helicopter-based laser scanning: a method for quantitative analysis of large-scale sedimentary...

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July 16, 2013; doi 10.1144/SP387.3, first publishedGeological Society, London, Special Publications

J. Hampson and Julien ValletAndreas Rittersbacher, Simon J. Buckley, John A. Howell, Gary architecturequantitative analysis of large-scale sedimentary Helicopter-based laser scanning: a method for

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Helicopter-based laser scanning: a method for quantitative analysis

of large-scale sedimentary architecture

ANDREAS RITTERSBACHER1,2,3*, SIMON J. BUCKLEY1, JOHN A. HOWELL1,

GARY J. HAMPSON4 & JULIEN VALLET5

1Uni CIPR, University of Bergen, PO Box 7800, 5020 Bergen, Norway2Department of Earth Science, University of Bergen, PO Box 7803,

5020 Bergen, Norway3Present address: Statoil ASA, Sandslihaugen 30, 5254 Bergen, Norway

4Imperial College London, South Kensington Campus,

London SW7 2AZ, UK5Helimap System SA, Le Grand-Chemin 73, 1066 Epalinges, Switzerland

*Corresponding author (e-mail: [email protected])

Abstract: Studies of large-scale sedimentary architecture are mainly based on the interpretation oftwo-dimensional photomosaics. This method cannot account for the natural rugosity of outcropexposures, introducing errors in the measurement of geobody sizes and orientations. In the past,three-dimensional outcrop studies have relied on time-intensive fieldwork, with irregular samplingand low geometric accuracy. More recently, terrestrial laser scanning, or LiDAR (Light Detectionand Ranging), has been widely applied to small-scale outcrops, but range and accessibility precludeits usage on larger-scale outcrops. Oblique helicopter-based laser scanning, however, allows thecollection of tens of kilometres of outcrop sections in a relatively short time frame. In thispaper, a procedure for collecting and processing such virtual outcrop data is outlined, and the appli-cation of the technique for extracting dimensions of fluvial geobodies from two large and otherwiseinaccessible outcrops from Utah is presented. The results are compared to interpretations frommore conventional photomosaicking of the same outcrops. Results show that the use of helicop-ter-based laser scanning enables geoscientists to rapidly acquire georeferenced data that canthen be used for sedimentological interpretation and analysis on reservoir scales. It is concludedthat helicopter-based laser scanning promotes sedimentological research and is well suited tocapturing quantitative geometrical data from large outcrops.

Vertical cliff sections and escarpments can provideuseful data on large-scale sedimentary architectureand sandbody geometry. Studies of sedimentaryarchitecture are important for understanding thesequence stratigraphy of sedimentary successions,while studying the geometry of sandbodies iscentral to understanding connectivity and potentialfluid flow pathways in hydrocarbon reservoirs andaquifers. Consequently, outcrop studies are essen-tial for recording variations in the geometry, sizeand spatial distribution of sedimentary geobodies(Friend 1983; North & Prosser 1993; Labourdette2011). Conventional methods of studying large out-crops typically involve correlation between loggedsections, often supplemented by photomosaicsand/or scaled outcrop sketches (Mountney &Howell 2000; Howell et al. 2008). Such methodslack precision at large scale and are only semi-quantitative, failing to capture three-dimensional(3D) geometry with sufficient precision or spatial

resolution (e.g. Bhattacharya 2011), although theyare still useful for adding qualitative information.

Outcrop data have long been used as analoguesto improve understanding of subsurface reservoirsthat are only sampled by sparse well penetrationsand seismic data which typically have too low a res-olution to resolve the sandbodies that comprise thereservoirs (Alexander 1992; Keogh et al. 2007;Jones et al. 2008; van Lanen et al. 2009). Empiricalstudies of large and continuous outcrops are there-fore useful to fill knowledge gaps and to providequantitative data on sandbody sizes. Data on geome-tries have a strong 3D anisotropy, best capturedfrom outcrops with cliff faces in multiple orien-tations. Accordingly, these outcrops are less wellrepresented by 2D photomosaics.

In the past decade, terrestrial LiDAR (LightDetection and Ranging) scanning has been usedto create virtual outcrops (Buckley et al. 2008a)that provide 3D views of vertical cliff sections

From: Martinius, A. W., Howell, J. A. & Good, T. (eds) Sediment-Body Geometry and Heterogeneity: AnalogueStudies for Modelling the Subsurface. Geological Society, London, Special Publications, 387,http://dx.doi.org/10.1144/SP387.3# The Geological Society of London 2013. Publishing disclaimer: www.geolsoc.org.uk/pub_ethics

at Yale University on September 30, 2014http://sp.lyellcollection.org/Downloaded from


and can be used for the extraction of accurate, geos-patially-constrained geobody dimensions. Engeet al. (2010), for example, used terrestrial LiDARto capture the 3D geometry of deltaic clinoformsin order to characterize clinothems for reservoirmodelling. In recent years, LiDAR has become astandard method in small-scale outcrop studies,and its value has been proven for the architecturalanalysis of particular geological units in a varietyof depositional environments (Fabuel-Perez et al.2010; Pyles et al. 2010). Terrestrial LiDAR is,however, limited by the range of the scanner (typi-cally c. 1 km), by the availability of suitable scan-ning locations, and by the time taken to move andset up the scanner and perform the outcrop scans.This has typically limited the horizontal extent ofmost virtual outcrops to less than 5 km, althoughlarger examples do exist (Wilson et al. 2009).

Large-scale photomosaics remain the keymethod for studying larger outcrops, where rangeor accessibility are problematic for LiDAR usage(Miall 1993; Miall & Jones 2003; Currie et al.2009; Romans et al. 2009; Jensen & Pedersen2010; Leleu et al. 2010). Complemented by strati-graphic logs of the investigated area, photomosaicsprovide insights into architecture at the scale of geo-body stacking and internal geobody architectures(Friend et al. 2001; Kumar et al. 2004; Jensen &Pedersen 2010). However, geometric accuracy islow, especially as the degree of three-dimensionalityof exposure increases. Airborne LiDAR, mountedon aeroplanes or helicopters (Wehr & Lohr 1999),and satellite-based remote sensing methods areunsuited for most outcrop studies as they have aninappropriate field of view (pointing downwards;nadir view). Therefore, they cannot account for near-vertical outcrop sections at the resolution necessaryto record small-scale geobodies. Currently, there isno technique available for geologists to account forthe (partial) inaccessibility and three-dimensionalityof outcrops, whilst being suitable for large-scalearchitectural analysis.

As a means of addressing this identified techno-logical gap, this paper aims to demonstrate theapplication of oblique helicopter-based LiDARas a technique to quickly, efficiently and accuratelycapture quantitative architectural data from large-scale 3D outcrops. An overview of the data collec-tion and processing techniques needed to carry outsuch a study are explained, and the method is com-pared to a range of other widely used approaches.A discussion of the benefits and limitations of thepresented workflow is given to outline the possi-ble fields of application of helicopter-based laserscanning in the geosciences. To illustrate the meth-odology, a case study of fluvial sandbodies fromnon-marine strata of the Upper Cretaceous Black-hawk Formation of central Utah, USA is presented.

Fundamentals and methods

Terrestrial laser scanning

The use of terrestrial LiDAR in the geosciences isbecoming increasingly widespread in applicationswhere accurate, high-resolution surveying of topo-graphy is necessary as it provides high-resolutiondata and is reasonably user-friendly.

LiDAR instrumentation records distances andangles to a target (e.g. an outcrop), and simulta-neously determines the XYZ coordinates of pointson this target (Bellian et al. 2005) in a global coor-dinate system based on an integrated Global Navi-gation Satellite System (GNSS). Most LiDARsystems record thousands to hundreds of thousandsof points per second to achieve the necessary pointspacing, resulting in a cloud of 3D points (Bellianet al. 2005) that can subsequently be used tocreate a meshed surface based on triangulation ofthe points. The point cloud (and the mesh) can beused to view the topography of the outcrop, althoughthe discrete sampling makes it difficult to interpretgeological details. Complementary to the pointcloud, a built-in digital camera is therefore typicallyused to obtain images that are used to texture themesh, to achieve a photorealistic depiction of thescanned area commonly called a ‘virtual outcrop’(Bellian et al. 2005; Buckley et al. 2008a). Formore information on terrestrial LiDAR applicationsin geology, especially the technology behind it, seePringle et al. (2004), McCaffrey et al. (2005) andEnge et al. (2007).

Oblique helicopter-mounted laser scanning

Many geological outcrops are too large to be effi-ciently captured using terrestrial LiDAR. Highercliff section areas may be out of range of the scan-ner, or the scanner angle becomes very obliqueresulting in poor image quality and data gaps. Thismay especially be the case if the cliff is stepped,leading to sections that cannot be seen fromground in front of the outcrop, resulting in ‘scanshadows’. Using a side-looking LiDAR systemmounted on a helicopter gives access to such pre-viously inaccessible outcrops and also provides anoptimal view of the cliff (Buckley et al. 2008b).Data quality is improved relative to conventionalnadir-looking airborne LiDAR systems, as laserpoints and digital images are captured at angles per-pendicular to the terrain. However, scanning from ahelicopter presents a different set of challenges thatare described below.

The scanner used in this study is a Riegl LMSQ240i-60 airborne laser scanner, encapsulated inthe Helimap System (Vallet & Skaloud 2004).This scanner operates using a similar principle to

A. RITTERSBACHER ET AL.



the ground-based LiDAR instruments. However,instead of being tripod-mounted with a rotatinghead, the instrument records a continuous vertical2D profile, and the movement of the helicopter isused to extend the data in 3D in the horizontal scan-ning direction. A Hasselblad H1 22 megapixelcamera with a calibrated 35 mm lens is used in com-bination with the laser scanner, with its focal lengthchosen to match the field of view of the laserscanner. Digital images are therefore taken simul-taneously with the laser-based data.

As the helicopter is in constant motion, precisioninstruments are required to track the orientation andposition of the scanner and camera through time.This is the single main difference between air-borne and terrestrial LiDAR where the scanner is ina fixed position. To achieve a precise point cloudfrom the moving platform, an inertial measurementunit (IMU) and a dual frequency GNSS are inte-grated with the LiDAR and camera (Fig. 1). TheIMU measures orientation angles hundreds oftimes a second, whilst the GNSS records the sys-tem trajectory up to 10 times per second. All

system components are synchronized by a time-stamp, allowing the point cloud to be recreatedduring post-processing. To ensure high measure-ment accuracy, calibration is carried out duringevery scanning campaign for the camera and aftereach assembly of the sensors for the scanner itselfto determine the precise offsets and alignment ofall system components. The Helimap system isdescribed in detail by Vallet & Skaloud (2004)and, as shown by Buckley et al. (2008b), is well-suited for geology-related purposes.

Processing and texturing

To facilitate interpretation, the raw point cloud datarequire several processing steps before the finalvirtual outcrop is ready for interpretation and analy-sis. While it is possible to use the point clouddirectly for interrogation, the non-continuous rep-resentation of the outcrop makes it difficult to dis-tinguish geological details, as described above forterrestrial LiDAR. The sheer quantity of 3D points(tens of millions) may be a barrier to working withthe raw data, and there can be heavy oversampl-ing with respect to outcrop topography (Buckleyet al. 2008a). This is especially apparent duringmeshing of the point cloud, when the number of tri-angles created is approximately double the inputnumber of points. In addition, because the densityof points is greater than the point precision of theintegrated LiDAR, IMU and positioning system,significant random noise can exist in the datasets.To alleviate this, and to save on the hardwareresources required, the original point cloud is deci-mated and smoothed based on terrain curvature,leaving more points in increasingly rugose areas.After this stage, a typical outcrop section of about1 km consists of approximately 1.5–2 millionpoints. The Wasatch Plateau dataset describedbelow contains 7.9 million points and 595 imagesof 22 megapixel resolution each, giving an uncom-pressed processed dataset size of 73 GB (gigabytes).

Triangulation of the point cloud creates a 3Dsurface commonly called a mesh or DEM (digitalelevation model). This processing step is carried outin PolyWorks version 11.0.12, and operates on thethinned point cloud. To create a photorealistic vir-tual outcrop, the 3D mesh needs to be textured withthe digital imagery acquired simultaneously withthe point cloud. Processing principally involvesapplying colour data from the digital photographson to each triangle of the processed mesh, usingthe known photo orientation (Labourdette & Jones2007). Selection of the images for texturing isbased on the optimal angle of the images in relationto the mesh, as well as the area in pixels of the tri-angles within each image. In some cases, imagesof poor quality have to be removed or adjusted

Fig. 1. Laser scanner system mounted on a helicopterand ready for geological applications: Riegl LMSQ240i-60 airborne LiDAR scanner, showing mountedHasselblad H1 22 megapixel camera, GNSS antenna andinertial measurement unit below the camera. The systemcan be mounted on to most types of commerciallyavailable helicopters.

HELICOPTER-BASED LASER SCANNING



Fig. 2. Screenshots of the northern part of the Wasatch Plateau virtual outcrop (see Fig. 4 for location). (a) The complete virtual outcrop. The red line depicts the top of theStar Point Formation, which is used as a datum. The yellow rectangle shows the position and size of images (b) and (c). (b) Details of the virtual outcrop without interpretedsandbodies. The blue rectangle shows the position and size of image (d). (c) Details of the virtual outcrop with interpreted sandbodies outlined in blue and green. The section shown isidentical to the one in (b). (d) Close-up of the outcrop. The detail that can be viewed and conveniently worked on is about 30 cm. Note the different levels of detail on which theoutcrop can be viewed and worked on.

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manually to ensure similar lighting and colour for allimages in a project (Enge et al. 2007). Texturing ofthe mesh with the selected images then createsthe final virtual outcrop that captures both the topo-graphy and photographic detail of an outcrop. Geo-metric measurements of surfaces, points or lines ona virtual outcrop are straightforward, as points

digitized on screen correspond to 3D coordinatesin the textured model (e.g. Enge et al. 2007).

Challenges and accuracy considerations

The foremost challenge when using helicopter-based LiDAR data is the large size of the processed

Table 1. Overview of potential errors during the workflow, their significance and dependencies. Expectederrors that may affect the entire workflow, from outcrop data acquisition to geological interpretation (for atypical long-range laser scanner)

Item Frequency Errorbudget*

Significance forgeology results

Dependence

LiDAR scannerInternal LiDAR

calibrationOnce mm–cm Very low Manufacturer calibration

Instrument precision Each systemmodel

cm–dm Low Instrument specification

Beam divergenceoverlap

All measurements cm–dm Low Chosen resolution; range

Target material All measurements cm–m High for darkermaterials

Reflectivity of material; range

Obliquity of laser Each scan cm–dm Low Helicopter position relativeto outcrop topography

Range shadows Each scan m High if datainterpolated

Helicopter position relativeto outcrop

Boresight calibration Per mappingcampaign

cm–m Very high System calibration

CameraCalibration Per mapping

campaigncm–m High for geology

interpretationCamera calibration validity

Camera mounting Per mappingcampaign

cm–m Affects image orscan integration

System calibration

Image orientation Each image cm–m Very high GPS, IMU data quality

ProcessingPoint cloud

processingPer flightline cm–m Very high if poor

GPS conditionsGPS, IMU data quality

Point cloud merging Project cm–m High GPS, IMU data quality betweenflight lines

Point cloud editing Per point cloud cm–m High if incorrectpoints removed

User

Point clouddecimation

Project dm–m Potentially high Choice of algorithm andparameters

Triangulation Project dm Generally low Meshing algorithm; user editingTexture mapping Project cm–m Potentially high All input data: mesh quality;

image quality; cameracalibration; imageregistration

InterpretationQuality of

interpretationAll objects dm–m Medium Outcrop quality; geological

understanding; virtual outcropquality; style of interpreter(lump – split)

*The error budget is an estimate of each item, and can potentially be combined to reach the end of the processing chain: interpretation ofresults. From this it can be seen that even with very high accuracy input, there is still potential for large discrepancies to affect the finalgeology data.Modified from Buckley et al. (2008a) to address the specifics of helicopter-based LiDAR scanning.




virtual outcrops, mainly a result of the large num-ber of high-resolution images that are used for tex-turing. Even models that are segmented (e.g. intosegments of c. 2 km length) reach gigabyte size,and their display poses challenges to the graphicsand memory system of the computer used. Thus,an intelligent viewing framework is required. Ina standard viewer, all textured triangles are shownat the same resolution, and the random accessmemory (RAM) and graphics card need to load allof the triangle and texture data at once. This isespecially problematic at interactive frame rateswhen the model is manipulated by the user (e.g.rotated or zoomed). To overcome this problem,the virtual outcrops are processed employing amulti-resolution strategy using in-house software(Buckley et al. 2008b). The original, high-resolutionmesh is also saved at several lower resolutions andtextured accordingly, and the overall data extent isthen segmented into small sections. These sectionsare linked in a hierarchical structure. In this way,specialized viewing software can display the appro-priate resolution on demand, according to the pos-ition and level of zoom of the user’s interaction,whilst not overloading the graphics memory. Thisprocedure has the advantage of keeping thehighest model resolution for the fine-scale geologi-cal interpretation, whilst also allowing the fullmodel to be displayed in overview within thesame 3D view (Fig. 2).

The laser scanner used in this study has a quotedpoint accuracy of 0.02 m (1s under test conditions)at 50 m distance (Riegl 2010), although there area number of factors that affect the precision of themeasurements and reduce the accuracy. Atmos-pheric conditions, including the concentration ofmoisture and dust, variable distances over whichmeasurements are taken, oblique angles of measure-ments relative to the scanned surface, and variableterrain type influence the precision (but not theresolution) of the LiDAR data. These errors aremostly of minor importance for geological prob-lems, and are often beyond the geologist’s control.Errors associated with the position and orientationof the scanner are more likely when using a mobileplatform. Such errors have the potential to distortthe post-mission calculation of point cloud coordi-nates. They may be reduced but not fully removedby frequent in-flight calibration of the inertialsystem to reduce drift, the quality of the GNSS sat-ellite constellation and the boresight calibration.

Errors that result from processing are more con-trollable than data acquisition errors, and typicallyhave a more serious impact on the final virtualoutcrop (Buckley et al. 2008a). Point cloud edit-ing, meshing and subsequent texture mapping ofthe triangulated mesh have the largest impact onthe final model. Special care must be taken to mini-mize such errors, and their propagation, throughoutthe workflow (Table 1). In particular, a faulty mesh

undifferentiated

non-marine

Blackhawk

Mancos Shale

Formation

Buck Tongue

Castlegate

spatial distributionage litho-

stratigraphy

CA

MPA

NIA

N

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Low

er

Sa

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ton

ian

Bla

ckh

awk

FmP

rice

Riv

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Fm

(SE)(NW)

Desert Mbr

Grassy Mbr

Sunnyside Mbr

PantherTongue

Storrs Mbr

Spring Canyon Mbr

Aberdeen Mbr

Kenilworth Mbr

Sta

rP

oin

tFm

1 2

Fig. 3. Stratigraphic framework for the Blackhawk Formation in the Book Cliffs, Utah. Striped columns show theapproximate stratigraphic position covered in the case study. Column 1 shows the stratigraphic position of the WasatchPlateau area; column 2 the position of the Beckwith Plateau area (i.e. the Book Cliffs). Modified from Howell & Flint(2003); based on Young (1955).




that deviates from the original point cloud willaffect the geological interpretation stage. Manualquality control of the meshed surface against theoriginal point cloud can highlight areas of unaccep-table deviation between the virtual model and thereal outcrop. Care must also be taken when register-ing the digital imagery that is used to texture thefinal triangulated model since incorrectly registeredimages will result in erroneous positioning of anyinterpreted features in subsequent work steps. Thisis especially important since much of the geologicalinterpretation is based upon the images, which aretypically of a much higher resolution than thepoint cloud. Such errors are reduced by selectingthe most suitable images from the acquired photo-graphs and avoiding the use of images taken frominappropriate angles or with poor exposure prop-erties in the texturing stage. It is also desirableto avoid using photographs taken from signifi-cantly different distances on adjacent triangles.The different resolutions significantly degrade theoverall quality of the final virtual outcrop since the

seams highlight the triangles and detract from theunderlying geology. An advantage of the helicopter-based LiDAR approach is that the distance to theoutcrop is usually fairly consistent between flightlines.

For interpretation on the virtual outcrop it isimportant to remember that, even though themodel provides a spatially accurate 3D represen-tation of the outcrop, it is not a full 3D representa-tion of the geological features that continue behindthe cliff face and have been eroded from its frontside. Therefore, any interpreted features, such asbedding planes or channels, must be extrapolatedinto true three dimensions (Buckley et al. 2008a).

Case study

To demonstrate the benefits of helicopter-basedLiDAR scanning, and the resulting virtual outcropsand data analysis, a case study from coastal plaindeposits of the non-marine Blackhawk Formation

STUDY AREA

UTAH

Interstate 70

Green River

Castle Dale

Price

US Route 6

San Rafael Swell

Book Cliffs

Was

atch

Pla

teau

20 km

Wasatch Plateau Section Beckwith

Plateau Section

Fig. 4. Location of the study area. The black solid line represents the continuous cliff face of the Wasatch Plateau in thewest and the Book Cliffs in the east. The cross-line pattern outlines the scanned parts of the cliffs.




in central Utah is presented. LiDAR data acquisitiontook place in late spring 2009, when the outcropswere free of snow, and during mostly stable light-ing conditions preferred for obtaining consistentimagery for model texturing. The aim of this casestudy was to collect a large dataset of fluvial

sandbody geometries within proximal and distalcoastal plain settings.

Geological setting of field area

The Late Cretaceous Blackhawk Formation wasdeposited as part of a siliciclastic wedge along thewestern margin of the Western Interior Seaway, anepeiric sea trending from north to south throughthe North American continent. The principal con-trol on deposition of the Blackhawk Formationwas the Sevier Orogen, a fold and thrust belt to thewest of the Western Interior Seaway from whichmost of the siliciclastic material was derived. TheBlackhawk Formation consists mainly of coastalplain and shallow-marine deposits, and representsan overall eastwards regression interrupted byperiods of marine incursion. Six shallow-marinemembers are formally defined in the BlackhawkFormation (see Fig. 3), each containing severalshorefaces and wave-dominated deltaic tongues orparasequences (Young 1955; Howell & Flint2003). Underlying and interfingering to the eastwith the shallow-marine deposits is the time-equivalent Mancos Shale, which represents deposi-tion in an offshore shelf setting. The shallow-marinedeposits are overlain by, and interfinger to the westwith, the non-marine portion of the BlackhawkFormation (Young 1955), which was deposited ina coastal plain environment with fluvial systemstransecting a low-gradient landscape dominated bylagoons, flood plains and peat swamps (Floreset al. 1984). The Blackhawk Formation is cappedby sandstone-dominated braided river deposits of

single channel multilateral channel

multistorey channel connected channels

(a) (b)

(c)

(d)

Fig. 5. Terminology for the description of channelized sandbodies. (a) A single channel without contact with otherchannels visible in the outcrop. (b) Multilateral channelized sandbodies occur through lateral migration of a channelresulting in bodies cannibalizing lateral parts of older deposits of the same channel. (c) Vertical stacking of sandbodiesto create a multistorey channel may be caused by a long period of stable conditions with one channel building up thedeposits or by reoccupation of an older channel. (d) The term ‘connected channels’ describes a situation in whichchannels within a sandbody show both vertical and lateral connectivity with other channels in the outcrop to form aconnected sandstone unit. Modified from Gibling (2006).

0

90

180

270

n = 60Mean 67˚StdDev 53

Circle =

8 measurements

Fig. 6. Palaeocurrent diagram for the BlackhawkFormation in the Wasatch Plateau virtual outcrop area.The dataset combines the values measured in both thenorthern and the southern part of the Wasatch Plateauoutcrop section. Mean palaeocurrent direction is towards678, with a standard deviation of 538.




the overlying Castlegate Formation (Young 1955;Van Wagoner 1995). The nature of the contactbetween the Blackhawk Formation and the Castle-gate sandstone has been debated. Van Wagoner(1995) favoured a major regional sequence bound-ary, while, more recently, Adams & Bhattacharya(2005) argued that the fluvial style and scale ofrivers do not change from the non-marine Black-hawk Formation to the Castlegate Formation but,rather, that changes in accommodation are reflectedin the different sandstone content and fluvial archi-tecture of the two units. The complete eastwards-prograding, Blackhawk–Castlegate wedge locallyexceeds 2 km in thickness (Young 1955; VanWagoner 1995) and has been uplifted by at least6000 m, undergoing no tectonic deformation otherthan the gentle folding and small-scale structure cre-ation ( joints) associated with the formation of theLaramide-aged anticline of the San Rafael Swell(Bump & Davis 2003).

Major outcrops of the Blackhawk Formationoccur in the cliff faces of the Book Cliffs east ofthe San Rafael Swell and in the eastern WasatchPlateau west of the uplift. Numerous valleys and

canyons cut both cliff faces and add a 3D compo-nent to the outcrops. In outcrops of the WasatchPlateau, which lie in a more proximal location, thenon-marine Blackhawk Formation is 200–300 mthick, and is comprised of interbedded mudstone,siltstone, coal and channelized sandbodies (Fig. 3)(Spieker & Reeside 1925; Flores et al. 1984;Adams & Bhattacharya 2005). The successionmay be subdivided into a coal-rich lower portionand a coal-poor upper section (Hampson et al.2012). This upwards decrease in coal reflectsthe increasing distance to an easterly progradingshoreline. The Book Cliffs section lies 70 km fur-ther basinward and the non-marine interval therecomprises similar lithologies but is only 40–50 m thick.

The studied outcrops are located in the easternWasatch Plateau, covering two cliff faces northand south of the entrance to Straight Canyon, withlengths of 3.5 and 13 km, respectively, and theBook Cliffs, covering a cliff face 28 km longbetween Woodside Canyon and Battleship Butteon the Beckwith Plateau (Fig. 4). The outcropsform steep, mostly inaccessible cliffs. All sections

Fig. 7. The mouth of the Gilbert–Einasleigh River in Queensland, northern Australia, showing a distributivefluvial-system pattern. The individual branches of the river system show a narrow spread of flow direction on a variety ofscales, with a standard deviation of 278 from the main flow direction. This river system seems to be a good analogue tothe studied outcrops in the Wasatch and Beckwith plateaus. Map screenshot from Google Maps.




Fig. 8. Plot of results from the interpretation of sandbodies of the Wasatch Plateau. (a) shows that sandbody dimensions demonstrate an upward increase in width/thickness ratio inthe Wasatch Plateau. The increase is similar for multistorey and single-channel sandbodies, although multistorey channels are generally slightly wider than single-channelsandbodies. (b) shows a decrease in vertical spacing, measured on virtual logs with 1000 m spacing, while (c) shows a decrease in abundance of sandbodies from the base to the top of

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Fig. 8. (Continued) the formation. An increase in maximum sandbody width with increasing height is recorded in (d), while average sandbody width shows the same trend slightlyweaker in (g). This pattern is repeated in (e) and (h), with the thickness of sandbodies showing a slight up-section increase. There is no obvious trend in width/thickness ratios in thevertical section (f ) but a subtle overall increase in sandbody volumes (not measured as real values but approximated by multiplying thickness and width of individual sandbodies)towards the overlying Castlegate Formation (i).

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have a broadly depositional strike orientation(north–south).

Measured parameters

Channelized sandbodies were identified on the vir-tual outcrops and their outlines were digitized as3D polylines. Width and maximum thickness weremeasured. Sandbodies were classified according totheir internal geometries into multilateral/singlechannel (-belt) and multistorey/connected channels(-belts) (Fig. 5) (cf. Gibling 2006). The height of thetop of the channel above a chosen datum was alsorecorded. In the Wasatch Plateau sections, thedatum was the top of the marine shorefaces in theStar Point Formation. In the Book Cliffs section,the datum was the top of the marine shorefacedeposits of the Grassy Parasequence 1 (GPS 1 ofO’Byrne & Flint 1996). In both cases, the datumwas close to planar horizontal, and laterally continu-ous throughout the sections.

Sandbody width was measured as the distancealong the outcrop between the two interpreted outer-most points of a geobody, and then corrected forvariations in outcrop orientation using the approachof Fabuel-Perez et al. (2009). The method is to usea simple trigonometric operation to calculate thetrue width of a channelized sandbody with respectto the regional flow direction.

Palaeocurrent data collected in the field, com-bined with a regional understanding of palaeoflow,were used as a proxy for sandbody orientation(Fig. 6). Given that it was not possible to collectpalaeoflow data from each specific sandbody, poten-tial error exists with this method. For example, therecorded data show variability (standard deviation)of 538 for all measured data in the Wasatch Plateauarea. To correct the sandbody orientation, a meanpalaeocurrent towards 678 and 1438, respectively,was established individually for both the Wasatchand the Beckwith Plateau area with the help of theEZ-ROSE programme, and subsequently used forcorrection of the sandbody sizes (Baas 2000).

The eastern coast of the Gulf of Carpentaria innorthern Queensland, Australia is a potentialmodern analogue for the Blackhawk Formation,with deposition in a low gradient, subtropical,coastal plain, lying landwards of wave-dominatedshorelines and prograding into an epeiric seaway.Fluvial systems in this setting show a broadly distri-butary nature (Weissmann et al. 2010) with a stan-dard deviation of 278 in channel-belt orientation(Fig. 7). The narrower spread of palaeocurrentvalues obtained from the potential modern analogue(compared to the ones observed in the outcrop)can be explained with a wider range of palaeocur-rents within a channel belt that has been recordedin the field data. Owing to these different scales,

the two sets of palaeocurrent data are not directlycomparable.

Results

Figure 8 shows the sandbody dimensions (width,thickness) partly coded by type (single storey, multi-storey) and in relation to a datum (the underlyingStar Point Fm) in the Wasatch Plateau section.In addition, the vertical distance of (erosive) sand-body bases above the datum was measured every1000 m along the outcrop (Fig. 8b) and thenumber of channels per height interval above thedatum across the entire length of the outcrop wasrecorded (Fig. 8c).

Analysis of the parameters described abovereveals several trends:

† Sandbody dimensions in the Wasatch Plateaushow a slight increase in sandbody thickness asthe corresponding width increases:W this increase is similar for both multistorey

and single-channel sandbodies, although mul-tistorey channels are generally slightly widerthan single-channel sandbodies (Fig. 8a).

† A decrease in the vertical spacing and abundanceof sandbodies from the base to the top of the non-marine Blackhawk Formation (Fig. 8b, c):W a break at approximately 50 m height might

correspond to a sea-level highstand correla-tive to the top of the lower parasequence ofthe Aberdeen Member.

† An increase in maximum widths that sandbodiesreach at a specific level (i.e. the widest 10% of allsandbodies) is increasing upwards within bothsections, highlighting a general trend from prox-imal to distal locations (Figs 8d & 9):W in the Wasatch Plateau, not only does the

maximum sandbody width increase but alsothe average sandbody widths within 10 mintervals show a widening-upwards trend(Fig. 8g).

† There is no obvious trend in width/thicknessratios in the vertical section (Fig. 8f ) but a subtleoverall increase in sandbody cross-sectionalsurface area (not measured as real values butapproximated by multiplying thickness andwidth of individual sandbodies) towards theoverlying Castlegate Formation (Fig. 8i).

The comparison of the measured dimensions fromthe Beckwith and the Wasatch Plateau sections(Fig. 9) shows that a relatively uniform proportionof sandbodies of 20–150 m width is recorded inboth outcrops. Maximum sandbody widths increasefrom 200 m at 20 m height above the datum to430 m at 40 m height above the datum in the Beck-with Plateau section. The lowermost 50 m of thesuccession in the Wasatch Plateau section shows




the same architectural pattern of a uniform pro-portion of sandbodies that are 10–70 m widethroughout the succession, while the maximumsandbody width increases from 110 m at 10 mheight up to 260 m at 28 m height. As indicated bythe error bars, the propagation of uncertaintiesfrom the width correction also affects the interpret-ation of these trends and care must, therefore, betaken not to overestimate the significance of thedata, if, as in this case, the input data are not indivi-dually ground-thruthed (i.e. corrected using a meanpalaeocurrent direction).

Interpretation

Analysis of the geometric data derived from thevirtual outcrops of the Blackhawk Formationsuggests that the channel width/thickness ratios liewithin the delta distributary envelope of Gibling(2006) (see Fig. 8a). This is typical for a coastalplain setting.

The systematic upwards-increase in maximumchannel-belt widths, as well as the relatively con-stant sediment input, as recorded by the volume ofsandbodies (Fig. 8i) may reflect an upwardsdecrease in accommodation, as postulated byAdams & Bhattacharya (2005). However, this modelis not supported by the upward decrease in the fre-quency of erosional surfaces. If the preservation oflarger sandbodies was related to a decrease inaccommodation, the frequency of erosion surfacesshould also increase. Alternatively, the increase inmaximum channel-belt width (and thickness) mayreflect an upward increase in the size of the fluvialsystem as the contemporary coastline movedfurther to the east. Such a scenario would reflectthe preservation of a distributive fluvial system, asdocumented from modern systems by Weissmannet al. (2010) and Hartley et al. (2010).

These provisional results illustrate the utility ofthe very large datasets that have been collected assuch subtle changes cannot be recorded with

Fig. 9. Height of sandbodies above the underlying shoreface plotted against sandbody width (with error bars). Bothdatasets show a steady number of sandbodies with widths up to about 150 m throughout the succession. Maximumsandbody widths show some variability, with the Beckwith Plateau section sandbodies showing a clearupwards-increasing trend.




conventional selective probing (e.g. unevenlyspaced sedimentary logs). Further analyses arebeyond the scope of this paper.

Comparison with photograph-based

measurements

Similar measurements have been made for the non-marine Blackhawk Formation in the WasatchPlateau using low-angle aerial photographs takenfrom a light aeroplane (cf. Hampson et al. 2011).The thickness of the formation and the dimensionsof the sandbodies within it were calculated by cali-brating the photographs with 1:24 000-scale topo-graphical maps. This photograph-based approachis most accurate for vertical cliff faces that arenearly linear in plan view and lack vegetation orscree cover. Non-vertical cliff faces introduce aperspective effect to the thicknesses and depthsapparent in the photographs, and cliff faces thatare highly rugose in plan view contain some por-tions that are captured only in highly oblique orien-tations. Heavily vegetated or scree-covered clifffaces introduce uncertainty when interpretingcovered sections of the outcrop.

The northern virtual outcrop (see Fig. 4) ofthe Wasatch Plateau Section covers a rugose cliffface that cannot be appropriately analysed usingthe photograph-based approach. The southern vir-tual outcrop covers a near-vertical, near-planar,sparsely vegetated section of cliff face, whichallows the helicopter-based LiDAR method and thephotograph-based approach to be compared.

Comparison suggests that only large (.3 mthick, .60 m wide) sandbodies are consistent-ly identified by both methods, although thephotograph-based method may under- or overesti-mate the thickness of such sandbodies by severalmetres relative to LiDAR-based measurements(Fig. 10a). Discrepancies in sandbody widths mea-sured along the cliff face (Fig. 10b) mainly reflectdifferences in interpretation of scree-covered parts,which are independent of the data collectionmethod; if sandbodies are interpreted to terminate

50

0

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150

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vert

ical

pos

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of

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body

mea

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omLi

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t [m

]

500 100 150 200 250

vertical position of sandbody measured fromlow-angle aerial photographs [m]

line

of 1

:1 co

rrelat

ion

line of best-fit linear regression

2000 400 600 800 1000 1200

sandbody width measured fromlow-angle aerial photographs [m]

200

0

400

600

800

1000

1200

sand

body

wid

th m

easu

red

from

LiD

AR

data

set [m

]

small sandbodies notconsistently identified

line

of 1

:1 co

rrelat

ion

20 4 6 8 10 12 14 16 18 20

2

0

4

6

8

10

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sandbody thickness measured fromlow-angle aerial photographs [m]

sand

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set [m

]

small sandbodies notconsistently identified

line

of 1

:1 co

rrelat

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(a)

(b)

(c)

Fig. 10. Comparison of sandbody sizes and positionidentified on low-angle aerial photographs and onhelicopter-based LiDAR scans. (a) Thicknesses of largesandbodies are consistently identified but over- orunderestimation is common with the photograph-basedmethod. (b) Differences in widths between the twomethods can be largely assigned to interpreter’s bias; thatis, whether one prefers to correlate sandbodies over screeslopes or not. (c) Vertical positions of sandbodies areaffected by a systematic error in the aerial photographsused in this example. This can be assigned to thetwo-dimensionality of the photographs as the thickness isoverestimated from basemap contours.




where the cliff face is covered in scree, then theirwidths are measured to be narrower than the truevalues (e.g. LiDAR measurements in Fig. 10b).Whereas if sandbodies are interpreted to correlateacross scree-covered areas, then their widths aremeasured to be wider than the true values (e.g.photograph-based measurements in Fig. 10b). Com-parable differences in the interpretation of sand-body type (single storey, multilateral, multistorey)also arise because previous workers emphasizedifferent criteria to define architectural elementsand storeys (see Bridge 1993 for a review). How-ever, the LiDAR dataset has a higher resolutionthan the photographs and thus allows smaller-scalegeometrical features to be used in interpreting sand-body type. The photograph-based method results insmall, systematic discrepancies in the vertical pos-itions of sandbodies in the Blackhawk Formation(,10%: Fig. 10c). This discrepancy arises fromthe low resolution of the topographic maps used tocalibrate thicknesses in the photographs, whichhave a contour interval of 24.4 m (80 ft). Overall,the comparison suggests that the photograph-basedmethod is not sufficiently accurate to robustlymake detailed measurements (e.g. sandbody thick-ness: Fig. 10b), although it is adequate to make

large-scale measurements with reasonable accuracy(e.g. sandbody position: Fig. 10c). In contrast, thehelicopter-based LiDAR method can make accuratemeasurements across the full range of measurementscales, and it can also be used on a wider range ofoutcrop terrain (both near-planar and rugose clifffaces).

Discussion

As shown with the examples from the non-marineBlackhawk Formation of central Utah, the helicop-ter-based LiDAR method is suitable for sedimento-logical studies of very large outcrops. The techniqueprovides access to physically inaccessible outcropsin a rapid and efficient manner, whilst achieving aspatial accuracy and resolution better than otheracquisition techniques at this scale. Empirical stud-ies of large-scale sedimentary architecture can thusbe carried out with much higher quantities of sedi-mentary bodies than otherwise possible, increasingthe statistical validity of the results. It has to be men-tioned, however, that the results of the case studypresented here are preliminary and will be thesubject of further more detailed research.

Table 2. Comparison of costs, speed, accuracies and possible applications of different remote-sensing methodsemployed in geoscientific contexts

Method/hardware Typical claimedaccuracy

Collectionspeed

Use/applications Cost

Handheld GPS c. 3–10 m c. 2 h Reconnaissance and regionalmapping

Very low

DGPS c. 0.3 m c. 2 h Detailed mapping and attributecollection

Low

Real-time kinematic(RTK) GPS units

Better than10 mm

c. 3 h Attribute collection atapproximately 10 cm resolutionover outcrops; surveying outcropsand base stations for othermethods

Medium

Reflectorless totalstation

3 mm at 200 mrange

c. 6–8 h Attribute collection atapproximately 10 cm resolutionover outcrops; better for verticalfaces than RTK GPS

Low

Terrestrial laserscanner (mid range:300–1000 m)

10 mm at 50 mrange

c. 10 h Acquiring surface topography onsmall–medium outcrops, allowsdraping of photographs to form a3D image of an outcrop

High

Helicopter-based laserscanner

20 mm at 50 mrange

c. 30 min Acquiring surface topography onlarge outcrops, allows draping ofphotographs to form a 3D imageof an outcrop

Very high

Photomosaicking 1–5 m at 50 mrange

1 h/6 h(unscaled/scaled)

Surface mapping and attributecollection

Very low

Collection speed refers to the time necessary to record a single-bed boundary on a 5 km-long steep outcrop. Modified from McCaffreyet al. (2005).




Limitations in the method are also apparent.Relatively high costs for equipment and helicopterusage, and logistical planning required to conducta successful field campaign may affect the deci-sion to employ helicopter-based LiDAR scanning.Although the system can be mounted on varioushelicopter models, and may be quickly attached andready to use after an initial calibration flight (c.10 min), the method is reliant on the presence of asuitable helicopter in the region of the study site.As the mounting of the system may require minormodifications of the helicopter, depending on themodel available, approval is required from localaviation authorities, or the helicopter operators, tocarry out the campaign. Table 2 shows a compar-ison of hardware, costs, accuracies and applica-tions of various remote-sensing methods used ingeosciences.

Helicopter-based laser scanning is dependent onsuitable flying conditions, and is also reliant on thegeometric configuration of the GNSS satellite con-stellation for accurately tracking the trajectory ofthe LiDAR system. Strong signal reception fromseven or more satellites is needed, requiringthorough planning ahead of the field campaign. Inthe presented case study, mission-planning softwarewas used to identify periods where too few satelliteswere visible, or when the location of satellites in thesky was not optimal for providing a good geometricsolution (e.g. Hofmann-Wellenhof et al. 1997).

Owing to the large amount of data that needs tobe handled, special processing and viewing softwareis required, and, thus, low-grade computer andgraphics hardware may not be suited to displayingthe final virtual outcrops.

Conclusions

In this study, helicopter-based LiDAR scanning wasapplied to sedimentological problems where it wasnecessary to obtain geometric information fromlarge fluvial outcrops that were otherwise inaccess-ible. The method was demonstrated on an exam-ple study from the Cretaceous Wasatch Plateau inUtah, where fluvial channels could easily be ident-ified and measured on the resulting virtual out-crop. Large datasets that lend themselves well toquantitative analysis are efficiently and rapidly col-lected and interpreted from the virtual outcrops,enabling geologists to scrutinize large-scale archi-tectures of any depositional environment with anunprecedented accuracy. Initial analysis and com-parison of proximal and distal parts of the non-marine Blackhawk Formation show that modelsfor fluvial deposition based on tributary riversystems may not be able to fully explain the subtle-ties found in these outcrops. A model based on

distributive fluvial systems, similar to the delta-plain facies of Flores et al. (1984), is much bettersuited to explain the distribution of fluvial sandbo-dies found in Utah. However, more data analysisis needed in order to confirm or refute thishypothesis.

As shown on the example from Utah, the virtualoutcrop models derived from helicopter-basedLiDAR scanning provide a 3D framework for thesedimentological interpretation of large structures,and show clear advantages in terms of accuracyand resolution over other available methods, suchas photomosaics.

Editorial assistance from A.W. Martinius, and constructivereviews from K. Keogh and an anonymous referee, havehelped to improve this paper. Funding for this projectwas received from the Research Council of Norwaythrough the Petromaks projects 193059 and 176132 andthe FORCE Safari Project. Riegl LMS GmbH are acknowl-edged for software support, and Classic Aviation, SaltLake City are thanked for helicopter services. The firstauthor would like to thank J.A. Torland for assistance inthe field.

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