STUDY OF CRETACEOUS DELTA FRONT DEPOSITS, … · (Miall and Tyler, 1991). Studies of the 3-D facies...
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STUDY OF CRETACEOUS DELTA FRONT DEPOSITS, INTEGRATING OUTCROP, GPR AND 3-D PHOTOREALISTIC DATA, PANTHER TONGUE SANDSTONE, UTAH. by CORNEL OLARIU THESIS Presented to the Faculty of The University of Texas at Dallas In Partial Fulfillment Of the Requirements For the degree of MASTER OF SCIENCE IN GEOSCIENCES THE UNIVERSITY OF TEXAS AT DALLAS August, 2002
Transcript of STUDY OF CRETACEOUS DELTA FRONT DEPOSITS, … · (Miall and Tyler, 1991). Studies of the 3-D facies...
STUDY OF CRETACEOUS DELTA FRONT DEPOSITS, INTEGRATING
OUTCROP, GPR AND 3-D PHOTOREALISTIC DATA,
PANTHER TONGUE SANDSTONE, UTAH.
by
CORNEL OLARIU
THESIS
Presented to the Faculty of
The University of Texas at Dallas
In Partial Fulfillment
Of the Requirements
For the degree of
MASTER OF SCIENCE IN GEOSCIENCES
THE UNIVERSITY OF TEXAS AT DALLAS
August, 2002
To
My family
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ACKNOWLEDGMENTS
I would like to give special thanks to my advisor Professor Janok P. Bhattacharya
for his support throughout my graduate studies. I am grateful to my committee members
Professor George A. McMechan and Professor Carlos L. V. Aiken for their careful and
thoughtful reviews. They helped me in the field to collect data and guided me with
patience and passion, encouraging me to make use of new technologies in achieving the
goal that I have proposed. I would also like to thank to Professor Emil Pesagno Jr. for his
understanding and patience.
I am grateful to Dr. Xueming Xu and Dr. Xiaoxian Zeng for helping me with field
work and valuable suggestions and advice in computer work. I would like to thank to
Bobbie Neubert, Rui Ge and Fanny Marcy for their assistance in my fieldwork. I also
wish to express my sincere gratitude to my professors and colleagues of the Geoscience
Department and the Center for Lithospheric Studies for their help and friendship.
The British Petroleum and Chevron-Texaco companies supported the research
leading to this thesis. Financial was also supplied through a ACS-PRF grant # 35855-
AC8. Financial support was also received by me as graduate research grant from the
Geological Society of America and the Colorado Scientific Society.
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STUDY OF CRETACEOUS DELTA FRONT DEPOSITS, INTEGRATING
OUTCROP, GPR AND 3-D PHOTOREALISTIC DATA,
PANTHER TONGUE SANDSTONE, UTAH.
Publication No.___________
Cornel OlariuThe University of Texas at Dallas, 2002
Supervising Professor: Janok P. Bhattacharya
The Spring Canyon / Sow Belly Gulch area in Utah contains the most proximal facies
within the Panther Tongue delta represented by terminal distributary channels deposits
alternating with mouth bar deposits in the delta front. Ground penetrating radar (GPR)
and 3-D photorealistic techniques together with sedimentary section measurements, are
used to image the 3-D facies architecture.
The terminal distributary channel facies exposed in the northern cliffs of the canyon die
out over less than 100 m on the south side of Spring Canyon where heterolithic deposits
representing distal mouth bar facies of the delta front are exposed.
The 3-D photorealistic technique consists of draping oblique, close-range photographic
images on 3-D terrain models of outcrops to generate a digital three-dimensional model
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of the outcrop. Using these 3-D photorealistic models in GoCadTm, 3-D bedding diagrams
of the outcrops are built.
2-D ground penetrating radar (GPR) profiles, collected parallel with cliff faces, are tied
with the 3-D outcrop model using a Global Positioning System. GPR lines are correlated
with 3-D bedding diagrams to extend mapping of sedimentary features behind the
outcrop.
For the first time “terminal” distributary channels and upstream accretion bars were
described in ancient delta front deposits.
Three main distinctive facies differentiated in study area were “terminal” distributary
channel, upstream accreting bars and distal bars. “Terminal” distributary channels and
upstream accretion bars were observed on cliffs oriented perpendicular and respective
parallel to the paleoflow direction.
Elongate scours representing the bases of “terminal” distributary channels, were mapped
20 m behind the cliff face. Mapping of 3-D surfaces and bodies show that “terminal”
distributary and mouth bar deposits have surfaces with maximum topography of 1-2
meters.
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TABLE OF CONTENTS
Acknowledgments ……………………………………………………………………… iv
Abstract ………………………………………………………………………………… v
List of Figures …………………………………………………………………………… viii
List of Tables …………………………………………………………………………… x
Chapter 1. Introduction ………………………………………………………………… 1
Chapter 2. Regional Settings and Previous Work …………………………………… 4
Chapter 3. Methods …………………………………………………………………… 9
3.1. Ground Penetrating Radar (GPR) ………………………………………. 9
3.2. GPR Data Collection and Processing …………………………………… 13
3.3. Photorealistic Technique ………………………………………………….. 15
3.4. Photorealistic Data Collection and Processing ………………………… 16
3.5. Sedimentary Measurements ……………………………………………… 23
Chapter 4. 3-D Interpretation …………………………………………………………. 29
Chapter 5. Discussion ………………………………………………………………….. 37
Chapter 6 Conclusions …………………………………………………………………. 42
Appendix A: Measured Sections ……………………………………………………… 43
Appendix B: Radar profiles ……………………………………………………………. 54
References ………………………………………………………………………………. 59
Vita………………………………………………………………………………………… 66
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LIST OF FIGURES
Figure 1: Terminal distributary channels in modern delta formedby successive bifurcations, Lena delta, Arctic Sea, Russia……...........…3
Figure 2. Outcrop belt of Panther Tongue Sandstone and locationof data collected in Spring Canyon area. (modified afterHoward, 1966a)………………………………………………………….5
Figure 3. Stratigraphic relations of Upper Creaceous rocks ineast-central Utah (modified after Young, 1955, Weimer, 1960)………...6
Figure 4. Paleoshoreline during early Campanian (modified afterMc Gooket et al., 1992; Williams and Stelck, 1973;Cobban et al., 1994)………………………………………………..…….8
Figure 5. Block diagram of a typical GPR system (from Davies andAnnan, 1989)…………………………………………………………...10
Figure 6. The relation between resolution and bandwidth for100 MHz radar in rock and wet soil (from Davies andAnnan, 1989)………………………………………………………...…11
Figure 7. Processing steps applied to GPR data……………………………..…...14
Figure 8. Major steps in collection of data for photorealistic outcrop model…….18
Figure 9. Data processing steps for building the digital outcrop model…………..20
Figure 10. Detailed view of raw points and built terrain surface of theoutcrop……………………………………………………………….…21
.Figure 11. Pinpoint principle of coordinate translation from x, y, z, to
u, v. (modified after Xu, 2000)……………………………………....…22
Figure 12 2-D photomosaic of terminal distributary channels, located inFig.2, Area 1……………………………………………………….……24
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Figure 13. 2-D photomosaic of upstream aggradation of mouth bardeposits, located in Fig.2, Area 2. legend is the same asin Fig. 12……………………………………………………………..…26
Figure 14. 2-D photomosaic of distal bars, located in Fig.2, Area 3.legend is the same as in Fig. 12…………………………………………27
Figure 15. GPR line (GPR1) collected parallel to cliff face, located onFig. 2, Aria1…………………………………………………………......30
Figure 16. GPR line (GPR4) collected parallel to cliff face, located onFig. 2, Area2…………………………………………………………….31
Figure 17. 3-D view of surfaces built based on digital outcrops and GPRdata, Aria 1 in Figure 2……………………………………………...…..33
Figure 18. 3-D view of surfaces built based on digital outcrops and GPRdata, Aria 1 in Figure 2…………………………………………….....…34
Figure 19. 3-D sedimentary bodies built based on 3-D surfaces and sedimentological data, Aria 1 in Figure 2………………………........…35
Figure 20. 3-D sedimentary bodies built based on 3-D surfaces and sedimentologicaldata, Aria 2 in Figure 2…………………………………………….....…36
x
LIST OF TABLES
Table 1. Equipment used for photorealistic acquisition and technicalcharacteristics………………………………………………………….17
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CHAPTER 1
INTRODUCTION
The study of outcrops remains a primary tool for understanding facies architecture
and for reservoir characterization studies.
Delta deposits form major hydrocarbon reservoirs worldwide and represent more than
60% of the sandstone reservoirs in Texas alone (Tyler and Finley, 1991). In places such as
Prudhoe Bay, Alaska and the Gulf of Mexico, a great percentage of oil reservoirs are in
deltaic or fluvial/deltaic rocks (Tye et al., 1999; Tye and Hickey, 2001). Despite that great
hydrocarbon potential, these classes of reservoirs experience significant recovery problems
related to depositional heterogeneity (Tyler and Finley 1991; Ainsworth et al., 1999; Tye et
al., 1999). A 3-D approach is necessary to build more realistic models of reservoirs
associated with delta front deposits.
Facies architectural studies of ancient delta deposits are typically regional and large
scale (Bhattacharya, 1991; Bhattacharya and Walker, 1992; Broussard, 1975; Coleman and
Wright, 1975; Ori et al., 1991, Reading, 1996, Willis et al., 1999). More accurate,
quantitative detailed descriptions of sand body shapes and their relationships are required in
the hydrocarbon industry. Small-scale heterogeneity models are required for more effective
reservoir engineering and the building of realistic 3-D fluid flow models.
The heterogeneity of deltaic reservoirs is especially complicated because of the great
variety of processes operating in deltas, but quantification of this heterogeneity lags behind
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the understanding of fluvial and deep-water (Bouma and Stone, 2000) depositional systems
(Miall and Tyler, 1991). Studies of the 3-D facies architecture of delta deposits compared to
fluvial (e.g. Miall, 1996) or deep water systems (e.g. Bouma and Stone, 2000) have been
largely neglected.
This paper focuses on imaging the 3-D facies architecture of “terminal” distributary
channel deposits within delta front deposits of the Cretaceous-age Panther-Tongue delta in
central Utah, using digital mapping techniques and ground penetrating radar (GPR). There
are no 3-D studies that document the architecture of “terminal” distributary channels, despite
the abundance of these features in modern deltas (Bhattacharya et al. 2001).
“Terminal” distributary channels form at the distal end of shallow water deltas and
form by multiple bifurcation of larger delta plain channels. “Terminal” distributary channels
are typically shallow and narrow as the discharge of the “trunk” feeder channel is distributed
among many shallow channels (Fig. 1).
Methodologies applied in this paper, GPR and 3-D photorealistic techniques together
with classical sedimentary measurements, allows 3-D reconstruction of sedimentary deposits.
This study demonstrates an approach that provides quantitative 3-D data, which can be used
by reservoir engineers to construct more accurate 3-D volumetric fluid flow models for
hydrocarbon reservoirs.
The Panther Tongue sandstones are analogous to other hydrocarbon reservoirs in
delta front deposits and as a consequence the results of this study can be used for reservoir
characterization in areas where only subsurface data are available.
20 km
N Terminal distributary channels
Trunk channel
Nodal avulsions
Figure 1. Terminal distributary channels in modern delta formed by successive
bifurcations, Lena delta, Arctic Sea, Russia.
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CHAPTER 2
REGIONAL SETTING AND PREVIOUS WORK
Delta front deposits containing “terminal” distributary channels within the Panther
Tongue sandstone are superbly exposed in central Utah along Spring Canyon (Fig. 2).
Previous work (Howard, 1966b; Newman and Chan, 1991; Morris et al., 1995; Posamentier
et al., 1995) show that the Panther Tongue is a river-dominated delta front. The deposits were
interpreted as “terminal” distributary channel deposits in Spring Canyon / Sow Belly Gulch
outcrops, (Bhattacharya et al., 2001).
The Panther Tongue Sandstone is Campanian in age and represents the lower of two
sandy tongues of the Star Point Formation within the Mancos Formation shale. The thickness
of the Star Point Formation varies between 7 m and 100 m (Hintze, 1988). The Star Point
Formation is overlain by a “Shale Tongue” of the Upper Mancos. Sandstones of the Panther
Tongue interfinger to the east (paleo-seaward) with shale of Mancos Formation (Fig. 3)
(Young, 1955, Weimer, 1960).
The sedimentary succession has been interpreted as a nearshore depositional
environment formed in the Western Interior Seaway (Young, 1955; Howard, 1966a). Young
(1955) distinguishes a longshore bar oriented northeast-southwest. The Panther Tongue
sandstone was specifically interpreted as deltaic by Howard (1966b) and Newman and Chan
(1991). A detailed ichnological study of the Panther Tongue suggested environmental facies
intermediate between offshore and nearshore (Frey and Howard, 1985). Morris et al. (1995)
5
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Figure 3. Stratigraphic relations of Upper Creaceous rocks in east-central Utah
(modified after Young, 1955; Weimer, 1960).
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7
described the Panther. Tongue deposits from Sow Belly Gulch, north of Helper, Utah, as a
top truncated lowstand delta front containing channel deposits alternating with mouth bar
deposits. The Panther Tongue contains two distinct types of delta deposits, distal deposits
interpreted as bed-load dominated, Gilbert-type delta (Barrell, 1912), and more proximal
facies interpreted as a mixed load, turbidite-dominated delta (Morris et al., 1995). The
proximal facies are the focus of this study. Prodelta shales bound the sandstone channel and
bar deposits (Morris et al., 1995).
Despite the regional stratigraphic studies, no detailed studies of the facies architecture
of these deltas have been presented. Adding Panther Tongue deposits on a regional
paleogeographic map (Fig. 4), shows that the delta lies landward relative to the published
paleoshoreline position. These maps were based on the distribution of marine fauna such as
Baculites sp. (McGookey et al., 1973), Haploscaphytes hippocrepis (Williams and Stelck,
1972) and Scaphites hippocrepis (Cobban et al., 1994). The Panther Tongue delta is inland
relative to previously mapped shorelines because all authors estimate shoreline position on
the basis of distribution of marine fossils. As a consequence, interpretations usually over-
estimate shorelines basinward, because of lack of marine fossils in more proximal, delta-front
environments. Average paleoflow direction is S 271° W (Fig. 4). This value is consistent
with previous measurements (Newman and Chan, 1991) but raises questions related to
subparallel direction of propagation relative to paleoshoreline (Fig. 4). The southward
direction of delta progradation might be controlled by N-S oriented longshore currents or
might be structurally controlled.
Campanian shore line in Utah
After Williams and Stelck, 1973
After McGookey et al., 1972
After Cobban et al. , 1994
Cre
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Panther Tongue Delta
Paleoflow direction
207.1
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S
Figure 4. Paleoflow direction and paleoshoreline during early Campanian (modified after McGookey
et al., 1992; Williams and Stelck, 1973; Cobban et al., 1994)
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CHAPTER 3
METHODS
3.1 Ground penetrating radar (GPR)
Ground penetrating radar is a geophysical technique in which propagation of an
electro-magnetic pulse is used to study shallow deposits. Due to heterogeneity of the
deposits, the magneto-electrical properties vary with depth. Reflections from variations of
electrical impedance are recorded by the system. The system is not expensive, is simple to
use and is suitable for fieldwork (Fig. 5). For geological purposes antennas with frequencies
between 25 MHz and 500 MHz are typically used. Different frequency bandwidths have
different resolutions (Fig. 6) (Davis and Annan, 1989; Smith and Jol, 1992; van Dam, 2001).
Therefore, frequencies are chosen based on the goals of survey. Most studies collect data
with different frequencies, but the most common 100 MHz represents a good compromise
between depth of penetration and vertical resolution for fluvial / deltaic deposits (Corbeanu
et al., 2001; Gawthorpe et al., 1993; McMechan et al., 1997; Smith and Jol, 1992; Szerbiak et
al., 2001). The logistics of GPR acquisition and processing is similar to seismic, but with
some differences. Similar to seismic, depth of penetration increases with decreasing
frequency and vertical resolution decreases with decreasing frequency. In contrast to seismic
data where velocity increases with depth, velocity decrease with depth in ground penetrating
radar (Fisher et al., 1992b). Raw ground penetrating radar data represents a distorted
DISPLAY
TRANSMITTER
RECORD
TIMING
RECEIVER
ANTENNA ANTENNA
BEDROCK
SOIL
Figure 5. Block diagram of a typical GPR system (after Davis and Annan, 1989).
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102
100
10-1
10-2
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103
102
100
101
101
100 MHz
SYSTEM
ROCK
WET SOIL
BANDWIDTH (MHz)
RE
SO
LU
TIO
N (
m)
Figure 6. The relation between resolution and bandwidth for a 100 MHz radar in rock and
wet soil (after Davis and Annan, 1989).
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unfocused image of the subsurface (Fisher et al., 1992b). Because of kinematic similarities
with seismic data, many commonly used seismic processing principles and steps can be
applied to GPR data (Fisher et al., 1992a, 1992b; Zeng, 1998). Also, interpretation of GPR
data can be made on the basis of seismic stratigraphic principles (Vail et al., 1977) using the
analogous radar facies and radar stratigraphy (Jol and Smith, 1991).
Three-dimensional GPR data have been collected and studied in both modern and
ancient deposits (Beres et al., 1995; Corbeanu, 2001; Corbeanu et al. 2001; McMechan et al.,
1997; Szerbiak et al., 2001). These datasets were processed and interpreted with seismic
software. 3-D GPR data is extremely useful for reservoir analog studies, because GPR
attributes can be extrapolated throughout an entire volume and realistic 3-D fluid flow
models can be built from them (Corbeanu et al., 2001; Szerbiak et al., 2001).
GPR has been mostly used on recent unconsolidated sediments (Jol and Smith, 1991;
Smith and Jol, 1992; Gawthorpe et al., 1993; van Heerden and Roberts, 1998). Studies in
unconsolidated sediments are more common because these are more accessible and also GPR
has better results because air in the sediment pores gives a high velocity and low attenuation
to the signal (van Hetern et al., 1998; Davies and Annan, 1989; Jol and Smith, 1991; Smith
and Jol, 1992; Gawthorpe et al., 1993). In addition to GPR data, cores or trenches are used to
tie radar reflections with sedimentary facies (Jol and Smith, 1991; van Hetern et al., 1998).
Studies of ancient deposits have been pioneered by McMechan et al. (1997),
Corbeanu et al. (2001) and Szerbiak et al. (2001). In studies of ancient deposits, it is rare to
find flat topped outcrops with large areas to collect GPR lines. Ancient deposits usually are
capped by thick soil which attenuates the signal and limits the depth of acquisition. Outcrop
13
or cliff face data are used more often than cores to tie GPR data to sedimentary facies in
studies on ancient deposits (Corbeanu et al., 2001; McMechan et al., 1997).
3.2. GPR Data collection and processing
We collected 450 m of 2-D GPR along four profiles (Fig. 2). The topography and soil
cover of the study area restrains our capability to collect 3-D or more extensive 2-D data. A
pulse EKKO IV system with 50 MHz antennas, spaced 3 m apart, and 100 MHz antennas
spaced 2 m apart, both with a 1000 V transmitter was used. In this paper only the 50 MHz
data will be interpreted because it has a deeper penetration, although resolution was
approximately 0.5m. Common mid-point (CMP) data were collected with 50 MHz and 100
MHz antennas and were used for velocity estimation. To process the data we used an average
velocity of 0.12 m/ns.
Figure 7 shows the GPR data processing steps. Each step represents an important
improvement in imaging primary radar reflections. The first step, signal dewowing,
eliminates the low frequency background caused by diffusion of electric current into the
ground (Annan, 1999). Time zero alignment, moves the traces so that the direct arrivals
occur at the same time. Trace editing, replaces noisy traces (or only a part of a trace) with
values from adjacent traces. Air wave average removal is necessary to remove the direct
ground and air waves (Annan, 1999). Direct ground and air waves appear because of the high
contrast of electro-magnetic properties between air and ground. Topography and migration
correction are made for a realistic positioning of radar reflectors in depth. Migration is
extremely useful but without a good knowledge of velocity, distortions can be generated
(Annan, 1999).
14
Raw data
Dewowing (Subtract exponentialbaseline)
Time zero alignment.
Trace editing.
Air wave average removal.
Topography correction and prestackmigration
Figure 7. Processing steps applied to GPR data.
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Historically, most published GPR studies stop with processing after time zero
alignment and only a few remove have air waves or correct topography. Migration of GPR
data is relatively new, (e.g. Fisher et al., 1992); for our data, migration was done using a
prestack Kirchhoff algorithm (Epili and McMechan, 1996).
3.3. Photorealistic technique
Global Positional Systems (GPS) and rangefinder lasers allow more accurate
collection of spatial data. There are different approaches to collect digital data to describe the
geology of the outcrops. One approach is to measure geological features directly with GPS
(Xu, 2000; Xu et al., 2000; Thurmond et al., 2001). Outcrops for such studies must have
accessible slopes, because the methodology requires “walking out” features. Another
approach is to map geological features on the outcrops remotely, using reflectorless laser
guns (Nielsen et al., 1999, 2000; Xu, 2000; Xu et al., 1999, 2002). This approach can be used
on steep cliff faces. It uses GPS methodology to locate laser guns with cm accuracy. Laser
guns have different ranges from 100 m to 500 m, and decimeters accuracy (Xu, 2000). The
pitfall of using laser guns to map geological features is the difficulty of re-interpretation. A
wrong interpretation (mapping) of some geological features in the field is difficult to correct
in the computer or may require additional fieldwork to collect new data.
A new and better alternative approach (which was used in this project) is to drape
close-range color photographic images on a digital terrain model of the outcrop (Xu, 2000).
This method allows us to build a realistic 3-D model of the outcrop with cm to dm accuracy
with which the geology can then be interpreted interactively on a computer screen instead of
16
on a 2-D photomosaic. An advantage is the quantitative accuracy of the data and the use of
real color images which can be easily interpreted.
3.4. Photorealistic data collection and processing
We collected data from more than 2 km of cliffs in Spring Canyon and Sow Belly
Gulch (Fig. 2).
For data collection we used a Leica 500 RTK GPS system in differential mode, two
reflectorless robotic MDL Atlanta Laser Systems (ALS) stations, a Topcon GPT-1002 total
station with non prism capability and a Fuji Pro digital SLR camera (Table 1). The flow chart
of the data collection is shown in Fig. 8. A site for a GPS base station and its radio
transmitter is determined by satellite visibility and is accurately located (step 1 in Fig. 8) by
being differentially corrected after the location by post-processing with data from Salt Lake
City CORS (Continuously Operating Reference Station) (step 2 in Fig. 8) (Parkinson and
Spilker, 1996). The “rover” GPS is located by real time differential GPS utilizing the
correction from the base station to the satellite signal (step 3.1 in Fig. 8) provided by radio
signal in real time received from the base station (step 3.2 in Fig.8) (Parkinson and Spilker,
1996). The rover GPS was used to measure the topography of the area, and to locate the GPR
lines (step 4.1 in Fig. 8), the tops of the sedimentary sections on the cliff (step 4.2 in Fig. 8)
and the robotic scanners (step 4.3 in Fig. 8) and the reflectorless total station (step 4.4 in Fig.
8). From the known scanner locations, cliff faces were scanned with robotic ALS stations
(step 5 in Fig. 8). To scan the outcrop, the robotic scanner was set so that the relative distance
between points on the outcrop was ~1 m.
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Table1. Equipment used for photorealistic acquisition and technical characteristics.
Leica 500 GPS Systems Used in Stop and Go in Real Time Kinematic(RTK) mode. Accuracy 1-2 cm.
MDL Laser ACE System,MDL Laser Atlanta System
Three dimensional robotic laser scanningsystems. Acquire relative positions fromdifferent surface types without the need of aprism. Range is 300 m and accuracy 5 cm.
Topcon GPT 1002 Reflectorless total station. In reflectorless modehas a range of 80 meters and 1cm accuracy.
Fuji S1 Pro Professional digital camera with a maximumresolution of 3040 X 2016 pixels.Different Nikon lenses (35 mm, 50 mm, 135mm) can be attached to the body.
Sate
llit
e S
ign
al
Sate
llit
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ign
al
CO
RS
Sta
tio
ns
Rad
io s
ign
al
GP
S b
ase
(cen
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r accu
racy)
GP
S r
over
(cen
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r accu
racy)
Ro
bo
tic S
can
ner
To
tal sta
tio
n
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nin
g
ou
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p
Ou
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p
Dig
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am
era
GP
R lin
e
(1)
(7)
(6)
(5)
(4.4
)(4.3
)
(4.2
)
(4.1
)
(3.2
)
(3.1
)
(2)
Fig
ure
8. M
ain s
teps
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oll
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r photo
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isti
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rop m
odel
.
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With a Topcon GPT-1002 electronic tacheometer (total station), control points were
postprocessed in the field (step 6 in Fig. 8), using ordinary bicycle reflectors or paint as
identifiers of the stations. Digital images of the cliff faces were collected using a digital
camera (step 7 in Fig. 8). Images were collected using 35 mm, 50 mm and 135 mm
lenses(depending on distance) to increase maximum resolution. Each photographic image
had at least eight control points.
All data sets from different stations were corrected and tied to global coordinates by
GPS. Processing data for a photorealistic outcrop was developed by Xu (2000) and involves
several major steps in building the terrain surface of the outcrop and draping images on the
terrain surface (Fig. 9). GoCadTm software was used to generate surfaces of the scanned
outcrops. GoCadTm has directional constraints to apply on fitted surfaces. Directional
constraints are necessary to fit surfaces which are not necessarily vertical (and may even
have overhang). GoCad Tm software uses the algorithm described by Mallet (1989). It is also
relatively easy to fit surfaces defining geological bodies with GoCadTm. With constraints
allowed by the software, surfaces are fit to the raw data points (Fig. 10). Surfaces are not
required to pass exactly through every raw point; the degree of detail desired in an image
depends on the data and the purpose for which it is to be used. To drape images on the terrain
surface of the outcrop, corrections for lens distortion has been made. For the approach used a
pinhole camera model in which x, y, z, world coordinates are translated into (u, v), image
coordinates (Fig. 11) (Xu, 2000). The pinhole camera model is a simplified model which
does not include radial and tangential distortions made by camera lenses. Thus, a least
squares method is used to minimize the radial and tangential distortion by calibrating the
lenses (Xu, 2000).
Fig
ure
9. D
ata
pro
cess
ing s
teps
for
buil
din
g t
he
dig
ital
outc
rop m
odel
.
Sca
nn
ed
ra
w d
ata
po
ints
in g
lob
al x,
y,
z c
oo
rdin
ate
s
Pro
cessin
g s
tep
s
Imag
es
Te
rra
in s
urf
ace
of
the
ou
tcro
p
Dra
pin
g d
igita
l im
ag
es
1 32
20
Figure 10. Detailed view of raw points and the GoCad terrain surface of the outcrop
(the blue dots represent raw datapoints and the line from surface to the points
represent the constraint direction).
21
1m
P
p
lens
f
x
z
y
photo plane
(u, v, image coordinates)
u
v
object
(x, y, z, global coordinates)
Figure 11. Pinpoint principle of coordinate translation from x, y, z, to u, v
(modified after Xu, 2000).
22
23
3.5. Sedimentology
Thirty-six vertical stratigraphic sections were measured along the cliff face using
technical climbing devices. GPS (Global Positioning System) measurements allow accurate
location of measured sections at the top of cliffs (Fig.2). In this paper, the only sections
measured on cliffs close to GPR data are used to build 3-D geometries of the deposits. The
other sections are used in a detailed analysis of the sedimentology , which will appear
elsewhere.
Three areas were mapped in detail. The first area (Fig. 2) shows terminal distributary
channels in cliff faces oriented perpendicular to paleoflow. The 2-D bedding diagram shows
shallow channels alternating with tabular beds (Fig. 12). Channel deposits reach 4 m thick
and 20 m wide, with lateral transition to tabular, submeter thick beds which extend tens to
hundreds of meters laterally. Measured sections show overall coarsening-upward facies
successions within which occur meter scale fining upward beds. Beds associated with the
channels are structureless but locally show trough cross stratification or hummocky cross
stratification (HCS).
We interpret these channel deposits as storm-flood deposits related to times of high
discharge in the feeding trunk streams. Channel deposits with trough cross stratification and
structureless sandstone show a gradual transition to mouth bar deposits with tabular beds
consisting of structureless to planar laminated sandstone interbeded with highly bioturbated
very fine sandstone. Transition between these deposits was observed in vertical and lateral
facies associations.Massive sandstones are capped by bioturbated fine sandstone. These beds
are submeter scale; bioturbation ranges from low to very intense. Trace fossils consist of
Skolithos, Paleophycos and Ophiomorpha, an association which defines a Skolithos
claysilt sand
vf f m c
claysilt sand
vf f m c
S10W
S50W
claysilt sand
vf f m c
claysilt sand
vf f m c
claysilt sand
vf f m c
claysilt sand
vf f m c
claysilt sand
vf f m c
claysilt sandvf fmc
claysilt sand
vf f m c
claysilt sand
vf f m c
S32W
claysilt sand
vf f m c
4 56 7
8 9 10 11 121514
13
S50W
S32W
claysilt sand
vf f m c
2m
10 m10 m
LEGEND
Cross Stratification
Hummocky Cross
Stratification
Parallel Stratification
Assymetric ripples
Scour
Iron concretion
Organic matter
Bioturbation scarce
medium
abundant
Skolithos
Ophiomorpha
Paleophycos
Indistinct - ind
Paleo current S18E
Shell FACIES BEDDING DIAGRAM
GPR
WE
Paleoflow direction
10 m10 m
Channel Mouth bar
Figure 12. 2-D photomosaic of terminal distributary channels, located in Fig. 2, Area 1.
24
claysilt sandvf fmc
claysilt sandvf fmc
claysilt sandvf fmc
claysilt sandvf fmc
claysilt sandvf fmc
claysilt sandvf fmc
claysilt sandvf fmc
claysilt sandvf fmc
claysilt sandvf fmc
claysilt sandvf fmc
claysilt sandvf fmc
25
ichnofacies. Asymmetric ripples are observed within these beds. Very rare, centimeter thick
organic rich beds are associated with highly bioturbated beds. Based on facies description a
facies bedding diagram was built using the 2-D photomosaic diagram and measured sections
(Fig. 13).
The second cliff is oriented subparallel to parallel relative to the paleoflow direction
(Fig. 2). Lithology as well as ichnofacies assemblages are similar to those at the previous
location. Beds are meters thick, fine to medium massive sandstone alternating with sub-meter
highly bioturbated, rippled sandstone. This cliff is particularly interesting because the beds
are inclined in an upstream direction, relative to paleocurrents. These beds were therefore
interpreted as upstream accreting mouth bars in channel cuts (Fig.12). Upstream accretion of
bars was observed in flume experiments (Ashworth et al., 2001) as well as in acient deposits
(Corbeanu et al., 2001) in fluvial environments, and on modern deltaic deposits (Van
Heerden and Roberts, 1988).
The third area lies about 100 m seaward of the forst area and is oriented oblique to the
paleoflow (Fig. 2). The photomosaic shows sub-meter tabular beds of fine to very fine
sandstones (Fig. 14). Beds thicker than 1 m are rare. For the most part, beds are laterally
continuous across the outcrop, or show low angle pinchouts. Measured sections show a
higher wave /storm influence with wave ripples and HCS. Highly bioturbated beds with
undistinguished trace fossils are common. Organic rich beds extend tens of meters laterally
and are usually associated with highly bioturbated beds. These beds were interpreted to form
in the distal mouth bar environment within the delta front.
Based on previous environmental descriptions, the Panther Tongue deposits from
Spring Canyon / Sow Belly Gulch area were interpreted as a river influenced delta lobe.
S75W
S50W
claysilt sand
vf f m c
claysilt sand
vf f m c
claysilt sand
vf f m c
GPR
S Paleoflow direction
10 m10 m
10 m10 m
N
10 m
10 m
FACIES BEDDING DIAGRAM
Channel Mouth bar
Figure 13. 2-D photomosaic of upstream aggradation of mouth bar deposits, located in Fig.2, Area 2, legend is the same as in Fig. 11.
26
claysilt sandvf fmc
claysilt sandvf fmc
claysilt sandvf fmc
i1ii2ii1
Figure 14. 2-D photomosaic of distal bars, located in Fig. 2, Area 3, legend is the same as in Fig. 12.
r8 r9
FACIES BEDDING DIAGRAM
NE Paleoflow direction
10 m10 m
SW
10 m10 m
27
10 m10 m
Channel Mouth bar
claysilt sand
vf f m cclaysilt sandvf fmc
claysilt sand
vf f m cclaysilt sandvf fmc
28
No evidence for subaerial exposure was observed. HCS and Skolithos ichnofacies are
indicators of shallow water with depths less than 10 m. Existence of storm wave influence
structures were formed because water depth was low. Little fair-weather wave structures can
be explained through river dominance during fair-weather or was a relative protected basin
where wave energy was low. Thick massive sandstone alternating with highly bioturbated
facies are interpreted to be caused by highly seasonal river discharge. Periods of high river
discharge caused by floods are interpreted to produce the massive sandstone beds. Times of
lower discharge are associated with finer grained deposits and invasion of organisms.
29
CHAPTER 4
3-D INTERPRETATION
GPR data was collected parallel to cliff faces in two areas. The first area represents
cliffs oriented perpendicular to the paleoflow direction of the Panther Tongue delta and the
second area represents cliffs oriented parallel to paleoflow (Fig. 2).
The location of the first data collection area is shown in Fig. 2. The GPR data shows
channel type features similar to those observed on the outcrop (Figs. 15, 16). The 2-D
photomosaic of the outcrop (Fig. 12) shows channels filled with trough cross stratified
sandstone or structureless sandstone.
Measured sections were correlated based on bedding diagram and facies types are
distinguished.
Using the 3-D model of the outcrop and ground-penetrating radar in global
coordinates bedding surfaces are build in 3-D. Surfaces were constrained by points digitized
from the outcrop and by a ground-penetrating radar line behind the outcrop for the two areas
where GPR data was available (Figs. 17, 18). Between these surfaces, sedimentary bodies
were built and each was assigned a sedimentary facies (Fig.19). Resolution of surfaces in
global coordinates is at decimeter scale, due to GPR resolution and to uncertainties in fitting
of the outcrop surfaces.
Channel deposits described on cliff faces (Figs. 12, 13, 14) are up to 6 meters thick
and less than 100 m in width. Channel deposits can laterally pass into mouth bar deposits.
4 56 7
8 9 10 11 12
151413
10 m10 m
GPR
WE
Paleoflow direction
10 m10 m
50 MHz uninterpreted
50 MHz interpreted
10 m
Figure 15. GPR line (GPR1) collected parallel to cliff face, located on Fig. 2, Area1.
30POSITION (m)
0 12010080604020 140 160 180
DE
PT
H (
m)
20
10
0
DE
PT
H (
m)
20
10
0
GPR
S Paleoflow direction
10 m10 m
10 m10 m
N
10 m
i1ii1
ii2
10 m
50 MHz uninterpreted
50 MHz interpreted
Figure 16. GPR line (GPR4) collected parallel to cliff face, located on Fig. 2, Area2
POSITION (m)
0 12010080604020 140
DE
PT
H (
m)
20
10
0
DE
PT
H (
m)
20
10
0
31
Reflection from a metalic flag pole
32
Mouth bar deposits are less than 1 meter thick and can extend hundreds of meters (Figs. 12,
13, 14). Channel and mouth bar deposits were extended in 3-D, behind the outcrop using the
GPR images. 3-D surfaces and bodies show that “terminal” distributary form swell linear
features. “Terminal” distributary channels and mouth bar deposits have surfaces with
maximum topography of 1-2 meters. The difference between 3-D surfaces and the outcrop
observation is given by the fact that GPR penetrate only the upper half of the outcrop. In
upper half of the outcrop, no channel with significant topography was identified (Fig. 12) .
The resulting 3-D surfaces show same characteristic of deposits observed on the
correspondent part of the outcrop, with slight lateral variation of channel deposits (Fig. 17).
20 m
GPR profile
Terrain surface
Outcrop
model
Interpreted
surfaces
33
5 m
N
2 x vertical
exageration
Paleoflow direction
Figure 17. 3 - D view of Gocad surfaces built based on digital outcrop and GPR data,
Area 1 in Figure 2.
Detailed view of 2 surfaces from top figure
20 m
Outcrop
model
GPR profile
Interpreted
surfaces
34
Paleoflow direction
Figure 18. 3 - D view of Gocad surfaces built based on digital outcrop and GPR data,
Area 1 in Figure 2.
Detailed view of 2 surfaces from top figure
NN
Horizontal
surface
20 m
Horizontal
surface Upstream direction
5 m
N
35
Figure 19. 3 - D sedimentary bodies built based on 3-D Gocad surfaces and sedimentological
data, Area 1 in Figure 2.
Pinching out
Paleoflow
the same surface
36
CHAPTER 5
DISCUSSION
Geologists agree that digital acquisition of outcrops will improve interpretation made
on outcrop data. Also, geological models based on digital outcrop models provide more data
than classical 2-D photomosaics. Additional approaches have been used to build 3-D models
of the outcrops. One approach is to use LIDAR (Light Detection and Ranging) systems,
(Bellian et al., 2002). With this approach, the result is a highly accurate 3-D image of the
outcrop. Using the intensity of the reflected beams, a 3-D black and white digital image
based on very dense data points is created. The advantage of this approach is the rapidity of
the system and high accuracy of the data. The weaknesses are the high cost of the equipment
and that the final image, based on reflection intensity, needs to be linked to geology. Some
geological features, such as faults or sedimentary structures, can be misinterpreted or missed.
Lithology can not be seen and beds can not be differentiated on the outcrop model, especially
without color information.
Photorealistic acquisition and digital mapping provide a "virtual outcrop". The
photorealistic technique used with GPR is a new quantitative approach to reservoir analog
studies; quantitative results are extracted directly from 3-D digital model of the outcrop.
The resolution and accuracy of geologic features interpreted on the "virtual outcrop"
(clinoforms, channels, cross bed dip, sole marks orientation) depend on the photo resolution,
the laser scanning density and the accuracy of scanners used to scan the outcrop.
37
The rapid increase in computer capabilities will enhance the development of these
techniques, allowing higher resolution images to be draped on densely scanned terrain
models of the outcrop.
GPR technology was previously used for analog reservoir studies (McMechan et al.,
1997), tied with GPS-laser technology (Corbeanu et al., 2001). Acquisition and processing of
GPR data was improved, 3-D GPR data is now used for reservoir analog studies (Corbeanu et
al., 2001). The methodology described in this paper shows that combination of GPR with
digital mapping technique could be used for 3-D study of bed geometry in areas where 3-D
GPR data can not be collected.
Numerous studies on Panther Tongue sandstone were made at large scale (Young,
1955; Howard 1966a, 1966b; Newman and Chan, 1991; Morris et al., 1995; Posamentier et
al., 1995), (Fig. 2) in contrast to this study, which is focused on 3-D facies architecture of
specific depositional elements within the delta front (Fig. 2).
For the first time, “terminal” distributary channels were identified in an ancient delta
deposits (Figs. 2, 12). “Terminal” distibutary channels are common features in modern deltas
(Bhattacharya et al., 2001), but have been previously referred to as “secondary” or “tertiary”
channels, since they sometimes represent the second or third order of branching within a
multiple-bifurcating delta system, such as the modern-day Atchafalaya delta (van Heerden
and Roberts, 1988) or the Lena delta (Fig. 1). In ancient deposits it is more appropriate to use
the term “terminal” distributary channel, because information about branching order can not
be readily or easily determined from an outcrop.
“Terminal” distributary channel deposits are relatively small features that lie at the
transition from delta-plain fluvial - distributary channel deposits to mouth bar – marine
38
deposits. Because of this transitory position, “terminal” distributary channel deposits have
often been misinterpreted and attributed to be fluvial channels or mouth bar deposits. In cores
or subsurface, they can easily be missed, especially because they are contained completely
within the delta front, and do not cut down into underlying pro-delta facies. Many subsurface
examples of “distributary channel deposits” (e.g. Busch, 1971; Cleaves et al., 1988;
Rasmussen et al., 1985) actually refer to far larger features, many of which are probably
better interpreted as incised valleys rather than as distributary channels (Willis, 1997;
Bhattacharya et al., 2001). In general, “terminal” distributary channel deposits are contained
within the delta front and are intimately associated with mouth bar deposits. Not all
“terminal” distributary channels deposits have trough cross stratification, rip up mud clasts or
show obvious cut banks. This is especially true where the channels are filled with mouth bar
deposits, such as we interpret much of the strctureless sandstone within otherwise clearly
shallowly-incised features. Evidence of unidirectional flows (trough cross beds) are found
within some of the Panther Tongue “terminal” distributary channels (Fig. 12).
“Terminal” distributary channel deposits are potentially important in defining
heterogeneities in delta front deposits because they are formed mainly from clean sands like
mouth bar deposits but have a more or less channel-shaped geometry.
Upstream accretion was also observed on Panther Tongue deposits on a cliff parallel
with the paleoflow (Figs. 2, 13). In flume experiments, upstream accretion has been related to
channel avulsion and migration (Ashworth et al., 2001). Upstream accretion of bars has also
been observed in the modern Atchafalaya delta using successive aerial photos (van Heerden
and Roberts, 1988).
39
In ancient deposits, the only descriptions of upstream accretion of bars is described by
Corbeanu (2001) in delta plain channels in the Cretaceous Ferron sandstone in Utah and in
distributary mouth bars of the Ferron within synsedimentary growth faults (Bhattacharya and
Davies (2001). In the growth faulted example, there was some question as to whether the
upstream accretion was related to infilling of sand as a consequence of hangingwall rotation
or as a consequence of loss of discharge at the terminus of the distributary channel. Although
not well documented, the modern examples suggest that upstream accretion should be quite
common in the delta front, and especially within “terminal” distributray channels. Flume and
modern examples of upstream accretion were made on subaerially exposed deposits but the
particularity of Panther Tongue upstream accretion is that mouth bar deposits were formed in
shallow water.
The presence of “terminal” distributary channels and upstream accretion bars in delta
front deposits suggest that delta formation is more complicated than a simple seaward
prograding of bars, as is most commonly assumed in subsurface studies of delta front
deposits (e.g. Ainsworth et al., 1999; Tye et al., 1999). This study suggests that facies
architecture of delta fronts can be quite complicated and that bedding surfaces may dip both
downstream and upstream, especially within the proximal delta front. These needs to
incorporated into 3D facies architectural models of delta front deposits and may have
important implications for how and where sediment is sequestered in deltaic sedimentary
sinks.
The new data set of this study is represented by a digital model of the outcrop, which
allows an accurate construction of 3-D architecture of deposits. The 3-D shape and
40
relationships between “terminal “distributaries and associated mouth bar deposits was used to
build a 3-D sedimentary model (facies architecture) of delta front deposits.
3-D sedimentary bodies of Panther Tongue deposits built based on data collected
show that aggradation and lateral migration are related processes. Aggradation of delta front
deposits has a lateral migration component as well. As it is expected surfaces and deposits do
not have exact the same geometry as outcrop data behind the outcrop. “Terminal”
distributary bodies are thinning laterally (Fig. 18), away from channel axis. This approach
shows that most 3-D fluid flow models extrapolate from 2-D outcrop studies, assume that
deposits have little variation in the third dimension.
The 3-D outcrop studies documented here also may be used to extract quantitative
data for understanding the relative proportion of processes occurring in delta front areas as
either aggradation, lateral migration, switching of the “terminal” distributary channel
location, upstream accretion, or erosion. Quantitative outcrop data is required not only by the
oil industry but also by the sedimentary modeling system community, (Paola, 2000).
Computer models need to be tested on real 3-D data sets such as that presented in this paper.
41
CHAPTER 6
CONCLUSIONS
1. GPR used with photorealistic techniques is a powerful tool for the study
of reservoir analogs.
2. 3-D digital photorealistic models of the outcrops allow extraction of
quantitative geometric data about the deposits.
3. The study was focused on the 3-D geometry of “terminal” distributary
channels in delta front deposits, so that the 3-D sedimentary bodies
which are modeled can be associated with the facies distribution in
delta front deposits.
4 . For the first time “terminal” distributary channels and upstream
accretion bars in ancient delta front deposits are described.
5. In the study area three main distinctive facies were differentiated; these
are a “terminal” distributary channel, upstream accreting bars, and
distal bars.
6. 3-D surfaces of GoCad and bodies show that “terminal” distributary
and mouth bar deposits have surfaces with maximum topography of 1-2
meters.
7. Delta front deposits contain upstream (landward) inclined beds and
channelized beds not only seaward dipping clinoforms.
42
APPENDIX A
MEASURED SECTIONS
S75W
LEGEND
Cross Stratification
Hummoky Cross Stratification
Parallel Stratification
Assymetric ripples
Bioturbation scarce
medium
abundant
Scour
Iron concretion
Organic matter
Skolithos
Ophiomorpha
Paleophycos
Paleo current - S18W
clay
silt fine
med.v.finecoarse
sand
0
5
10
15
20
25
Section 1
N
6800
6800
7400
7000
7000
7200
7000
6800
7000
6600
C a n y o nG
ils
on
G
ulc
h
So
w B
el l y
Gu
l ch
S p r i n g
1000 m
GPR1
GPR4
GPR2
GPR3
GPR1
6
Scanned outcrop
GPR line
Measured section
Road
3i2i
1ii
1i
10 12864
3
1
9r
8r
2ii
2
5r
4r
3r2r
1r
4i5i6i
6r
7r
14
16
1918Area1
Area3
Area2
Map with location of measured section
(triangle for this particular section).
43
clay
silt fine
med.v.finecoarse
sand
0
5
10
15
20
25
Section 3
clay
silt fine
med.v.finecoarse
sand
0
5
10
15
20
25
Section 4
clay
silt fine
med.v.finecoarse
sand
0
5
10
15
20
25
Section 5
clay
silt fine
med.v.finecoarse
sand
0
5
10
15
20
25
Section 2
44
Sections 2 to 5. For location and scale please refer to first section or Figs. 2 and 12.
clay
silt fine
med.v.finecoarse
sand
0
5
10
15
20
25
Section 6
45
clay
silt fine
med.v.finecoarse
sand
0
5
10
15
20
25
Section 7
S38E
clay
silt fine
med.v.finecoarse
sand
0
5
10
15
20
25
Section 8
S18W
clay
silt fine
med.v.finecoarse
sand
0
5
10
15
20
25
Section 9
Sections 6 to 9. For location and scale please refer to first section or Figs. 2 and 12.
clay
silt fine
med.v.finecoarse
sand
0
5
10
15
20
25
Section 10
46
S32W
clay
silt fine
med.v.finecoarse
sand
0
5
10
15
20
25
Section 11
clay
silt fine
med.v.finecoarse
sand
0
5
10
15
20
25
Section 12
S10W
S50W
clay
silt fine
med.v.finecoarse
sand
0
5
10
15
20
25
Section 13
Sections 10 to 13. For location and scale please refer to first section or Figs. 2 and 12.
clay
silt fine
med.v.finecoarse
sand
0
5
10
15
20
25
Section 14
51
S50W
S32W
clay
silt fine
med.v.finecoarse
sand
0
5
10
15
20
25
Section 15
clay
silt fine
med.v.finecoarse
sand
0
5
10
15
20
25
Section 16
clay
silt fine
med.v.finecoarse
sand
0
5
10
15
20
25
Section 17
Sections 3r to 6r. For location and scale please refer to first section or Figs. 2 and 12.
clay
silt fine
med.v.finecoarse
sand
0
5
10
15
20
25
Section 18
48
S28W
clay
silt fine
med.v.finecoarse
sand
0
5
10
15
20
25
Section 19
S75W
S50W
clay
silt fine
med.v.finecoarse
sand
0
5
10
15
20
25
Section 1i
clay
silt fine
med.v.finecoarse
sand
0
5
10
15
20
25
Section 2
Sections 18, 19, 1i, 2i. For location and scale please refer to first section or Figs. 2 and 12.
clay
silt fine
med.v.finecoarse
sand
0
5
10
15
20
25
Section 3i
49
clay
silt fine
med.v.finecoarse
sand
0
5
10
15
20
25
Section 4i
clay
silt fine
med.v.finecoarse
sand
0
5
10
15
20
25
Section 5i
clay
silt fine
med.v.finecoarse
sand
0
5
10
15
20
25
Section 6i
Sections 3i to 6i. For location and scale please refer to first section or Figs. 2 and 12.
clay
silt fine
med.v.finecoarse
sand
0
5
10
15
20
25
Section 1ii
50
clay
silt fine
med.v.finecoarse
sand
0
5
10
15
20
25
Section 2ii
clay
silt fine
med.v.finecoarse
sand
0
5
10
15
20
25
Section 1r
Sections 1ii, 2ii, 1r, 2r. For location and scale please refer to first section or Figs. 2 and 12.
Section 2r
clay
silt fine
med.v.finecoarse
sand
0
5
10
15
20
25
clay
silt fine
med.v.finecoarse
sand
0
5
10
15
20
25
Section 14
47
S50W
S32W
clay
silt fine
med.v.finecoarse
sand
0
5
10
15
20
25
Section 15
clay
silt fine
med.v.finecoarse
sand
0
5
10
15
20
25
Section 16
clay
silt fine
med.v.finecoarse
sand
0
5
10
15
20
25
Section 17
Sections 14 to 17. For location and scale please refer to first section or Figs. 2 and 12.
clay
silt fine
med.v.finecoarse
sand
0
5
10
15
20
25
Section 14
52
Sections 7r to 9r. For location and scale please refer to first section or Figs. 2 and 12.
clay
silt fine
med.v.finecoarse
sand
0
5
10
15
20
25
Section 8r
clay
silt fine
med.v.finecoarse
sand
0
5
10
15
20
25
Section 9r
53
APPENDIX B
RADAR PROFILES
Profile GPR 1
N
6800
6800
7400
7000
7000
7200
7000
6800
7000
6600
C a n y o n
Gils
on
G
ulc
h
So
w B
el l y
Gu
l ch
S p r i n g
1000 m
GPR1
GPR4
GPR2
GPR3
GPR1
6
Scanned outcrop
GPR line
Measured section
Road
3i2i
1ii
1i
10 12864
3
1
9r
8r
2ii
2
5r
4r
3r2r
1r
4i5i6i
6r
7r
14
16
1918Area1
Area3
Area2
Map with location of GPR profile
(triangle for this particular profile).
100 MHz
50 MHz
54
POSITION (m)
0.0 30.0 150.0120.090.060.0
DE
PT
H (
m)
0.0
10.0
180.0
50.0
20.0
POSITION (m)
0.0 30.0 150.0120.090.060.0
DE
PT
H (
m)
0.0
10.0
180.0
20.0
N
6800
6800
7400
7000
7000
7200
7000
6800
7000
6600
C a n y o n
Gils
on
G
ulc
h
So
w B
el l y
Gu
l ch
S p r i n g
1000 m
GPR1
GPR4
GPR2
GPR3
GPR1
6
Scanned outcrop
GPR line
Measured section
Road
3i2i
1ii
1i
10 12864
3
1
9r
8r
2ii
2
5r
4r
3r2r
1r
4i5i6i
6r
7r
14
16
1918Area1
Area3
Area2
Map with location of GPR profile
(triangle for this particular profile).
100 MHz
50 MHz
Profile GPR 3
56
POSITION (m)
0.0 10.0 50.040.030.020.0
DE
PT
H (
m)
0.0
4.0
12.0
8.0
POSITION (m)
0.0 10.0 50.040.030.020.0
DE
PT
H (
m)
0.0
4.0
12.0
8.0
N
6800
6800
7400
7000
7000
7200
7000
6800
7000
6600
C a n y o n
Gils
on
G
ulc
h
So
w B
el l y
Gu
l ch
S p r i n g
1000 m
GPR1
GPR4
GPR2
GPR3
GPR1
6
Scanned outcrop
GPR line
Measured section
Road
3i2i
1ii
1i
10 12864
3
1
9r
8r
2ii
2
5r
4r
3r2r
1r
4i5i6i
6r
7r
14
16
1918Area1
Area3
Area2
Map with location of GPR profile
(triangle for this particular profile).
100 MHz
50 MHz
Profile GPR 2
55
POSITION (m)
0.0 10.0 50.040.030.020.0
DE
PT
H (
m)
0.0
4.0
12.0
8.0
POSITION (m)
0.0 10.0 50.040.030.020.0
DE
PT
H (
m) 0
.010.0
20.0
N
6800
6800
7400
7000
7000
7200
7000
6800
7000
6600
C a n y o n
Gils
on
G
ulc
h
So
w B
el l y
Gu
l ch
S p r i n g
1000 m
GPR1
GPR4
GPR2
GPR3
GPR1
6
Scanned outcrop
GPR line
Measured section
Road
3i2i
1ii
1i
10 12864
3
1
9r
8r
2ii
2
5r
4r
3r2r
1r
4i5i6i
6r
7r
14
16
1918Area1
Area3
Area2
Map with location of GPR profile
(triangle for this particular profile).
50 MHz
Profile GPR 4
57
POSITION (m)
0.0 30.0 150.0120.090.060.0
DE
PT
H (
m)
0.0
10.0
180.0
20.0
58
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64
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66
VITA
Cornel Olariu was born in Bucharest, Romania, on April 28, 1971. He graduated
in the summer of 1995 from University of Bucharest, Faculty of Geology and Geophysics
with a Bachelor of Science degree in Engineering Geology. He worked from 1995 to
2000 as a researcher at GEOECOMAR in Bucharest. He joined the graduate program of
University of Texas at Dallas, Geoscience Department in fall 2000 to work under the
supervision of Dr. Janok P. Bhattacharya.
