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Quantitative Characterization of a Naturally Fractured Reservoir Analog

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Quantitative Characterization of a Naturally Fractured Reservoir Analog Research Paper GEOSPHERE Quantitative characterization of a naturally fractured reservoir GEOSPHERE; v. 14, no. 2 analog using a hybrid lidar-gigapixel imaging approach doi:10.1130/GES01449.1 Kivanc Biber1,2, Shuhab D. Khan1, Thomas D. Seers3, Sergio Sarmiento4, and M.R. Lakshmikantha4 1 14 figures; 7 tables Department of Earth and Atmospheric Sciences, University of Houston, 4800 Calhoun Road, Houston, Texas 77004, USA 2Statoil North America, 2107 CityWest Boulevard, Houston, Texas 77042, USA 3Department of Petroleum Engineering, Texas A&M University at Qatar Engineering Building, Education City, Doha, Qatar 23874 CORRESPONDENCE: kbiber@ uh .edu 4Repsol USA, Technology Hub, 2455 Technology Forest Boulevard, The Woodlands, Texas 77381, USA CITATION: Biber, K., Khan, S.D., Seers, T.D., Sarmiento, S., and Lakshmikantha, M.R., 2018, Quantitative characterization of a naturally fractured ABSTRACT 1. INTRODUCTION reservoir analog using a hybrid lidar-gigapixel imag- ing approach: Geosphere, v. 14, no. 2, p. 710–730, The inability to accurately resolve subseismic-scale structural discontinui- Understanding the orientation distribution and spatial configuration of doi:10.1130/GES01449.1. ties such as natural fractures represents a significant source of uncertainty natural fractures is important because these structural discontinuities signifi- for subsurface modeling practices. Fracture statistics collected from outcrop cantly influence the behavior of many oil and gas reservoirs. As such, they Science Editor: Raymond M. Russo Associate Editor: Francesco Mazzarini analogs are commonly used to fill the knowledge gap to reduce the uncer- impact fluid flow (e.g., Wilson et al., 2011b) and geomechanical state of the tainty related to fracture-induced permeability anisotropy. The conventional reservoirs (e.g., Heffer, 2012; Couples, 2013). Therefore, it is a common prac- Received 31 October 2016 methods of data collection from outcrops are tedious, time consuming, and tice to include the contribution of fractures into static and dynamic reservoir Revision received 23 September 2017 often biased due to accessibility constraints. Recent advances in virtual out- models and simulations (e.g., Wilson et al., 2011a, 2011b; Bisdom et al., 2014). Accepted 29 November 2017 crop-based methods in fracture characterization enhance conventional meth- Recent advances in the 3D seismic imaging and analysis now allow the con- Published online 12 January 2018 ods by streamlining data collection and analysis. However, certain limitations struction of geometrically accurate models with depositional and structural and challenges exist in virtually obtained fracture data sets. The ability to architectures constrained at resolutions of tens to hundreds of meters (Caers identify fractures that are both exposed as lineations and as planes from a et al., 2001). However, most structural heterogeneities that can significantly im- digital outcrop model depends heavily upon the fidelity and resolution of its pact reservoir behavior manifest at scales below the conventional subsurface surface display of RGB color, reducing the capacity of light detection and rang- imaging thresholds (~20 m; Mrics et al., 2005). Unobservable structural hetero- ing ( lidar) to the resolution of the scanner-attached camera. In the present geneities such as faults, fractures, and compression structures (e.g., stylolites study, we adopted a hybrid approach, combining lidar-based digital outcrop and compaction bands) introduce significant anisotropy within the rock mass models and georeferenced high-quality photomosaics, providing improved resulting in permeability corridors or baffles and/or barriers, with hydraulic texture maps in terms of pixel density compared to maps generated from conductivities typically several orders of magnitude higher or lower than the on-scanner camera images. With this approach, the effects of truncation on surrounding rock mass (Aydin, 2000). digital outcrop models were limited, giving the ability to detect fractures that The use of outcrop analogs to generate geological conditioning data is OLD G would otherwise be aliased from on-scanner camera imagery. The fracture a common strategy employed within reservoir modeling studies (e.g., Enge system developed within the exposures of the Mississippian Boone Forma- et al., 2007; Pranter et al., 2008). Scalable observations can be made from out- tion, an outcrop analog for age-equivalent reservoir objectives in Mississippi crops that are below conventional seismic thresholds, while providing spa- Lime hydrocarbon play, was characterized using conventional and virtual out- tially (especially laterally) continuous data (Jones et al., 2011). However, con- OPEN ACCESS crop-based techniques. To test the fidelity of the virtual fracture extraction ap- ventional methods of outcrop fracture characterization suffer from deficiencies proach, fracture orientation statistics generated from lidar are compared with in relation to their ability to efficiently capture sufficient information about equivalent data sets collected using traditional surveys. The results suggest fracture geometry, intensity, and orientation that can accurately represent the that terrestrial lidar, coupled with referenced gigapixel photomosaics, provide overall characteristics of the rock mass. A typical analysis of fractures in out- an effective medium for fracture identification with the capacity of resolving crop consists of collecting detailed observations manually using window map- fracture characteristics with sufficient fidelity to potentially act as condition- ping or scanline surveys (Priest, 1993). Manual survey techniques, although This paper is published under the terms of the ing data for discrete fracture network models, making it an attractive alterna- precise, are labor and time intensive, with resultant data sets restricted by the CC-BY-NC license. tive tool for fracture modeling workflows. lack of spatial continuity offered by the sampling domain, due to inaccessibility © 2018 The Authors GEOSPHERE | Volume 14 | Number 2 Biber et al. | Fracture characterization with lidar and gigapixel imaging Downloaded from http://pubs.geoscienceworld.org/gsa/geosphere/article-pdf/14/2/710/4110424/710.pdf 710 by guest on 02 October 2021 Research Paper of the upper reaches of most outcrops. Terrestrial laser scanning (TLS; also known as terrestrial lidar) is a proven close-range remote-sensing technique A B — SB for outcrop studies, which may serve to enrich observations of a geological, geochemical, or geotechnical in nature, through the addition of a geospatial component (Enge et al., 2007; Buckley et al., 2008; Burton et al., 2011; Olariu et al., 2011; Hartzell et al., 2014). The inherent millimeter to submillimeter reso- m lution and accuracy of laser scanning means that a wealth of high-quality data can be collected and analyzed within a relatively short period of time (Buckley 15 et al., 2008; Seers and Hodgetts, 2014). In the present work, we use terrestrial lidar characterization of rock discon- tinuities that encompasses fracture characteristics such as orientation, size, density, and spacing. We review existing methods, both conventional and — MFI digital outcrop based, to derive important fracture parameters from rock ex- posures. Building upon these studies, we utilize a combination of terrestrial Sandstone lidar and georeferenced gigapixel photomosaics to map exposures of the Mis- Oolitic grainstone sissippian Boone Formation, an analog for reservoir objectives in the Arkoma Wackestone and/ or carbonate breccia Basin, USA. Cherty wackestone and/or packestone 2. GEOLOGICAL SETTING Figure 1. (A) Generalized lithostratigraphy of Lower Mississippian subsystem in northwest Arkan sas (modified after Handford and Manger, 1990; Manger and Shelby, 2000). Red box denotes the stratigraphic position of the rocks in War Eagle quarry. (B) Coarsening upward The outcrop that forms the focus of this study is located at the War Eagle lithofacies observed in the quarry. SB—sequence boundary; TST—transgressive systems tract; quarry, 6 km northeast of Huntsville, Arkansas on Highway 412 (W93°41.227′, HST—high stand systems tract; MFI—maximum flooding interval. N36°7.168′). Approximately 15 m of strata within the upper part of the Carbon- iferous Boone Formation is exposed within the quarry. The exposed strata be- long to the lower Mississippian sequence and correspond to carbonate-ramp wackestone, mudstone, and carbonate breccia. Chert is nearly absent through- deposits with varying conditions of energy and depth (Handford and Manger, out the rest of the section. The upper unit (termed as “layer 3”) is ~7 m thick 1990). The range of depositional environments viewed in the War Eagle quarry and only exposed in the east wall of the quarry. It is composed of oolitic grain- has previously been interpreted as being deep-shelf margin to open-marine stones with common occurrence of cross stratification (see Fig. 2 for outcrop shallow-shelf edge settings (Liner, 1979). Lisle (1983) recognized that upper- photos). This interval represents the periodic establishment of higher-energy most parts of the outcrop belong to Short Creek Oolite member (Fig. 1). On the environment within a low-energy carbonate shelf setting (Zachry, 1979). other hand, virtually no oolites are present at the base of the outcrop, suggest- The outcrop exposed in War Eagle quarry belongs stratigraphically to the ing a more characteristic “Boone” style of deposition. Stratigraphically, the upper
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