A 3 - D, P-wave Velocity Model o f Scandinavia n Crust Mohammad Raeesi and Jens Havskov

1. A 3-D, P-wave Velocity Model of ScandinavianCrust Mohammad Raeesi and Jens Havskov

2. IFJF: # Read the question that we are going to address its answer is: ...... # Why we give more weight to crust in mislocation is due to its heterogeniety. Purpose of work: • Build a 3 D velocity model to reduce bias in earthquake locations • Use 3D- model as a starting model for tomographic inversion 2

3. Seismicity of Scandinavia • Period: 1985-2002 • Magnitude > 2.5 • Number : 4464 Topography & Bathymetry map of Scandinavia IFJF: # In th estudy region there are lots of seismic activity epecially in western parts which coincides with mid-oceanic ridge. ________________________________________ # surprisingly the study area includes all 3 types of crusts. In another word we have a variation in thickness of heterogenious part, from less than 10 km to more than 50 km. # In addition existence of fracture zones adds the complexity of problem. For example recordings of seismic stations in Jan-Mayen Island cannot be analysed simultaneously with recordings of other stations in Norway. 3

4. IFJF: # Despite what I mentioned earlier, we tried to use forward method because of these reasons. # There have been lots of small-scale but detailed studies in Scandinavia, which most of them are source controlled. Seismic velocity sections of these studies should not be abondened. # There is a Moho-depth map for part of Scandinavia. Later on, during the explanation of the method that we have appied, the importance of Moho-depth would be reavealed. # The mentiond seismic velocity data are mostly have very good depth resolutions (in some cases less than half a kilometer), while the best resolved tomographic studies in regional scale which is carried out in Japan has depth resolution of 10 km which is equivalent to Crust thickness in some parts of the model that we are going to make. # So, the decision to use forward method is not illogical. Why did we build a model from existing data? • Availablity of high-resolution seismic velocity sections in Scandinavia • Availablity of the Moho-depth map of part of Scandinavia 4

5. + Depth < 5 km + 5 km < Depth < 10 km + 10 km < Depth < 15 km + 15 km < Depth < 20 km + Depth > 20 km IFJF: # The velocity data that we are talking about have been taken from different sources. # Geological survey of Canada has assembled some of data for Arctic region on a website called Arctic Refraction catalogue. # The crosses are data taken from that website. Depth of penteration of these sections are variable. Which are mostly penetrate to less than 5 kms, and in some cases they go deeper than 30 km. # The qualityof the data varies from those recorded in the 1960's, where seismic profiles were often run with only a few shots and receivers, to those recorded in 1990's, where seismic surveys were carried out with thousand of shots to multiple ocean bottom seismometers. # Totally, a subset of 550 velocity sections out of the catalogue was selected. Velocity Data From Arctic Refraction Catalogue(The Geological Survey of Canada) 5

6. IFJF: # These surveys were carried out by various institutions, and as you see university of Bergen also is one of them. I was surprised that I could not find data here in the institute but I found it there. Contibuters to Arctic Refraction Catalogue • University of Oslo, Norway • University of Bergen, Norway • Norwegian Petroleum Directorate, Norway • Centre Oceanologique de Bretagne, France • Bundesanstalt für Geowissenschaften und Rohstoffe, Hanover, Germany • Elf Aquitane, France; IG, Hamberg, Germany • GEOMAR, Kiel, Germany • Alfred Wegener Institute, Bremerhaven, Germany • Shirshov Institute of Oceanology, Russian Academy of Sciences, Russia • Institute of Physics of the Earth, Russian Academy of Sciences, Russia • Ministry of Geology of the ex-USSR. • Lamont-Doherty Geological Observatory, America • U.S. Naval Oceanographic Office, America 6

7.  Receiver Function for Seismic Stations in Norway  8A-96  BALTIC  EUROBRIDGE  BABEL  MONA LISA  CABLES  UIB IFJF: # Scandinavia and North-western Russia have been covered with a network of Deep Seismic Sounding(DSS) profile observations crossing the region in different directions. Those parts of some of the profiles that locate in the study region were used in this study. # These profiles include Monalisa, Babel, Eurobrdge, Baltic, and Cables. # The dark purple triangles show the location of some of seismic stations that were used in a receiver function study. # These DSS data are much more reliable in comparison with those we had in Arctic Refraction Catalogue (crosses), since they are mostly done in 90s and their depth of penetration covers the lower bounds of the model that we are going to make. Velocity Data From Deep Seismic Sounding Profiles 7

8. IFJF: # The most complete Moho-depth map for Fennoscandia is prepared by Kink and others in 1993. Their map does not cover whole area that is shown below. For the vacant regions supplimentary moho depths were taken from a website of Geological department of Coronell university. Thes eregions are ...... # As you see the Moho-depth map does not cover whole region and since Moho-depth is a key player in the method (we will see later), we had to truncate the velocity model to borders of the Moho map. Moho Depth (elevation) Map of Scandinaviacompiled from combining Kinck et al. (1993) and Barazangi (1993) 8

9. IFJF: # Read: Now we come to this question: ... # Making background velocities and also using the Moho surface as a boundary layer with constant velocities just above and just below for regions that no velocity is available was the solution that we used. # These two inturn push us to divide the study region into smaller regions in order to have firstly more relighable background velocity for every smaller region(from now on we call it a velocity zone) and secondly to reduce the error of the assumption that velocity about the moho is constant. # In fact this assumption is not far from reality. For about 250 samples of velocity about the moho in Scandinavia we found 7,16 with variances of ,14 and 8,12 with ,03 for just above and just below moho respectively. How can we use these scattered and sparse velocity data for the regions that no velocity data is available? • Makeing background velocities • Using Moho surface property • Dividing the study region into smaller zones from velocity point of view. 9

10. IFJF: # Now we should divide the study region to zones from velocity point of view. # The philosophy behind zoning process is finding similar velocity regions. Of course to some degree! # These are the criteria which were used in this regard. # We found that bulk physically related properties like Gravity (explicitly Bouger gravity) and age could be very useful. # Geology and Morphology to a less extent were used. Criteria for zoning process: • Gravity • Age (ocean bottom age and continental crust age), • Geology (inclusively tectonic province) • Morphology and structure (specifically the fracture zones) 10

11. IFJF: # The tools that we have for zoning: # this simplified gelogical map Simplified Geological Map of Fennoscandiahttp://www.geofys.uu.se/eprobe/Projects/svekal/Fig5_1.gif 11

12. IFJF: # also this gelogical map based on age. # Please note here the age differences of 400 My and 14 handered to 18 hundered in this small map Generalized Geological Map of Fennoscandia based onAge determination byRb-Sr and U-PbWilson and Nicholson (1973) 12

13. ____ Zone Boundary ____ 3-D Velocity Model Bondary III Zone Label IFJF: # Muller and others in 1997 made digital age grid map of ocean basins for the entire globe. # Since some parts of the study region locate in Oceanic part, we used the age map for dividing it into. ____________________________________ # zones I,V, X, and XII comprise the transition zones. # The other zones are divided using other criteria. Digital Age Grid Map of Ocean Basins(Müller et al., 1997) 13

14. ____ Zone Boundary ____ 3-D Velocity Model Bondary III Zone Label IFJF: # The south-western part has low resolution. As you see. ______________________________________ # Depite not being the main measure for dividing the oceanic part we see good matches. # A combination of geology and Bouger anomaly was considered for dividing the continental parts. Bouguer Gravity Anomaly Map of ScandinaviaAsbjoern and Dag Solheim (personal comunication) 14

15. ____ Zone Boundary ____ 3-D Velocity Model Bondary III Zone Label IFJF: # Free air anomaly map did not show to be good measure for dividing the zones, and it was almost useless. Free Air Gravity Anomaly Map of Scandinavia 15

16. Gridding the Moho-depth Discontinuity to gradient conversion Background velocity computation Velocity section extension Model parameterization Velocity computation for all nodes of the model Derivatives of the velocity at all nodes IFJF: # Once the zonesl were established we can follow rest of job in an automated way. In another words the zoning process is a subjective matter. # These seven steps should be carried out for fullfilment of the job. Automated Steps of Model Generation 16

17. Gridding the Moho-depth Discontinuity to gradient conversion Background velocity computation Velocity section extension Model parameterization Velocity computation for all nodes of the model Derivatives of the velocity at all nodes IFJF: # Using a 2-D interpolator the sparse data of Moho-depth would be converted to a regular grid. Automated Steps of Model Generation 17

18. Gridding the Moho-depth Discontinuity to gradient conversion Background velocity computation Velocity section extension Model parameterization Velocity computation for all nodes of the model Derivatives of the velocity at all nodes Original discontinuous section Reconstructed gradient section IFJF: # Since in grid or gradient method no discontinuity is allowed we should change all velocity discontinuities to sharp gradients. # The green lines is the original section, and the red one is the the same after converting to gradient. This process may be reapeated several times to get an apropriate gradient. Automated Steps of Model Generation 18

19. Gridding the Moho-depth Discontinuity to gradient conversion Background velocity computation Velocity section extension Model parameterization Velocity computation for all nodes of the model Derivatives of the velocity at all nodes d’1 = d1M2  M1 d’2 = { (d2 - M1) (D - M2)  (D - M1) } + M2 IFJF: # Background velocity (normalized to Moho depth) for each velocity zone should be found. # For each point of background velocity section we find the velocity by avaraging the points of all sections in a zone that locate at the same normalized dapth. # This means that if we consider these two sections, with some simple geometry point A’ would be correspondent to A, and B’ correspond to B. # To make it easy in the normalized model the Moho would be a horizontal layer and correspondent points also locate in the same horizon. Automated Steps of Model Generation 19

20. Gridding the Moho-depth Discontinuity to gradient conversion Background velocity computation Velocity section extension Model parameterization Velocity computation for all nodes of the model Derivatives of the velocity at all nodes IFJF: # The background velocity for the zones that locate in the model region are shown in this figure. # It should be noted that all thse curves are for a Moho at 30 km. Automated Steps of Model Generation 20

21. Gridding the Moho-depth Discontinuity to gradient conversion Background velocity computation Velocity section extension Model parameterization Velocity computation for all nodes of the model Derivatives of the velocity at all nodes Background velocity section IFJF: # All velocity sections had to be extended to the deepest point of the model. The se sections finally make the skeleton of the model. # For extending sections, we assumed that only those sections that locate in the proximity of the section should be used. The radius of this proximity was 50 km. # again, every point in the extended portion should be found by using a c-2 class interpolator which applied on the corresponding Moho-normalized poits. # end of section D seems that are deeper than end of section C, but in Moho-normalized case this point would be shallower and has no effect in extension process. # in the absense of adequate sections, to be geometrically surround the main section, we add 1, 2, or 3 background velocities at appropriate points. Automated Steps of Model Generation 21

22. Gridding the Moho-depth Discontinuity to gradient conversion Background velocity computation Velocity section extension Model parameterization Velocity computation for all nodes of the model Derivatives of the velocity at all nodes Original portion Extended portion IFJF: # This is an example of extesion af a section from Arctic refraction Catalogue. Red part is the original section and the blue part is the extended portion. Automated Steps of Model Generation 22

23. Gridding the Moho-depth Discontinuity to gradient conversion Background velocity computation Velocity section extension Model parameterization Velocity computation for all nodes of the model Derivatives of the velocity at all nodes IFJF: # There are 3 ways of parameterization of models, analytical, blocks and grids. # Sphrical harmonics is appropriate for global cases, because large wavelegth anomalies could be revealed by them. # Using polynomials is another analytical method which could be used in this study. So far I have seen only one study that have used polynomial parameterization in regional local scale. # In almost all regional scale studies people use Block or Grid methods. # Blocks introduce artificial boundaries between blocks, and assumes constant velocity in each block. # In this study we used the grid approach for setting up the pseudo-3-D velocity model. The main criteria for this choice were, applying the gradient method and also having enough resolution to image small-scale features. # One drawback of the grid method is that the velocity must be continuous in both horizontal and depth directions and no velocity discontinuity is allowed to exist. contradiction # Why gradient: geologically resonable and ottomoler study Automated Steps of Model Generation • Earth structure can be presented by: • 3-D analytic function • Block • Grid 23

24. Gridding the Moho-depth Discontinuity to gradient conversion Background velocity computation Velocity section extension Model parameterization Velocity computation for all nodes of the model Derivatives of the velocity at all nodes IFJF: # In this step, at least five geometrically appropriate velocity sections had to be within the proximity radius of the node, otherwise, background velocity sections with appropriate geometrical distribution were used. # By applying a C2 class 3-D non-uniform interpolator, the velocity at all nodes would be calculated. # Here I should remind that the role of background velocity is not only providing velocity data for regions that no velocity available, but another important role is preventing from divergence of interpolator. # For nodes closer than 75 km to zone boundaries, the effect of neighboring zones had to be considered. This was needed to reduce the effect of artificial boundaries that were made in the zoning process. If no velocity section from neighboring zones was available in the proximity radius of the node, background velocities from these zones would be incorporated. Automated Steps of Model Generation A C2-class 3-D non-uniform interpolator was applied on the velocity data in the proximity sphere of a node -a sphere with radius of 75 km and the node as its canter- to obtain the velocity at the node. 24

25. Gridding the Moho-depth Discontinuity to gradient conversion Background velocity computation Velocity section extension Model parameterization Velocity computation for all nodes of the model Derivatives of the velocity at all nodes IFJF: # using a 1-D differentiator, the derivatives of velocities along radius dV/dr, latitude dV/d , and longitude dV/d at each node was computed. Automated Steps of Model Generation using a 1-D differentiator, the derivatives of velocities along radius dV/dr, latitude dV/d , and longitude dV/d at each node were computed. 25

26. IFJF: # The model contains 273823 grid nodes. 73 in latitudinal direction, 121 nodes in longitudinal direction and 31 in depth direction. # The distances between nodes are about 27,8 in latitudinal, 7,7-15,9 in longitudinal direction, and 2 km in depth direction. Elements of the Model • The model contains 273,823 grid nodes in the geographical span of 55°N-73°N/0°-30°E and depth interval of 0-60 km. • 73 nodes with spacing of 15 arc-minute (27.85 km) in the latitudinal direction • 121 nodes with 15 arc-minute (7.73-15.92 km) spacing in the longitudinal direction • 31 nodes with 2 km intervals in the depth direction. 26

27. 3-D, P-wave Velocity Model of Scandinavia IFJF: # Here is the final model and this is longitudinal direction, latitudinal direction, and depth direction, surface at top, bottom 60 km, 55N to 73 N, 0-30E. 27

28. Travel-time Curves for Bergen (BER) Station Travel-time Difference Curves for Bergen (BER) Station IFJF: # Here we check to see how the model affects the travel-time curves, for some of stations. # Using a 3-D Ray-tracer # The red line shows the travel-time of current 1-D model in layerd mode that is used in Bergen, the brown line is the same 1-D model in gradient mode. The other colored lines were produced by tracing the rays in the 3-D model. # It should be mentioned that here is the the first place that we compare and use the 1-D bergen Model. _______________________________________ # In this graphs we show travel-time differences. Deviation from 1-D layered model. As we see there are differences in the range of less than 3 seconds. 28

29. Travel-time Curves for Tromsø (TRO) Station Travel-time Difference Curves for Tromsø (TRO) Station IFJF: # This is the same as before for another station but such peaks is due to falling of the 3-D ray tracer that we used in a local minimum . # As you see here differences toward west is larger. 29

30. Travel-time Difference Curves for Kongsberg (KONO) Station Travel-time Curves for Kongsberg (KONO) Station 30

31. Travel-time Difference Curves for Rogaland (BLS5) Station Travel-time Curves for Rogaland (BLS5) Station 31

32. Travel-time Difference Curves for Odda (ODD1) Station Travel-time Curves for Odda (ODD1) Station 32

33. Conclusions • Moho surface can be used as a strong boundary surface for evaluating fine changes of seismic velocity in the crust. • Dividing the crust based on velocity similarities can be done using bulk physically-related properties like gravity and age. Global availability of such data is an advantage. • A basis is made for extending the model toward west and north. • Model has variable accuracy and more data should be added • The computed travel-times in the 3-D model shows deviations up to 3s from the current 1-D model of Bergen University. 33