Generation of a Three-dimensional Geo-cellular Outcrop Model for Use as a Training Image to Model Fluvial Systems Barbara I. Holzweber, Adrian J. Hartley University of Aberdeen
Contents Introduction Modelling of fluvial reservoirs Multiple-Point Statistics-based reservoir modelling Methodology for collecting outcrop data Description of study area Location Palaeogeography & tectonic setting Geologic background Data collection Results LiDAR data processing 3D geo-cellular outcrop model Discussion & conclusion 2
Introduction: Modelling of fluvial reservoirs Object-based & pixel-based modelling methods Multiple levels of heterogeneity within fluvial reservoirs Modelling of small scale heterogeneities using Multiple-Point Statistics algorithm in order to increase accuracy 3
Introduction: Multi-Point Statistics Multi-Point Statistics (MPS) algorithms rely on the use of training images (TI) Training images can either be two- or three-dimensional, e.g. maps, aerial photographs, satellite images, outcrop data The training image should represent the repetitive geometrical structure of the reservoir 2 types of training images: stationary & non-stationary 4
Introduction: Methodology Outcrop photopanels (Arnot et al. 1997) & GPS data & digital elevation model Optimal position of camera for collection of outcrop photopanels with minimal distortion within and between frames (after Arnot et al. 1997). Scale changes between adjacent frames can be significantly reduced by maintaining a constant distance from the outcrop and overlapping adjacent frames by 50 60% (after Arnot et al. 1997). 5
Introduction: Methodology LiDAR survey (Bellian et al. 2005) Example of LiDAR equipment. 6
Description of study area B) A) Caineville 100 km C) A) Map of the United States (www.onlineatlas.us); B) Location of the field area (in Google Maps ) and of a cross section through the Morrison Formation; and C) Detailed map showing the location of the field area. 7
Palaeogeography & tectonic setting W area of interest E 1000 km Palaeogeographic map of North America during the late Jurassic (150 Ma) (from www.cpgeosystems.com), including schematic block diagram of the Morrison depositional basin (after Demko et al. 2004; ages from Kowallis et al. 1998).. 8
Geologic background Upper Jurassic (148 155 Ma) (Kowallis et al. 1998) Tidwell, Salt Wash & Brushy Basin Member (Peterson 1980) Salt Wash Member: fluvial environment Palaeolatitudes of 30 35 N (Van Fossen & Kent 1992) Warm & dry palaeoclimate (Robinson & McCabe 1998) Stratigraphy of the Morrison Formation, modified from Kjemperud et al. (2008) and AAPG fieldtrip guide (1994). 9
Field season 1 (Oct.-Nov. 2010) 3D exposure combination of plan view and cross sections Log sections (60 logs; combined thickness ~ 600 m) Palaeocurrent data (1041 measurements in plan view) Outcrop photographs (~ 350 photopanels) ~ 400 x 700 m Google Earth satellite image showing the extent of the field area. 10
General stratigraphy Up to 4 sandstone packages divided by fine grained strata 4 5 different sandstone lithofacies 3 2 Log section, illustrating general stratigraphy. 1 Position of log section within field area. Log section 11
Lithofacies A B C D E F Six different lithofacies can be distinguished: A) Pebbly sandstone and conglomerate; B) Planar bedding and low angle lamination; C) Planar cross-bedding; D) Trough cross-bedding; E) Fine-grained sandstone, ripple laminated; and F) Mudstone, siltstone and fine grained sandstone. 12
Outcrop photographs lateral accretion surface pebbly layers cross-strata bar cross-strata An example of outcrop photopanels, taken on the outer side (western side) of the first bend (displayed extent 11 m). 13
Log positions Google Earth satellite image showing where sections were logged. 14
Log section 6 m waypoint 001 waypoint 002 waypoint 003 waypoint 092 waypoint 004 W 092 W 003 W 004 W 002 W 001 1 m An example of log sections which were taken on the inner side (eastern side) of the first bend. 15
Modern day example lateral accretion unit bars flow direction Example from the Mississippi of how individual bars develop on the larger point bar (Google Earth satellite image). 16
Field season 2 (May 2011) LiDAR survey Mapping of lithofacies 17
Results: LiDAR data LiDAR data after texturing and draping of pictures (in profile). 18
Results: Interpretation Interpretation of LiDAR data. 19
Results: 3D digital outcrop model mudstone/siltstone/ fine-grained sandstone planar bedded and low angle lamination sandstone planar cross-bedded sandstone trough cross-bedded sandstone 3D digital outcrop model created in Paradigm GOCAD 2009.3p3. 20
Results: 3D digital outcrop model 3D digital ( sugar box ) model based on outcrop data, created in Paradigm GOCAD 2009.3p3, displaying lithofacies. Cross-sections of the 3D digital model, displaying lithofacies. Realisation based on 3D digital model, displaying lithofacies. 21
Discussion Series of cross-cutting bars Trough & planar cross-strata, separated by large scale strata lateral accretion surfaces (?) Characteristics of a braided system Deposition in a sinuous channel system (morphology, palaeocurrents) Field data might need to be simplified to provide an appropriate training image 22
Conclusion The deposits of meandering and braided systems look similar in the rock record There are various scales of heterogeneity within a reservoir (e.g. rock properties, lithofacies, facies, ), which need to be represented individually Field data have to represent the appropriate scale of heterogeneity (e.g. the data collected in Utah might be used to populate single bars with different lithofacies) A simple training image, capturing only the main features might result in more accurate realisations than a complex training image 23
Thank you! 24
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