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).

13

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.

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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