to INTRODUCTION building of the geocellular model. The workfl ow illustrate the application of the workfl ow to is illustrated with two case studies that illustrate sedimentary and structural problems at a The intention of this study is to present new the application to sedimentary and structural reservoir scale. methodologies for the acquisition and utilization reservoir, geology-related problems. Subsurface reservoir models are limited of three-dimensional (3D) information gener- Lidar, which stands for light detection and by available geological data. Outcrop analogs ated by the ground-based laser scanning (lidar) ranging, includes both aerial and ground-based from comparable systems, such as the Roda of geological outcrops. In particular, the focus is techniques (Ackermann, 1999; Buckley et al., Sandstone and the Grabens, are commonly on (1) the accurate representation of geological 2006; Wehr and Lohr, 1999). Originally devel- used to provide additional input to models of entities from outcrops on a computer (referred to oped for aerial surveying, especially topographic the subsurface. Outcrop geocellular models in this paper as a “virtual outcrop”); (2) utilizing mapping, the technique allows the rapid collec- can be analyzed both statically and dynami- the virtual outcrop to extract data for the build- tion of spatially constrained point data that can cally, wherein static examination involves ing and testing of 3D geocellular models using capture the shape of a scanned feature (Baltsav- visual inspection and the extraction of quan- conventional, hydrocarbon reservoir-modeling ias, 1999; Baltsavias et al., 2001; Nagihara et *[email protected] Geosphere; December 2007; v. 3; no. 6; p. 469–490; doi: 10.1130/GES00099.1; 17 fi gures; 1 table. For permission to copy, contact [email protected] 469 © 2007 Geological Society of America Downloaded from http://pubs.geoscienceworld.org/gsa/geosphere/article-pdf/3/6/469/854380/i1553-040X-3-6-469.pdf by guest on 26 September 2021 Enge et al. al., 2004). A geocellular model is a computer- fi eld; (4) safe access to vertical and sub-vertical rapidly in popularity (McCaffrey et al., 2005). based representation of a geological volume, portions of the outcrop; (5) the ability to iter- These methods were reviewed by Pringle et typically a subsurface reservoir. The model ate between the outcrop and the model during al. (2006) and include a variety of techniques comprises mapped surfaces that defi ne zones. the model-building phase; and (6) the ability for producing data of different resolutions Zones are populated with cells, which, in turn, to illustrate the model and outcrop side by side and accuracies. The application of laser scan- are assigned parameters such as porosity, per- for training and teaching purposes. The collec- ning as a method for ground-based geological meability, facies, etc. Such models are routinely tion of ground-based lidar data and the building fi eldwork is now proven (Bellian et al., 2005; used to visualize and simulate the subsurface of virtual outcrops provide a means to address Buckley et al., 2006; Leren, 2007; Pringle et in the oil industry. Given the poor resolution these issues. al., 2004a; Pringle et al., 2006; Redfern et al., of seismic data (e.g., Pickup and Hern, 2002) 2007). The employment of lidar and the cre- and sparse frequency of wells in most oil fi elds Previous Work Review ation of virtual outcrops from the point clouds (typical spacing ~1 km), outcrop data are com- provide a means for the rapid collection and monly used to provide information on interwell The application of digital data collection tech- interpretation of large volumes of accurate facies and structural architectures (e.g., Alexan- niques for outcrop studies is not new. Stafl eu et geometric outcrop data. A particular advantage der, 1993; Dreyer et al., 1993; Pickup and Hern, al. (1996) acquired photogrammetric stereopairs of terrestrial lidar scanning is that resultant sur- 2002; Reynolds, 1999) (Fig. 1). Reservoir mod- of carbonate rock outcrops to form digital eleva- faces are more effi cient to produce and have eling software has long been used to represent tion models (DEMs). These were then linked a higher accuracy potential than photogram- geological outcrops (Bryant et al., 2000; Bryant with petrophysical data to identify a relation- metric surfaces, especially in areas that exhibit and Flint, 1993; Dreyer et al., 1993; Joseph et ship between erosion and rock impedance. Xu high relief, such as good quality geological al., 1993), both for direct reservoir analogs and et al. (2000; 2001) used the Global Positioning outcrops (Baltsavias et al., 2001; Buckley et also as a tool for capturing structural and strati- System (GPS) and a refl ectorless laser to col- al., 2006). graphic architecture (e.g., Bellian et al., 2005; lect outcrop data and construct surfaces. Adams The techniques for collecting, preparing, Weber, 1986; White et al., 2004; Willis and et al. (2005) used real-time kinematic GPS and and presenting scan data in a geologically White, 2000). Key issues with the utilization a total station for recording 3D datapoints from meaningful context have been reviewed by of outcrop data have been: (1) the collection of the outcrop. These were combined with a DEM several authors (McCaffrey et al., 2005; Prin- suffi cient volumes of spatially accurate data; created from photogrammetry to form the basis gle et al., 2004a; Pringle et al., 2006). Other (2) correlation of surfaces over long distances for a geocellular outcrop model. examples (e.g., Bryant et al., 2000; Pringle et and between individual outcrops; (3) the rec- Recently, the use of modern data collec- al., 2004b) show that the use of digital spatial ognition of subtle dip and strike changes in the tion techniques in fi eld geology has increased information in outcrop modeling is increasing. The utilization of the collected data, especially for the building of geocellular models is only beginning to be addressed (Dreyer et al., 1993; Løseth et al., 2003). While recent studies by authors such as Bryant et al. (2000) and Bel- 100m Virtual Outcrop lian et al. (2005) have discussed the possibili- ties for broader geological application, as yet Seismic data very little has been published other than “state- 10m of-the-art” papers describing the potential of ~ parasequences the technology. Simulation model Overview of the Paper 1m Grid-cell geological model This paper documents for the fi rst time a Grid-cell simulation “mini-model” systematic workfl ow from the collection of Logs 10cm raw scan data to utilization of the fi nal vir- Vertical Thickness Core/ tual outcrop and the building and testing of plug ~ bed models. The workfl ow is illustrated by the construction of two, detailed geocellular mod- 1cm els. The resulting models range in size from 100 × 100 × 2 m to several kilometers wide Probe ~ lamina and tens or even hundreds of meters thick, respectively, and illustrate the utility of vir- 1mm 1cm 10cm 1m 10m 100m 1km 10km tual outcrop data.