UNIVERSITY OF GOTHENBURG Department of Earth Sciences Geovetarcentrum/Earth Science Centre

A 3d GIS study of

stratigraphy and late stage

Quaternary development

in the Skara-Götene area,

south-central

Stefan Seger

ISSN 1400-3821 B648 Master of Science (One Year) thesis Göteborg 2011

Mailing address Address Telephone Telefax Geovetarcentrum Geovetarcentrum Geovetarcentrum 031-786 19 56 031-786 19 86 Göteborg University S 405 30 Göteborg Guldhedsgatan 5A S-405 30 Göteborg SWEDEN A 3d GIS study of stratigraphy and late stage Quaternary development in the Skara- Götene area, south-central Sweden

Stefan Seger, Earth Sciences Centre, Department of Geology, University of Gothenburg, Box 460, SE-405 30 Gothenburg Abstract

Using drill logs from the National Well Archive, literature and recent field work together with available soil maps, a geological model of the Skara-Götene area was constructed in ArcGIS. 214 drill holes were used together with outcrop information to define the bedrock surface and stratigraphy was described using information from 264 wells combined with surface mapping observations. Two approaches were tested to visualize the stratigraphy of the basin. Construction of sections at selected grid positions across the entire study area was favoured in comparison to the all out 3d approach of creating an isopach which was only tested in a smaller area. The quality of the latter could be improved by incorporating sections during construction. Due to the uncertain quality of well data and the clustered geographical distribution of wells, a simplified lithological classification was adapted. This resulted in a three-layer model where a thin layer of frictional material was present in part below a major, basin-wide cohesive unit. This was interpreted to mainly consist of glacial clay and silt deposited during the final retreat of the ice margin and it was partly covered by a second frictional layer with varying thickness throughout the area.

Keywords: Middle Swedish Ice-Marginal Zone, Quaternary stratigraphy, 3d visualization, ArcGIS

ISSN 1400-3821 B648 2011

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Studie av stratigrafi och senkvartär utveckling i området mellan Skara och Götene med hjälp ut av 3d-GIS

Stefan Seger, Institutionen för geovetenskaper, Avdelningen för geologi, Göteborgs universitet, Box 460, SE- 405 30 Göteborg

Sammanfattning

En GIS-modell över stratigrafin i området mellan Skara och Götene har tagits fram utifrån det nationella brunnsarkivet, tidigare publicerade beskrivningar samt nya fältundersökningar. 214 borrhål användes tillsammans med ytliga bergobservationer för att bestämma bergytans läge. Geologisk information från 264 loggar användes tillsammans med SGU:s kartering som underlag för beskrivning av områdets stratigrafi utifrån två olika metoder. Sektioner orienterade i rutnät ansågs generellt ge ett bättre resultat än framställande av en lagermodell enbart baserat på 3d-visualisering men en kombination av de båda metoderna skulle kunna ge ett bra resultat förutsatt att tillräckligt med indata finns tillgängligt. På grund av bristande kvalitet i indata samt dess begränsade geografiska täckning i området så valdes en förenklad klassificering av geologin. Den sammanlagda tolkningen innefattade en trelagersmodell med ett tunt lager friktionsmaterial sporadiskt förekommande ovan berg. Ovanpå återfanns ett tjockare lager glacial lera och silt vilket delvis täcktes av ytterligare friktionsmaterial av varierande tjocklek.

Nyckelord: Mellansvenska israndzonen, kvartär stratigrafi, 3d-visualisering, ArcGIS

ISSN 1400-3821 B648 2011

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TABLE OF CONTENTS INTRODUCTION ...... 5 Purpose ...... 5 Area description ...... 5 Location ...... 5 Regional bedrock geology ...... 5 Regional glaciation history ...... 6 Local topography, geology and geomorphology ...... 10 Comparison between old and new SGU Quaternary maps ...... 11 Previous work in the area ...... 11 Digital data ...... 11 Reference system ...... 11 Maps ...... 11 Well data ...... 12 METHOD ...... 13 Study area ...... 13 Elevation model ...... 13 Drilling database ...... 15 Bedrock surface model ...... 16 Stratigraphy ...... 17 Sections ...... 17 Isopach ...... 18 RESULTS ...... 19 Study area ...... 19 Elevation model ...... 19 Drilling database ...... 20 Bedrock surface model ...... 20 Stratigraphy ...... 22 Sections ...... 23 Isopach ...... 33 DISCUSSION ...... 36 Elevation model ...... 36 Drilling database ...... 36 Bedrock surface model ...... 36 Stratigraphy ...... 37

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Sections ...... 37 Isopach ...... 38 CONCLUSIONS ...... 39 ACKNOWLEDGEMENTS...... 40 REFERENCES ...... 41 APPENDICES ...... 44 Appendix 1 ...... 45 Appendix 2 ...... 45 Appendix 3 ...... 54

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INTRODUCTION Purpose The purpose of this paper is to describe basin sediment stratigraphy and interpret late stage Quaternary development in association with the latest deglaciation of the area between Mount Kinnekulle and Mount Billingen in South-Central Sweden based on 3d visualization of well logs from the National Wells Archive as well as other spatially distributed information available. Area description Location The study area is located between the municipalities of Skara and Götene in South-Central Sweden (Figure 1) and is bordered by Mount Kinnekulle to the northwest and Mount Billingen to the east.

Figure 1: Overview map of study area in South-Central Sweden compiled from Lantmäteriet data.

Regional bedrock geology Cambro-Silurian mesas in Västergötland (including Kinnekulle and Billingen mountains) rest on a Precambrian denudation surface slightly inclined to the west-northwest (Johansson et al., 1943). Precambrian rocks in the area belong to the Eastern segment of the Southwest Scandinavian Province and contain reddish to grey, 1.78-1.65 Ga old, granitoidic orthogneisses (Lindström et al., 2000). These rocks are interpreted to have formed through continental margin magmatism (subduction) and accretion of island arcs as the grew westward during the Gothic orogeny. Rocks were later deformed by two folding events prior to 1.61 Ga and one folding event that occurred prior to 1460 Ma. (Lindström et al., 2000).

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Between 1.50-1.20 Ga, anorogenous magmatism occurred in the area with a possible metamorphic and magmatic event occurring in the south at 1.45 Ga.

Between 1.15-0.90 Ga, the Sveconorwegian orogeny produced deformation through regional metamorphosis of the province. The Eastern segment displays amphibolite facies with granulite facies occurring in the south. Regional north-south trending shear zones developed during this orogeny, e.g. on the eastern border of the Eastern Segment where the coincides with the eastern extent of the influence of Sveconorwegian deformation. Further west, a major shear zone, the Mylonite zone, developed separating the Western and Eastern segments. It has a moderately, westerly dip with a recorded thrust movement to the east (Lindström et al., 2000). Rifting in Neoproterozoican time resulted in formation of the Vättern graben further to the east (Andréasson and Rodhe, 1990).

An extended period of erosion (0.9-0.5 Ga) during the late Proterozoic resulted in the evolution of a regional denudation surface across southern Sweden, which is referred to as the subcambrian (Rudberg, 1954; Lidmar-Bergström, 1996; Lindström et al., 2000). Initiated during the Ediacaran, a regional transgression resulted in the formation of Cambrian sandstones with basal conglomerates and aluminous shale followed by Ordovician limestones, marls and shales. Silurian shales were followed by formation of limestones and sandstones in a regressive environment through the Devonian. Extensional processes in the west initiated formation of the Oslo graben with associated magmatism during the late Carboniferous and early Permian. This also resulted in formation of dolerite sills within the accumulated sediment cover in south-central Sweden at 280 Ma (Lindström et al., 2000).

Several periods of uplifting and faulting, with subsequent weathering and erosion, lead to the evolution of additional denudation surfaces in southern Sweden throughout the Phanerozoic (Lidmar-Bergström, 1996). However, in south-central Sweden (Area 1 in Figure 3, Lidmar- Bergström, 1995), the Precambrian denudation surface was only exposed in the Neogene, resulting in a better preserved surface than elsewhere (Lidmar-Bergström, 1988; Lidmar- Bergström, 1995). Paleozoic rocks are preserved in some areas as mesas on the denudation surface, partly protected by dolerite caps (Lindström et al., 2000). Regional glaciation history A global cooling of the climate during the Paleogene and Neogene eventually lead to the formation of regional ice sheets, first initiated in Antarctica (Benn and Evans, 1998). In the late Pliocene and early Pleistocene, continental ice sheets were also formed in North America and Eurasia even though minor glaciations probably occurred in northern Europe already in the Miocene. Glacial sediments deposited during the Elster glaciation indicates an extensive ice sheet advance from the north into Central Europe with other deposits indicating extensive glaciation as early as Menap (Lindström et al., 2000; Ehlers et al., 2004).

Saalian deposits are very sparse in Sweden but undated tills stratigraphically below Eemian sediments in Skåne may be of this age or older (Lindström et al., 2000). However, in Germany, three major northerly ice advances have been interpreted indicating major glaciations during this stage (Lindström et al., 2000; Ehlers et al., 2004). Interglacial deposits from the Eemian have been documented throughout Scandinavia at a few locations but, as with older sediments, the preservation rate is low due to subsequent glaciations removing and re-depositing older deposits (Lindström et al., 2000; Robertsson, 2000).

The latest glacial cycle has had significant influence on present day topography and sediment cover throughout Sweden. Early Weichselian glaciations originated in the Scandinavian

6 mountains, possibly with dispersial centres in both northeast Sweden and southwest Norway that later inter-grew and extended westerly towards the Norwegian shelf as well as easterly across northern Sweden. The southern extent of the ice sheet is unknown but it may have extended down to Skagerrak (Lundqvist, 2004; Mangerud et al., 2004; Larsen et al., 2009). In the north-east, the ice limit has been interpreted to have extended across Finnish Lapland and along the coastal areas of northern Russia with an ice sheet covering the shallow Barents Sea up to Svalbard (Svendsen et al., 2004).

Early Weichselian ice formed during marine conditions resulting in warm basal conditions for the south-easterly advancing ice. This had great influence on geomorphology in northern Sweden producing landforms that are still preserved due to later advances in the area experiencing a frozen basal regime (Lundqvist, 2004).

Two interstadials, the Peräpohjola and the Tärendö, have been identified in northern Sweden and they correspond to Marine Isotope Stages (MIS) 5c and 5a respectively (Mangerud et al., 2004). Glaciation limits during the intermediate 5b cold phase are unknown but ice extent may have been restricted to areas close to the mountains (Lundqvist, 2004).

Starting during MIS 4, the Scandinavian Ice Sheet (SIS) once again grew to cover most of the Scandinavian Peninsula. It extended down to the Swedish west coast where the ice margin oscillated for most of the time leading up to the final advance (Houmark-Nielsen and Kjaer, 2003; Lundqvist, 2004; Larsen et al., 2009) although there are indications of major temporary ice marginal retreats during MIS 3 (Boulton et al., 2001; Arnold et al., 2002; Ukkonen et al., 2007).

In MIS 2, maximum glacial extents of the Weichselian were finally reached at the Late Glacial Maximum (LGM) when the SIS once again moved south into Germany and Poland as well as into Denmark and across the North Sea connecting with the Devensian ice sheet covering northern parts of the British Isles (Svendsen et al., 2004; Larsen et al., 2009). At 22-20 cal ka BP, an ice sheet from northeast reached its maximum at the Main Stationary Line trending north-south across Jutland. Subsequent retreat towards the Swedish west coast was followed by several easterly re-advances into Denmark through ice-streams flowing out of the Baltic depression across Skåne up until approx. 16 cal ka BP (Houmark-Nielsen and Kjaer, 2003; Houmark-Nielsen et al., 2004).

The front of the ice stream across Skåne retreated to the east simultaneously as the main ice retreated to the north-east on the Swedish west coast. A rapid breakup of the ice in the most southern part of the Baltic depression resulted in a change in direction of retreat towards north. Due to isostatic rebound of the crust and low eustatic sea level, a Baltic Ice Lake (BIL) was eventually formed south of the retreating ice sheet (Lundqvist et al., 2007; Björck, 2008).

In southwest Sweden, the ice front initially aligned parallel to the coastline and retreated inland (Figure 2). Temporary climate deteriorations resulted in local oscillations and re- advances of the ice margin which lead to the subsequent formation of the coastal moraines (HCM) at approx. 18-16 cal ka BP, the Göteborg line (GÖ) at approx. 15.4-14.5 cal ka BP and the Berghem line (BE) earlier than 14.4-14.2 cal ka BP. Further north, ice marginal features like the, earlier than 14.1 cal ka BP, Trollhättan line (TR) and the, earlier than 13.4 cal ka, Levene line are oriented in northwest-southeast direction indicating a minor change in the direction of ice retreat. TR and BE have been correlated respectively to the Hvaler and the Onsøy moraines south of Oslo, Norway (Lundqvist and Wohlfarth, 2001).

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Figure 2: Summary of dated ice regression features with suggested west-east correlation. Sk in map shows the location of the town of Skara (From Lundqvist and Wohlfarth, 2001). Across the South Swedish Highlands, distinct morphological features of ice marginal oscillation, as seen in the west, are missing. Here, the ice sheet retreated supra-aquatically and left a cover of hummocky moraines and smoother moraine surfaces (Lundqvist et al., 2007).

Along the East coast of southern Sweden, ice retreat resulted in an increasing accommodation space for the proglacial BIL. As long as the elevated areas of the South Swedish Highlands dammed the BIL, it drained through the Öresund Strait which was constantly being raised due to isostatic rebound. About 14 cal ka BP, the threshold was elevated above sea level leading to a raised BIL surface level (Björck, 2008).

When the ice sheet retreated from the Levene line it is suggested to have passed the northern tip of Mount Billingen, thus creating the possibility for a new drainage path for the BIL (Björck, 2008). This resulted in an estimated 10-20 m drop down to the level of the sea that inundated parts of southwest Sweden (Lundqvist et al., 2007). Shortly after, at approx 12.8 cal ka BP, a significant climatic deterioration called the Younger Dryas cold event and possibly a result of major melt water drainage into the Atlantic from ice-dammed lakes in North America, occurred. Once again, the SIS expanded south past the northern tip of Mount

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Billingen and down to the Skara area resulting in a renewed lake level rise within the BIL (Jakobsson et al., 2007; Björck, 2008).

Around the SIS, significant ice marginal features formed during the Younger Dryas (YD) cold stage including the Norwegian Ra moraines, the Finnish Salpausselka ridge system and ridges within the Middle Swedish Ice-Marginal Zone (MSIMZ) west of Mount Billingen (Lundqvist et al., 2007).

A second, 25 m high, drainage of the BIL occurred at approx 11.7-11.6 cal ka BP when the ice sheet once again retreated north of Mount Billingen (Figure 3). As the ice front retreated into lower terrain, a connection with the sea was established that eventually allowed saline water to temporary penetrate into the Baltic depression during the Yoldia Sea stage (Björck, 2008).

Figure 3: Reconstruction of the final retreat of the SIS. Light grey color is sea, dark grey is fresh water lake (From Lundqvist et al., 2007) 9

Recent work on varved clay sediments in the MSIMZ indicates deposition of Younger Dryas marine clay during retreat from the Skara ridge ice margin position with minor oscillations resulting in subsequent formation of ridges, as previously suggested for the area east of Billingen (Strömberg, 1994; Johnson and Ståhl, 2010).

North of MSIMZ, one more zone with ice marginal features is located at the northern end of present day Lake Vänern. Large glaciofluvial deposits in this area and minor moraine ridges in the west are possibly correlated to the Ås, Ski and Aker moraines in the Oslo area indicating a late YD to an early Preboreal age formation. The transition into an interglacial resulted in a rapid downwasting of the ice in the Baltic depression with the SIS eventually retreating towards a central area in the northern part of the Fennoscandian mountains (Lundqvist et al., 2007).

Shortly after the second opening of the Billingen connection between the BIL and the Vänern bay area, crustal rebound resulted in shallowing of the straits in south-central Sweden and an end to the saline inflow even though this area remained the drainage path for the Baltic depression to the sea. A similar situation occurred subsequently in the west where the isostacy initiated a damming effect along the western and southern edges of the Vänern basin gradually reducing the outflow capacity and inducing a transgression in the southern areas of the Baltic depression. At approx. 10.2 cal ka BP a new drainage path in the south opened up and Lake Vänern was shortly after separated from the Ancylus Lake in the east. A further marine connection south of Sweden, due to rising global sea levels in combination with crustal subsidence, later evolved into the Littorina Sea (Björck, 2008). Local topography, geology and geomorphology Surface topography in the study area can be characterized as a gently sloping surface dipping west-northwest with several east-west trending ridges crossing from the east (Figure 1). A major fault trending north-northeast by south-southwest is visible in the terrain west of Lake Lången at the northern tip of Mount Billingen and continues to the south where it is covered by Quaternary sediments. East of this fault, Cambrian sandstone is preserved on the Precambrian bedrock surface and is covered by sediments in the Valle Härad kame area (Björck and Digerfeldt, 1984; Antal Lundin et al., 1999). On the western side of this fault, the Precambrian bedrock surface outcrops in several locations (Munthe, 1905). An offset of 50 m (east side down) suggests a significant dip-slip component and the preserved sandstone suggests a Phanerozoic activity along a fault that possibly was created already during the tectonic formation of the Vättern depression. Another topographically indistinct fault zone is located south to southwest of Mount Kinnekulle where drilling results are reported to show a vertical displacement of 30 m. (Ahlin, 1987).

A suggested fault zone extends south from Mount Kinnekulle and turns to southeast towards Skara. It can be traced as a low anomaly in the SGU magnetic airborne survey map (Antal Lundin et al., 1999). Finally, east of Götene, a north-northeast trending fault zone is suggested in the literature and coincides in the northern part with minor relief changes separating the Klyftamon area to the east from lower areas in the west (Johansson et al., 1943). It can partly be traced on airborne magnetics but is topographically indistinguishable in the south (Antal Lundin et al., 1999).

The Precambrian bedrock surface in the Kinnekulle area is reported to slope gently (0.3% relief) towards west-northwest (Johansson et al., 1943).

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Central parts of the study area are covered by Quaternary sediments with bedrock outcrops observed south of Götene, in elevated areas in the northwest part of the study area, southeast of Kinnekulle and within and to the east of Skara. No bedrock outcrops are reported in the southwest by early 20th century SGU investigations (Munthe, 1903; Munthe, 1905; Lundqvist et al., 1931; Johansson et al., 1943). However, recent SGU re-mapping of the area indicate exposure of bedrock in a stream-eroded ravine (Påsse, 2006b).

Early 20th century geological mapping by the SGU also show that there is a till cover in the elevated areas in the northeast and southeast as well as south of Mount Kinnekulle. Areas below the Highest Coastline (HC) are mostly covered by glacial silt and clay. Washed sand and gravel cover the cohesion sediments in many areas.

Glaciofluvial sediments are found in the south extension of the eskers near Holmestad and Österäng. South of Mount Kinnekulle, there are also glaciofluvial deposits which indicate a subglacial drainage path along the western side of the mountain. Peat is mostly occurring in the easterly parts that have a more undulated topography. The east-west orientated ridges in the central parts of the area have complex internal composition (Johansson et al., 1943). Comparison between old and new SGU Quaternary maps North of Skara town, recent SGU mapping have extended units with mixed glacial and sorted sediments into areas previously mapped as clay. In between the Skara and Skånings-Åsaka ridges, recent mapping shows glaciofluvial sediments extending from the east to Highway E20 which have previously been mapped as swash material (sand and gravel). North of the Skåne-Åsaka ridge, this difference in interpretation extends even further west (Munthe, 1903; Påsse, 2006b). Previous work in the area Geological mapping of the study area was initiated in the early 20th century by the Geological Survey of Sweden (SGU) (Munthe, 1903; Munthe, 1905; Lundqvist et al., 1931; Johansson et al., 1943). The entire area was re-mapped a few years ago and new Quaternary maps have become available online in pdf-format but the final report on this recent mapping is yet to be published (Påsse, 2006a; Påsse, 2006b; Unknown, 2010). This new information has been used in this thesis although the final report is yet to be published. Digital data Reference system Starting in 2007, the default planar reference system used by Swedish government agencies (e.g. Geological survey of Sweden (SGU) and the Swedish mapping, cadastral and land registration authority (Lantmäteriet)) was changed with the introduction of SWEREF 99 (TM). However, since this work was initiated prior to this change, the older planar RT 90 (2.5 Gon W) coordinate system has been used consistently throughout this thesis work (Ekman, 1998; Jivall, 2000). Similarly, elevation values are referenced in RH 70 height system and not according to its successor RT2000 (Ekman, 1998; Ågren, 2009). Maps The map sheet Terrängkartan 8D NV Skara was used during field work and the corresponding digital dataset was acquired for GIS-database construction from Digitala Kartbiblioteket, an online service from Lantmäteriet (Unknown, 2005b). Both raster and vector datasets were acquired containing contour lines (5 m equidistance), although no elevation information was included in the line attribute data.

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According to the metadata description provided, contour lines available as vector data were initially created through scanning of contour line originals. Later processing included corrections of digitizing errors and line continuity. Four types of line segments were included in the vector dataset:

Contour line, 5 m equidistance (category code 568 in attribute data) Contour line, 25 m equidistance (571) Depression, 5 m equidistance (575) Cutting (598)

The statistical quality description for the dataset is stated as unknown (Unknown, 2005d).

Regional elevation data in raster format (50 m grid size) were also acquired from Digitala Kartbiblioteket. This information was initially collected from contour lines in older maps with the aim of a maximum standard error of 2.5 m (Unknown, 2001). Further studies of data quality for this national elevation database indicate an estimated accuracy of approximately 2 m in open areas but with less accuracy in areas of undulating topography (Klang and Burman, 2006).

Data was delivered as georeferenced TIFF images and with 8-bit data storage, only 256 different values were represented in the national database. Thus, according to instructions, each value had to be multiplied with 8.59375 in order to get representative elevation values for the studied area. This resulted in this value being the actual DTM z-resolution (Unknown, 2005c).

Area wide orthophotos in georeferenced TIFF format with a pixel resolution of 1 m were also acquired from Digitala Kartbiblioteket (Unknown, 2005b). Well data In accordance with Swedish legislation (SFS 1975:424, SFS 1985:245), well drillers have to report the geology of any water- or energy wells drilled to the SGU. This information is stored in the National Wells Archive and is available for the public via an online map service on the SGU website. When wells for this project database were extracted in February 2005, the database contained over 230 000 wells with a yearly addition of 10 000-15 000 new posts. Reporting is standardized using a template describing where and when a well has been drilled as well as drilling method and other technical data. Additional information include well depth, strata sequence data and pumping test capacity (Unknown, 2005a).

RT 90 2.5 Gon W was, at the time, used in the National Wells Archive database and collar positions were presented with x- and y-coordinates. Each collar position was classified according to an accuracy description (VXY-field in attribute data). Rank 0 and 1 corresponded to a x;y-accuracy of <100 m and <250 m respectively. Posts marked with a rank value of 2 had uncertain planar accuracy. A short text describing location was sometimes available in the database but this were not included for all posts and the quality varied from exact (e.g. 5 m northwest of farm house) to only describing the property number where the drilling had been done (Unknown, 2005a).

Strata sequence data descriptions varied in quality with no standardized terminology in place. Soil descriptions were, at best, rough (e.g. “0-12 m Sand; 12-13.5 m Clay; 13.5-17.5 m Till”) but more often generalized (e.g. “0-44 m Sand, Clay, Gravel”) or undefined (e.g. “0-25.5 m soil above bedrock”). Total depth presented was assumed to be accurate (Unknown, 2005a). 12

METHOD Study area The study area was initially planned to cover the entire area between the Kinnekulle and Billingen mountains. Because east of the Valle härad fault, well information was sparse and with complicated Quaternary geology, initial modeling of bedrock and stratigraphy lead to poor interpolation results. As a result, the extent was reduced to only include the thick sediment package to the west of the Valle härad fault bordered by outcrops in the north, south and E (Figure 4).

Figure 4: Study area outline compiled from Lantmäteriet data. Red dots indicate centre of outcrop mapped in recent SGU study (Påsse, 2006b).

Elevation model To be able to compose a 3d model of well data and integrate it with other observations from field work and literature, drill holes had to be geo-referenced. Since each collar only had x- and y- coordinates included in the database and no other information of elevation was available from the actual drilling, all collars had to be assigned a z-value. This was done by extracting elevation values for the given positions from available topography datasets.

Available raster data (50 m grid size) from Lantmäteriet were used to describe regional topography but in order to increase the z-accuracy of the collar positions, a more detailed digital terrain model (DTM) was created from contour lines with 5 m equidistance.

A dataset containing a study area excerpt of Terrängkartan was acquired in vector format from Digitala Kartbiblioteket, an online service from Lantmäteriet (Unknown, 2005b). All available contour lines were extracted from the dataset and saved in a separate shape file. Since this dataset originally had been created from paper copies, there was no elevation

13 information associated with individual contour lines. This had to be manually added to attribute data for each line segment and during this work; the entire dataset was checked for dangling nodes and other topology errors in order to avoid interpolation errors.

Geographically scattered point information can be interpolated through various mathematical and geostatistical methods such as Inverse Distance Weighting (IDW) and Kriging. When data is available in vector format (points, lines and/or polygons) terrains can be easily visualized as a Triangulated Irregular Network (TIN) (Longley et al., 2005).

TINs are constructed by creating triangular, topologically correct surfaces from points or line segments. This method, in which the triangles longest side is minimized and where the internal angles of each triangle are as similar as possible, is called Delaunay triangulation. It benefits from using lineations (e.g. cuttings, streams and shorelines) with defined z-values to carefully reproduce changes to surface morphology.

However, there are some drawbacks with using TINs together with contour lines. Upper parts of hills and lower parts of depressions tend to be flattened out by this approach unless there is additional information available on crest and bottom elevation, e.g. as stream line segments. A flattened crest or depression could theoretically have an error in height of less than one equidistance, in this case <5 m. The dataset acquired from Lantmäteriet contained some elevation points located on crests in the study area but they were too few for providing enough detail if elevation was to be modelled by a TIN.

In order to reduce the potential errors in crest and depression areas of the elevation model and to utilize the available data in the best way, another method was used to create the project elevation model. A

This method, available as a script for Arcview B 3.2, interpolated linearly between each contour line as well as extrapolated values in crest- and depression areas based on the surrounding slope rake. Extrapolation could not exceed one C equidistance and was controlled by both slope- and threshold factors (Figure 5). The script had been developed by Jan Stuckens and was D downloaded from the ESRI web site (Stuckens, 2009).

Several combinations of slope- and threshold E settings were tested to identify the most appropriate setup. The resulting raster image was compared visually with a TIN-model, Figure 5: Graphical description of interpolation method. A) available maps and orthophotos in order to Elevation profile from linear interpolation of contour lines identify errors (e.g. inverted crests or (or a TIN without additional crest and depression information. B) Red line shows actual surface profile. C) depressions). Any error identified was Extrapolation with adjacent slope rake. D) Extrapolation corrected by locally editing the raster image limited by elevation coefficient (blue=1, cyan=0.5). E) Rake using the Raster Calculator available in the coefficient <1 produces a gentler transition in slope rake ArcGIS extension Spatial Analyst. (green=0.5). (Modified from Stuckens, 2009)

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Drilling database Well information was acquired from SGU and an initial data review revealed several incorrect posts (e.g. wells with zero depth) that were removed from the dataset. In order to georeference the wells in 3d, the DTM was queried for z-values for all collar positions concerned. Since collar position accuracy varied significantly within the dataset, a review of each collar position was carried out where site descriptions and elevation variance within each uncertainty buffer zone were considered. Elevation variance was studied for all collars classified to have at least 100- or 250 m accuracy (VXY=0;1). Z-value statistics for each buffer zone were calculated and used together with orthophotos, property maps and other available information to define which wells could be used in modeling. A few collar locations were also checked during field work.

This detailed review was also carried out Definition VXY Drilled to bedrock # on some collar positions that were Yes 175 0 classified as unknown (VXY=2) but had No 27 Yes 105 detailed log descriptions. For all wells Wells in study area 1 with detailed log descriptions, a No 33 Yes 96 comparison of geology descriptions of 2 the top layer and the SGU quaternary No 42 Summary 478 maps were made in order to further verify collar positions. A summary of Table 1: SGU well data in the study area, classified by accuracy well categories within the study area is (Unknown, 2005a). presented in Table 1.

For 3d-visualization and analysis of well-archive information, linear referencing along drill traces was implemented. This method is usually used for describing events along routes in e.g. transport- or water distribution networks but has also been used within the exploration business (Unknown, 2003).

There were no deviation measurements available in the well archive dataset so all wells were assumed to be vertically drilled and with 3d start and end coordinates separated only by well depth.

By interpolating a 3d-line between the start and end coordinates, a drill trace could be visualized in ArcScene. However, due to software limitations, a vertical 3d line could not store route events properly unless there was an offset in plan coordinates (X;Y) between the start and end point. As a result, all end points were offset by one cm to the west in order to bypass this limitation of using a 2,5d-tool (as the ArcGIS platform) for 3d purposes.

In order to display SGU Well Archive geological information along drill traces, a master data table Figure 6: Visualization of well data with linear referencing in a two-layer soil sequence above bedrock. containing start and end values for each geological interval along with a geological description were compiled (Figure 6).

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Simultaneously, all geological descriptions were reviewed and adjusted to fit into a uniform terminology. Six grain size classes (clay, silt, sand, gravel, cobbles and boulders) were included according to the SGF´81 definition (Larsson, 2008). Further, three combo classes (cohesion, friction and cohesion-friction) were introduced to facilitate single units with uncertain intervals or descriptions. Additional classes included till, organic and undefined material.

In addition to the unit classification above, all other available information from the SGU Well Archive were included in the master data table making it accessible for viewing and querying purposes in ArcScene. All geological intervals were ranked according to their vertical position above bedrock starting with 1 at the bottom. Bedrock surface model In order to model the bedrock surface in the study area, bedrock elevation values were extracted by subtracting the depth to bedrock from the collar elevation value. Only collars with an adequate positioning (as defined for the drilling database above, see Table 1 above) were initially considered. This dataset was then reviewed from a geostatistical point of view in order to select an appropriate interpolation method.

Based on this examination and on the knowledge of the terrain DTM and well information accuracy levels, Natural Neighbour spatial Interpolation (NNI) was chosen for the creation of a bedrock DTM. This is a local mathematical method that is appropriate for clustered scatter points and deals efficiently with point datasets of any size. It uses area defined weighted averages based on Thiessen polygon networks and requires no additional user interaction (e.g. search radius) during interpolation as required in geostatistical modeling (Sibson, 1981; Watson, 1992).

Additional information on bedrock topography was incorporated in the interpolation process from recent SGU quaternary mapping (Påsse, 2006a; Påsse, 2006b). Outcrop observations in the study area have generally been mapped as small and clustered areas. Small areas are normally exaggerated in geological maps for viewing purposes and each polygon in the map was honoured by its centre point in modeling with z-values from the surface DTM.

Since 3d-data points useable for interpolation of a bedrock DTM were not evenly distributed over the study area, there were some areas with low point density which most likely would produce a poor interpolation result. When the preliminary bedrock DTM was compared vs. the bottom of all useable wells that were not drilled into bedrock, several locations were spotted where the bedrock DTM had a higher z-value than expected from well data. In order to reduce these errors, 3d-points representing the bottom coordinates of these drill holes were included in a new interpolation procedure even though these wells were not drilled to bedrock. This resulted in a bedrock DTM that was in better compliance with the entire dataset.

The terrain DTM was used as a boundary condition in order to restrain the upper limit of the bedrock DTM. In addition to this, soil depth in areas not mapped as outcrop or thin soil cover where restrained to a depth of at least 0.5 m in order for the model to better honour outcrop mapping. See Appendix 1 for workflow.

Reports of blind faults, possibly offsetting the bedrock surface within the study area, could not be verified in the well dataset and were not accounted for in the modeling process. The interpolated bedrock surface was created with a 10 m raster resolution.

16

Stratigraphy Area wide soil depths were deduced from ground- and bedrock surfaces but in order to distinguish individual sedimentological units, a closer review of the quaternary map and well logs was necessary. Two approaches were considered and are described below. Sections For visualization of stratigraphical data in the main study area, a method for preparing sections was designed. Viewing available geological data and interpreting it to units in section could provide further understanding of the stratigraphy within the area. Available data were: Topography (from DTM) Quaternary surface mapping (recent SGU work) Drill logs (from the SGU Well Archive) Drill logs (from literature) Drill logs (from recent field work within this project) There is existing commercial software on the market that can prepare 2-d sections from this type of data (e.g. Target for ArcGIS, Discover for Mapinfo) but these software extensions were not available for use within this project. Instead, an alternate approach was chosen that included using the ArcGIS Model Builder to design a model (script) that would present data georeferenced in 3d (RT90 2.5 g W, RH70) onto a selected section that was chosen by a polyline on a plan view map of the area. By creating this model in ArcGIS Model Builder and running it with various polylines as input, both long sections and cross sections could be produced for the area.

Initially, the entire area was planned to be covered by sections with a 1 km gap in between individual lines. Each section was to use a 500 m buffer zone surrounding each centre line and with wells within the buffer zone being projected onto the section, the entire area would thus be covered. This would require 21 sections in each direction and due to limited time and data availability, a more selective approach were chosen where the aim was to pick a few sections containing as many wells as possible for review.

The orientation of the cross- and long sections (XS & LS) was outlined parallel and perpendicular to the estimated main deglaciation direction of the area as interpreted from regional ice marginal morphological features and reported isostatic tilt (Påsse, 1983).

To choose sections, a dense grid (100 m*100 m) was created across the area and the distance for each sample point to the nearest well useable for stratigraphical studies was calculated by point sampling of a prepared Euclidian distance map. By summarizing the number of points along each line that were located less than or equal to 500 m away from a well and combining the results based on line orientation, a smaller number of cross- and long section positions could be selected for review based on data availability.

A complete outline of the various models used (entire process subdivided into 14 stages to be run after each other) are presented in Appendix 2. Interaction with the process was to be kept at a minimum but in order to visualize the data in a section covering the entire area and still be able to see the details, the option of selecting a vertical exaggeration factor had to be implemented. This value, together with the selected polyline that represented the plan view trace of the section was selected at the beginning of the process. A selection buffer surrounding the straight plan view trace was also implemented to define which drill holes to incorporate based on distance to profile.

17

Due to restrictions in use of the ET Geowizard extension freeware with Model Builder, a snap process that normally could be integrated in the modeling process had to be carried out manually for each type of drill log dataset as described in Appendix 2.

A simplified, section-based, presentation of geology was carried out by digitizing interpreted borders as polylines which, together with available border condition lines (bedrock, ground surface), formed polygons of interpreted units. Isopach A review of the well dataset in planar view, displaying only intervals ranked as 1, produced a point sample map of geological units on top of bedrock. Since point density was estimated to be too low for straight forward, point to point interpolation in the north and east, a smaller subarea in the southwest was defined for this exercise. Although this increased the overall observation density slightly, there were still significant distances between wells with useful information of stratigraphy which made it hard to define the position of unit borders at depth. A simple approach of defining the influence radius of each well through Thiessen polygons, where each polygon included all positions which were closest to a common centre point (well), was chosen for creating a continuous map of soil units above bedrock.

Since the quality of log descriptions varied in the dataset and grain-size and/or geology descriptions could not be assumed to have been fully standardized, each category was reclassified into either cohesion or friction. The former included clay and silt while the latter was composed of all other grain-sizes (sand-boulder) and till. This result was the basis for further construction of the first layer above bedrock.

Areas with similar geology were defined and by subsequently viewing additional intervals in 3d according to rank and mapping areas of similar geology, a simplified sediment isopach was constructed. Each unit’s top surface was interpolated with NNI and terminated either at the border of the study area or onto a lower surface. Boundary criterions were based on the Thiessen polygons described above as well as recently produced Quaternary surface maps (Påsse, 2006a; Påsse, 2006b).

Using well- and surface observation data according to the above mentioned observations, a basal friction layer (FR1) was interpolated in the subarea. Unrestrained interpolation did not honour the constraints set by basal Thiessen polygons so the interpolation surface was reprocessed with a minimum thickness set to 1 m for all friction areas and 0 m for all cohesion areas.

Above FR1, a cohesion layer (CL1) was then interpreted from well logs. Boundary conditions used for restraining the model included the underlying bedrock and FR1 surface as well as the ground surface DTM in areas which has been mapped as glacial clay. Where this unit was estimated to be present but covered with a second friction layer (FR2), a boundary criterion (z <= 0.5 m below ground surface) was implemented to honour surface mapping.

FR2 was constrained by the upper layer of CL1 and the ground surface DTM in areas not used in FR1 or CL1. See Appendix 3 for details of all processing of layers mentioned above.

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RESULTS Study area The final study area measured 331 km2 and stretched from Götene in the north to Skara in the south and across to south of Mount Kinnekulle. Elevation model In order to construct a detailed surface topography model, a DTM with 5-m pixel size was created from contour lines using Contour Gridder. When comparing the script interpolation result to a TIN-model generated from the same dataset, significant improvements were identified (Figures 7 a and b). Despite this, further systematic visual comparison of the interpolated surface with available orthophotos, topographical and geological maps as well as field observations identified 367 possible errors where the interpolation script generated depressions instead of crests. Most commonly, this occurred in areas where the surrounding terrain was sloping towards the considered contour line. This was corrected by inverting cell values Figure 7: Examples of contour lines within the contour lines concerned when mirrored on the interpolation problems (All lines have same TIN-model (Figures 7 b and c). z-value). a: TIN-model (Flat areas near foot of slope to the left and flat areas on the valley floor. b: Linear interpolation with There were ten additional areas in terrain depressions slope and extrapolation correction. c: where the interpolated elevation surface was located Corrected results from b. higher than the nearby contour line. Also, there were nine areas that displayed both higher and lower elevation values than was defined by the surrounding contour line. All of these areas were reclassified to match the nearby contour line.

Figure 8: Interpolated terrain DTM with wells used in project.

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Within the study area, elevation ranged between 53.3-160.5 m above sea level with a general slope aspect sector from north to west (Figure 8). Five, east-west trending ridges were located within 10 km between Skara and Götene. A drainage pattern with eroding stream valleys originating from flat areas in between ridges was clearly visible in the DTM. There was a significant change in relief north and northeast of Lundsbrunn where there was a 20-25 m drop in elevation per km. Drilling database The final study area contained 478 Purpose VXY Drilled to bedrock # wells that were classified for Yes 128 0 further use according to Tables 2 No 13 and 3. Used for definition of Yes 56 1 bedrock surface No 8 Among the 264 wells used in the Yes 8 2 stratigraphy interpolation, 25 wells No 1 were found inconsistent with the Summary 214 stated location criteria but Table 2: Wells used for interpolation of bedrock surface. contained interesting stratigraphy Purpose VXY Drilled to bedrock # descriptions and were thus Yes 128 0 included in the study as reference No 27 descriptions. Used for definition of Yes 68 1 stratigraphy No 25 For viewing purposes of wells Yes 12 2 used in stratigraphical modeling, No 4 four classes of well intervals were Summary 264 introduced, as seen in Table 4. Table 3: Wells available for stratigraphical modeling.

Table 4: Further classification Purpose Category Drilled to bedrock # of wells available for 1 Yes 192 stratigraphical modeling. Wells with approved location 2 No 47 Wells with undefined location but 3 Yes 16 with good log descriptions 4 No 9 Summary 264

Bedrock surface model Out of 478 wells available in the study area, 45% were used in bedrock surface modeling. Of these 214 wells, 22 were not drilled into bedrock but their total depths were found to be situated below the initial interpolated surface and were thus included to lower the surface in the areas concerned. In addition to the selected wells, 352 elevation points representing outcrop locations (polygon centre points) digitized from recent SGU mapping were included in the dataset in order to honour surface observations in peripheral areas for a total of 566 data points.

A statistical check on the horizontal distribution of all points used for bedrock surface interpolation produced a Nearest Neighbour Ratio (NNR) of 0.74, a Z-score of -11.8 and a p- value of zero indicating a clustered distribution. The distance between data points used in bedrock surface modeling range from zero to 2.40 km with a mean distance between data points of 0.66 km (Figure 9). In the central and southeast part of the study area, the interpolated bedrock surface displayed a slightly dipping surface to the northwest (Figure 10).

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Figure 9: Euclidian distance map for data points used in bedrock surface interpolation.

Figure 10: Interpolated bedrock surface with well locations and outcrop positions used for interpolation.

21

This trend was inconsistent in the west to the north sector where the interpolation result was irregularly undulated. Surface roughness was pronounced in areas with clustered data points from outcrop mapping with a smoother interpolated surface appearing in areas with less clustered well information.

A regional trend among bedrock observation points was studied by fitting a plane (1st order polynomial interpolation) to the data points compiled from wells. This surface dipped 0.25 degrees (0.44%) and was oriented towards 312º (N48W). A RMS value of 6.65 (m) in cross validation indicated local deviations which were also observed in the trend analysis plot (Figure 11).

Figure 11: Trend analysis plot of data points compiled from wells used in bedrock surface interpolation. Colored points represent source data projections onto trend axis surfaces with colored trend lines included. X-Y-Z axis (shown in red) represent east, north and elevation respectively. Graph is angled along the dominant trend surface orientation. Green line is down dip, blue line is along strike.

The green line in Figure 11 represented a trend line along the identified global trend surface dipping towards 312º surrounded by the corresponding projected data points, also displayed in green. An increased deviation of projected data points away from the green line was observed towards the northwest (elevated areas near Mount Kinnekulle and in the north) and could indicate faulting of the Precambrian bedrock surface. The blue trend line (which extended northeast-southwest) displayed a curved shape which could be due to limited data points in the wide areas as well as an irregular study area.

When reviewing elevation of generated data points representing SGU mapped outcrops, a relief of 0.40% facing 323º and with a RMS of 4.54 (m) was calculated. Mean undulation of the interpolated bedrock surface was 0.63%. Stratigraphy Regional soil depth (10 m raster resolution) was calculated as the z-value difference between ground- and bedrock surfaces (Figure 12). Depth to bedrock varied between zero and 64.6 m with a mean depth of 19.1 m for the entire study area. The thickest soil cover was found in the area in and around Lundsbrunn in the central part of the study area where depths of >60 m were modelled. South of Vinninga in the west, there was another area with >50 m depths. The model also revealed shallow depths (outcropping) in the north, northwest and southwest.

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An initial review of all useful well logs identified several positions where till or coarse grained material were identified in several positions throughout a sequence of fine grained material. However, this did not seem to be a general and consistent feature that could be tracked throughout the area.

Figure 12: Soil depth calculated from surface topography DTM and bedrock DTM. A statistical check on well positions available for stratigraphical modeling (n=239) produced a NNR of 0.90, a Z-score of -2.91 and a p-value of 0.0036 indicating a rejection of the null hypothesis of randomly distributed features (i.e. data points were clustered). Sections Results of the study to select section positions among 250 XS and 250 LS suggestions are summarized in Charts 1 and 2. The total number of sample points along each sample line with a well within 500 m where summarized and used for ranking purposes with the highest number ranked as 1. This meant that a local minimum in the rank curve showed a line position with more wells within the buffer zone than its neighbours. Preferred positions of sections were chosen at local minima in areas of interest, i.e. covering the central basin area and to the southwest. When several adjacent lines received the same rank value, the line with lowest mean distance to wells was preferred. In total, six XS and six LS were selected for further review (Figure 13).

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Chart 1: Result of grid sampling of Euclidian distances to wells along possible long-section lines across the study area. For details, see text.

Chart 2: Result of grid sampling of Euclidian distances to wells along possible cross-section lines across the study area. For details, see text.

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Figure 13: Selected sections with 500 m buffers and wells used on top of the corresponding map of Euclidian distances to nearest well used for determination of soil depth and stratigraphy.

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In Figures 14-17, each section line is presented in planar view with collar locations and the SGU soil map, with a hill-shade effect calculated from the DTM, within the 500 m buffer zone. The corresponding section (with a 20 times vertical exaggeration) is displayed with topography as a line that is colour-coded according to the units of the soil map and with the interpolated bedrock surface displayed as a grey line. Wells within the buffer zone are also presented with drill traces colour-coded according to the defined geological categories. Based on this data, simplified geological interpretations for each section were outlined using the three combo-classes described above and with (sandy) till included into the friction class.

XS1 was the eastern-most section and displayed a soil depth of 20-30 m. Well information was sparse and clustered but showed a uniform stratigraphy with a thick cohesion unit (glacial clay) mostly covered by a thinner friction unit (mapped as post-glacial washed sand with minor eolian deposits). A thin (patchy?) layer of till and/or sorted frictional sediments could be present beneath the clay in parts of the area.

XS2 was located 2.3 km east of XS1 with similar stratigraphical content but with less total overburden, especially in the north where the soil cover thickness often was less than 10 m and possibly with significant till content. The central and southern parts had a 5-10 m thick sand cover that was underlain by 15-20 m of clay with or without a thin till cover on top of bedrock.

XS3 was located another 2.3 km east of XS2 and displayed a similar stratigraphy as its neighbour. Soil depth in the north was shallow with till at the surface but further south, there was a 20-30 m thick sediment package of clay with sand on top. Patches of till and/or other frictional material could be present at the bottom of the cohesion unit. The contact between the interpreted upper friction and main cohesion unit seemed to be very flat in the central and southern part of the section but was not, according to the SGU map, present in two eroded valleys where this contact surface was supposed to intercept the ground surface.

XS4 was located a further 3 km to the east and the buffer zone contained several well observations in a clustered pattern. Outcropping bedrock and shallow till cover were present in both ends of the section and the soil depth increased to more than 50 m in the centre.

As revealed in the SGU mapping of the area, section XS4 differed from the previous ones in that there was a significant cover of glaciofluvial sediments in the central part of the area overlying the glacial clay. There were also east-west trending ridges that contained a mixture of glacial clay and sorted sediments. The spatial distribution of this type of material at depth was uncertain from available well logs and these areas were thus marked as a mixture of cohesion and friction units in section.

In the Skara area there was a clear pattern of glacial clay with a thin sand cover at the surface and possibly a coarser material (till and/or glaciofluvial sediment) on top of bedrock. To the north of the town there was a gap in well observations where the surface mapping revealed mixed sediments. This was in the westerly extension direction of the Skara ridge (see XS5) and was thus marked with a hatched pattern in section indicating a possible mixture of both cohesion and friction material.

5 km to the north was the next cluster of wells which displayed 10-15 m of glaciofluvial and washed sand on top of a significant unit of glacial clay. There could also be a 10-20 m thick

26 sequence of till and/or other friction material above bedrock but the presence and extent of this material was uncertain.

The glaciofluvial sediments above clay extended at the ground surface for another 4-5 km before the underlying clay again was exposed at the surface. With the only detailed logs in this area intercepting only the upper 5-10 m of the sediment package (revealing thin units of both sand and clay), the vertical distribution of sediments was very uncertain.

Further north, there was a significant decrease in soil depth and without well logs available. The interpreted section units were very sketchy but glacial clay with overlying coarser material was expected to be draped on till and/or bedrock.

XS5 was located another 1.9 km east and had a similar overall layout as XS4. In the north part of Skara town, there was a pronounced ridge built up of clay and sand according to available well data. On both sides of the ridge there were areas with glacial clay on top of bedrock. Further to the north, washed sand and glaciofluvial material overlaid the main clay package and there were also indications from wells that there were a few meters of till and/or gravel on top of bedrock.

Further north, several ridges with limited well information at depth were located. Since these had been mapped on the surface as containing mixed sediments, a hatched pattern was used in section although this was not verifiable in the well dataset on these locations. As in XS4, there was a general lack of well information towards the north. The thick clay sequence seemed to taper out towards the north with bedrock outcropping or covered by a shallow soil layer of sand, till and/or clay in the Götene area.

XS6 was located 1.8 km east of XS5 and had a similar look in the south. North of the Skara ridge there were 3-5 m of glaciofluvial sediment on top of a thick sequence of glacial clay. The central part of the section displayed well logs from both ridges and flats that supported the idea of a thin friction cover above bedrock covered by 15-20 m of clay and with some 5 m of glaciofluvial sand on top. Several well logs from the Skånings-Åsaka ridge displayed a varying mix of sediments, predominantly clay with some intervals of coarser material.

The basal friction layer seemed to be thicker south of the Ledsjö ridge area. This coincided with a depression in the interpreted bedrock surface but was also described in well logs. North of Ledsjö, there was a 4 km gap in well data where SGU mapping indicated glaciofluvial sediments on top of glacial clay with minor ridges of mixed sediments. At the northern end of the area, bedrock occasionally came to the surface but was mostly covered by a thin sequence of till and/or sorted sediment with a patchy cover of clay.

LS1 displayed a decreasing bedrock surface elevation and an increasing soil depth from a few meters of overburden in the east to almost 30 m of soil in the west with wells distributed fairly evenly along the profile. SGU surface mapping generally corresponded to the well logs and most of the section showed a thicker cohesion unit (mainly glacial clay) which was partly covered by a thinner friction unit. In the east, bedrock was covered by till and glaciofluvial sediments.

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Figure 14: XS1-3 sections

28

Figure 15: XS4-6 sections

29

Figure 16: LS1-3 sections

30

Figure 17: LS4-6 sections

31

Well logs in the central part of the section displayed mainly clay with some descriptions of inter-layers of friction material. The SGU surface mapping described this area, which was part of the Skara ridge as a mixture of glacial clay and sorted sediments. Since the information available at depth was limited, that part of the section was classified as a zone of mixed cohesion and friction material with no further sub-division although there might be mostly clay at depth, i.e. in line with what was done in the previous sections. In the west, a thick clay sequence seemed to be partly covered by up to 10 m of washed sand.

LS2 was located 1 km north of LS1 which meant that the buffer zones of these two lines together covered a 2 km wide continuous area. Wells along LS2 were mostly located in the central part of the section and gave a better view of the complex stratigraphy west of the Skara ridge where units of coarse material were appearing within the clay package. A till unit seemed to be present on top of the bedrock in this area. Further west, a two unit stratigraphy was interpreted with a shallow surface cover of sand on top of a thicker clay sequence.

LS3, located 1.7 km to the north of LS2, contained fewer but more well distributed well logs that mainly showed a thick clay sequence capped by sand with recent fluvial erosion exposing the bedrock according to SGU mapping. East of the section centre there seemed to be a thin basal layer of friction material and glaciofluvial sands above glacial clay. An area of mixed sediments associated with the Skara ridge separated the main clay unit from thin glaciofluvial material and till units above bedrock, which was occasionally outcropping. At the western end of the section, there were significant glaciofluvial sediments.

LS4 was located 2.1 km north of LS3 and cut through the Skånings-Åsaka ridge area where well logs displayed a complicated stratigraphy. The western part was similar to the previous section with an esker interpreted as interrupting the thick clay sequence. In the central and eastern part of the section, a glaciofluvial cover was present and in the far east, a shallow till unit covered bedrock. Much of the section had a thin basal layer of friction material above bedrock.

LS5 was located another 2.3 km to the north of LS4. The undulated terrain in the east consisted of various units of coarse and fine-grained material that could not be separated in section. Glaciofluvial sand and gravel at the ground surface covered most of the central part of the section area although the thickness of this top unit was uncertain due to limited amount of well observations. A lower friction unit on top of bedrock was interpreted to be extensive but the available observations were restricted to a few wells intercepting to bedrock. A bedrock depression with more than 10 m of till was suggested from available well data and the interpolated bedrock (see also XS6 above). A continuation of the glaciofluvial unit in the west was suggested for LS5 as well.

LS6 was the most northern section and stretched across and along the Ledsjö ridge. Glaciofluvial sediments in the west were present here as well and there was an area of till above bedrock that intercepted the clay sequence. Further east, a thick clay unit above a thin basal unit of friction material was interpreted from a few wells. Several shallow well observations from the Lundsbrunn area revealed a complex stratigraphy near surface with clay and sand. There was no information available at depth in this area. On the northern side of the ridge, logs revealed a thick clay sequence with a glaciofluvial unit on top. A thin basal layer on bedrock had been interpreted from sparse well data. The eastern part of the section was interpreted to consist of till and glaciofluvial sediments above bedrock.

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Isopach Interpolation from 3d points were restricted to an area of 141 km2 in the southwest where inter-collar distances varied between zero and 1941 m with an average distance of 628 m (Figure 18).

Figure 18: Euclidian distance map showing wells available for stratigraphical modeling in study area. Dashed line indicates border of subarea for stratigraphical 3d modeling.

Figure 19: Geology above bedrock from well logs. Influence area based on Thiessen polygons.

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Figure 20: Generalized geological mapping used as basis for modeling layer above bedrock.

An influence area of each well used for stratigraphical descriptions adjacent to bedrock (Rank 1, Category 1) was initially calculated based on Thiessen polygons (n=108) (Figure 19) and further generalized (Figure 20). The result was later checked visually vs. Rank 1, Category 2- 4 well log intervals (Table 4 above).

A mostly thin (a few m thick) layer of friction material covered bedrock in vast parts of the study subarea according to available well logs. South of Mount Kinnekulle, an area with glaciofluvial sediments was observed in the SGU mapping (Påsse, 2006b). A continuous depth of these sediments to bedrock was supported, at least for parts of the area, by several well log descriptions although these logs were not all included in the modeling due to insufficient location information. A 2 m thick till layer at the bottom of a well within this area suggested a thin basal till layer beneath the glaciofluvial deposit but this was not separated in the model.

Continuity of friction material down to bedrock could not be verified in the well dataset for the elevated ridge areas between Skara and Götene where the SGU have mapped mixed glaciofluvial and clay sediments. These observations, as well as some minor patches of till near and southwest of the Skara ridge area, were thus excluded in the interpolation of a lower, area-wide friction layer.

The interpolated FR1 unit had a maximum thickness of almost 58 m in the west where the glaciofluvial sediments were thick and extended north-south as a significant esker. There was also a thicker unit (almost 20 m) in the northeast where a depression in the interpolated bed rock surface coincided with a description of glaciofluvial sediments (overlying till) in nearby wells.

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Except for these two areas with significant frictional sediment units above bedrock, this layer was interpolated mostly as a very thin (0 or 1 m) unit controlled by the stated boundary conditions. An exemption was present in the central part of the area where a thickness of approximately 5 m was estimated for a west-northwest trending patch located in the westerly extension of the Skara ridge.

The main interpolated unit of the area was a thick cohesion package (CL1) with a maximum and mean thickness of 46.4 m and 20.1 m respectively. It was described from well logs and surface mapping to mainly consist of glacial clay with minor patches of silt. Thickest parts were located in the northeast part of the area, east of the esker in the west and in central areas with a thin friction unit above bedrock and/or limited stream erosion. Areas with a thin or non-existing CL1 cover were the exposed esker in the west as well as peripheral parts in the northwest and southeast where bedrock was outcropping or covered by a thin basal friction unit.

Finally, interpolation of an upper friction layer (FR2) produced a unit that had a maximum thickness of 22.6 m and a mean of only 2.8 m as well as fairly large areas that were controlled by the 0.5 m mapping depth boundary condition. 10-20 m of depth was calculated in the east and northeast where glaciofluvial sediments extended westwards in between the elevated ridges of mixed sediments (not separated in this isopach model). Other places where significant friction material (5-10 m thickness) was reported above CL1 were in the central area as well as in the southwest part of the study area where washed sand overlaid glacial clay.

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DISCUSSION Elevation model Given that the interpolated terrain DTM was the basis for all other work when it came to georeferencing surface and well observations in 3d, the accuracy of this process would influence all other processing within the project. By selecting to interpolate from contour lines with 5 m equidistance instead of using the available regional coverage raster data, a better accuracy was achieved. However, using this dataset required significant manual editing of the original data in order to achieve a topologically correct polyline layer with elevation values as attribute and was thus not an optimal approach for large areas (datasets).

The selected interpolation method, with subsequent minor manual editing, produced a topographically more correct model compared to using e.g. a standard TIN approach. However, this required using a script designed for an outdated version of the used GIS software (Arcview 3.2) as well as still experiencing limited accuracy due to both inherited uncertainties from the original dataset and some effects of interpolation between contour lines.

Since the initiation of this project, Lantmäteriet has started to produce a new national elevation model based on LIDAR data from an ongoing airplane laser scanning survey (Unknown, 2011). This data is being available for use in surveyed areas once post-processing is completed. Elevation data will be available as laser survey point data and as nationwide elevation grid with a vertical accuracy of <0.5 m, which will be very useful for this type of work. Drilling database Without the availability of a separate extension software designed for section and 3d presentation of drill holes, linear referencing of observations along line segments was used for visualizing well data in section and 3d. Once the database structure with a master data table was ready and a polyline layer of expected drilling traces was created, observations were easily plotted in 3d space. This method did not require drill traces to be straight but could have also been used with down hole survey data, if available.

Available data from the SGU well archive varied in quality regarding both collar position and geological description. Uncertainty regarding collar positioning contributed to the overall vertical inaccuracy of data positions in 3d since z-values for all well data were determined based on the terrain DTM value for the given collar coordinates. With the best description locating collars within a 100 m radius, some variation in z-value could be expected, especially in areas with undulating terrain morphology. Given enough time in the field, a systematic approach of revisiting all useful wells to resurvey collar positions with a handheld GPS could be done in order to reduce this uncertainty if using similar type of data in future projects.

Availability and quality of geological descriptions in the SGU well archive varied from nonexistent to acceptable which limited the final interpretation to a broad description of units of cohesion or friction. Information from recent and historical scientific drilling were much more detailed but the number of observations were very limited when compared to the SGU well archive and were thus mainly useful for local studies, especially due to limited depth extent for many observations compiled from literature. Bedrock surface model Overall trend of the interpolated bedrock surface (northwest/0.44%) differed slightly in aspect and relief compared to estimations of the nearby denudation surface from literature (west-

36 northwest/0.30%). The higher mean value for slope calculations on the interpolated bedrock surface (0.63%) was in line with the visual impression of a locally undulating surface, most clearly demonstrated in areas with a denser observation point interval.

As suggested in the trend analysis plot there were data points near Kinnekulle in the northwest and near Götene in the north with z-values higher than the expected trend. These areas had thin soil cover and outcrops mapped as Precambrian bedrock which indicated that these observations were not related to an incorrect interpretation of depth to Precambrian bedrock in the well dataset.

Whether or not the observed undulations could be due to inaccuracies in the data processing, offset by faults or represent some kind of older drainage pattern was hard to say given the vertical uncertainties inherited from the ground surface DTM and collar locations. Regarding blind faults suggested in literature there was no clear evidence in the interpolation result of a structure extending south from east of Götene but since the dataset was sparse in the area, a possible bedrock surface offset could be present below the extensive soil cover.

A weak magnetic geophysical anomaly that extends from Mount Kinnekulle and south towards Skara town coincides with a depression in the interpolated bedrock surface which could be related to a structural offset of the bedrock. Stratigraphy Sections Designing a work flow for presenting well and surface information in section view using ArcGIS standard components and freeware together in Model Builder was time consuming but doable. Further streamlining of the proposed workflow could have reduced processing time slightly. Standardizing and merging the available well datasets (SGU well archive as well as recent and historical scientific drillings) to a greater extent prior to processing would have reduced the number of interactive steps needed for presenting the data on sections.

Selecting section positions solely based on number of wells within each buffer zone produced a section coverage that incorporated many wells but lacked in quality descriptions in some areas. Implementing a more qualitative ranking of the stratigraphical information for each well or using the initial plan to cover the entire area with sections (and buffer zones) could have increased the overall quality of the interpreted sections. The latter would also have improved the possibility to honor continuity from section to section.

The simplified approach of combining various types of sediment such as till and coarse sorted sediments into one classification unit (friction) reduced the details of the section presentations but was deemed necessary given the limited data available as well as the uncertainty in the quality of geological observations from the SGU well archive database.

By implementing a two-unit category approach when interpreting the prepared sections, a general outline of the distribution of sediment in the study area could be created. The use of a combo category was deemed necessary wherever a more complex stratigraphy was suggested in well logs or from surface mapping, i.e. mostly within the ridge zones.

The reviewed cross sections support a three-layer approach where a mostly thin unit of till and/or coarse sorted sediment cover the bedrock in parts of the study area. This combined unit was interpreted to locally have significant thickness (e.g. in the central part of XS4) which

37 could be associated with accumulation of ice marginal deposits due to a temporary stand still during the deglaciation. Further northeast (as seen in XS6) there was also an increased thickness of the basal layer associated with a depression in bedrock.

The main cohesion unit, which has been shown by Johnson and Ståhl (2010) to consist of varved glacial clay in the ridge area, was interpreted to extend across the entire area. Some log descriptions described this unit as continuous silt and whether or not there was a local variation to a slightly coarser dominated material or only a deviation in field classification could be up for discussion.

There were also a few reports of layers of till and gravel within this unit but this seemed to be associated with local oscillations at stationary ice marginal positions (e.g. a blind western extension of the Skara ridge). There was no clear evidence in the well logs that this unit, on a regional scale, was separated by friction material which could be an indicator of preserved older cohesive sediments below the YD glacial clay. This suited the idea that the advancing late Weichselian ice sheet eroded away all unconsolidated material and re-deposited it downstream, thus wiping out any trace of an earlier Quaternary record in the area. This implies that if Björck’s (2008) first drainage at Billingen occurred, there appears to be no evidence of it, and, if it had occurred, the Younger Dryas advances have erased it.

SGU surface mapping was assumed to describe the upper friction unit since the available dataset (and section interpretation) did not provide any further details on interlayer variations with depth. Isopach As for the section interpretation work, a simplified approach, with only cohesion and friction categories used to define stratigraphical units, was implemented. Several boundary conditions were also introduced into modeling to control the interpolation process and compensate for sparsely distributed data points.

Technically, this was straight forward using workflows in Model Builder where several parameters could be adjusted and tested for but the overall outcome of 3d point interpolation was unsatisfying, mainly due to low data point density in the study area.

The interpolated lower friction layer included both basal till and thick glaciofluvial sediments which was interpolated as a continuous, north-south stretching esker in the west. A few well logs supported the idea of thick glaciofluvial deposits although the final horizontal extent at depth was mainly controlled by a boundary condition and not delineated by well observations.

Several areas, especially in between the ridges in the east but also further west, presented a thin FR2 cover (0.5 m) where the interpolated thickness was controlled by the mapping depth boundary condition. Observations, available for comparison but not useable for interpolation, suggested that the thickness of the surface unit was significantly underestimated, mostly due to insufficient data point density in the area between ridges. The upper contact of the main cohesion unit was thus expected to be too high in many areas where the unit was not exposed at the ground surface.

Further work with incorporating section results in the 3d interpolation process could help improve the quality of the model result but was not covered within the scope of this project.

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CONCLUSIONS The SGU Well Archive contained a large number of well data from the area and provided a good indication of e.g. regional variation of soil depth. However, the dataset lacked accuracy in terms of collar positions and geological descriptions which limited its use in detailed modeling work. Creating a terrain DTM from contour lines was time consuming and should be avoided once a nationwide, terrain grid with high resolution based on ongoing LIDAR surveys will be available. Using ArcGIS standard components and freeware to compile, present and analyze well data in section and 3d was doable but initially time consuming. Once a process flow had been designed, additional modeling was fairly easy and quick. Interpretation in section was preferred to straight-forward 3d interpolation given that the available data was clustered and sparsely available. Incorporating section information into the 3d interpolation process could increase the quality of the outcome but this was not studied in this project. The interpreted stratigraphy of the area supported the idea of a thick unit of glacial clay and silt that was deposited on top of bedrock or a thin cover of coarser sediment during a retreating ice sheet. This was later covered by coarser material such as glaciofluvial sediments and washed sands as well as late stage fluvial deposits along the drainage paths. Several zones with mixed sediments and undulating topography suggested local oscillation to produce ice marginal features along the front of the ice sheet during temporary breaks in the main deglaciation pattern.

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ACKNOWLEDGEMENTS The author would like to thank Associate Professor Mark D. Johnson for providing the opportunity to get involved in this exciting project which, among other things, resulted in some great days in the field and the possibility to further develop skills in various GIS software. He would also like to thank the SGU for providing data and funds for the overall project. Management at Northland Exploration Sweden AB is together with colleague Mikael Edland Faber thanked for their support in finishing this thesis work and Sr. GIS Analyst Sergey Kozhevnikov is thanked for useful comments on GIS-related issues regarding section work.

Finally, I would like to thank my wife Helena for comments on the text (and for making my life fantastic in general, you are the best!). All our study colleagues and friends are also thanked for making the years at University such a great time.

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APPENDICES

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Appendix 1 Outline of processing steps (using Model Builder in ArcGIS) for interpolating the bedrock surface.

Appendix 2 Outline of processing steps (using Model Builder in ArcGIS) for presenting data from project database on sections. There are 14 models that need to be run after each other with some minor interaction from the user as well as some manual work in between executing models.

The first model creates the temporary data structure used for the section data.

The next model (below) extracts surface data for the planned section profile.

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46

Next, profile lines are constructed for the topography and bedrock surface.

The model below (next page) then converts the latest SGU mapping data from plan view to profile surface lines.

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48

In order to present the available drill hole data in the created section, each data set (well archive, drill logs from literature and recent drilling within this project) will be queried for drill data within a buffer range from the planned profile trace. The selected data is then converted to the local section reference system.

Due to restrictions in the use of ET Geowizard extension freeware with Model Builder, a snap process that normally could be integrated in the modeling process has to be carried out manually at this point using the global snap function in the ET extension within ArcMap.

The output file from the snapping process is further used in the ongoing conversion of well data to section.

49

The converted data is then presented as events along the drill trace using line reference (as was used for 3d visualization earlier).

The latest three models have prepared the Well Archive drill data for section presentation and the upcoming six models will do the same for the drill logs presented in the literature and from recent field work.

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Manual snapping is required again (as described for Well Archive data above) followed by further geoprocessing as outlined below.

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52

Manual snapping is required again (see above).

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Finally, a merging operation to finalize the data conversion for presentation in section is required.

Appendix 3 Model flow sheets for preparing isopach layers are outlined below

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55