ACTAUNIVERSITATIS

UPSALIENSISUPPSALA

2014

Digital Comprehensive Summaries of Uppsala Dissertationsfrom the Faculty of Science and Technology 1143

Reflection seismic investigation inthe Skellefte ore district

A basis for 3D/4D geological modeling

MAHDIEH DEHGHANNEJAD

ISSN 1651-6214ISBN 978-91-554-8937-3urn:nbn:se:uu:diva-221225

Dissertation presented at Uppsala University to be publicly examined in Hambergsalen,Geocentrum, Villavägen 16, Uppsala, Thursday, 5 June 2014 at 10:00 for the degree of Doctorof Philosophy. The examination will be conducted in English. Faculty examiner: AssociatedProfessor Charles Hurich (Memorial University of Newfoundland, Department of EarthSciences, Faculty of Science).

AbstractDehghannejad, M. 2014. Reflection seismic investigation in the Skellefte ore district. A basisfor 3D/4D geological modeling. Digital Comprehensive Summaries of Uppsala Dissertationsfrom the Faculty of Science and Technology 1143. 68 pp. Uppsala: Acta UniversitatisUpsaliensis. ISBN 978-91-554-8937-3.

The Skellefte ore district in northern Sweden is a Palaeoproterozoic volcanic arc and one of themost important ones hosting volcanogenic massive sulfide (VMS) deposits, producing mainlybase metals and orogenic gold deposits. Due to high metal prices and increased difficulties infinding shallow deposits, the exploration for and exploitation of mineral resources is quicklybeing moved to greater depths. For this reason, a better understanding of the geologicalstructures in 3D down to a few kilometers depth is required as a tool for ore targeting. Asexploration and mining go deeper, it becomes more and more evident why a good understandingof geology in 3D at exploration depths, and even greater, is important to optimize bothexploration and mining.

Following a successful pilot 3D geological modeling project in the western part of the district,the Kristineberg mining area, a new project "VINNOVA 4D modeling of the Skellefte district"was launched in 2008, with the aim of improving the existing models, especially at shallowdepth and extending the models to the central district. More than 100 km of reflection seismic(crooked) profiles were acquired, processed and interpreted in conjunction with geologicalobservations and potential field data. Results were used to constrain the 3D geological modelof the study area and provided new insights about the geology and mineral potential at depth.

Results along the seismic profiles in the Kristineberg mining area proved the capability of themethod for imaging reflections associated with mineralization zones in the area, and we couldsuggest that the Kristineberg mineralization and associated structures dip to the south down toat least a depth of about 2 km. In the central Skellefte area, we were able to correlate mainreflections and diffractions with the major faults and shear zones. Cross-dip analysis, reflectionmodeling, pre-stack time migration, swath 3D processing and finite-difference seismic modelingallowed insights about the origin of some of the observed reflections and in defining the imagingchallenges in the associated geological environments.

Keywords: Skellefte district, reflection seismic, mineral exploration, 3D/4D modeling,mineralization, faults and shear zones

Mahdieh Dehghannejad, Department of Earth Sciences, Geophysics, Villav. 16, UppsalaUniversity, SE-75236 Uppsala, Sweden.

© Mahdieh Dehghannejad 2014

ISSN 1651-6214ISBN 978-91-554-8937-3urn:nbn:se:uu:diva-221225 (http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-221225)

Dedicated to My love Alireza and

My lovely daughters Armita & Camelia

List of Papers

This thesis is based on the following papers, which are referred to in the text by their Roman numerals.

I Mahdieh Dehghannejad, Christopher Juhlin, Alireza Malehmir, Pietari Skyttä, Pär Weihed, (2010), Reflection seismic imaging of the upper crust in the Kristineberg mining area, northern Sweden. Journal of Ap-plied Geophysics, 71:125–136

II Mahdieh Dehghannejad, Tobias E. Bauer, Alireza Malehmir, Christo-

pher Juhlin, Pär Weihed, (2012), Crustal geometry of the central Skel-lefte district, northern Sweden – constraints from reflection seismic in-vestigations. Tectonophysics, 524–525:87–99

III Siddique Akhtar Ehsan, Alireza Malehmir, Mahdieh Dehghannejad,

(2012), Reprocessing and interpretation of 2D seismic data from the Kristineberg mining area, northern Sweden. Journal of Applied Geo-physics, 80:43–55

IV Mahdieh Dehghannejad, Alireza Malehmir, Christopher Juhlin and

Pietari Skyttä, (2012), 3D constraints and finite difference modeling of massive sulfide deposits: The Kristineberg seismic lines revisited, north-ern Sweden. Geophysics, 77(5):WC69–WC79

Reprints were made with permission from the respective publishers. Selection of additional refereed conference and journal publications dur-

ing my PhD studies, which are not included in this thesis: • Christopher Juhlin, Mahdieh Dehghannejad, Björn Lund, Alireza

Malehmir, Gerhard Pratt, (2010), Reflection seismic imaging of the end-glacial Pärvie Fault system, northern Sweden. Journal of Applied Geo-physics, 70:307–316

• Mahdieh Dehghannejad, Christopher Juhlin, Alireza Malehmir and Pär Weihed, (2010), High-resolution reflection seismic imaging in the Kris-tineberg mining area, northern Sweden. 72nd European Association of

Geoscientists and Engineers Conference & Exhibition - Incorporating SPE EUROPEC 2010, Barcelona, Curran Associates, Inc. 5368-5371

• Tobias E. Bauer, Pietari Skyttä, Mahdieh Dehghannejad, Saman Tavakoli, Pär Weihed, (2011), Geological Multi-Scale Modelling as a Tool for Modern Ore Exploration in the Skellefte Mining District, Swe-den. International Association for Mathematical Geosciences (IAMG) conference, Salzburg, 759–764, doi: 10.5242/iamg.2011.0032

• Magnus Andersson, Alireza Malehmir, Valentin A. Troll, Mahdieh Dehghannejad, Christopher Juhlin & Maria Ask, (2013), Carbonatite ring-complexes explained by caldera-style volcanism. Scientific Reports, 3:1677, doi: 10.1038/srep01677

• Mahdieh Dehghannejad, Christopher Juhlin, Alireza Malehmir, María García Juanatey, Pietari Skyttä, Pär Weihed & Tobias E. Bauer, (2013), Reflection seismic imaging in the Skellefte ore district, northern Swe-den. 12th SGA Biennial Meeting, Uppsala, Sweden, Extended Abstract, 1:126–129

• Pietari Skyttä, Tobias E. Bauer, Tobias Hermansson, Mahdieh Dehghannejad, Christopher Juhlin, María García Juanatey, Juliane Hübert and Pär Weihed, (2013), Crustal 3-D geometry of the Kristine-berg area (Sweden) with implications on VMS deposits. Solid Earth, 4:387–404

Contents

1. Introduction ............................................................................................... 11  

2. The Skellefte district ................................................................................. 14  2.1. Geological background ...................................................................... 14  2.2. Pilot 3D geological modeling study .................................................. 17  2.3. VINNOVA 4D modeling ................................................................... 18  

3. Challenges in hardrock seismic imaging ................................................... 22  3.1. Why reflection seismic for mineral exploration? .............................. 22  3.2. Key imaging aspects .......................................................................... 24  3.3. Crooked line seismic survey .............................................................. 24  

3.3.1. Cross-dip analysis ...................................................................... 25  3.3.2. Swath 3D processing of 2D crooked line ................................. 27  

3.4. Reflector modeling ............................................................................ 28  3.5. Migration ........................................................................................... 30  

3.5.1. Post-stack time migration .......................................................... 30  3.5.2. Pre-stack time migration ............................................................ 31  

3.6. Finite-difference (forward) modeling ................................................ 31  

4. Summary of papers .................................................................................... 34  4.1. Paper I: Reflection seismic imaging of the upper crust in the Kristineberg mining area, northern Sweden ............................................. 35  

4.1.1. Summary .................................................................................... 35  4.1.2. Conclusions ................................................................................ 37  

4.2. Paper II: Crustal geometry of the central Skellefte district, northern Sweden – constraints from reflection seismic investigations ................... 39  

4.2.1. Summary .................................................................................... 39  4.2.2. Conclusions ................................................................................ 42  

4.3. Paper III: Re-processing and interpretation of 2D seismic data from the Kristineberg mining area, northern Sweden ....................................... 43  

4.3.1. Summary .................................................................................... 43  4.3.2. Conclusions ................................................................................ 46  

4.4. Paper IV: 3D constraints and finite difference modeling of massive sulfide deposits: The Kristineberg seismic lines revisited, northern Sweden ...................................................................................................... 48  

4.4.1. Summary .................................................................................... 48  4.4.2. Conclusions ................................................................................ 51  

5. Conclusions ............................................................................................... 54  

6. Summary in Swedish ................................................................................. 56  

Acknowledgments ......................................................................................... 58  

References ..................................................................................................... 60  

Abbreviations

2D Two-dimensional 3D 4D CDP CMP DMO Ga Hz Kg Km m ms Mt NMO s S/N VMS

Three-dimensional Four-dimensional Common depth point Common midpoint Dip moveout A billion years (Gigayears) ago Hertz Kilogram Kilometer Meter Milisecond Megaton Normal moveout Second Signal-to-noise ratio Volcanogenic massive sulfide

11

1. Introduction

The Skellefte mining district in northern Sweden is a Palaeoproterozoic dis-trict that covers an area of 120 km by 30 km (Figure 1.1). The district is one of the most important mining districts in the country, producing Zn, Cu, Pb, Ag and Au from volcanogenic massive sulfide (VMS) and orogenic gold deposits and has a large potential for new discoveries (Allen et al., 1996; Kathol and Weihed, 2005; Carranza and Sadeghi, 2010). The Kristineberg mine in the western part of the Skellefte district and Maurliden (E & W) in the central district are the main VMS-deposits in mining operation (Bauer, 2010). The majority of shallow deposits are believed to have already been discovered and therefore the main focus is nowadays to explore at depth (>500 m), especially near existing mining infrastructures (brown- or near-field exploration). For this reason, good control on the three-dimensional (3D) architecture of the uppermost 5 km of the Earth’s crust in the Skellefte district is crucial for focusing on the most promising areas.

3D modeling is based on a combination of different types of information such as geophysical data, petrophysical information on rock properties, and information about the geology. The 3D model acts as a structural framework in which mineralization occurs and allows an improved understanding of the structural evolution of the mining district. Subsequent four-dimensional (4D) modeling adds the time aspect to the 3D models and with the aim of visualizing the geological history and supporting ore targeting. Moreover, adding geological time to the modeling allows for validation of both the conceptual models and the 3D models.

Particular interest in the Skellefte district is to define characteristics of the major deformation zones and their association with the regional structures and lithostratigraphy, where the majority of the VMS deposits are located (Figure 1.1). It is also important to investigate, if any, how the observed transitions in metamorphic grade across the district (Kathol and Weihed, 2005) are related to the structural evolution of the crust.

Results from early reflection seismic work by Elming and Thunehed (1991), Juhlin et al. (2002), and a 3D pilot study in the Kristineberg mining area (Tryggvason et al., 2006), suggested reflection seismics as one of the best suitable methods for improved understanding of crustal structures, but also for providing constraints for 3D geological modeling. To obtain knowledge on the 3D geometry of the ore-bearing volcanic rocks and their

12

associated structures and as a continuation of the 3D pilot geologic modeling study, a new project (VINNOVA 4D project) was formed by both industry and academia, aiming at producing geological 3D/4D models of the upper 5 km of the Earth’s crust in the Skellefte district by combining geological and different types of geophysical investigations. For this, more than 100 km new reflection seismic profiles were acquired in the Kristineberg mining area and the central Skellefte district during 2008-2010.

These data, their processing, analysis and interpretations in conjunction with other geological and geophysical data constitute the backbone of this thesis. A major component of the work was to acquire and obtain high quali-ty reflection seismic images of the upper 5 km of the crust, providing con-straints for the 3D/4D geological modeling of the Skellefte district.

This thesis is divided into two sections: a summary and a collection of papers. The summary is divided into six chapters. The summary starts with this introduction (Chapter 1). In Chapter 2, a brief introduction to the re-gional geology of the Skellefte district, previous work in the area and the new VINNOVA 4D project is given. In Chapter 3, important seismic pro-cessing techniques used in this research are introduced. Chapter 4 consists of a summary of the papers that are included in the second section. Conclusions are summarized in Chapter 5. A summary in Swedish is provided in Chapter 6.

13

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14

2. The Skellefte district

2.1. Geological background The Skellefte district (Figure 1.1) comprises Palaeoproterozoic supracrustal and intrusive rocks that formed in a volcanic arc setting and were deformed and metamorphosed during the Svecokarelian orogeny (Allen et al., 1996; Lundström et al., 1997; Mellqvist et al., 1999; Kathol and Weihed, 2005). The district lies in-between two major tectonic units: (i) an area with Palae-oproterozoic and reworked Archaean rocks of the Norrbotten craton north of the district, and (ii) Bothnian Basin metasedimentary rocks to the south and east of the district (Allen et al., 1996; Kathol and Weihed, 2005). The district has been interpreted as a transitional zone between these two units (Skyttä et al., 2012).

The Archaean-Proterozoic boundary has been defined by a shift in Nd signatures (Lundqvist et al., 1996; Wikström et al., 1996; Mellqvist et al., 1999) that coincides with a gently south dipping subsurface crustal reflection imaged by the BABEL reflection seismic profile, interpreted as NE-verging thrusts tectonics (BABEL working Group, 1990).

Metasedimentary rocks of the Bothnian Supergroup are suggested to form the basement of the mainly 1.89–1.88 Ga felsic volcanic and volcaniclastic Skellefte Group (Allen et al., 1996; Billström and Weihed, 1996; Montelius, 2005; Skyttä et al., 2011). Allen et al. (1996) put forth that the VMS deposits formed partly as sub-seafloor replacement and partly as exhalative deposits within the volcaniclastic and sedimentary rocks and in the uppermost part of the Skellefte Group stratigraphy.

The uppermost stratigraphical unit of the Skellefte district consists of the metasedimentary rocks of the Vargfors Group (1.88–1.87 Ga), and is coeval with the subaerial, predominantly volcanic Arvidsjaur Group that is present further to the north (Skiöld et al., 1993). The sedimentary rocks of the Varg-fors Group at the southern part of the Skellefte district grade into Bothnian Supergroup rocks, but the contact is drawn in a rather arbitrary manner (Kathol and Weihed, 2005).

The oldest intrusive rocks in the Skellefte district are Jörn-type granitoids (1.89–1.88 Ga), which have been suggested to be as co-magmatic with the volcanic Skellefte Group (Gonzales Roldan, 2010; Skyttä et al., 2010). The most prominent rocks are the GI-phase of the Jörn intrusive complex and the Viterliden intrusion (Kathol and Weihed, 2005; Gonzales Roldan, 2010;

15

Skyttä et al., 2010; 2012). Younger intrusive rocks, GII to GIV phases of the Jörn intrusive complex and intrusive rocks of the Perthite-Monzonite suite, post-date the volcanic activity between 1.88 and 1.86 Ga (Kathol and Wei-hed, 2005; Bejgarn et al., 2013). Late Svecokarelian rocks ranging from 1.82 to 1.78 Ga surround the Skellefte district (Kathol and Weihed, 2005).

Structurally, a complex fault pattern and shear zones largely control the structural evolution of the district. The Kristineberg mining area is dominat-ed by E-W striking shear zones (Skyttä et al., 2013), but in the central Skel-lefte, the shear zones strike WNW-ESE and are associated with NNE-SSW striking shear zones. A major WNW-ESE striking shear zone (Dehghan-nejad et al., 2012a) at the southern part of the central district separates two crustal domains with characteristic deformational signatures (Skyttä et al., 2012). Recent studies revealed that these shear zones have a syn-extensional origin and influenced the sedimentation in the Vargfors Group (Bauer et al., 2011 and 2013; Skyttä et al., 2012). These syn-extensional faults have been interpreted to act as fluid conduits for ore-forming hydrothermal fluids (Bauer et al., 2014). Subsequent crustal shortening resulted in inversion of the WNW-ESE syn-extensional faults at shallower levels (1.88–1.87 Ga) and was oriented SSW-NNE, and coaxial in nature (Bauer et al., 2011; Skyt-tä et al., 2012). This deformation resulted in the transposition of VMS de-posits and a penetrative pattern of steep to sub-vertical mineral lineations (Skyttä et al., 2012). Finally, an E-W directed crustal shortening at 1.82–1.80 Ga (Weihed et al., 2002) resulted in the reactivation of major ~N-S striking high-strain zones (e.g., Deppis-Näsliden shear zone and Vidsel-Röjnoret shear system in Figure 1.1; Bergman Weihed et al., 1996; Bauer et al., 2011; Skyttä et al., 2012). Figure 2.1 shows an example of the recon-structed geological history of the central Skellefte district.

Identification of inverted faults resulting from the crustal shortening is thus essential for mineral exploration in the district. Also, since the majority of VMS deposits are located in the uppermost part of the volcanic Skellefte Group the contact relationships between the Skellefte Group and the overly-ing sedimentary Vargfors Group is important to identify. Therefore, some of the objectives of this thesis were to image regional-scale structures, especial-ly fault systems, and to correlate them with the surface geology and also to provide detailed seismic images of subsurface geological structures near known VMS deposits.

16

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17

2.2. Pilot 3D geological modeling study Previous studies such as BABEL Working Group (1990) and (1993), a test seismic profile at Norsjö (Elming and Thunehed, 1991), Luleå seismic pro-file (Juhlin et al., 2002) aimed at better understanding the tectonic evolution of the district at large crustal scales. Results of these studies revealed a need for detailed study of the tectonic evolution of the district and its link to min-eralization. Results of such a study would help to define better strategies for the exploration of deposits in the district and the district’s potential, espe-cially at depth.

A 3D pilot study (GEORENGE 3D project) was then initiated in the Kris-tineberg mining area in 2003. For the 3D pilot study, two parallel 2D crook-ed reflection seismic profiles (Profiles 1 and 5 in Figure 2.2) were acquired during Fall 2003 (Tryggvason et al., 2006). The goals were to focus on un-derstanding the contact relationships between the ore-bearing volcanic and volcano-sedimentary formations and the surrounding intrusive rocks and to provide a framework along which a 3D geological model of the area could be constructed. Results from the reflection seismic data (Tryggvason et al., 2006) revealed numerous reflections from the top 12 km of the crust some that could be correlated with the surface geology. Further studies focused on cross-profile seismic data (Rodrigues-Tablante et al., 2007), constrained 2D and 3D modeling of potential field data (Malehmir et al., 2006; 2007 and 2009a) and magnetotelluric data modeling (Hübert et al., 2009). One of the interesting results from the pilot study was a north-dipping package of re-flections associated with conductivity anomalies and interpreted as structural basement to the Skellefte Group rocks and possibly from Bothnian Basin rocks.

These studies helped to improve and partly validate the seismic interpre-tations and led to the construction of the 3D geological model of the Kris-tineberg mining area down to 12 km depth (Malehmir, 2007; Malehmir et al., 2009a).

18

Figure 2.2. Geological map of the Kristineberg mining area showing the locations of the previous (black lines; Tryggvason et al., 2006) and new reflection seismic pro-files (blue lines; Dehghannejad et al., 2010) and the CDP processing lines (green and orange lines). Black box in the figure shows the location of the 3D swath imag-ing area discussed later in this thesis. Deposits: Kr = Kristineberg, Kh = Kimheden, H = Hornträsk, Rm = Rävlidmyran, R = Rävliden, Rä = Räkå. The geological map is modified after Skyttä et al. (2009).

2.3. VINNOVA 4D modeling The successful work of the pilot study led to the establishment of a new project entitled ''4D geological modeling of mineral belts'' (VINNOVA 4D project) in 2008 financed by the VINNOVA (Swedish Governmental Agen-cy for Innovation Systems), Boliden Mineral AB, and initially by Lundin mining, with major emphasis on 3D/4D modeling of the geological struc-tures of the Skellefte district.

The new project was collaboration between geologists and geophysicists from academia (Uppsala University and Luleå University of Technology) and industry (Boliden Mineral AB and Geovista AB) and based on combin-ing the results from new high-resolution reflection seismic data with results from new detailed structural mapping of the same areas.

One of the main objectives of the new project was to improve the existing pilot 3D geological model in the Kristineberg mining area especially in shal-lower parts down to 5 km and develop it to the central Skellefte district to

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Rm

R

400

1600

1200

800

200

600

1000

1400

200

800200 800

H Kh

RöProfile 2

Profile 1Profile 5

HR

Surface expression of mineralizationsLate-post Svecokarelian granitoidsMafic intrusions (undifferentiated)Vargfors Group metasedimentary rocks

Early Svecokarelian granitoidsSkellefte Group metavolcanic rocks

FaultOld seismic profile (2003)

CDP lineNew seismic profile (2008)

7215

19

obtain a better understanding of the area and how to define a target for a scientific deep hole. The final model should constitute the basis for choosing a well defined drilling site to test the models, constrain the 3D architecture and eventually verify parts of the accretionary tectonics that led to the growth of the Fennoscandian Shield during the Palaeoproterozoic (Weihed, 2010).

During this project, available potential field data, geological observations (Bauer, 2010; Bauer et al., 2011; 2013; 2014; Skyttä, 2012; Skyttä et al., 2010; 2011; 2012 and 2013), new magnetotelluric measurements (Hübert et al., 2013; García, 2012; García et al., 2013) as well as potential field and deep IP measurements (Tavakoli et al., 2012a and 2012b), accompanied the reflection seismic data (Dehghannejad et al., 2010; 2012a and 2012b) and were used to facilitate their interpretations and the construction of the 3D/4D models.

More than 100 km of new reflection seismic data with varying resolution and research objectives were acquired during 2008-2010. Two new profiles, high-resolution profile (HR profile) and Profile 2 in the Kristineberg area (Figure 2.2) and three new profiles in the central Skellefte district, Profiles C1, C2 and C3 (Figure 2.3) were acquired in the framework of the VINNO-VA 4D project. Details about the acquisition parameters of the new seismic profiles in comparison with the previous seismic profiles of the pilot study are summarized in Table 2.1.

During this project, I was dealing with acquisition, processing and inter-pretation of the reflection seismic data as part of my PhD study and results of the seismic profiles were used as a backbone for the 3D geological mod-els of the study area.

20

Figure 2.3. Geological map of the central Skellefte district showing the locations of the new seismic profiles (black lines) and processing CDP lines (red lines). The geological map is modified after Bauer (2010).

15

Bjurliden

Bjurfors

Österbacken

Maurliden W

Maurliden E

ÅlidenMensträsk

Maurliden N

Högkulla E

Holmtjärn

10

Norrliden

200

400

600

800

1000

1200

1400

1600

1800

200

400

600

800

1000

1200

1400

1600

200

400

600

800

1000

1200

1400

1600

1800

2000

1670000 1680000

1670000 1680000

0 2,5 5 km

7230

000

7220

000

7210

000

Finnliden anitform

7230

000

7220

000

7210

000

N

Vargfors Group c. 1.88 - 1.86 Ga

Unclassified rocks

General

Structural form lines

Ultramafic intrusionsMafic volcanic to clastic rock

Lakes and riversSulfide mine, in operationSulfide ore prospect

Fault and shear zoneSkellefte Group c. 1.90 - 1.86 Ga

Extrusive basalt - andesite: lava, hyaloclastite and stratified to massive clastic units

Bedding with dip directionBedding, inferred

Rhyolite lavas, intrusions, hyaloclastites

Synform with plunge directionAntiform with plunge direction

Sediments, unspecifiedRhyolitic - dacitic breccia-conglomerate

Alterning laminated mudstones and sandstones

Monomict conglomerate and sandstone

Polymict conglomerateFelsic volcanic rock

Polymict conglomerate with carbonate-cemented matrix

Mafic volcanic rock, Gallejaur-type

Jörn intrusive complex; c. 1.90 - 1.86 GaTonalite - Granodiorite

Gallejaur intrusion; c. 1.88 - 1.86 GaSyenite - MonzoniteGabbro, diorite

Transscandinavian Igneous Belt; c. 1.82 - 1.76 Ga

Granitoid - syenitoidGabbro, diorite

CDP-lineSeismic profile

Profile C2Profile C1

Profile C3

Profile C2Profile C1

Profile C3

Tabl

e 2.

1. M

ain

acqu

isiti

on p

aram

eter

s for

the

refle

ctio

n se

ism

ic d

ata

(see

Try

ggva

son

et a

l., 2

006;

Deh

ghan

neja

d et

al.,

201

0 an

d 20

12a)

.

Pr

ofile

1

Prof

ile 5

Pr

ofile

2

HR

pro

file

Prof

ile C

1 Pr

ofile

C2

Prof

ile C

3

Yea

r acq

uire

d 20

03

2003

20

08

2008

20

09

2009

20

10

Type

of s

urve

y 2D

cro

oked

line

Rec

ordi

ng sy

stem

SE

RC

EL 3

48

SER

CEL

408

Sour

ce

Dyn

amite

D

ynam

ite

VIB

SIST

Shot

spac

ing

100

m

100

m

25 m

10

m

25 m

25

m

25 m

Rec

eive

r spa

cing

25

m

25 m

25

m

10 m

25

m

25 m

25

m

Act

ive

chan

nels

14

0 14

0-20

0 24

0-30

0 30

0-36

0 33

0-40

0

Rec

ord

leng

th

20 s

20 s

20 s

20 s

20 s

20 s

20 s

Sam

plin

g ra

te

2 m

s 2

ms

1 m

s 1

ms

1 m

s 1

ms

1 m

s

Geo

phon

e G

roup

of s

ix 1

0 H

z Si

ngle

28

Hz

Leng

th o

f pro

file

25 k

m

25 k

m

13.7

km

6.

3 km

30

km

33

km

31

.5 k

m

22

3. Challenges in hardrock seismic imaging

3.1. Why reflection seismic for mineral exploration? Due to an increased demand, and prices, for metals, especially base metals, iron and high-tech metals and difficulties to find shallow deposits, a renewed interest for the exploration and exploitation of mineral resources using seis-mic methods at depth is attracting many researchers and industry (e.g., Eaton et al., 2003; Malehmir et al., 2012 and references therein). Various geophys-ical methods such as potential field and electromagnetic ones have been used by the mineral industry to investigate the subsurface and these methods have been used in mineral exploration to delineate potential mineralized zones and also discover resources at shallower depths (e.g., Roy and Clowes, 2000; Goleby et al., 2002; Malehmir et al., 2006). Reflection seismic method is the only surface method that provides high-definition images of the subsurface with suitable penetration depth for exploration and mining purposes (e.g., Schmidt, 1959; Ruskey, 1981; Wright, 1981; Cosma, 1983; Fatti, 1987; Pre-torius et al., 1989; Milkereit et al., 1992; Urosevic and Evans, 1998; Duweke et al., 2002; Perron et al., 2003; Chen et al., 2004; Murphy et al., 2006; Har-rison and Urosevic, 2012). Therefore, reflection seismic methods were pro-posed as a deep mineral exploration, and complementary, method with the ability of imaging geological structures hosting mineral deposits, and im-proving the knowledge of structures and stratigraphy towards providing optimum drilling targets in mining areas (e.g., Wright et al., 1994; Milkereit et al., 1996; Eaton et al., 2003; Malehmir et al., 2010). This brings new op-portunities for geophysicists, but also new challenges, especially in crystal-line environments (e.g., Snyder et al., 2009; Malehmir et al., 2010).

Several studies refer to that the useful application of seismic methods for mineral exploration was as the result of successful imaging of fault and frac-ture zones in the hardrock environment (e.g., Green, 1972; Green and Mair, 1983; Juhlin, 1995a). Large-scale seismic investigations were also very im-portant in developing the necessary techniques for imaging challenging and complex geological structures in the crystalline environment (Milkereit et al., 1992; Juhlin et al., 1995; Milkereit and Eaton, 1998; Perron and Calvert, 1998; Ayarza et al., 2000; Roy and Clowes, 2000; Stolz et al., 2004; Urose-vic et al., 2005; Willman et al., 2010).

3D surface seismic surveys are known as an ideal solution for complex geological environments (e.g., mining areas), however, due to economic

23

restrictions, 2D surveys are often conducted. Therefore, one of the main challenges here is the interpretation and processing of 2D seismic data, es-pecially in the presence of 3D geology and where the data are often acquired along crooked lines, violating even 2D seismic imaging assumptions (Wu, 1996; Zaleski et al., 1997; Nedimović, 2000; Nedimović and West, 2003a and 2003b). Out-of-the-plane structures normally are present in crooked line data, and these add further challenges for both the processing and interpreta-tion of the data acquired in mining areas. For example, Malehmir et al. (2010) showed a comparison between a strong seismic anomaly observed in 2D data with that observed in 3D data (Figure 3.1). Their observation was that a high-amplitude anomaly observed on the 2D section originated from a massive sulfide deposit, but nearly 700 m away from the 2D line (Malehmir et al., 2010). The 2D data showed the anomaly deeper than that in the 3D data. The important point is that the 2D seismic anomaly led to the discovery of the deposit through a dedicated and proper 3D seismic survey and, for the first time, demonstrated why reflection seismic methods can be used to di-rectly delineate mineral deposits (Matthews, 2002).

Figure 3.1. Comparison between 2D and 3D surveys showing a seismic anomaly observed in 2D data with its actual location in 3D data. The seismic anomaly is from an approximately 6-8 Mt massive sulfide deposit known as the ''deep zone'' at about 1.2 km depth (from Malehmir et al., 2010).

~700 m2D

3D

24

Further success in this case came from a systematic exploration approach by follow up studies such as downhole seismic survey and petrophysical meas-urements as well as seismic modeling of the response of the deposit (Belle-fleur et al., 2004 and 2012). This example shows why regional 2D seismic data followed by 3D seismic data can be very useful for not only defining new targets by imaging the host rock structures, but also for directly deline-ating deep-seated deposits. While 3D seismic data are not often available, the main issue remains on how to obtain as much as information as possible from the 2D crooked line data.

3.2. Key imaging aspects The main components of a seismic survey are acquisition, processing and interpretation, and the overall success depends on proper accomplishment of each of these components. Eaton et al. (2003) suggested six aspects that need careful consideration when planning a seismic survey for mineral ex-ploration. These are (1) acquisition of high-fold data, (2) the need to obtain high-frequency data, (3) forward seismic modeling of mineral deposits and their host rocks, (4) processing considerations with focus on refraction stat-ics, surface consistent deconvolution, and dip moveout (DMO) corrections, (5) physical rock property measurements, and (6) migration considerations. Most of these aspects still require careful consideration when planning, however, the first three generally are given insufficient attention (Eaton et al., 2003). Only a few attempts have been performed to carry the most ad-vanced processing methods often exercised by the hydrocarbon industry. Pre-Stack Depth Migration (PSDM), Reverse Time Migration (RTM), Common Reflection Surface (CRS) stack are now routinely tested even in complex sedimentary areas (e.g., Li et al., 2003; Jones, 2008; Gierse et al., 2009).

3.3. Crooked line seismic survey It is worth to note that the term common midpoint (CMP) is not the same as common depth point (CDP), but the terms are often used interchangeably. We have also used both terms in this thesis; however, the correct terminolo-gy should be CMP, unless DMO has been applied.

As discussed by Wu (1996), a straight CMP line for stacking is often su-perior to a slalom line, so consequently 2D straight lines are more desirable than crooked lines. One important reason for this is that straight line binning better satisfies the assumptions of 2D processing algorithms than slalom line binning (Wu, 1996). As evident, straight line 2D acquisition is usually im-possible over crystalline environment; 2D surveys are forced to follow exist-

25

ing roads for logistical and economic reasons (Nedimović and West, 2003a). Crooked line profiling, coupled with the complex structures of the geologi-cal targets, brings special challenges for 2D reflection seismic data pro-cessing and interpretation (Wu, 1996) and more attention needs to be paid to the geometry, selection of stacking lines and binning of the data (Wu et al., 1995).

Several experiments have shown that with a proper processing approach one can produce high quality seismic images and turn the disadvantages of the 2D crooked line into interpretational advantages by providing (i) cross-dip corrections to obtain more information on the possible out-of-the-plane origin of reflections (e.g., Bellefleur et al., 1995; Wu et al., 1995; Rodriguez-Tablante et al., 2007; Urosevic et al., 2007), and (ii) by 3D swath processing of the 2D seismic data (e.g., Wu et al., 1995; Nedimović and West, 2003a and 2003b; Malehmir at al., 2009b and 2011) to obtain 3D information about the reflections which otherwise it would be impossible using straight 2D lines, unless many are available that cross each other. In this thesis, both approaches were tested and each provided valuable input to the interpreta-tion of the seismic data.

3.3.1. Cross-dip analysis When seismic profiles are acquired along crooked lines, the positions of midpoints are spread out around the actual acquisition line. If there is a sig-nificant spread of midpoints perpendicular to the CMP line, then it is possi-ble to analyze the seismic data for the possible contribution of cross-dip from out-of-the-plane structures (Wu et al., 1995).

Cross-dip is the component of reflector dip in the vertical plane perpen-dicular to the seismic profile (Larner et al., 1979; Wu et al., 1995; O’Dowd et al., 2004). Given constant cross-dip and medium velocity, the reflection times for the traces within a CMP gather will vary due to distance from the midpoint to the processing line (Larner et al., 1979; Wu et al., 1995). Cor-rection Δtij can be calculated by equation 3.1 to account for the cross-dip component (Larner et al., 1979):

Δtij = [2 * yij * sin(γi)] / Vi (3.1)

where γi is the cross-dip angle at the ith CMP, yij is the offline distance of the midpoint (from the stacking line), j is the trace number within the CMP gather and Vi is the velocity of the shallowest dipping layer (we considered it as a constant value without any lateral variations).

A noticeable example of the cross-dip correction and its effect for an ob-served reflection is illustrated in Figure 3.2 (data along Profile C3 of the central Skellefte district, see Figure 2.3 for the location of the profile). A comparison between Figure 3.2a and 3.2b suggests that a cross-dip correc-

26

tion of 30° to the west allows imaging a long reflection that is not imaged using standard stacking methods. This further challenges the 2D interpreta-tion of these data.

Figure 3.2. (a) Stacked section along a portion of the Profile C3, and (b) cross-dip corrected section of the same portion as (a) using a cross-dip component of 30° to the west using a stacking velocity of 5500 m/s. Note a long reflection marked by arrows in Figure 3.2b that is not as evident in (a).

Tim

e (s

)

Distance along profile (m)

30°,

550

0

CDP

Tim

e (s

)

Distance along profile (m)

CDP

0°, 5

500

800 1000 1200

800 1000 1200

12000 15000

12000 15000

0.5

1.0

1.5

2.0 S N

0.5

1.0

1.5

2.0

a

b

S N

27

3.3.2. Swath 3D processing of 2D crooked line If the midpoints of a 2D crooked line data are spread enough around an ac-quisition line, data can be treated as semi-3D data (e.g., Nedimović and West, 2003b; Urosevic et al., 2007). However, because of lack of enough data (azimuth and offset) in the crossline/perpendicular direction of the crooked line the resultant images may be significantly affected by artifacts during migration (both 3D pre-stack and post-stack migration) such as ''smiles''. Nedimović and West (2003b) summarized the fundamental limita-tions of resolving 3D structures from 2D crooked line data: • lack of wide azimuth coverage which does not allow the full resolution

of the cross-dips; • lack of sufficient cross-line horizontal aperture in the data set to resolve

the cross-line position of reflectors; and • irregular spatial distribution of the data (e.g., CMP fold).

The first and second points can be related to any swath 3D survey. The third condition results when shot and receiver positions are along the crook-ed line (Nedimović and West, 2003b). However, besides these, the 3D swath imaging of the 2D crooked line (if it is possible) can be an option to extract 3D information about the geometry of geological structures (e.g., Nedimović and West, 2003b; Urosevic et al., 2007; Malehmir et al., 2009b) and also sometimes to preserve shallow reflections for correlation with the surface geology (Malehmir et al., 2011).

A previous study of 3D swath imaging of the 2D crooked line in the Kris-tineberg mining area (Profile 5, see Figure 2.2 for the location of the profile) was successful in imaging a series of diffractions that were not observed completely by the 2D crooked line processing (Malehmir et al., 2009b). Figure 3.3 shows the 3D visualization of one of the observed diffractions obtained using a 3D swath processing approach. The results of this study demonstrated how the 3D swath imaging can be useful and allowed the ex-traction of 3D information from the diffractions towards improving the in-terpretation of the results. Another experiment of 3D swath imaging by Malehmir et al. (2011) showed that additional source points located off a 2D crooked line, where the line was bending, could allow preservation of shal-low reflections that could not be observed by 2D crooked line processing. Results were obvious: an improved image plus interpretation. So, adding a few source points is fairly inexpensive and can be considered for future sur-veys with 2D crooked lines (Malehmir et al., 2011; Lundberg, 2014).

28

Figure 3.3. A time slice extracted from the unmigrated stacked cube at about 1.6 s, showing a portion of a diffraction hyperbola (D1). Analysis of the diffraction allows locating its origin in 3D (from Malehmir et al., 2009b).

3.4. Reflector modeling Due to the crookedness of seismic profiles, energy from out-of-the-plane may degrade the stacked images (Wu et al., 1995), moreover, reflections observed in the shot gathers may not necessarily appear on the final stacked sections. To analyze how reflections on the shot gathers correspond to the reflections in the stacked section, and also in order to extract information on the 3D orientation of the more prominent reflections, 3D reflector modeling can be used based on an assumption that reflections are planar and are within a constant velocity medium (e.g., Ayarza et al., 2000; Juhlin and Stephens, 2006; Malehmir et al., 2006).

The modeling is based on calculating traveltimes of the reflector in both shot and stack domains using the true acquisition geometry of the source, receivers (for shot gathers) and CDPs (for the stack). Constant P- and S-velocity and density are assumed for both bedrock and the reflectors. Reflec-tion coefficients are calculated based on the equations published by Aki and Richards (1980). The planar reflector is allowed to dip in any direction by different strike and distance to a reference point, until the calculated trav-

Time slice: 1.6 sec

D1

N

CM

P in

line

1622

1625

7220

7232

CMP crossline

D1

D1

D1

E-W

(km

)

N-S (km)

29

eltimes from the planar reflector match the observed traveltimes in both the shot gather and stacked section (see Ayarza et al., 2000 for details). Figure 3.4 shows an example of fitting traveltimes on both a shot gather and stacked section for reflection C1 of the HR reflection seismic data of the Kristineberg mining area.

Figure 3.4. (a) Modeling example for a shot gather, and (b) the unmigrated stacked section of the HR profile down to 1.5 s. The modeled traveltimes for reflection C1 match the observed traveltimes both in the shot gather and the stacked section.

E2

CDP

W1

R1

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

Time (s)

NS

b

M1

M1

C1

W1

C1

200 400 600 800 10000.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

Tim

e (s

)

shot 351a

300 400 500Receiver location

E2

R1

C1

E2

CDP

W1

R1

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

Time (s)

NS

d

M1

M1

C1

W1

C1

200 400 600 800 10000.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

Tim

e (s

)

shot 351c

300 400 500Receiver location

E2

R1

C1

30

3.5. Migration Migration is a process that transforms an image from data space to model space. During migration dipping reflections move to their true positions in the subsurface and diffractions collapse to a point. Migration, thus, further improves the spatial resolution, especially the horizontal resolution com-pared to that of vertical resolution (Yilmaz, 2001). Actually, the main aim of migration is to make a stacked section more similar to the geological section (Yilmaz, 2001). During the migration process, a dipping reflection moves up-dip and the migrated segment becomes steeper and shorter than that in the unmigrated section (Yilmaz, 2001). Yilmaz (2001) expressed that migra-tion strategies include: • 2D versus 3D migrations; • time versus depth migrations; and • post- versus pre-stack migrations.

Crooked line seismic data challenges 2D pre-stack and post-stack migra-tion algorithms, which are based on a straight line geometry (e.g., Schmelzbach et al., 2007). There are several studies that show how perform-ing a 3D pre- or even occasionally post-stack migration of 2D crooked line data have a good potential to obtain an interpretable 3D image of the subsur-face in comparison to 2D migrations (e.g., Nedimović and West, 2003b; White and Malinowski, 2012). However, the effectiveness of such ap-proaches will vary case-by-case, because they depend on the crooked nature of the acquisition line. In this thesis, 2D post-stack time migration was car-ried out in Paper I, II and III, but in Paper IV, 3D swath processing and also pre-stack time migration was carried out. 3D post-stack migration was also carried out, but did not result in an improved image.

As long as seismic velocity varies with depth, time migration can be suf-ficient, but when there is strong lateral velocity variation (e.g., fracture sys-tem, intrusions, etc.), time migration is not accurate and depth migration should be considered (Yilmaz, 2001). Due to lack of velocity information (e.g., borehole sonic data) and models in the study area, the main focus was given to performing time migration in this study. However, we do not nor-mally expect large lateral velocity variations in the crystalline environment, the velocities are not so variable in the common igneous rocks compared with the wide range in sedimentary rocks (Adam et al., 2003; Juhlin and Stephens, 2006). Therefore, a time migration approach may provide a suffi-ciently good image as compared with the depth migration approach.

3.5.1. Post-stack time migration It has been discussed by Yilmaz (2001) that in the case of structural dips or with the aim of preserving diffractions in the seismic section in an area with small laterally velocity variations, post-stack time migration can be consid-

31

ered. Adam et al. (2003) also suggested that pre-stack DMO along with a post-stack migration algorithm still may be more useful in hardrock data processing and mining applications than pre-stack time or depth migrations. Several studies in different mining camps have shown that diffractions may originate from ore deposits (e.g., Milkereit et al., 1996; Malehmir and Belle-fleur, 2009; Malehmir et al., 2010). This motivated us to use post-stack time migration to preserve diffractions since VMS deposits in the Skellefte dis-trict were one of our main targets (Paper I, II and III).

3.5.2. Pre-stack time migration Pre-stack time migration is usually applicable in the case of conflicting dips of reflections while post-stack time migration cannot handle this situation (Yilmaz, 2001). In Paper IV, a 2D pre-stack time migration was used in order to extract more information from the data and also to compare the results with the 2D post-stack migration. By doing this, a shallow reflection, which was not observed before by 2D post-stack migration was observed. We also performed a 2D post- and pre-stack time migration on synthetic data to compare results against the real data. Processing of the synthetic data showed artifacts were manifested as steeply dipping events and these arti-facts are stronger when the data were processed using post-stack migration than pre-stack migration. It also showed that pre-stack migrated sections contain less details than the post-stack migrated sections.

3.6. Finite-difference (forward) modeling To support interpretation of seismic data, numerical modeling is often used to provide synthetic data for testing processing techniques and acquisition parameters (Keiswetter et al., 1996; Kazemeini, 2009). One of the methods, which has become a very popular tool for seismic applications, is finite-difference forward modeling. In complex geological environments like min-ing areas, forward modeling techniques can be very useful (e.g., Thomas et al., 2000; Cheng et al., 2006) to provide a better understanding of the geo-logical signature of mineral deposits. In the context of hardrock seismic exploration, forward modeling has been used to study the dependence of the seismic response to ore body shapes and composition (e.g., Eaton, 1999; Bohlen et al., 2003; Clarke and Eaton, 2003; Hobbs, 2003). Several authors discussed how finite-difference modeling allows the investigation of wave-mode conversions that may occur at lithological contacts (e.g., Bohlen et al., 2003; Snyder et al., 2009; Malinowski and White, 2011). Bellefleur et al. (2012) also suggested that forward modeling techniques are instrumental when trying to understand the key characteristics of VMS deposits on seis-mic data.

32

Finite-difference modeling is necessary to understand the seismic re-sponse of mineral deposits and to validate geological models against seismic data (Bellefleur et al., 2012). Ideally, finite-difference modeling should be based on accurate and complete petrophysical data and 3D elastic (and may-be even visco-elastic (e.g., Malinowski et al., 2011)) modeling should be applied. However, 2D acoustic and elastic modeling algorithms can be use-ful because of the fast examination of geological models.

In Paper IV, both acoustic and elastic finite-difference modeling were carried out to determine the response of the geological model and validate the interpretation along the HR seismic profile in the Kristineberg mining area. The geological model used for forward modeling was created based on a compilation of geological observations and borehole data constraints from interpretation of the HR seismic profile. Finite-difference algorithms (Pratt and Worthington, 1990; Juhlin, 1995b) were used to generate the synthetic data for both acoustic and elastic modeling. A major step with any forward modeling is how to generate the model that is as close to the geology as pos-sible and prepare it properly for various modeling algorithms. For details about the algorithms, readers are advised to read the cited papers. Figure 3.5 shows an example snapshot of the seismic wavefield from the acoustic mod-eling that indicates that the massive sulfide or high contrast zones should produce strong seismic signal in this area.

33

Figure 3.5. Snapshots of the seismic wavefield from the acoustic modeling for a shot at the center of the model at (a) 300 ms and (b) 600 ms, showing that the mas-sive sulfide or high contrast zones (shown in red color) should produce strong seis-mic signal.

34

4. Summary of papers

This chapter presents a brief summary of the four papers which constitute the main part of my thesis. Each paper is summarized by its objectives, methods, results and conclusions. A statement of my own contribution to each paper is provided here:

Paper I: Besides participating in the seismic data acquisition during Fall 2008 (for four weeks), I mainly processed the seismic data. I carried out the cross-dip analysis and reflector modeling in order to obtain information on the 3D geometry of the reflections. Interpretation of the data was done in collaboration with my co-authors. Main writing was done by me and co-authors helped to improve it by their comments.

Paper II: Besides participating in the fieldwork to acquire three seismic profiles during summer 2009 and 2010, I processed the seismic data. Geo-logical mapping was carried out by Tobias E. Bauer (Luleå University of Technology) and he provided the micro-photographs. Manuscript was writ-ten by me and Tobias E. Bauer had a main responsibility for the geological parts. Interpretation was carried out in close collaboration with Tobias E. Bauer and all co-authors improved the paper with their comments and sug-gestions. 3D modeling figures were also prepared by Tobias E. Bauer.

Paper III: Assisting on re-processing of the previous seismic data from the Kristineberg mining area (Profile 1). Preparing the geological map and 3D visualization with the HR profile and Profile 2 in the Kristineberg min-ing area were carried out by me. I also contributed to the interpretation of the results and their correlation with the new seismic lines (my main focus in this paper).

Paper IV: This study includes: pre-stack migration, 3D swath imaging of the 2D seismic data in the Kristineberg mining area that were done by me. Acoustic seismic modeling was carried out by Alireza Malehmir and elastic modeling was carried out by me and Christopher Juhlin. 3D visualization of the data along the HR profile was performed together with Pietari Skyttä (University of Helsinki). Manuscript was written by me and Pietari Skyttä had a main responsibility for the geological parts. All co-authors improved the quality of the paper by their suggestions and comments.

35

4.1. Paper I: Reflection seismic imaging of the upper crust in the Kristineberg mining area, northern Sweden 4.1.1. Summary As a part of the VINNOVA 3D/4D geological modeling project over the Skellefte district, two new crooked reflection seismic profiles, a N-S di-rected high-resolution one (HR) and an E-W directed one (Profile 2) were acquired in the Kristineberg mining area, western part of the Skellefte dis-trict (see Figure 2.2), in Fall 2008.

The main aims of this study were to: • examine the capability of using high-resolution reflection seismic data to

image the shallower portions of the subsurface for further correlation with the surface geology; and

• validate and refine some of the previous geological interpretations. Earlier seismic lines (Profiles 1 and 5) focused on the deeper parts of the

subsurface and used longer shot and receiver spacing. The total length of the new seismic profiles was about 20 km (6.3 km for the HR profile and 13.7 km for Profile 2). Receiver and source spacing was 10 m for the HR profile and 25 m for Profile 2. An hydraulic hammer, VIBSIST (Cosma and Enescu, 2001), was used to generate the seismic signal. For the recording system, a SERCEL 408UL from the Department of Earth Sciences, Uppsala University was used. Data processing was carried out along a straight CDP line for both profiles using a conventional processing sequence. Refraction statics, choice of temporal filter, and velocity analysis had the greatest influ-ence on the results. DMO corrections allow crossing reflections with differ-ent dips to stack simultaneously (Deregowski, 1986), but it was not possible to obtain a good image for Profile 2 by preforming DMO and it only worked well for the HR dataset. Since major reflections appear at the edge in Profile 2, but believed to be mainly from out-of-the-plane of the profile, we only migrated the HR profile. The best migrated image was obtained using a fi-nite-difference migration algorithm with a constant velocity of 5000 m/s. The processed seismic data imaged a series of steeply dipping to sub-horizontal reflections, some of which reach the surface and allow correlation with surface geology and recent field geological mapping.

3D visualization of the seismic data with location of the Kristineberg ore lenses is shown in Figure 4.1. This shows reflection M1 to be directly asso-ciated with mineralization and seems to generate a diffraction (K1) signal in Profile 2. It is not clear if reflection E1 is directly related to a mineralization zone. However, its strong seismic character describes a high impedance contrast and suggests a suitable target for future deep exploration to a depth about of 2.25 km.

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Figure 4.1. 3D views showing the migrated seismic section along the HR profile and stacked section along Profile 2 (a and b) as well as locations of different ore zones. Projection of the Kristineberg ore body onto the HR profile indicates it to be correlated with reflection package M1 (b). Different colors in solid bodies locally represent different ore lenses in the Kristineberg deposit. Ore body geometries are kindly provided by Boliden Mineral AB.

Cross-dip analysis (described in section 3.3.1 and described in detail by Nedimović and West (2003a)) and reflection modeling (described in section 3.4) were carried out to study the out-of-the-plane nature of some of the reflections and to obtain additional information about their 3D geometry. Reflections were modeled to extract information on their 3D orientation in

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both shot gathers and stacked sections, using the true acquisition geometry (described in section 3.4 of this thesis). The surface projections of some of the steeply dipping reflections onto a combined high-resolution aeromagnet-ic and ground magnetic map and the geological map are shown in Figure 4.2. Figure 4.2 shows that reflection C1 represents a shear zone at the boundary between the Skellefte Group volcanic rocks and the Vargfors Group metasedimentary rocks and reflection R1 appears to correlate well with mafic-ultramafic sheet-like intrusions. We could also obtain the 3D orientation of reflection W1 that was also observed in both previous profiles (Tryggvason et al., 2006). We attributed this reflection to a fault zone within the Viterliden intrusion or internal lithological boundaries in it (see Figure 4.2). Cross-dip analysis could help us to obtain a cross-dip component of 30°-40° to the north for reflection N1 which relates it to the mafic-ultra mafic rocks or the contact between the Skellefte and Vargfors Groups.

4.1.2. Conclusions The new seismic data and results in the Kristineberg area confirmed some of the previous interpretations, but also provided additional and local-scale constraints on the subsurface geology. High-resolution data along the HR profile proved to be successful in imaging reflections potentially associated with mineralization zones, and suggest that the Kristineberg mineralization and associated structures dip to the south down to at least a depth of about 2 km, although this needs further support. The study further illustrates that shorter shot and receiver spacing is required to successfully image the com-plex geological structures of the Kristineberg mining area.

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Figure 4.2. Surface projections of the modeled reflector planes mapped onto (a) the geological map and (b) combined high-resolution aeromagnetic and ground magnet-ic map of the Kristineberg area. Most of the modeled reflections correlate well with magnetic lineaments derived either from lithological boundaries, faults or mafic-ultramafic sill intrusions. Aeromagnetic data are published with kind permission from the Geological Survey of Sweden and the ground magnetic measurements are kindly provided by Boliden Mineral AB.

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4.2. Paper II: Crustal geometry of the central Skellefte district, northern Sweden – constraints from reflection seismic investigations 4.2.1. Summary In the continuation of the VINNOVA 3D/4D geological modeling project, three new sub-parallel reflection seismic profiles were acquired in the cen-tral Skellefte district during summer 2009 and 2010 (Figure 2.3).

The aims of this study were to: • image regional-scale structures down to a depth of about 5 km and their

correlation with surface geological studies; and • to provide a base for 3D/4D modeling in the central part of the district.

Three profiles (Profiles C1, C2 and C3, see Figure 2.3) were acquired with a length of about 30 km for each. Shot spacing and receiver spacing was about 25 m except in places where profiles cross the Skellefte river or where due to road inaccessibility it was not possible to have a regular shot spacing. For the data acquisition and generating seismic signal, we used the same system that was used in the Kristineberg mining area (VIBSIST and a SERCEL 408UL, but with more channels, up to 400). For processing, we chose a straight CDP line for Profiles C1 and C2, and a slalom CDP line for Profile C3 using 12.5 m wide bins for stacking. Refraction statics, deconvo-lution, choice of temporal filter and velocity analysis were again major pro-cessing steps which had the greatest influence on the results. Implementation of DMO corrections also failed for these datasets, attributed to the irregular shot spacing as well as irregular offset distribution in the data (Deregowski, 1986). For the migration, we used a phase-shift migration algorithm with a constant velocity of 5800 m/s, except for Profile C1, where a finite-difference migration algorithm with a constant velocity of 5600 m/s gave the best result.

In general, all these three seismic profiles resulted in imaging gently to steeply dipping and sub-horizontal reflections as well as diffraction packages (D1-D4 in Figure 4.3a). Reflections and diffractions are interpreted to be from major faults and shear zones and/or represent lithological contacts. Figure 4.3 shows a portion of the stacked section and migrated one along Profile C3. A comparison between the stacked and migrated sections along this portion suggests that diffractions D1-D4 are generated at the edge of a series of faults at the contact between metasedimentary rocks and their un-derlying Skellefte Group metavolcanic rocks (e.g., D1 and D2) or may rep-resent lithological contacts within the Skellefte Group or the contact be-tween the Skellefte Group rocks and their unknown basement (e.g., D3 and D4).

40

Figure 4.3. (a) A portion of the stacked section along Profile C3, where the profile passes the Maurliden deposit, and (b) the migrated section along the same portion of the Profile C3 (b). Note that surface geology is shown on top is along the acquisition line.

Since there are sharp changes in the geometry of the acquisition lines (Fig-ure 2.3), we decided to analyze the cross-dip component of the main reflec-tions. Figure 4.4 shows an example of the effect of the cross-dip correction

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41

for reflection R1 that was observed in the southern portion of both Profiles C1 and C3, suggesting that reflection R1 has a cross-dip component of 15°-20° to the east. Another example of the cross-dip correction has already been shown in Figure 3.2.

Figure 4.4. (a) Stacked section along a portion of Profile C1, and (b) cross-dip cor-rected section of the same portion as (a) using a cross-dip component of 15° to the east using a stacking velocity of 5500 m/s. (c) Stacked section along a portion of Profile C3 and (d) cross-dip corrected section of the same portion as (c) using a cross-dip component of 20° to the east using a stacking velocity of 6000 m/s. Note reflection R1 is imaged longer and stronger in (b) and (d).

Reflection seismic modeling was carried out to obtain the orientation of the major reflections. This modeling helped us to better interpret and correlate the reflections from one profile to another one. A 3D visualization of the seismic data and comparison with surface geological observation was per-formed (Figure 4.5). This shows most of these reflections correlate with surface geological observations, and most extend to the surface, correlate well with geological features either observed in the field or interpreted from the aeromagnetic map of the study area. For example, we suggest that reflec-tion R1 to be from a shear zone separating meta-sedimentary rocks to the south from meta-volcanic rocks to the north.

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Figure 4.5. 3D visualization of the three seismic profiles in the central Skellefte district and their correlation with surface geology. Majority of reflections are mod-eled to be from shear zones, most of which dip to the south.

4.2.2. Conclusions The three seismic profiles in the central Skellefte helped us to better under-stand the geological structures and shear zones at depth. We could correlate the main reflections and diffractions with the major faults and shear zones and/or lithological contacts. Results of these three seismic profiles provided constraints for the construction of the first large-scale 3D geological model of the central Skellefte ore district to about 5 km depth. Further study and data are required to determine the origin of the observed reflection in Figure

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3.2b. It is generated from the top of the Skellefte Group rocks, lithological contacts within the volcanic succession, partly from unknown basement to the Skellefte Group rocks or from some other feature. Seismic data at the Maurliden deposit area show a number of interesting features, thus, a couple of seismic profiles perpendicular to Profile C3 would allow a better and more constrained interpretation of them.

4.3. Paper III: Re-processing and interpretation of 2D seismic data from the Kristineberg mining area, northern Sweden 4.3.1. Summary In this study, one of the previous seismic profiles from the 3D pilot geologi-cal modeling study (Tryggvason et al., 2006; Malehmir et al., 2007) in the Kristineberg mining area (Profile 1, see Figure 4.2) was re-processed and re-interpreted.

The aims of this paper were to: • improve the seismic near the mine; and • correlate the re-processing results with the data along the HR profile.

The crooked line acquisition geometry, low fold coverage, complex geol-ogy and sparse outcrops in the area, made the data re-processing and re-interpretation challenging. Re-processing of the seismic profile was per-formed by focusing on important processing steps crucial for the crystalline environment. In particular, refraction static corrections and data filtering combined with a good estimation of stacking velocities were important steps in improving the seismic results. Figure 4.6 shows a portion of the unmigrat-ed stacked data near the Kristineberg mine from the previous work and the re-processed one. This comparison demonstrates that the re-processed seis-mic section is significantly improved with more reflections observed at both shallow and deep levels; also in terms of event continuity and resolution. The re-processed seismic section shows higher frequency content than the previous seismic section. After testing various migration algorithms, Stolt migration with a constant velocity of 6000 m/s was used and preserved the steeply dipping reflections while produced less migration artifacts.

Cross-dip analysis (Nedimović and West, 2003a) also was carried out to obtain additional information about the main reflections. The analysis sug-gests a cross-dip component of 55° to the west for the main reflections in the central portion of the line which is consistent with the geological observa-tions that most geological structures plunge to the west at this location.

Figure 4.7 shows 3D visualization of the re-processed seismic data with the recent seismic profiles in the area. With this visualization, we better cor-related the new observed reflections with the results of the recent seismic

44

profiles in the area. The majority of the reflections are interpreted to origi-nate from fault zones and in some cases lithological contacts. We can see that reflection K1 is likely in direct association with the main Kristineberg mineralization.

Figure 4.6. A portion of (a) the previous and (b) re-processed unmigrated stacked section. Both sections are comparable for strong reflections; improvements (black arrows) in seismic reflections can be noticed at all levels (b) with relatively higher frequency content (modified from Ehsan et al., 2012).

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Figure 4.7. 3D views (a and b) showing visualization of the re-processed migrated seismic section of Profile 1 with the HR profile, Profile 2 (unmigrated section) as well as mineralization surfaces from borehole data in the Kristineberg mine. Reflec-tion K1 clearly correlates with the location of the mineralization horizon (dark blue, green and light blue). Reflections M1 and E1 correlate well on both Profile 1 and the HR profile. Blue surfaces in the western side of the 3D view (b) are Rävliden mas-sive sulfide deposits. The depth of the seismic profiles is 3800 m. No vertical exag-geration. Ore body shapes are kindly provided by Boliden Mineral AB (modified after Ehsan et al., 2012).

Comparison of the re-processed results with the newly acquired seismic data, earlier potential field modeling results and geological observations from the area helped to better explain the structural complexity of the Kris-

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tineberg mining area with the aid of a rift model and a sequences of com-pressions and oblique slip movements using the simple sketch shown in Figure 4.8. During volcanic activity (Figure 4.8a) a large number of normal faults, were generated. North-south and east-west compressional regimes reactivated these major faults (Figure 4.8b), but in a reverse movement and also generated new ones along weak structural and contact lithologies (Skyt-tä et al., 2010). Local basin inversion is also expected during this episode (Bauer et al., 2011). The Revsund granite (post-tectonic), the youngest intru-sion in the area, cross-cut major structures in the study area (Figure 4.8c).

4.3.2. Conclusions Seismic data re-processing of the Kristineberg seismic profile (Profile 1) was performed with a special focus on the data near the mine and on the processing steps crucial for data acquired in the crystalline environment. It showed that with careful attention to refraction static corrections as well as retaining useful high frequencies in the data, it is even possible to obtain a reasonably good seismic image of subsurface structures from low fold seis-mic data (about 17). Combined with the newer seismic data more infor-mation about large-scale geological structures was obtained. This can be helpful for exploration in the area or at least to help better understand the tectonic evolution of the study area.

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Figure 4.8. A simplified geological model across the Kristineberg area (modified after Skyttä et al., 2011), showing (a) syn-extensional volcanism (e.g., Skellefte volcanic rocks), mineralization, sedimentation and intrusive activity (e.g., Viterliden intrusion), (b) subsequent crustal shortening leading to basin inversion (Bauer et al., 2011) and related transposition of the mineralized horizons. (c) Post-tectonic Revsund type granite intruded at about 1.8 Ga and cross-cut major geological struc-tures. K1, K2, and E1 schematically represent reflections from the re-processed migrated seismic section (from Ehsan et al., 2012).

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4.4. Paper IV: 3D constraints and finite difference modeling of massive sulfide deposits: The Kristineberg seismic lines revisited, northern Sweden 4.4.1. Summary In this study we carried out pre-stack time migration, swath 3D imaging of the 2D crooked line and generated synthetic seismic data using both acoustic and elastic finite difference algorithms for the Kristineberg data.

The aims of this study were to: • provide further insight about the nature of the main reflections; • provide 3D geometrical information on a reflection observed in the

western part of Kristineberg; and • better understand processing challenges in the Kristineberg mining area.

Petrophysical measurements carried out by Malehmir et al. (2006 and 2013) indicate that the massive sulfide samples have large grain size varia-tions and densities as high as 4300 kg/m3, but most show low P- and S-wave velocities. Still, due to their high density, we expect that they can produce strong seismic signal. However, this depends on the S/N, the orientation of seismic lines with respect to the dominant dip, good ground coupling, and the degree of signal distortions through the near surface. Results of the measurements are summarized in Table 4.1, and this was used for the finite difference seismic modeling.

Table 4.1. Compilation of physical property measurements in the Kristineberg area (Malehmir et al., 2006 and 2013). Reflection coefficient (R) is calculated for the P-waves and is relative to a background velocity of 5750 m/s and density of 2700 kg/m3. Superscript numbers are referred to the legend of Figure 4.9.

Rock type Density (kg/m3) VP (m/s) VS (m/s) R

Granodiorite1 2850 5500 0.0048

Gabbro2 2900-3000 6250 3500 0.0858

Altered volcanics3 2800 5650 2600 0.0094

Massive sulfide4 4300 5000 2800 0.1614

Alteration zone5 2850 4800 2850 -0.0632

Volcanics6 2750 5800 3150 0.0135

Metasediments7 2650 5750 3150 -0.0093

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Based on the results from the post-stack migration of the HR profile in the Kristineberg area, a constrained geological cross-section was constructed using seismic results from the HR profile, borehole data from the mine, as

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well as surface and ground geological observations (Figure 4.9; D. Coller, personal communication, 2011).

Figure 4.9. (a) Post-stack migrated seismic section along the HR profile, and (b) interpreted geological cross-section along the HR profile. A constant velocity of 5800 m/s was used for the time-to-depth conversion. The numbers shown in the geological legend are related to physical properties listed in Table 4.1.

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Figure 4.9 shows that the Kristineberg ore laterally projects to a highly re-flective zone (M1) that dips towards the south and may flatten out at a depth of about 2.2−2.5 km. Two sets of flat-lying reflectors at these depths (E1 and E2) are considered to be important geological targets for future deep explo-ration. The geological cross-section shows that the reflective zones, possibly indicative of mineralization, occur predominantly within the felsic volcanic rocks. Figure 4.9b and its interpretation was used further to study the seismic response of the massive sulfide ore bodies and their host rock structures using finite difference seismic modeling methods.

Re-processing of the HR profile near the Kristineberg mine was done us-ing a pre-stack time migration algorithm. A pre-stack Kirchhoff time-migration algorithm operating in the common-offset-domain was used. Since no sonic log information is available, it was not possible to build a constrained velocity model for the migration. However, large, long wave-length velocity changes are not expected in this crystalline environment in comparison with sedimentary environments (Adam et al., 2003; Juhlin and Stephens, 2006). Thus, our approach in this work was to use constant migra-tion-velocity stacks and inspect visually the quality of the obtained migrated stacked sections. We ran a series of pre-stack time migration tests using velocities ranging from 5500 m/s to 6500 m/s with 100 m/s increments. The best results were obtained using a velocity of 5800 m/s. Figure 4.10a and 4.10b show a comparison between post-stack and pre-stack migrations along the HR profile. We could image a high-amplitude gently dipping reflection (S1) that was not observed before and this is now presented within the main reflective zone above the ore horizon (Figure 4.10b). This processing result-ed in a migrated section that appeared to contain less artifacts, but also showed less detail than the post-stack migrated section (Figure 4.10a and 4.10b).

2D acoustic and elastic finite difference modeling along the HR profile was carried out to compare the results of post-stack and pre-stack migrations and also to support our interpretation of the seismic data (Figure 4.10c, 4.10d, 4.10e and 4.10f). Processing of the synthetic data suggest that pro-cessing artifacts are present that manifest themselves as steeply dipping events. These artifacts are stronger when the data are processed using post-stack migration methods but reduced with the application of pre-stack mi-gration (Figure 4.10c and 4.10e). Steeply dipping structures are not imaged clearly on the synthetic data, note that reflection C1 is only observed in the post-stack migrated section and C1 at a depth below 3000 m is a processing artifact as it is demonstrated from the post-stack migration of the synthetic data.

In order to provide 3D geometrical information on a shallow flat-lying re-flection (L1), observed west of the Kristineberg mine on both previous and new seismic data (Profiles 5 and 2 see in Figure 2.2 for the location of the profiles, stacked sections are shown in Figure 4.11a and 4.11b), we com-

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bined data from the two crossing profiles where the reflection was observed and then we processed the data in 3D (see box in Figure 2.2 showing the location of the 3D swath imaging). The observed reflection has a dip com-ponent to the southwest and this is noticeable on crossline 1040 (Figure 4.11c). We suggested that this reflection correlates with the contact of the metasedimentary and metavolcanic rocks and has a dip of about 30°. The dip is calculated based on the apparent dip observed on the stacked section for a given velocity of 5750 m/s (see Stolt, 1978). Later Boliden Mineral AB con-firmed these dips from borehole data in the area, making the reflecting hori-zon on ideal candidate for further study.

4.4.2. Conclusions Pre-stack migration allowed imaging a reflection (S1) that was not observed from the previous processing results and we suggest this reflection to be an important target for future mineral exploration in the study area. Processing of the synthetic data suggests that processing artifacts are present that mani-fest themselves as steeply dipping events. Using pre-stack migration for the HR profile resulted in a section containing less artifacts, but also showed less detail than the post-stack migration. These artifacts are stronger when the data are processed using post-stack migration methods but reduced with the application of pre-stack migration. The 3D swath processing also was useful to define an attitude of the contact between the metasedimentary and metavolcanic rocks, and indicating an approximately 30° southwestly dip. This contact also is an important target for further mineral exploration in the area.

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Figure 4.10. Comparison between post-stack migrated sections (a, c and e) and pre-stack time migrated sections (b, d and f), for (a) real data along the HR profile, (c) synthetic acoustic data, and (e) synthetic elastic data, suggesting a good correspond-ence between the real data and the synthetic migrated sections. M1 represents a highly reflective south-dipping zone where major VMS deposits occur. E1 and E2 are two sets of strong reflections observed in the real data. S1 is only observed in the pre-stack migrated section of the real data (b). Steeply dipping structures are not imaged clearly on the synthetic data, note that reflection C1 is only observed in the post-stack migrated section and C1 at a depth below 3000 m is a processing artifact as is demonstrated from the post-stack migration of the synthetic data. A constant velocity of 5800 m/s was used for the time-to-depth conversion (based on Dehghan-nejad et al., 2012).

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Figure 4.11. (a) A portion of the stacked section along Profile 2 and (b) Profile 5, showing a flat-lying reflection (L1) marked by arrow at about 450 ms observed in both profiles. (c) The 3D view of an inline and a crossline extracted from the stacked seismic volume, demonstrating that the reflection L1 dips about 30° towards the southwest.

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5. Conclusions

The 2D crooked line reflection seismic data acquired over the crystalline environment present challenges and opportunities. Results from these data sets clearly demonstrate that reflection seismic data can be of great value to the mining industry for precise targeting of extensions of existing deposits and mapping new potential targets. 3D integration of seismic results with verified geological observations and other geophysical results show an im-portant interdisciplinary approach in the district.

These 2D crooked line reflection seismic data clearly allowed imaging of diffractions, sub-horizontal to steeply dipping reflections related to lithologi-cal structures, shear zones and potentially mineralized zones.

In Paper I, results along the seismic profiles in the Kristineberg mining area allowed imaging of reflections associated with mineralized zones or structures in the area, and one could note that the Kristineberg mineraliza-tion and associated structures dip to the south down to at least a depth of about 2 km. The high-resolution seismic data in the area showed much more detailed structures and provided local-scale constraints on the subsurface geology than the seismic data from the pilot studies.

In Paper II, results from the three seismic profiles in the central Skellefte district showed a different seismic character compared with those from the Kristineberg mining area, and in conjunction with detailed geological obser-vations, led us to correlate main reflections and diffractions with major faults and shear zones in the area. These results provided constraints for the construction of the first large-scale 3D geological model of the central Skel-lefte ore district to about 5 km depth.

In Paper III, results of the re-processing of a seismic profile from the pilot study demonstrated how further improvements were possible by giving es-pecial attention to some of the processing steps. Refraction static corrections as well as retaining useful high frequencies in the data helped to obtain an improved seismic image of subsurface structures from low fold seismic data, providing more information about large-scale geological structures. Results of the re-processed line had higher quality and together with the high-resolution line (HR) allowed better quality interpretations.

In Paper IV, pre-stack migration allowed imaging a reflection that was not observed from the previous processing results near the Kristineberg mine and suggested this reflection to be an important target for future mineral exploration in the study area. Finite-difference modeling was helpful to de-

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termine the response of the geological model and validate the interpretations along the seismic profile in the Kristineberg mining area. Processing results of the synthetic data compared to the real data suggested that pre-stack mi-grated sections contain less artifacts, but also show less detail than the post-stack migrated sections. These artifacts that manifested themselves as steep-ly dipping events were stronger when the data were processed using post-stack migration methods compared with pre-stack migration methods.

Cross-dip analysis, reflection modeling, swath 3D processing allowed the 3D geometry of some of the observed reflections to be obtained and it is suggested that these be carried out as routine processing and analysis ap-proaches for the 2D crooked line reflection seismic data.

At the end, I would like to highlight a few lessons that can be helpful for future studies: • Shorter shot and receiver spacing was required to successfully image the

complex geological structures of the district; • While acquiring 2D crooked reflection seismic data, extra shots on ei-

ther or both sides or parallel roads would not only increase the seismic fold but also allow increased midpoint coverage and these would then be helpful to extract 3D information from the semi-3D data;

• Accurate 3D forward modeling using finite-difference modeling algo-rithm and a physical property database would help to better understand the seismic response of ore deposits and to validate geological models;

• Use of multicomponent sensors could be useful to be tested in the future to constrain seismic interpretations and may allow the prediction of composition and information about anisotropic structures;

• A significant effort could be made to produce high-quality true-amplitude sections (amplitude versus offset (AVO) analysis). This is, however, a significant challenge in hardrock areas characterized with low S/N and discontinuous reflections that are difficult to image without the application of pre-stack automatic gain control to partly balance the amplitudes;

• Downhole seismic studies can be useful for suitable exploration targets; • 3D seismic surveys following the 2D studies can increase the accuracy

of structural images of the subsurface, and also can provide stratigraphic information that is not present in 2D seismic data. A detailed deep ex-ploration-drilling program should only be considered after the imple-mentation of 3D surveys.

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6. Summary in Swedish

Skelleftefältet i norra Sverige har tolkats som en paleoproterozoisk vul-kanbåge. Det är ett av de viktigaste malmdistrikten i Sverige och malmkropparna är av typen Vulkaniska Massiva Sulfider (VMS) och pro-ducerar i huvudsak basmetaller, men även guld och silver. Prospektering och brytning av mineralresurser flyttas mot större djup på grund av svårigheten i att finna ytnära malmkroppar, men också tack vare de höga metallpriserna. Därför är det viktigt att bättre förstå de tredimensionella geologiska struktur-erna ner till några kilometers djup. En sådan tredimensionell förståelse av berggrunden är viktig för att hitta fler malmkroppar samt för att planera framtida gruvdrift.

Efter ett lyckat pilotprojekt med 3D geologisk modellering i de västra delarna av skelleftefältet (omkring Kristineberg gruvan) lanserades 2008 ett nytt projekt ”VINNOVA 4D modeling of the Skellefte district” i syfte att förbättra existerande geologiska modeller på grunda djup, samt utöka model-len mot de centrala delarna. Mer än 100 km (krokiga) reflektionsseimiska profiler mättes in, bearbetades och tolkades integrerat med geologiska ob-servationer och potentialfältsdata. Resultaten användes för att förbättra ex-isterande 3D geologiska modeller, men gav även ny information om geologi och potentiella malmfyndigheter på större djup.

Två nya (i de närmaste vinkelräta) profiler i Kristineberg området förbät-trade den existerande lokala geologiska modellen jämfört med modellen från pilotprojektet och visade även på förmågan att lokalisera starkt mineral-iserade zoner med reflektionsseismik i området. Den mineraliserade zonen i Kristineberg samt strukturer associerade med denna stupar mot syd ner till ett djup av ungefär två kilometer. I de centrala delarna av Skelleftefältet visade tre (nästan parallella) profiler en annan seismisk karaktär jämfört med seismiskt data från Kristineberg området. De starkaste reflektionerna och diffraktionerna kunde korreleras med förkastningar och skjuvzoner i om-rådet. Dessa resultat kunde användas för att konstruera en första 3D geolo-gisk modell över de centrala delarna av Skelleftefältet ner till ett djup av ungefär fem kilometer. Tolkning av observerade reflektioner och svårigheter med standard seismisk processering förbättrades och förenklades med hjälp av användandet av Cross-dip analysering, reflektions modellering, pre-stack tidsmigrering, swath 3D processering samt Finit-differens seismisk model-lering. Även om 3D seismiska data är oftast att föredra för att uppnå en pre-cis lokalisering av potentiella mål för exploatering i gruvdistrikt, visar re-

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sultaten från denna avhandling att även 2D seismiska profiler kan ge mycket värdefull information i gruvdistrikt, särskilt då resultaten kan verifieras med geologiska observationer och andra geofysiska data.

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Acknowledgments

One of the many joys of this completion is to look back at the route and remember all the people who helped and supported me along this long but fulfilling road. I take this opportunity to express my sincere appreciation and gratitude to many of those who helped me finish this research project.

Foremost, I would like to express my sincere gratitude to my supervisor Christopher Juhlin. Chris: I met you in the Oskarshamn seismic fieldwork for the first time (my first practical fieldwork in the seismic group, April 2004) and my motivation to study for a PhD in Geophysics started there. I told myself, if I am going to do a PhD, I would want to have a supervisor like you. Thanks so much for having me accepted in the Geophysics group as your PhD student. I like your socializing and communications with your students, I had a comfortable time during my PhD, and I could express my opinions to you. I would like to thank you for allowing me to follow Alireza to Canada in the beginning of my study. During that time, you were in con-tact with me all the time and answered my questions quickly. I would like to thank you for all the time that you spent guiding me through seismic pro-cessing, modeling, reviewing my papers, and the thesis. Thank you for all your guidance, motivation, patience and support during this time. I also thank you for giving me opportunities to see nice cities and meet seismic experts by sending me to the conferences. I want to also thank you and your family for all your kindness and friendship since we moved to Sweden. Thank you very much!

Special thanks go to Hans Palm for all the practical lecturing on reflection seismic data acquisition. Hasse: I learned a lot from you during many differ-ent fieldworks not only throughout my PhD time, also before that. Your support made me brave enough to go forward. You guided me not only through seismic surveys, but also my life, cooking, Swedish and driving.

I would like to thank my co-supervisor, Ari Tryggvason, and my earlier co-supervisor Laust B. Pedersen. Ari: thank you for your friendship and help since we moved to Sweden. I never forget your kindness, thank you!

I would like to thank my former colleagues, Artem Kashubin, for teach-ing me how to operate the ‘White House’. Artem: you gave me confidence to operate the ‘White House’ and also drive it. I wish you and your family all the best wherever you are.

I would like to thank my former officemates, Swasdee Yordkayhun and María García. María: we shared lots of time together not only because we

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were office- or projectmates, but also because you were a nice friend to me. Thank you for all your kindness and help from Matlab debugging to arrang-ing my home’s curtains!

I would like to thank Emil Lundberg. Emil: I spent a lot of time with you during fieldwork and conferences. Thanks for all your help from seismic processing to Swedish. Thanks also for the nice foods; your cooking in the field was always excellent. I want to especially thank you for taking care of the Swedish summary of this thesis.

VINNOVA, Boliden Mineral AB and Lundin mining are thanked for funding my research project. I would also like to thank all the VINNOVA 4D project members for their great discussion and collaborations, especially Pietari Skyttä and Tobias Bauer. Thank you very much!

I would like to thank Alireza, Chris, Tobias B., Bjarne and Omid for re-viewing this thesis and their comments.

I am grateful to Taher Mazloomian and his family, Faramarz Nil-fouroushan and his wife, Tabasom, Mehrdad Bastani and his wife, Fariba, Elnaz Sherafat and her husband, Hossein, for their friendship, kindness, support and help since we moved to Sweden. Thank you very much!

I would like to thank Reza Younesi and his wife, Sahar (Fatemeh Sharifi) for their friendship and kindness to my family and me. I will never be tired of being with you and I wish you all the best and thank you!

I take the opportunity to thank all my Iranian and International friends that helped my family and me during my PhD time.

At Uppsala University, the academic and support staffs from the Depart-ment of Earth Sciences are acknowledged for their support and help. All my colleagues, former and present PhD students are thanked for a great time during these years. I spent many hours with you during coffee breaks, lunch times, parties, conferences and fieldtrips. I will not try to write down a full list of names, since I do not want to miss anybody. A big ''Thank you'' to all of you.

My families, including my in-laws, have always supported me throughout my PhD time and I really appreciate it. I would like to thank my family for accompanying me during many of my fieldworks and taking care of Armita. I am so lucky to have your support whenever and wherever needed!

I want to thank my lovely daughters, Armita and Camelia. I am greatly indebted to Armita for company during fieldworks, conferences and be pa-tient during my absence, and the times that I could have spent with her, but I spent on my own work. Thank you my dear Armita!

My deepest gratitude and love belong to Alireza, whose support, patience and guidance were with me in all these years. Your support and encourage-ment were in the end what made this dissertation possible. There are not enough words to thank you and I do not know many, but: Thank you.

Azita (Mahdieh) Dehghannejad, March, 2014

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