generation of a three-dimensional geo-cellular outcrop ... · conclusion the deposits of meandering...
TRANSCRIPT
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
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
Introduction: Multi-Point Statistics
4
Introduction: Methodology
Outcrop photopanels (Arnot et al. 1997) & GPS data & digital elevation
model
5
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).
Introduction: Methodology
LiDAR survey (Bellian et al.
2005)
6
Example of LiDAR equipment.
Description of study area
7
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.
Caineville
100 km
A)
B)
C)
1000 km
Palaeogeography & tectonic setting
8
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).
.
W area of interest E
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)
9
Stratigraphy of the Morrison Formation, modified from
Kjemperud et al. (2008) and AAPG fieldtrip guide (1994).
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)
10
~ 400 x 700 m
Google Earth® satellite image showing the extent of the
field area.
General stratigraphy
Up to 4 sandstone packages
divided by fine grained strata
5 different sandstone lithofacies
11
Log section, illustrating general stratigraphy.
1
2
3
4
Log section
Position of log section within field area.
Lithofacies
12
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.
F
A B C
D E
Outcrop photographs
pebbly layers
An example of outcrop photopanels, taken on the outer side (western side) of the first bend (displayed extent 11 m).
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cross-strata
cross-strata
“lateral accretion surface”
“bar”
Log positions
14
Google Earth® satellite image showing where sections were logged.
Log section
15
An example of log sections which were taken on the inner side (eastern side) of the first bend.
waypoint 001 waypoint 002 waypoint 003 waypoint 092 waypoint 004
6 m
1 m
W 001
W 002
W 003
W 092
W 004
Modern day example
16
Example from the Mississippi of how individual bars develop on the larger point bar (Google
Earth® satellite image).
lateral accretion
unit bars
flow direction
Field season 2 (May 2011)
LiDAR survey
Mapping of lithofacies
17
Results: LiDAR data
18
LiDAR data after texturing and draping of pictures (in profile).
Results: Interpretation
19
Interpretation of LiDAR data.
Results: 3D digital outcrop model
3D digital outcrop model created in Paradigm GOCAD 2009.3p3.
20
mudstone/siltstone/
fine-grained sandstone
planar bedded and low angle
lamination sandstone
planar cross-bedded
sandstone
trough cross-bedded
sandstone
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.
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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
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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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