oluwatosin akinpelu c 201009 phd thesisghgh
TRANSCRIPT
-
7/26/2019 Oluwatosin Akinpelu C 201009 PhD Thesisghgh
1/295
Ground Penetrating Radar Imaging of Ancient Clastic
Deposits: A Tool for Three-Dimensional OutcropStudies
by
Oluwatosin Caleb Akinpelu
A thesis submitted in conformity with the requirementsfor the degree of Doctor of Philosophy
Geology DepartmentUniversity of Toronto
-
7/26/2019 Oluwatosin Akinpelu C 201009 PhD Thesisghgh
2/295
Ground Penetrating Radar Imaging of Ancient Clastic
Deposits: A Tool for Three-Dimensional Outcrop Studies
Oluwatosin Caleb Akinpelu
Doctor of Philosophy
Geology DepartmentUniversity of Toronto
2010
Abstract
The growing need for better definition of flow units and depositional heterogeneities in petroleum
reservoirs and aquifers has stimulated a renewed interest in outcrop studies as reservoir analogues
in the last two decades. Despite this surge in interest, outcrop studies remain largely two-
dimensional; a major limitation to direct application of outcrop knowledge to the three
dimensional heterogeneous world of subsurface reservoirs. Behind-outcrop Ground Penetrating
Radar (GPR) imaging provides high-resolution geophysical data, which when combined with two
dimensional architectural outcrop observation, becomes a powerful interpretation tool. Due to the
high resolution, non-destructive and non-invasive nature of the GPR signal, as well as its
reflection-amplitude sensitivity to shaly lithologies, three-dimensional outcrop studies combining
two dimensional architectural element data and behind-outcrop GPR imaging hold significant
promise with the potential to revolutionize outcrop studies the way seismic imaging changed
basin analysis.
-
7/26/2019 Oluwatosin Akinpelu C 201009 PhD Thesisghgh
3/295
architectural-element mapping with GPR imaging to obtain three dimensional architectural data
from outcrops.
Case studies from a variety of clastic deposits: Whirlpool Formation (Niagara Escarpment),
Navajo Sandstone (Moab, Utah), Dunvegan Formation (Pink Mountain, British Columbia),
Chinle Formation (Southern Utah) and St. Mary River Formation (Alberta) demonstrate the
usefulness of this approach for better interpretation of outcrop scale ancient depositional
processes and ultimately as a tool for refining existing facies models, as well as a predictive tool
for subsurface reservoir modelling. While this approach is quite promising for detailed three-
dimensional outcrop studies, it is not an all-purpose panacea; thick overburden, poor antenna-
ground coupling in rough terrains typical of outcrops, low penetration and rapid signal attenuation
in mudstone and diagenetic clay- rich deposits often limit the prospects of this novel technique.
-
7/26/2019 Oluwatosin Akinpelu C 201009 PhD Thesisghgh
4/295
Acknowledgments
I sincerely appreciate the support and guidance of Dr. Andrew Miall throughout the
duration of my graduate studies and especially in seeing this research project to
completion; thank you for giving me an opportunity of a lifetime.
I am particularly grateful to Dr. Nick Eyles for releasing the Ground Penetrating Radar
equipment from his research group throughout the data collection phase of my research;
your guidance in the early years helped set me in the right direction. To Ms. Lynn
Slotkin, I appreciate your assistance from the inception of my graduate program; even
those blunt e-mails were motivational. The painstaking review of the thesis and
suggestions by Dr. Rebecca Ghent and Dr. Uli Wortmann are also well-appreciated.
GPR Field assistance by Thomas Meulendyk helped avoid several field seasons of futile
data collection efforts; I am thankful for helpful tips on GPR data collection and
processing. Field assistance and technical support from Tudorel Ciuculescu remains
matchless; I am highly indebted to you for those long summer days at the outcrops.
Gerald Bryant, I owe a few chapters of my thesis to your assistance, accommodation and
field guidance on all my Utah field trips; I am very thankful for your help.
I am also grateful for funding provided by Ontario Graduate Scholarship, Natural
Sciences and Engineering Research Council, American Society of Petroleum Geologists
-
7/26/2019 Oluwatosin Akinpelu C 201009 PhD Thesisghgh
5/295
To Toyin and Elizabeth who bore the brunt of my dedicated effort to complete this
research project and for the countless hours of field assistance and proof-reading; I owe
the completion of this research project to you.
-
7/26/2019 Oluwatosin Akinpelu C 201009 PhD Thesisghgh
6/295
Table of Contents
Abstract ii
Acknowledgement iv
Table of contents vi
List of Tables viii
List of Figures ix
List of Appendices xiii
Chapter 1: Research Problem, Objectives and Significance 1
Chapter 2: Research Methodology: 9
Pre-survey Assessment 13
GPR Survey Planning 18
GPR Data Acquisition and Recording 28
GPR Data Processing 29
GPR Interpretation Methodology and Radar Stratigraphy 47
Chapter 3: Case Studies:
-
7/26/2019 Oluwatosin Akinpelu C 201009 PhD Thesisghgh
7/295
Shinarump Conglomerate, Hurricane Mesa (Utah) 137
St. Mary River Formation (Monarch, Alberta) 153
Chapter 4: Summary, conclusion and recommendation for future research 170
References 179
Appendix 1: Conductivity, relative permittivity and radar velocity data in sediment 219
Appendix 2: GPR instrumentation 220
Appendix 3: List of published GPR studies on sediments 227
Appendix 4: GPR Data Processing Software and Display 279
Appendix 5: GPR profiles from study locations 280
-
7/26/2019 Oluwatosin Akinpelu C 201009 PhD Thesisghgh
8/295
List of Tables
Table 1 GPR data sheet 28
Table 2 Radar facies chart 61
Table 3 Whirlpool Sandstone lithofacies 75
Table 4 Whirlpool Sandstone Radar Facies 82
Table 5 Navajo Sandstone Radar Facies 105
Table 6 Dunvegan Formation Radar Facies 128
Table A1 Typical radar propagation data in sediment 219
Table A3 List of Published GPR studies on Sediments 227
-
7/26/2019 Oluwatosin Akinpelu C 201009 PhD Thesisghgh
9/295
List of Figures
Figure 1: Relative resolution of different typical geophysical, geological
and remote sensing measurement 2
Figure 2: Outcrop mapping combined with GPR profile 10
Figure 3: GPR measurement setup 11
Figure 4: GPR antennas size with decreasing antenna frequency 13
Figure 5: Various modes for antenna deployment 22
Figure 6: Single transmitter-receiver common offset survey mode 24
Figure 7: Single transmitter-receiver common midpoint survey mode 27
Figure 8: Artificial structure on downstream accretion element createdby elevation variation along the profile line 31
Figure 9: GPR profile before and after de-wow filtering 32
Figure 10: GPR profile before and after background removal 33
Figure 11: GPR profile before and after deconvolution 35
Figure 12: GPR profile before and after amplitude gain 37
Figure 13: GPR Profile before and after diffraction migration 38
Figure 14: Navajo sandstone outcrop and 100 MHz antenna GPR line 45
-
7/26/2019 Oluwatosin Akinpelu C 201009 PhD Thesisghgh
10/295
Figure 17: Analyses of published GPR studies on sediments 51
Figure 18: GPR Image of a fluvial channel from Dunvegan Formation outcrop 54
Figure 19: Radar facies from Fraser (B.C) and Niobrara River, Nebraska 55
Figure 20: Examples of inclined radar facies 57
Figure 21: Examples of reflection-free radar facies 58
Figure 22: Example of horizontal radar facies 59
Figure 23: Example of hyperbolic reflection 60
Figure 24: Radar facies chart of presumed characteristic reflection
patterns from various sedimentary environments 62
Figure 25: Generalized stratigraphic chart for the Silurian system in New York 69
Figure 26: Early Silurian paleogeographic map of the Niagara Region 70
Figure 27: Location of the Whirlpool sandstone outcrop at Artpark, New York 71
Figure 28: Outcrop photo of the Whirlpool sandstone at Artpark, New York 72
Figure 29: Raw, unprocessed GPR data from the Whirlpool Sandstone 73
Figure 30: Artpark vertical section summarizing the main outcrop observations 74
Figure 31: Location of GPR lines at Artpark State Park, New York 77
Figure 32: Annotated Whirlpool outcrop photo and GPR lines 79
Figure 33: GPR line orthogonal to the Whirlpool Sandstone outcrop at Artpark 81
-
7/26/2019 Oluwatosin Akinpelu C 201009 PhD Thesisghgh
11/295
Figure 37: 3D GPR image of the ancient Navajo dune complex 90
Figure 38: Generalized stratigraphy of the Navajo Sandstone 94
Figure 39: Map of Navajo Sandstone location within Utah 96
Figure 40:Map showing field locations of radar profiles at Big Mesa, Utah 98
Figure 41: Outcrop photo of Navajo Sandstone central dune giant cross-bed
compared with smaller cross-bed set at Big Mesa near Moab, Utah. 100
Figure 42: Outcrop photo showing damp eolian interdune deposits overlainby flat-bedded fresh 101
Figure 43: Outcrop photo and GPR profile at Big Mesa, Utah 103
Figure 44: Radar profiles and perspective views of 3D GPR surveys at Big Mesa 107
Figure 45: Outcrop photo from Moab (Utah) revealing damp phase interdunedeposit from the Carmell Formation 110
Figure 46: Paleogeography during deposition of Dunvegan Formation 118
Figure 47: Lithostratigraphic relationships between the Dunvegan Formation
and the underlying Shaffesbury and overlying Kaskapau formations 119
Figure 48: Map location of Dunvegan Formation outcrop and GPR lines 121
Figure 49: Map showing location of GPR lines at Dunvegan outcrop 123
Figure 50: Dunvegan annotated outcrop photomosaic and GPR line 130
Figure 51: Dunvegan annotated outcrop photo and GPR line 131
Figure 52: Dunvegan annotated outcrop photomosaic and GPR line 133
Figure 53: GPR line and 3D schematic of Dunvegan depositional model Pink
-
7/26/2019 Oluwatosin Akinpelu C 201009 PhD Thesisghgh
12/295
Figure 56: Location of Shinarump Conglomerate outcrop at Hurricane Mesa 142
Figure 57: Location of Shinarump Conglomerate outcrop at Hurricane Mesa
showing GPR line 144
Figure 58: Photomosaic of the Shinarump conglomerate outcrop 148
Figure 59: Uninterpreted and interpreted GPR line at Huricane Mesa 149
Figure 60: Combined Shinarump GPR profile and outcrop Photomosaic 151
Figure 61: St. Mary River Formation Upper Cretaceous Paleogeography 155
Figure 62: Alberta Cretaceous Stratigraphic chart showing St. Mary River 156
Figure 63: Location of St. Mary River formation outcrop 158
Figure 64: Location of GPR lines at St. Mary River formation outcrop 160
Figure 65: Outcrop photo showing St. Mary River Formation channelsandstone 161
Figure 66: Outcrop photo showing St. Mary River Formation crevassesplay sandstone 162
Figure 67: Radar image of St.Mary River Formation ribbon channel sandstone 163
Figure 68: Radar profile showing ribbon channels and horizontal reflectors 164
Figure 69: Uninterpreted and interpreted St. Mary River Formation GPR profile 165
Figure 70: Block diagram depicting depositional model of St. Mary RiverFormation at the study site near Monarch, Alberta 168
Figure 71: Three-dimensional GPR data display from Navajo Sandstone
interdune deposit at Big Mesa Utah 175
-
7/26/2019 Oluwatosin Akinpelu C 201009 PhD Thesisghgh
13/295
Figure A4: Mala Geoscience Rough Terrain Antenna (RTA) 224
Figure A5: Mala Geoscience shielded antennas 225
Figure A6: GSSI monostatic and bistatic 100 MHz antennas 226
Figure A7: Analyses of 150 published GPR studies on sediments 278
Figure A8: GPR profiles from Artpark (New York, USA) 280
Figure A9: GPR profiles from Big Mesa, near Moab (Utah, USA) 281
-
7/26/2019 Oluwatosin Akinpelu C 201009 PhD Thesisghgh
14/295
List of Appendices
Appendix 1: Radar propagation data in sediment 219
Appendix 2: GPR Instrumentation 220
Appendix 3: List of published GPR studies on sediments 227
Appendix 4 GPR Data Processing Software and Display 279
Appendix 5: GPR profiles from study locations 280
-
7/26/2019 Oluwatosin Akinpelu C 201009 PhD Thesisghgh
15/295
Chapter 1
Research Problem, Object and Significance
1.1 Introduction
The need for better prediction of reservoir architecture and distribution of lithological
heterogeneity in aquifer characterization, hydrocarbon primary field development and
enhanced recovery projects is driving a burgeoning interest in outcrop-based studies of
ancient clastic deposits both as analogues for subsurface reservoirs and as a tool for
refining existing facies models. This research is driven by the need to account for thevariability and architectural complexity in subsurface clastic reservoirs, especially for the
purpose of petroleum resource evaluation and development, where conventional seismic
resolution is too poor to unambiguously delineate sandbody geometry or map their
internal heterogeneity.
Subsurface interpretation of reservoir architecture currently relies on seismic, well logs
and core data which are rarely closely spaced enough to permit unequivocal
interpretation. Practical limitations of most sources of high-resolution data rarely permit
the close spacing required for unambiguous interpretation (Figure 1). Advances in
seismic data acquisition, data processing and three-dimension data visualization in the
last two decades have significantly improved the resolution of reservoir information
-
7/26/2019 Oluwatosin Akinpelu C 201009 PhD Thesisghgh
16/295
and fluid content in reservoirs. In spite of these advances, predicting sub-seismic scale
heterogeneities in reservoirs is still a daunting challenge for many primary fielddevelopment, enhanced oil recovery and aquifer characterization projects.
Figure 1: Chart showing trade-off between the relative resolution of the informationobtained using different typical geophysical, geological and remote sensing measurementacquisition approaches and the relative scale of the investigations for which thoseacquisition geometries are typically used. (Image taken from Rubin and Hubbard, 2005).
The development of affordable digital imaging technologies as well as advances in
photogrammetry, aerial photography, LiDAR scanning, satellite imagery and positioning
have significantly improved outcrop studies. Increased spatial accuracy from satellite and
laser positioning systems provides access to geostatistical and geospatial analyses that
-
7/26/2019 Oluwatosin Akinpelu C 201009 PhD Thesisghgh
17/295
captured and brought to the geological laboratory via LiDAR scanning for further
measurements and analysis; bedding orientations and dips can then be measured at thelaboratory, considerably saving time spent doing fieldwork.
Despite these developments, outcrop studies remain largely two-dimensional, as most of
these novel techniques are not penetrative; they only reveal outcrop-face sedimentary and
stratigraphic features that can only be inferred beyond the outcrop-face with much
difficulty. The need for a more reliable tool of reconstructing fluvial architecture from
outcrops led to Mialls (1985) proposition of architectural element analysis following
the pioneering work of Allen (1983). Architectural elements are associations of
genetically related facies, which have some environmental significance. In depositional
systems, they are packets of genetically related strata, which define depositional elements
larger than individual bedform and smaller than channels. In outcrops, they are defined
by grain size, bedform composition, internal sequence, and most importantly, their
external geometry. This mapping technique has not only been applied to ancient fluvial
deposits as proposed by Miall (1985); it has been successfully applied on outcrops of
diverse depositional origin (Kocurek, 1981; Nio and Yang, 1993; Clark and Pickering,
1996). While there have been many outcrop studies with geometry and lithofacies of
channel and channel-belt deposits determined in outcrops described as analogues for
subsurface strata (Tyler and Finley, 1991; Mjos and Walderhaug, 1993; Dreyer, 1993a,
1993b; Dreyer et al., 1993; Robinson and McCabe, 1997; Willis and Gabel; 2003), the
-
7/26/2019 Oluwatosin Akinpelu C 201009 PhD Thesisghgh
18/295
The need to address the two dimensional limitation of outcrop studies motivated the
recent interest surge in Ground Penetrating Radar (GPR) imaging. However, due to theoperational difficulties of GPR imaging on outcrops and the susceptibility of GPR signals
to diffraction resulting in noise-laden images, very few outcrop-based GPR studies
(Appendix 3) have been successfully conducted (Corbeanu et al., 2001; Szerbiak et al.,
2001; Lee et al, 2009). Consequently, much of the current GPR effort has focused on
modern environment and Quaternary sediments (Beres and Haeni ,1991; Jol and Smith,
1991; Gawthorpe et al 1993; Huggenberger et al., 1994; Beres et al., 1995; Bridge et
al.,1995,1998; Van Overmeeren 1998; Bristow et al.,1999,2000b; Baker et al., 2001;
Corbeanu et al., 2001, 2002; Nobes et al.,2001; Hammon et al.,2002, Hornung and
Aigner 2002; Best et al, 2003; Cardenas and Zlotnik, 2003; Heinz and Aigner 2003;
Skelly et al., 2003, Woodward et al., 2003) as radar profiling is more convenient in
modern environments usually of less rugged terrain and modern sediments are less prone
to diagenetic alterations, which often make sedimentological interpretation of GPR data
from ancient clastic deposits a Herculean task. Although there has been an improvement
in our understanding of many ancient deposits via GPR studies of modern sediments, the
varied and unpredictable preservation potential of facies units in their modern setting
limits the usefulness of these studies. It is the preserved ancient record that is ultimately
what reservoir geologists are interested in. Miall (2006) sounded a caveat in this regard
and underscored the continued role of three-dimensional studies of ancient outcrop
-
7/26/2019 Oluwatosin Akinpelu C 201009 PhD Thesisghgh
19/295
direct visual observation of rock types and their spatial arrangement, thereby providing
invaluable insight into reservoir complexities for subsurface modelling (Geehan, 1993).Key components of significant relevance to reservoir characterization include facies
types, macro-scale lithological heterogeneity, channel dimensions, sandbody geometry
and their stacking pattern in relation to local and regional controls. These outcrop-scale
features control fluid-flow behavior in petroleum reservoirs, and aquifer and outcrop
analogs have been shown to provide valuable insight into reservoir architecture
(Grammer et al, 2004). While outcrop studies typically provide valuable data on vertical
dimensions of architectural elements within a depositional system, rarely do they yield a
three-dimensional picture of potential reservoir distribution especially from the
standpoint of aerial dimensions. Knowledge of the internal architecture is generally
limited because the exposures are either strike-oriented, dip-oriented, or at an orientation
oblique to these directions. These limitations have significantly weakened the usefulness
of outcrop studies as analogs for subsurface clastic reservoirs in the past; successful
application of GPR imaging on outcrop will provide an opportunity to validate current
clastic facies and architectural models that are mostly actualistic and conceptual
constructs.
The purpose of this research is four-fold:
to demonstrate that sedimentological and stratigraphic data can be obtained from
b d fil d di l h id l h ld i h i i
-
7/26/2019 Oluwatosin Akinpelu C 201009 PhD Thesisghgh
20/295
to demonstrate the effectiveness of GPR imaging in addressing the limitations of
two dimensional outcrop studies of ancient non-marine sandstones in a mannerthat has not been successfully explored before,
to develop a field methodology for outcrop-based GPR surveys, and
to provide a reliable framework for stratigraphic interpretation of GPR images as
a guide for future research.
By incorporating ground penetrating radar data with outcrop architectural element
analysis, data that are often difficult to unambiguously obtain, such as local paleoflow
variability, channel belt width, channel dimension, sinuosity, sandbody connectivity,
stacking patterns and lithological heterogeneity can now be readily obtained. Successful
application of GPR imaging on ancient clastic deposits will have far-reaching
significance; being able to obtain data such as true channel dimensions, channel
sinuosity, incised valley dimensions and their internal geometry will not only provide
hard data to validate or dispel many of the current clastic facies models based mostly on
studies of modern environment and Quaternary deposits; it will also testactualistically-
derived empirical equations (often used to predict channel belt width in the subsurface)
that relate maximum channel depth, channel width, and channel-belt width (Collinson,
1978; Lorenz et al., 1985, 1991; Fielding and Crane, 1987; Bridge and Mackey, 1993b).
Two features of GPR imaging make the technology exceptionally suitable for addressing
-
7/26/2019 Oluwatosin Akinpelu C 201009 PhD Thesisghgh
21/295
Although GPR imaging has been used intermittently for outcrop studies for over 25
years, the technology was not widely embraced as GPR instrumentation and dataprocessing technology was in its infancy and many of the GPR profiles generated were
not thoroughly processed to remove extraneous reflections required to ensure
unequivocal sedimentological and stratigraphic interpretation (Pratt and Miall, 1993;
Stephens, 1994). In the last few years, there have however been significant advances in
GPR instrumentation, data processing and display. Recently developed GPR systems are
lightweight, portable, robust and digital. In addition, the fact that GPR data can be viewed
and test-processed in real time during surveys ensures that both quality and results can be
assessed in the field. These advances as well as the availability of GPR processing
applications with two and three-dimensional visualization and interpretation aids have
enhanced rapid acquisition of continuous, shallow subsurface profiles that are ideally
suited for the investigation of sediments, shallow stratigraphy and sedimentary
architecture from both a 2-D and 3-D perspective.
Outcrop studies will undoubtedly benefit more from full-resolution three-dimensional
GPR surveys which produce 3D volumes that can be sliced and rotated to reveal features
such as map views of channel geometry, dimensions, sinuosity, anabranching and
temporal changes in depositional patterns. However, most GPR surveys are still two-
dimensional due to operational difficulties of 3D GPR surveying on outcrops. The few
three-dimensional surveys conducted to date are limited to small areas because of the
-
7/26/2019 Oluwatosin Akinpelu C 201009 PhD Thesisghgh
22/295
outcrop analogs has been demonstrated with 2-D profiles from earlier studies (Meyers et
al., 1996; Lunt and Bridge, 2004) as well as with fence diagrams constructed fromstaggered GPR profiles obtained in different directions behind outcrop face, ground-
truthed with outcrop sedimentological and architectural element mapping.
-
7/26/2019 Oluwatosin Akinpelu C 201009 PhD Thesisghgh
23/295
Chapter 2
Research Methodology
2.1 Introduction
The reliability of GPR outcrop based reservoir analogue studies depends on the qualityof outcrop data and GPR survey as well as subsequent processing of the GPR data. Many
of the earlier outcrop studies utilizing GPR (Pratt and Miall, 1993; Stephens, 1994; White
et al, 2004; Zeng et. al. 2004) were plagued with noise making it difficult to correlate
outcrop observations to radar reflectors. This is attributed to susceptibility of
electromagnetic signals to diffractions resulting from fractures as well as diagenetic
cementation in rocks (Smith et al., 2006). Diffraction occurs at discontinuities of
reflectors (such as fractures) and objects whose dimensions are small compared to the
transmitted electromagnetic wavelength. Figures 2 A and B illustrate the prevalence of
diffraction noise in earlier outcrop GPR studies.
Advances in GPR instrumentation and data processing over the last decade have
significantly improved GPR data quality. The field methodology for this research
involves obtaining photomosaics of laterally extensive sandstone exposures
supplemented by GPR profiles behind the mapped outcrop face. The photomosaics serve
a dual purpose: they act as base maps for detailed mapping of bounding surfaces and
-
7/26/2019 Oluwatosin Akinpelu C 201009 PhD Thesisghgh
24/295
Figure 2: (A) An example of outcrop face mapping of major bounding surface combinedwith GPR profile behind the cliff face. (Image taken from Zeng et al, 2004) (B) Ground-penetrating radar traverse measured about 100 m behind a dip-parallel outcrop of theupper Frewens sandstone body. (Image taken from White et al., 2004); note the difficultyin correlating GPR reflections with outcrop bounding surfaces.
Architectural-element analysis involves delineating major bounding surfaces as well as
recognition of suites of geometric elements characterized by distinctive facies
B
20 m
A
Diffraction noise
Diffraction noise
-
7/26/2019 Oluwatosin Akinpelu C 201009 PhD Thesisghgh
25/295
fluvial and eolian deposits) and unraveling their three-dimensional architecture (Miall,
1996)
Acquisition and processing of GPR data are the more laborious phases of the research
involving selection of the appropriate GPR system as well as efficient field survey and
data processing procedures. GPR is an electromagnetic method that, in many ways, is
similar to seismic reflection survey. A transmitting antenna radiates an electric pulse into
the ground that, under ideal conditions, behaves kinematically similar to an acoustic
wave. The pulse is transmitted, reflected, and sometimes diffracted by features that
correspond to changes in the dielectric properties of the earth. The waves that are
reflected and diffracted back toward the earths surface may be detected by a receiving
antenna, amplified, digitized, displayed, and stored for further analysis (Figure 3)
-
7/26/2019 Oluwatosin Akinpelu C 201009 PhD Thesisghgh
26/295
sometimes, sequence boundaries. The transmitter and receiver units are usually separate,
so the survey design is flexible. Data can be collected either in continuous or step mode.
In continuous mode, the antennas are dragged over the surface, whereas in step mode, the
antennas are placed on the ground in steps progressively along the profile. GPR surveys
usually proceed by recording a trace at each of a large number of survey points along a
line (or over a grid) with a fixed transmitter-receiver offset. As in reflection-seismic data,
GPR profiles may be plotted directly, or combined and plotted as a volume. The main
differences are that the scale of a GPR survey is about three orders of magnitude smaller
than that of a reflection seismic survey, and the resolution is correspondingly higher,
making the technology suitable for outcrop scale imaging.
The choice of antenna frequency is a tradeoff between the depth of target beds and the
intended resolution of the survey; the lower the frequency of the antenna, the poorer the
resolution but the greater the depth of penetration (Davis and Anan 1989; Jol, 1995).
Currently commercially available frequencies are between 12.5 and 1200 MHz, the time
sample increment is usually about 1 ns, the propagation velocities are one-quarter to one-
half that of light in a vacuum, and the average depth of penetration ranges from 5 to 40m,
depending primarily on the electrical conductivity and water content of the subsurface
materials. Generally, the lower the frequency, the bulkier the GPR equipment (Figure 4) ;
this implies that low frequency antenna (below 100 MHz) ideal for regional-scale
geological imaging may require more than one person to handle during surveys especially
-
7/26/2019 Oluwatosin Akinpelu C 201009 PhD Thesisghgh
27/295
Attenuation of GPR signals in rocks increases with water saturation and decreasing grain
size; wet and clayey rocks significantly attenuate radar signals thereby reducing depth of
penetration.
Figure 4: GPR antennas get bulkier with decreasing antenna frequency. (Image takenfrom http://www.sensoft.ca/products/pulseekko/pulseekkopro.htmll; - accessed August6, 2010).
2.2 Pre-survey Assessment
While GPR has proven to be an invaluable tool for high-resolution imaging in outcrop-
-
7/26/2019 Oluwatosin Akinpelu C 201009 PhD Thesisghgh
28/295
cut; it is easier to rule out situations where georadar is totally unsuitable than to state with
certainty that ground radar imaging will be successful. The following criteria must be
thoroughly evaluated before embarking on a GPR survey program:
2.2.1 Depth of Formation of Interest
How deep is the formation of interest? is perhaps the most important question in planning
GPR surveys. Many geological formations that are potential targets for GPR imaging are
located beneath several metres of overburden (for instance, many outcrops of Whirlpool
Sandstone and St. Mary River Formation) or beneath formations that might significantly
attenuate transmitted radar signals. The lowest frequency antenna currently available for
GPR surveys is 12.5 MHz (Figure 4) and this is limited to less than 50 metres penetration
depth in most clastic rocks, even in dry, clay-free lithologies. In addition, the attenuation
characteristic of the overburden and target medium is critical to penetration depth of
radar signals. A conservative rule-of-thumb is that radar will be ineffective if the actual
target depth is greater than 50% of the maximum range. A rough guide to penetration
depth D is
where conductivity, is in mS/m. This equation is not universal but is applicable when
(2.1) (Annan, 2004)
-
7/26/2019 Oluwatosin Akinpelu C 201009 PhD Thesisghgh
29/295
In geological applications, the parameters which have the greatest influence on the
electrical properties, and hence on penetration depth, velocity and reflector characteristics
are: (i) water saturation, (ii) clay content and (iii) pore water salinity. Dry, clay-free
sediments generally have higher velocities of propagation and lower attenuation
coefficients than wet strata. Depth of penetration is therefore highest in dry, porous
sediments (e.g. limestone, where probing depths may theoretically be up to 100 m) andlowest in water-saturated clay where depth of penetration may be less than 1 m (Cook
1975). In some cases, sand-rich formations can have diagenetic clays not obvious in
outcrop and could result in severe signal attenuation; hence, the need for pre-survey
assessment.
2.2.2 Contrast in electrical properties required toreflect or scatter a detectable amount of energy
GPR investigates the subsurface by making use of electromagnetic signals, which
propagate into the subsurface. Because reflections of radar signals are generated by
changes in electromagnetic impedance (contrast in electric and magnetic properties)
across the lithologies that the signals travel through in the same way seismic reflections
are generated across lithological contacts with acoustic impedance changes, detectable
reflections are expected in geological formations with contrasting lithologies. When an
electromagnetic wave propagates through the ground and encounters a surface where the
l t i d/ ti ti f th d h t f it ill b
-
7/26/2019 Oluwatosin Akinpelu C 201009 PhD Thesisghgh
30/295
are usually weak, although occasionally, magnetic properties can affect radar responses.
This is often the case when imaging diagenetically altered formations containing iron
oxides; hence, it is important to be cognizant of such magnetic effects as they can
significantly distort interpretation. Transmission of electromagnetic signals through rocks
is controlled by three parameters: dielectric permittivity, electrical conductivity and the
magnetic permeability. Dielectric permittivity is the ability of a material to store andrelease electromagnetic energy in the form of electric charge or its ability to restrict the
flow of free charges or the degree of polarization exhibited by a material under the
influence of an applied electric field. Conductivity is the ability of a material to pass free
electric charges under the influence of an applied field; this in rocks typically occurs via
dielectric conduction (in resistive lithologies which require the atoms to slightly polarize
to produce displacement currents) and electrolytic conduction (dominant in moist or wet
lithologies). Magnetic permeability describes how intrinsic atomic and molecular
magnetic moments respond to a magnetic field. Magnetic permeability in most clastic
rocks is very low and its effect on electromagnetic signal transmission can be ignored.
Both dielectric permittivity and electrical conductivity are strongly dependent on water
content (which is largely dependent on lithology); hence radar reflections patterns are
closely linked with lithological variability in rocks. For outcrops with minimal
lithological heterogeneity, it is sometimes efficient to conduct a preliminary small scale
survey at the outcrop to determine optimal target depth, resolution and appropriateness of
-
7/26/2019 Oluwatosin Akinpelu C 201009 PhD Thesisghgh
31/295
2.2.3 Noise sources that could preclude the use of GPR
Recorded GPR signals during surveys can be masked by electromagnetic signals fromnearby sources such as a radio transmitter or an electric power line located near the
survey site; in such cases, external signals may saturate the sensitive receiver electronics.
Radio transmitters are potential sources of interference and powerful radio signals can
overwhelm receiver electronics. Mobile phones are increasingly becoming a ubiquitous
form ofinterference; proximity to metal objects can also be disastrous for GPR survey.
Reflections can come from objects away to the side (sideswipe) and may be very strong if
metallic reflectors are involved. Surface features can produce strong sideswipe resulting
from substantial radiation of energy along the ground/air interface if ground conductivity
is high. Shielded antennas are very useful in such situations and are available in the 100
MHz frequency range and above. The shields are about the same size as the antenna and
use absorbing material to damp out the undesired signals. At lower frequencies, antenna
size and portability makes shielding impractical (as antenna size increases with
frequency); these considerations probably explain why there are no commercially-
available shielded GPR systems for antenna frequencies below 100 MHz. Practical
limitation of portability also explains why most shielded GPR systems consisting of both
transmitter and receiver antenna elements are housed in a single housing; hence, bistatic
antennas useful for common midpoint surveys are rarely shielded.
-
7/26/2019 Oluwatosin Akinpelu C 201009 PhD Thesisghgh
32/295
surveying equipment to the target outcrop. Difficulty in accessing outcrops is one of the
major factors explaining why there has been limited application of GPR imaging to
solving three dimensional outcrop problems. Although some can be reached by short
hikes, many outcrops ideal for GPR surveys can only be reached by ATVs (All Terrain
Vehicles) or helicopters; hence, accessibility to outcrops should be thoroughly evaluated
before embarking on GPR surveys.
2.3 GPR Survey Planning
Once the feasibility of GPR survey at an outcrop has been ascertained, proper design of
the survey as well as optimizing data acquisition to meet expectations and honor surface
constraints is the next challenge of outcrop-based GPR studies and requires thorough
planning.
In planning for GPR surveys on ancient sedimentary deposits, the following factors
critical to obtaining high-fidelity profiles must be considered:
Choosing the right GPR system there is currently a wide range of
commercially available GPR systems to choose from (see Appendix 2); it is
therefore important to choose a GPR system suitable for the purpose of the study.
Stratigraphic studies requiring time-depth conversion via common mid-point
surveys (data collection by moving the antennas progressively apart at an equal
offset from a central survey point) which gives the flexibility of calibrating radar
-
7/26/2019 Oluwatosin Akinpelu C 201009 PhD Thesisghgh
33/295
project is also critical; this is a trade off between the depth of the geological
formations being studied and the resolution required in the study. Low frequency
antennas (below 100 MHz) are better-adapted for low resolution deeper target
(20-50 metres deep) surveys while high frequency antennas (above 100 MHz) are
better-suited for high resolution shallow (less than 20 metre deep targets). As a
rule of thumb, the vertical resolution is theoretically one-quarter of thewavelength = v/f, where v is the velocity of the electromagnetic wave in the
rock (see Appendix 1 for typical velocities in different lithologies) and f is the
center frequency of the GPR antenna. It is also important to note that the
bulkiness of most GPR systems increase with decreasing antenna frequency
(Figure 4); this should be considered when planning GPR surveys as such low
frequency systems may require two or more people to handle.
Surface Elevation Uneven topography is characteristic of most outcrop top.
GPR surveys require flat outcrop tops or centimeter-scale topographic survey over
the GPR transects or across the area covered by the 3D grid if three-dimensional
GPR survey is being planned. This is a major challenge in conducting GPR
surveys on outcrops. Collection of topographic data is an essential component of
GPR survey especially where the outcrop surface is not flat and this could gulp a
significant chunk of survey time. Improper incorporation of topographic data into
the GPR lines may result in inaccurate velocities for static correction, which often
-
7/26/2019 Oluwatosin Akinpelu C 201009 PhD Thesisghgh
34/295
and GPS. In areas with subdued topography (less than 5 m change in elevation),
laser levels provide a fast and accurate method for collecting topographic data. In
more complex terrains, a total station provides greater flexibility and higher
accuracy; optical levels are also ideal but increase survey time. Where GPS units
are being considered for GPR surveys, Differential GPS units with centimeter-
scale accuracy are required. GPS surveys significantly reduce GPR survey time
especially in three-dimensional surveys as GPS measurements obviate the need
for a survey grid. In addition, with GPS measurements, real world locations of
GPR profiles can be easily displayed in Google Earthor imported into digital
topographic maps. It is however important to note that GPS receivers have
difficulty working under thick vegetation and require post processing. Some high-
resolution GPS tools also have compatibility problems with GPR units; if possible
GPS unit should be connected to the GPR equipment and tested before setting out
on field surveys. Most of the GPR surveys for this research were conducted on
flat surfaces requiring minor or no elevation correction.
Mode of data collection and station spacing while GPR data can either be
collected by dragging the antenna over the surface (continuous mode) or by
progressively moving the antenna along the survey line (step mode); the step
mode of data collection is less prone to data degradation and more suitable for
stratigraphic studies although it is more time-consuming. GPR antennas couple to
-
7/26/2019 Oluwatosin Akinpelu C 201009 PhD Thesisghgh
35/295
distance between survey points must be small enough (usually between 0.25 to
0.5 metres) to be able to resolve steeply dipping and small features as well as to
minimize spatial aliasing of radar reflections. Due to less survey time required,
many GPR surveys are done in continuous mode. Most shielded GPR systems are
designed for continuous data collection mode; therefore, for surveys where
shielded antennas are being considered, care should be taken to ensure optimal
coupling with the ground for efficient transmission of radar signals.
Step size - Spatial resolution places a constraint on the survey design and
selection of antenna centre frequency. Step size (the distance between each data
collection point, also known as station spacing) is extremely important and should
be included in the survey design process. In order to ensure that the ground
response is not spatially aliased in sedimentary studies, a maximum step size of
one metre (less than 1m where antenna frequencies higher than 200MHz are being
employed) should be used to provide detailed horizontal resolution of sedimentary
structures, yet allow profiles to be completed in a timely manner. A typical survey
with 100MHz antenna theoretically should have a step size of 0.25m; however,
larger step sizes can be used where the subsurface stratigraphy is composed of
continuous horizontal layers. If the step size is too large, the data will not
adequately define steeply dipping reflectors or diffraction tails. For 3D GPR
surveys, using a GPR grid spacing larger than a quarter-wavelength in the
-
7/26/2019 Oluwatosin Akinpelu C 201009 PhD Thesisghgh
36/295
geological studies; hence, very low step sizes are required for thorough definition
of dipping beds and surfaces. The decision to increase or decrease the step size
should be based on a variety of factors including: size of the sedimentary feature
being investigated, dip angle, and areal extent of the survey. From a practical
viewpoint, increasing the station interval reduces data volume and survey time,
yet from a data interpretation standpoint, adhering to the Nyquist close sampling
interval (which requires that measurements be spaced in all horizontal directions
near a quarter-wavelength of the highest signal and noise frequency content to
avoid spatial aliasing) is very important.
Antenna Orientation - Antennas used for most GPR surveys are dipolar and
radiate with a preferred polarity. The antennas are normally oriented so that the
electric field is polarized parallel to the long axis or strike direction of the target;
there is no optimal orientation for an equidimensional target.
-
7/26/2019 Oluwatosin Akinpelu C 201009 PhD Thesisghgh
37/295
Antenna orientation does affect the quality of collected data (Lutz et al., 2003) and it
should be taken into consideration when planning GPR surveys. The various
arrangements of GPR antenna deployment are illustrated in Figure 5; the most
common orientation that provides the widest angular coverage of a subsurface
reflector is the perpendicular broadside to direction of survey approach (PR-BD).
This orientation is also the easiest for surveying in sedimentary environments. In
some instances, it may be advisable to collect two data sets with orthogonal antenna
orientations in order to extract target information based on coupling angle. If the
antenna system is one which attempts to use a circularly- polarized signal, the antenna
orientation becomes irrelevant; however, as most commercial systems employ
linearly polarized antennas, orientation can be important. Maintaining a consistent
antenna configuration and electronic connections throughout a survey is important
because this will allow changes in polarity, due to increases or decreases in
permittivity (impedance) with depth, to be determined. Most shielded GPR units have
fixed antenna orientation, hence no need of deciding optimal antenna orientation.
GPR units with separate antennas however require determination of optimal antenna
orientation.
2.4 GPR Survey Design
Radar surveys for stratigraphic purpose are carried out either in common offset or
-
7/26/2019 Oluwatosin Akinpelu C 201009 PhD Thesisghgh
38/295
spacing between the units at each measurement location. The transmitting and receiving
antennas have a specific polarization character for the electromagnetic field generated
and detected. The antennas are placed in a fixed geometry and measurements made at
regular fixed station intervals, as depicted in Figure 6. Data on regular grids at fixed
spacing are normally needed if advanced data processing and visualization techniques are
to be applied. The parameters defining a common offset survey are GPR center
frequency, the recording time window, the time-sampling interval, the station spacing,
the antenna spacing, the line separation spacing, and the antenna orientation. During
surveying, antennas are either dragged along the ground and horizontal distances
recorded on a time-base, which can be converted to a distance-base through manualmarking or measuring wheel, or they are moved in a stepwise manner at fixed horizontal
intervals (step size). Step-mode operation generates more coherent and higher
amplitude reflections, as antennas are stationary during data acquisition. This ensures
more consistent coupling between the antennas and the ground as well as better trace
stacking (Annan and Cosway, 1992).
-
7/26/2019 Oluwatosin Akinpelu C 201009 PhD Thesisghgh
39/295
The MAL antenna used for this research (250 MHz MAL Geoscience shielded
antenna-Appendix 2) is adapted for single-fold reflection profiling; this GPR unit has
fixed antenna distance and orientation, which makes it impossible to conduct common
midpoint surveys.
Common midpoint (CMP) soundings are primarily used to estimate the radar signal
velocity versus depth in the ground, by varying the antenna spacing (commonly referred
to as offset) and measuring the change of the two-way travel time. At all distances
between source and receiver with a fixed midpoint, most of the energy that is reflected
by, not too steeply dipping, subsurface reflectors comes from the same points straight
below that given midpoint (Figure 7A). From the differences in arrival time versus offset
very accurate velocity estimates can be obtained from all layers. When a CMP
measurement is carried out, different events can be distinguished in the received signal,
when plotted on a travel time versus offset plot as depicted in Figure 7C. These are the
results of the air wave (1), the ground wave (2), the direct reflection from an interface (3),
and the critically refracted airwave (4). Since the velocity in air is always greater than the
largest velocity in the ground, a critical angle of incidence exists where the transmitted
wave travels in the air along the interface. These angles only exist when the wave travels
from a slower medium to a faster medium, such as a reflection from below the ground
that travels toward the earth surface. In a common-offset survey, the above mentioned
-
7/26/2019 Oluwatosin Akinpelu C 201009 PhD Thesisghgh
40/295
-
7/26/2019 Oluwatosin Akinpelu C 201009 PhD Thesisghgh
41/295
-
7/26/2019 Oluwatosin Akinpelu C 201009 PhD Thesisghgh
42/295
2.5 GPR Data Acquisition and Recording
GPR data have the advantage of being viewed directly as they are being recorded in the
field and many GPR equipment control units have basic editing and data processing
capability. Despite this advantage over seismic data acquisition, radar data acquisition
parameters such as antenna frequency, sampling frequency, number of stacks and time
window can not be changed during data processing. To ensure that data acquisition time
is effectively used, laptop computers with installed data processing applications should be
taken to the field and GPR data edited, checked and test-processed in the field before the
completion of field surveys as it is often difficult to fix problems in GPR data that are due
to poor acquisition parameters without having to return to the field.
Detailed record of GPR lines, outcrop photos and their locations should be accurately
documented in the field as the effectiveness of data processing and geological
interpretation hinge on proper documentation of GPR line locations and other outcrop
observations. GPR data sheet such as Table 1 should be completed as each GPR line is
being recorded.
Table 1: Example data sheet that can be used for collecting data from daily GPR surveys
-
7/26/2019 Oluwatosin Akinpelu C 201009 PhD Thesisghgh
43/295
2.6 GPR Data Processing
GPR signals are usually processed like seismic data although the two are slightly
different. GPR data are most often treated as scalar although as electromagnetic fields,
they are vector quantities. Hence, GPR signals may behave differently due to frequency-
dependent absorption and phase changes at reflections.
In the early days of GPR data processing, much of the data processing was done withseismic data processing software. However, GPR-specific processing software is now
commercially available from packages offered by manufacturers of GPR or as add-ons
for seismic processing software. For this study, REFLEX and GPR Slice processing and
display software were used for data processing and perspective display.
Like seismic reflection data, GPR data require processing aimed at sharpening the signal
waveform by improving the signal to noise ratio of the radar profiles (Reynolds 1997).
The amount of processing depends on the quality of field data obtained, and this can
range from basic processing steps to the more complex application of data processing
algorithms. Data obtained with shielded antennas are often less cluttered with extraneous
signals and usually require less rigorous data processing. In most instances, basic
processing steps can be applied in real-time during data acquisition; however, these might
not be enough to remove extraneous noise from the acquired data. A detailed discussion
of GPR processing steps is important, as the final output of GPR surveys is dependent on
processing steps; radar facies must therefore be compared only between data processed
-
7/26/2019 Oluwatosin Akinpelu C 201009 PhD Thesisghgh
44/295
criteria can be significantly influenced by the processing steps. Continuous reflection can
appear discontinuous by applying inappropriate gains during data processing and
reflection dips can result from inappropriate processing algorithms; hence, the
importance of proper signal processing steps and outcrop data as ground truth to verify
the fidelity of radar data. This also underscores the importance of documenting data
acquisition and processing steps in GPR publications to allow comparison between
studies.
Commonly applied processing steps on GPR data include:
2. 6.1 Topographic Correction
The collection of topographic data is an essential component of GPR survey as radar data
collected in the field does not take into account topographic variation along a survey line.
This can be corrected by moving traces up and down by an appropriate two-way-time
relative to a common datum, based on knowledge of the velocity, and, therefore, depth
profile of the uppermost part of the radar profile. In order to do this, survey line
topography must be adequately characterized. Topographic surveys are typically
performed using a variety of instruments including optical levels, total station, laser
levels, and differential GPS as these have the required vertical resolution and allowrelatively rapid data collection. Spatial sampling in such surveys should ensure that all
significant breaks in slope are accounted for. While lower frequency antenna can tolerate
-
7/26/2019 Oluwatosin Akinpelu C 201009 PhD Thesisghgh
45/295
equipment was not available for this study; hence outcrops with flat surfaces were chosen
for this study to avoid the need for elevation correction of the recorded GPR profiles.
Figure 8: Artificial structure on downstream accretion element created by elevation
variation along the profile line. (Profile recorded on Castlegate sandstone outcrop, TusherCanyon, Utah).
2.6.2 Dewow
Wow noise is peculiar to ground penetrating radar and it is as a result of the close
proximity of receiver to transmitter. Dewow is one of GPR processing basic temporal
filtering steps aimed at removing very low frequency components from the data (Figure
9). Very low frequency components of GPR data are associated with either inductive
phenomena or possible instrumentation dynamic range limitations. This process has
historically been done using analog filters in hardware but with the advent of true digital
data acquisition, it has also become a data processing step (Gerlitz et al, 1993). Dewow
filter acts on each trace independently by calculating a mean value of each trace and the
-
7/26/2019 Oluwatosin Akinpelu C 201009 PhD Thesisghgh
46/295
Figure 9 (A)Display of a single data trace (left) and data section (right) with the lowfrequency wow component masking the real data. (B)Display of a single data trace (left)and data section (right) where the Wow seen in (A) above has been removed with thedewow high pass filter. (Image taken from Annan, 2004).
2. 6.3 Backgound Removal
One of the most common operations specifically applied to GPR data is the use of
B
A
-
7/26/2019 Oluwatosin Akinpelu C 201009 PhD Thesisghgh
47/295
Figure 10: (A)GPR profile before background removal (B)GPR profile afterbackground removal. (Image taken from http://www.malags.com/Downloads/Product-Brochures.aspx; accessed, August 6, 2010).
In situations where antenna ringing, transmitter reverberation and time synchronous
system artifacts appear, it is very effective in allowing subtle weaker signals, which are
l t t b i ibl i d ti B k d filt li i t t ll
A
B
-
7/26/2019 Oluwatosin Akinpelu C 201009 PhD Thesisghgh
48/295
(Figure 10 A and B). It is quite effective in relatively lossy materials (conductive
lithologies such as wet or shaly rocks).
2. 6.4 Deconvolution
Deconvolution is aimed at removing effects of a previous filtering operation (Yilmaz,
1987, 2001; Kearey and Brooks, 1991). In both seismics and radar signals, deconvolution
attempts to remove filtering effects resulting from propagation of a source wavelet
through a layered earth, and the recording system response. The intended effect of the
deconvolution process is to shorten pulse length and, therefore, improve vertical
resolution (Figure 11).
It is often tempting to apply seismic processing steps like deconvolution to GPR because
of their kinematic similarity; it is however important to note that deconvolution of GPR
data is not straightforward and rarely yields impressive results (Fowler and Still, 1977;
Payan and Kunt, 1982; LaFleche et al., 1991; Maijala, 1992; Todoeschuck et al., 1992;
Fisher et al., 1996; Arcone et al., 1998). The primary reason for this is that the radar pulse
is often as short and compressed as can be achieved for the given bandwidth and signal-
to-noise conditions. Another important factor is that some of the more standard
deconvolution procedures have underlying assumptions required for wavelet estimation
such as minimum phase and stationarity, which oftentimes are not appropriate for GPR
data (Annan, 1999). The rapid attenuation of GPR signal amplitude means that
-
7/26/2019 Oluwatosin Akinpelu C 201009 PhD Thesisghgh
49/295
Figure 11: (A)GPR profile before deconvolution (B)GPR profile after deconvolution.
(Image taken from http://www.malags.com/Downloads/Product-Brochures.aspx-accessed on August 6, 2010).
Few instances where deconvolution has proven beneficial occurred when extraneous
A
B
-
7/26/2019 Oluwatosin Akinpelu C 201009 PhD Thesisghgh
50/295
2. 6.5 Time Gain
Radar signals are prone to rapid signal attenuation as they propagate into the ground.
Signals from greater depths are often very weak, such that simultaneous display of this
information with signals from a shallower depth requires preconditioning for visual
analysis and display. When the amplitude of display is optimal for shallow depth signals,
events from greater depths may be invisible or indiscernible. Gains are required because
the amplitude of a reflected signal decreases with time and depth due to attenuation,
geometrical spreading, partial reflection and scattering (Davis and Annan 1989; Reynolds
1997). "Time gain" applied to radar data attempts to equalize amplitudes by applying
some sort of time-dependent gain function, which compensates for the rapid fall off inradar signals from deeper reflectors. A variety of gain functions can be applied to radar
signals (e.g. constant, linear and exponential gains); it is however important to understand
that the choice of gain adopted might alter the amplitude fidelity of the signals in the
data.
Geological radar surveys are especially susceptible to signal attenuation in mud-rich
environments; hence, for stratigraphic horizon continuity, displaying all the information
irrespective of amplitude fidelity might be important. In this case, manual gain or a
continuously adaptive gain such as AGC (automatic gain control) is often used. With
AGC gain, each data trace is processed such that the average signal is computed over a
time window and then the data point at the centre of the window is amplified (or
i f ti i h it h ld b l t d b d th ifi l f th d
-
7/26/2019 Oluwatosin Akinpelu C 201009 PhD Thesisghgh
51/295
gain function is chosen, it should be selected based on the specific goal of the survey and
data processing requirement; the objective should be to modify the data while retaining
fidelity without introducing artifacts.
Figure 12: (A) Un-gained Whirlpool Sandstone GPR Profile. (B)Manually-gainedprofile at the Whirlpool Sandstone outcrop at Artpark, USA.
It is important to document the type of gain function applied to radar data while
discussing radar facies as radar reflector character is dependent on the signal processing
steps applied to the data (relative amplitudes and/or phase relationships are changed); for
Queenston Shale
Whirlpool channel sand
A
B
2 6 6 Mi ti
-
7/26/2019 Oluwatosin Akinpelu C 201009 PhD Thesisghgh
52/295
2.6.6 Migration
Migration relocates reflections to their true spatial position based on the velocity
spectrum of radar signals through the rock layers to produce a real structure map of
subsurface features. Migration algorithms do this by removing diffractions, distortions,
dip displacements and out-of-line reflections resulting from the fact that radar antenna
radiate and receive electromagnetic energy in a complex 3- D cone.
The goal of migration is to make the reflection profile look like the geological structure
in the plane of the survey. It attempts to correctly position subsurface reflection events
(Hatton et al., 1986). However, due to various uncertainties, a significantly improved but
still imperfect image is usually achieved (Figure 13). Such improvements are quitebeneficial in sedimentological studies, where the nature and form of stratigraphic units
and primary sedimentary structure is of utmost importance.
A
B
Migration is generally used for improving section resolution and developing more
-
7/26/2019 Oluwatosin Akinpelu C 201009 PhD Thesisghgh
53/295
Migration is generally used for improving section resolution and developing more
spatially realistic images of the subsurface and is, perhaps, the most controversial of the
GPR processing techniques. Migration techniques, like deconvolution, were originally
developed for the seismic industry where they are considered as vital for even basic
interpretations. Unfortunately, migration tends to be less successful with GPR, and
although it can be used in relatively homogeneous environments, it is not so good with
complex, heterogeneous environments (lithologies) with variable radar velocity typical of
clastic many rocks. Despite this, migration is still a vital georadar processing step and
classical techniques have been applied successfully to a range of different applications.
Examples include reverse time migration (Sun and Young, 1995; Meats, 1996), FK
migration (Fisher et al., 1994; Pettinelli et al., 1994; Pipan et al., 1996; Yu et al., 1996;
Hayakawa and Kawanaka, 1998) and Kirchhoff migration (in Moran et al., 1998).
Specific GPR-based methods have been developed to overcome some of the limitations
in the seismic data migration algorithms. Examples include matched filter migration(Leuschen and Plumb, 2000); Kirchhoff migration modified for radiation patterns and
interface reflection polarisation (Moran et al., 1998; Van Gestel and Stoffa, 2000);
eccentricity migration for pipe hyperbola collapsing (Christian and Klaus-Peter, 1994),
3D-based vector and topographic migration (Lehman and Green, 2000; Heincke et al.,
2006; Streich et al., 2007) and frequency domain migration for lossy soils (Di and Wang,
2004; Sena et al., 2006; Oden et al., 2007). These new methods are yet to be incorporated
-
7/26/2019 Oluwatosin Akinpelu C 201009 PhD Thesisghgh
54/295
-
7/26/2019 Oluwatosin Akinpelu C 201009 PhD Thesisghgh
55/295
pulse is propagated through the host medium, Vm, and the depth to the bounding surface
-
7/26/2019 Oluwatosin Akinpelu C 201009 PhD Thesisghgh
56/295
p p p g g , m, p g
d, are related by the Equation
t= 2d/Vm
Velocity for depth conversion of the radar profiles recorded in this study was estimated
using this relationship. Although rarely, velocity required for time-depth conversion is
also estimated by direct laboratory measurements of dielectric permittivity on field
samples; measuring travel time between two wells using borehole radar; and
transillumination surveys between two parallel exposures (Annan and Davis, 1976; Topp
et al., 1980; Fisher et al., 1992a; Greaves et al., 1996; Reynolds, 1997; Binley et al.,
2001; Hammon et al., 2002; Tronicke et al., 2002a).
2. 7 Visualization and Display
Ground-penetrating radar has been used for geological imaging since the 1980s and has
since developed into a valuable tool for stratigraphic studies. Most studies utilize
common-offset, 2-D radar reflection profiles to display stratigraphic information obtained
in modern environments and outcrop. Where there is significant lateral variability in
internal structure, pseudo-3D or true 3D surveys may be desirable. Pseudo-3D surveys
involve collecting data on regular or irregular survey grids, usually in two mutually
perpendicular directions, and often displaying results as fence diagrams (for example,
B i t 1995 Ai t l 1996 B i t t l 1996 1999 2000b R b t t l
(2.4)
time in three dimensional seismic imaging revolutionized the way GPR results are
-
7/26/2019 Oluwatosin Akinpelu C 201009 PhD Thesisghgh
57/295
g g y
displayed and interpreted (Goodman et al., 1995), and recent GPR three-dimensional
imaging produced exciting results for visualization and enhanced interpretation (Conyers
et al., 1997; Jol et al, 2003; Leckebusch, 2003).
While full resolution 3D GPR surveys are generally more informative than single
profiles, it requires significantly increased data acquisition time. Hence, they are seldom
used in geological studies. Data processing for three dimensional GPR surveys is more
time consuming partly because of greater data volumes and complexity, but also due to
lack of efficient commercially available software for three dimensional GPR data
processing; these explain why there are few 3D GPR outcrop studies in the GPR
literature. Not all studies require 3D surveys; staggered GPR lines parallel and orthogonal
to the outcrop face displayed as a fence diagram often yield sufficient architectural details
for stratigraphic interpretation.
2. 8 Causes of GPR Reflections
Although GPR images appear similar to seismic reflections generated across surfaces due
to changes in acoustic impedance in the subsurface, GPR reflections are generated by
changes in electromagnetic impedance due to variation in the electrical and magnetic
properties of the lithologies that an electric pulse transmitted from the antenna into the
ground passes through as it makes its way through lithologies with different electrical and
have been loosely defined. Few studies that have investigated the causes of GPR
-
7/26/2019 Oluwatosin Akinpelu C 201009 PhD Thesisghgh
58/295
reflection in sediments (Van Dam and Schlager, 2000; Van Dam, 2001) discovered that
propagation of electromagnetic signals is primarily dependent on the electrical
conductivity and magnetic permeability of the medium that the signals pass through.
Electrical conductivity is the ability of the material to transmit electric charges under the
influence of an applied field. In rocks and sediment, this often depends on the dielectric
permittivity associated with variations in water content and ionic concentrations. Water
in sediment pore space normally contains ions, and the electrical conductivity associated
with ion mobility is the dominant factor in determining bulk-material electrical
conductivity. Since water is invariably present in the pore space of sediments and rocks,
it has a dominant effect on electrical properties. Magnetic permeability is the degree of
magnetization of a material that responds linearly to an applied magnetic field; this is
significant in rocks or sediments rich in ferromagnetic minerals. However, in most
sedimentary rocks, the amount of ferromagnetic minerals is minimal and hardly
contributes significantly to generation of radar reflections. Hence, in most GPR surveys
on sediments and rocks, the dominant control on radar transmission and reflection is
electrical conductivity governed by water content and the sediment static conductivity.
The variation in sediment water content often relates to both changes in sediment
porosity and permeability, which in turn is dependent on changes in grain size and fabric
often associated with lamination, cross-bedding and bounding surfaces. Rock property
bed laminae and the associated bottom-set layer (Pryor, 1973; Beard and Weyl, 1973,
-
7/26/2019 Oluwatosin Akinpelu C 201009 PhD Thesisghgh
59/295
Jordan and Pryor, 1987). Emmet et al (1971) observed that porosity and permeability
parallel to the cross-bed laminae are higher than perpendicular to the laminae. Such
porosity and permeability changes have direct control on water content, which determines
electrical conductivity changes that generate radar reflections (Figure 14).
A
High porosity cross-bedB
5 m
Sedimentary bedding is a product of changes in sediment composition and changes in the
-
7/26/2019 Oluwatosin Akinpelu C 201009 PhD Thesisghgh
60/295
size, shape, orientation and packing of grains (Collinson and Thompson, 1989) which
results in corresponding changes in porosity (Figure 15).
Figure 15: Bedding in sediments and sedimentary rocks and associated porosity resultingfrom changes in composition, size, shape, orientation and packing of sediment grains.(Image modified from Neal, 1994).
Van Dam et al., (2002a) reported that goethite iron-oxide precipitates, occurring either in
bands or irregular layers, were responsible for significant reflections in the aeolian sandsthey studied. This was due to the higher water retention capacity of goethite with respect
to the host quartz sand, which resulted in higher dielectric permittivity.
Higher porosity and permeability
Lower porosity and
permeabilitty
Textural differences between laminae of differing origins may also control cementation
-
7/26/2019 Oluwatosin Akinpelu C 201009 PhD Thesisghgh
61/295
patterns and, hence, post depositional diagenesis, which may influence radar reflection
patterns in consolidated sediments.
2. 9 GPR Interpretation Methodology and Radar Stratigraphy
Because seismic reflection and GPR data are analogous in terms of wave propagation
kinematics (Ursin, 1983; Carcione and Cavallini, 1995) as well as reflection and
refraction responses to subsurface discontinuities (McCann et al., 1988; Fisher et al.,
1992a) many of the broad assumptions that underpin processing and interpretation of
seismic reflection data (Sangree and Widmier, 1979; Yilmaz, 1987, 2001) are often
routinely applied to GPR data. However, it must be borne in mind that radar images are
different from seismic images in the following respect:
1. Signal penetration and reflection amplitude are controlled by water saturation,
clay content and magnetic property of the sediment.
2. Radar signals are more prone to scattering making diffraction noise more
prominent in radar profiles.
3. The investigation depth is much less.
4. Resolution is in sub-metre scale.
5. Radar surveys require direct contact between the pulse-transmitting antenna and
the medium which the signals are transmitted through (rocks or water/moist
From the interpretation standpoint, the basic assumption in both techniques is that, at the
-
7/26/2019 Oluwatosin Akinpelu C 201009 PhD Thesisghgh
62/295
resolution of the survey and after appropriate data processing, reflection profiles will
contain accurate information regarding the external geometry and internal structure of a
sediment body. This implies that the form and orientation of bedding and sedimentary
structures in the plane of the survey will be adequately represented by recorded
reflections, and non-geological reflections can be readily identified and removed by data
processing, or by simply discounting them from the interpretation. While this assumption
holds in many instances, accurate interpretation of GPR data is dependent on the nature
and appropriateness of data processing steps undertaken, the interpretation techniques
employed, and the overall understanding and experience of the interpreter with respect to
GPR; hence, care must be taken to ensure that GPR profiles are not treated as geological
cross sections but interpreted in the context of the local geology and ground-truthed with
outcrop data.
Based on the similarities between GPR and seismic reflection, the concept of seismic
stratigraphy was adapted for interpretation of GPR profiles soon after the realization that
GPR could provide useful data for stratigraphic and sedimentological studies (Baker,
1991; Beres and Haeni, 1991); Jol and Smith (1991) coined the term radar stratigraphy
for this new interpretation technique. Gawthorpe et al (1993) defined radar facies basedon the terminology used to describe seismic facies (Mitchum et al., 1977; Brown and
Fisher 1980) as three-dimensional packages that represent particular combinations of
erosional hiatuses despite acknowledging that while seismic sequences can be mapped
-
7/26/2019 Oluwatosin Akinpelu C 201009 PhD Thesisghgh
63/295
on at least a basin scale and reflect units that form over hundreds of thousands to millions
of years, radar sequences may be limited to particular depositional environments (e.g. a
point bar in a fluvial channel belt) and may form over a much shorter time scale of tens to
thousands of years. Although, this interpretation methodology has been widely
embraced over the years, it is important to underscore the fact that GPR resolution is an
order of magnitude higher than conventional seismic resolution and coverage of GPR
surveys rarely has the capability to image stratigraphic sequences and sequence
boundaries; it is more appropriate for imaging of meso-scale depositional features or
outcrop scale architectural elements. Although decimeter-scale resolution has been
reported in high resolution seismic surveys, the technology is rarely used for outcrop
studies; hence, ground penetrating radar remains the choice technology for high
resolution outcrop imaging.
To avoid interpretive connotations in describing radar reflections, it is recommended that
unambiguous descriptive criteria such as geometry; dip of reflections, relationship
between reflections be used to describe radar reflections rather than terms with
interpretive connotations like, sequence boundaries, systems tract, etc used in seismic
stratigraphy. Interpretations based solely on processing-dependent attributes such asreflection continuity and amplitude should also be avoided as these are dependent on the
data processing algorithms or gain magnitude applied to the data and are hardly
Reflection packages a, b and c (Figure 16A) could be interpreted as different architectural
-
7/26/2019 Oluwatosin Akinpelu C 201009 PhD Thesisghgh
64/295
elements based on reflection continuity but the reflectors are seen as continuous in the
better gained data (Figure 16B).
Figure 16:(A) Poorly-gained radar profile giving the impression of facies with lowcontinuity (B) Same data in (A) with gains applied to display all reflectors. GPR dataacquired at Whirlpool Sandstone.
Also, while in most cases, radar reflections parallel bedding and bounding surfaces, care
must be taken to ensure that reflections generated by the water table and diagenetic
horizons, diffractions generated by isolated reflector points, out-of-line reflections,
acb
A
B
0
6
0
6
Depth(m)
Depth(m)
2.10 Radar Facies
-
7/26/2019 Oluwatosin Akinpelu C 201009 PhD Thesisghgh
65/295
Analysis of 150 published studies in the last thirty years on stratigraphic imaging with
ground penetrating radar reveals an obvious bias towards studies of modern and recent
deposits (Figure 17 and Table A3, Appendix 3). Much of the GPR effort on rocks has
been concentrated on carbonates as the low electrical conductivity of carbonate rocks
make them highly conducive to georadar imaging.
Numberofpublishe
dGPR
studies
rofpublishe
dGPR
studies
A
B
Observations from analyses of published studies also show that highest radar signal
-
7/26/2019 Oluwatosin Akinpelu C 201009 PhD Thesisghgh
66/295
penetration is observed in carbonate rocks due to their high resistivity. This study
however focuses on the application of GPR imaging technology to the studies of ancient
clastic depositional units.
There is currently no formal methodology for documenting radar profiles and radar
facies; this in addition to different processing and display formats adopted by various
authors make comparison of radar facies rather challenging; but an attempt is made
below to summarize observations and describe radar facies commonly observed in a
variety of depositional environments. Radar facies are defined by: external reflection,
geometry, dip of reflections and relationship between reflections. Due to the paucity of
GPR studies on ancient sediments, most of the radar facies discussed in this section are
from modern sedimentary environments and Quaternary deposits.
Since the inception of its use as a tool for stratigraphic and sedimentological
interpretation, much of the emphasis of GPR studies has been on characterization and
interpretation of radar facies, with radar surfaces and radar packages typically not being
defined. This overemphasis on radar facies analysis, rather than true radar stratigraphy,
led to the common misconception that any radar reflection pattern constituted radar
facies. As a result, use of radar facies to describe reflections not related to primary
sedimentary structure and stratigraphy became rife in the GPR literature. Terms such as
water-table radar facies and hyperbolic or diffraction radar facies can be found
resolution of the radar profile). These examples are in violation of the correct use of the
-
7/26/2019 Oluwatosin Akinpelu C 201009 PhD Thesisghgh
67/295
term radar facies and, therefore, the true principles of radar stratigraphy. Further
confusion to the interpretation of radar profiles has also been caused by use of
interpretive facies names, such as channel-fill facies and overbank facies. If the
context is not made clear, use of interpretive facies names has the danger of suggesting
that particular depositional environments or sub-environments are characterized only by
certain radar facies which is not true based on the findings from published studies and
GPR outcrop data obtained in this study. Radar facies should therefore be described
without interpretive connotations and an uninterpreted version of the radar facies
provided to provide readers an unprejudiced data and basis for interpretation.
The value of radar facies interpretation is demonstrated in all the case studies for this
research especially at the Shinarump Conglomerate (Figure 21 A), Navajo Sandstone
(Figure 21 B) and Whirlpool Sandstone (Figure 22A). Common radar reflection patterns
(facies) typically observed from a variety of sedimentary environments are discussed
below:
2.10.1 Concave upward/trough-shaped reflectors
Concave-upward ground radar reflectors are observed as valley fill (Ilya, 2006), cut and
fill (Heinz et al, 2003) channel (Figure 18), chute, scour, bar top hollows (Best et al,
2006) and trough cross-beds (Bristow et al, 1999). Documented concave upward GPR
Channels are often several metres to hundreds of metres in width and may have simple to
l fill
-
7/26/2019 Oluwatosin Akinpelu C 201009 PhD Thesisghgh
68/295
complex fill.
Figure 18: GPR Image of fluvial channels from Dunvegan Formation outcrop (PinkMountain, British Columbia).
Valleys are typically hundreds of metres to kilometre-scale in width, they contain
channels and channel belts and are rarely defined in GPR profiles.
While the various concave-upward radar facies are sometimes geometrically-identical, it
might be difficult to correctly interpret them; they can however be discriminated by their
scale, internal geometry and facies associations. This underlines the importance of
documenting the horizontal and vertical scale of GPR profiles. The geometry of
reflectors often depends on the orientation of the GPR line in relation to the channel axis
(for bedload deposits). GPR profiles along the axis of a channel deposit usually reveal
different reflector geometry compared to profiles perpendicular to the channel axis; hence
it is important to document the orientation of GPR profile from which the radar facies are
obtained.
CH CH
A
-
7/26/2019 Oluwatosin Akinpelu C 201009 PhD Thesisghgh
69/295
B
2.10.2 Inclined Reflectors
li d d fl b d i i f i h f
-
7/26/2019 Oluwatosin Akinpelu C 201009 PhD Thesisghgh
70/295
Inclined radar reflectors are observed in a variety of environments; they range from
planar cross-beds, lateral accretion and downstream accretion in fluvial deposit to
Inclined Heterolithic Stratification (IHS) in tidal bars. Inclined radar facies are also
observed in eolian deposits as giant cross-beds and also in deltaic clinoforms (Figure 20).
They are often vital paleocurrent indicators; hence the orientation of the GPR profiles
where they are observed as well as the orientation with respect to channel trend or
regional paleocurrent direction should be carefully documented. They can be
discriminated by the vertical and horizontal scale of the reflectors as well as the
association with contiguous facies, ground-truthed with outcrop observations or sediment
trenches. Examples from modern and ancient sediments are given below:
2.10.3 Reflection-free facies
Reflection-free configuration often indicates one of the following:
massive homogenous lithological units with no contrasting dielectric properties
the presence of highly conductive dissolved minerals in groundwater
magnetic sediment
or the presence of sediments containing high clay content that rapidly attenuates
transmitted electromagnetic signal.
A
-
7/26/2019 Oluwatosin Akinpelu C 201009 PhD Thesisghgh
71/295
Figure 20: (A) Inclined Radar facies from Fraser and Squamish River (Image takenfrom Wooldridge and Hickins, 2005) (B) Downstream accretion macroform fromCastlegate sandstone, Utah (C) GPR profile at the aeolian Navajo Sandstone from ZionNational Park, Utah revealing a set of cross stratification. (Image taken from Jol et al.,2003).
B
C
deposits can be clearly interpreted in fluvial deposits and interdune deposit discriminated
from dry phase eolian dunes based on reflection geometry and amplitude (Figure 21)
-
7/26/2019 Oluwatosin Akinpelu C 201009 PhD Thesisghgh
72/295
from dry phase eolian dunes based on reflection geometry and amplitude (Figure 21)
Figure 21: (A)Example of reflection-free radar facies- Shinarump Sandstone (Hurricane
Mesa, Utah) (B)Radar facies from Navajo Sandstone (Moab, Utah)
2.10.4 Horizontal Reflectors
Reflection-free facies
Reflection-free facies
B
Shinarump Conglomerate
Moenkopi Shale
Muddy interdune deposits
Amplitude Scale
Low
High
A
floodplain deposits and lacustrine sediments. They are often recognized by their
reflection amplitudes and facies association; for instance, muddy horizontal overbank
-
7/26/2019 Oluwatosin Akinpelu C 201009 PhD Thesisghgh
73/295
reflection amplitudes and facies association; for instance, muddy horizontal overbank
deposits are usually high to medium amplitude reflectors with low amplitude at the
base as observed at the Whirlpool Sandstone Figure 22A) while sand-rich intra channel
horizontal reflectors are usually characterized by high amplitude sometimes underlain
by a thin layer of low amplitude reflectors indicating shaly channel base breccia or mud
chips (Figure 22 A and B). Mud beds typically have low amplitude thin horizontal
reflectors with indistinguishable reflectors at the base.
Figure 22: (A)Horizontal radar facies overbank deposit from Whirlpool Sandstone,Artpark, New York (B) Horizontal reflectors from Shinarump sheet conglomerate, Utahinterpreted as upper plane bed flood deposits.
Queenston Shale
Overbank deposit
Channel margin
A
B
Sandy Bedform
-
7/26/2019 Oluwatosin Akinpelu C 201009 PhD Thesisghgh
74/295
Table 2:Radar facies elements of different sedimentary depositional environments.(Table obtained from Van Overmeeren, 1998)
-
7/26/2019 Oluwatosin Akinpelu C 201009 PhD Thesisghgh
75/295
( )
Based on this surmise, Van Overmeeren (1998) suggested a compilation of radar facies
atlas from a variety of depositional environments as guide for facies interpretation and
-
7/26/2019 Oluwatosin Akinpelu C 201009 PhD Thesisghgh
76/295
Figure 24: Radar facies chart of characteristic reflection patterns from varioussedimentary environments. (Image taken from Van Overmeeren, 1998).
Analysis of radar facies observed in this study and from other published GPR studies
-
7/26/2019 Oluwatosin Akinpelu C 201009 PhD Thesisghgh
77/295
Huggenberger, 1993; Bristow, 1995; Beres et al., 1999; Neal and Roberts, 2000, 2001;
Corbeanu et al., 2001; Heinz, 2001; Neal et al., 2001, Russell et al., 2001; Szerbiak et al.,
-
7/26/2019 Oluwatosin Akinpelu C 201009 PhD Thesisghgh
78/295
2001; Hornung and Aigner, 2002; ONeal and McGeary, 2002; Heinz and Aigner, 2003;
Skelly et al., 2003). While these studies confirm the usefulness of GPR imaging as a
powerful technique for imaging clastic sedimentary rocks, the idea that radar facies
elements used in interpretation of radar reflection patterns are characteristic of certain
sedimentary depositional environments should be applied with caution while interpreting
outcrop data as