RUSSIAN JOURNAL OF EARTH SCIENCES VOL. 8, ES1003, doi:10.2205/2006ES000194, 2006
Crustal velocity structure under the RUKSA seismic array (Karelia, Russia)I. M. Aleshin, G. L. Kosarev, and O. Yu. RiznichenkoInstitute of Physics of the Earth, Russian Academy of Sciences, Moscow, Russia I. A. Sanina Institute for Dynamics of Geospheres, Russian Academy of Sciences, Moscow, Russia Contents
Abstract[1] Based on data of three three-component seismographs belonging to the temporary small-aperture Russian Karelia Seismic Array (RUKSA) in the Petrozavodsk region (Karelia), a 1-D velocity model of the crust is constructed by the method of the receiver function. Waveforms of distant earthquakes recorded by short-period instruments with improved characteristics are used. The data were inverted by the simulated annealing method. The inversion was stabilized by using phase velocities of Rayleigh waves and traveltimes of converted Ps waves from the 410-km boundary determined from broadband records of the SVEKALAPKO seismic array. Anomalously low seismic velocities are discovered in the upper part of the cross section beneath the RUKSA array. Introduction
Observation Conditions and Initial Data[3] The temporary small aperture RUKSA array (Institute of Physics of the Earth, Russian Academy of Sciences (IPE RAS)) was located in the Hautavaara settlement area (Karelia) 100 km west of the town of Petrozavodsk, between lakes Ladoga and Onega. The array observations (Figure 1) were conducted by a group of IPE RAS reserchears headed by M. V. Nevsky and S. G. Volosov within the framework of the large-scale SVEKALAPKO seismic tomography experiment for the study of the deep structure and evolution of the Baltic Shield. The array consisted of 3 three-component and 6 one-component ( Z ) instruments (SM-3KV seismometers) integrated with the digital recording system of the Ekspress station. The seismometers were positioned symmetrically on concentric circles of diameters of 640 m (outer ring C) and 300 m (inner ring B). The dynamic range of the recording instrumentation is 120 dB, and the recording sampling rate is 100 Hz. Time control was performed via GPS. The RUKSA recording channel after extending its frequency response toward lower frequencies [Bashilov et al., 1985] ensures reliable recording in the range 0.5-20.0 Hz. [4] The location of the array is characterized by a rather low level of microseismic noise. The noise spectrum includes stationary components of anthropogenic origin at frequencies of 12.5 Hz and 25 Hz and an intense episodic component with a maximum at 5 Hz. Upon examining the level and spatiotemporal variations in seismic noise at the RUKSA array, a frequency range of 0.5-3.0 Hz was chosen for the subsequent analysis. [5] Over 30 days of observations, the array recorded 100 seismic events of various origins including the largest earthquakes of 1999 in Turkey (Izmit), Taiwan (Chi-Chi), and Greece. This work uses records of the 12 strongest teleseismic events of magnitudes mb of 5.0 to 7.7 at epicentral distances of 20o to 70o (Table 1). Analysis of the Receiver Function Obtained from RUKSA Records[6] The procedure used for the construction and analysis of the receiver functions from P wave records has been repeatedly described in literature. In this work, we follow mainly the scheme described in [Kind et al., 1995]. The processing of P wave seismograms was performed with the use of the Seismic Handler software package [Stammler, 1993] and included the following operations. [7] (1) The observed vertical ( Z ) and two horizontal (NS and EW) components of a P wave were rotated to the ray coordinate system ( L, Q, and T ). The L axis lies in the ray plane and is directed from the source along the main motion in the P wave. The Q axis lies in the same plane and is perpendicular to the L axis. The horizontal projection of the Q axis is positive in the direction from the source. Together with the L and Q axes, the T axis forms a right-hand orthogonal triple. Displacements along the Q axis depend very weakly on the main motion in the incident P wave, determined mostly by the earthquake source, and are mainly composed of multiple and converted waves arising beneath the station. [8] (2) For applying the stacking procedure to a signal in order to increase signal-to-noise ratio, records of P waves from different earthquakes must be reduced to a standard source of the impulsive type. To do this, the L component of the signal, considered in this case as a source, is transformed into the standard form with the help of a deconvolution filter. The same filter is then applied to the components Q and T. It is the component Q that is called the receiver function. After this transformation, the noise can be suppressed by stacking Q components of all (or some) events, which yields the averaged receiver function Q obs(t).
[10] The inferred receiver functions display two main peaks at delay times of 0.27 s and 5.1 s. These peaks were initially identified as P to S conversions at an upper crust boundary and at the Moho. Particle motion analysis showed that oscillations at delay times longer than 10 s are associated with arrivals of scattered surface waves having a characteristic elliptic polarization rather than with multiple reflections of body waves. For this reason, we chose the time interval ( - 2 s, 8 s) for the receiver function used below for reconstructing the velocity structure of the medium. Surface Wave Data
Traveltime of the Converted Wave From the 410-km Boundary
[12] The SVEKALAPKO average traveltime of the converted wave from
the boundary at a depth of 410 km
tps = Ps410 - P = 42.3 Construction of a Velocity Structure by the Simulated Annealing Method[13] We modeled the medium under the array by a set of horizontal layers underlain by a homogeneous half-space. The model parameters m included P and S wave velocities, density, and layer thicknesses. The model was constructed through the minimization of the functional
A synthetic receiver function Q syn( m, t) was calculated by the formula [Kind et al., 1995]
The response components of the layered medium HQ ( m, w) and HL ( m, w) were calculated by the Thomson-Haskell method [Haskell, 1962]. ( R(w) is the surface wave dispersion curve, and wa are empirically chosen weights.) [14] The minimization problem formulated above is strongly nonlinear and ill-conditioned. The traditional method used for solving problems of this type is based on the regularization method [Tikhonov and Arsenin, 1979]. The minimization reduces to the solution of a system of linear equations that can be found very rapidly. However, the model obtained from an implementation of this method [Kosarev et al., 1987] is essentially dependent on the initial approximation whose choice is generally complicated. [15] Statistical (nongradient) methods (primarily, the Monte Carlo method) "scan" the entire space of parameters in the process of solution and are free from the necessity of specifying the initial approximation. However, the direct application of statistical methods to the search for the solution in a multidimensional space involves time consuming computations, which makes the practical use of these methods unrealistic. A possible way of solving this problem is to seek the solution in three stages: identification of one or more promising regions in the initial space of potential models, careful examination of each of these regions, and "fine adjustment" of the best solution inferred at the preceding stage. Such an approach is realized in the modern modification of the simulated annealing (SA) method [Ingber, 1989]. The software implementation of this method reduces the time of the search for the solution to an acceptable value (no more than one hour on a standard PC for the present case). [16] To invert data, we used a model consisting of 11 layers on a half-space. Velocities of S waves in the layers and the half-space and thicknesses of some layers were varied, whereas the ratio Vp/Vs was fixed (1.73 in the crust and 1.8 in the mantle) and the density was determined by the Birch formula. The chosen time interval of the receiver function minimization ( - 2 s to 8 s) bounds the overall depth of the model by about 70-80 km. Deeper layers have no effect on the receiver function. However, in order to use traveltimes of waves converted at the 410-km boundary, the velocity structure should be specified to a depth of 410 km. For this purpose, our current 11-layer model (more specifically, the line defining the velocity in the half-space) was continued downward until its intersection with the IASP91 standard model of the Earth. IASP91 velocities were used for the calculation of tps410 in the depth interval from the intersection point to 410 km.
Discussion and Conclusion
[19] One of the most noticeable features of the
inferred structures is anomalously low velocities
in the upper crust. Thus,
Vp [20] In the lower and upper crust, at depths of 10 km to 40 km, the P wave velocity slowly rises to about 6.6 km s-1. Its average gradient at these depths is an order of magnitude smaller than in the upper crust at depths of 0 km to 10 km. The Moho depth is about 40 km. The P velocity immediately under the Moho is 8.4 km s-1. This value is much higher than in the IASP91 model but is consistent with modern models of ancient shields. Thus, the velocity structure obtained in this work consists of an essentially heterogeneous upper part where the velocity (converted into P wave velocity values) rises from 3.5 km s-1 at the surface to 6.2 km s-1 at depths of 10-12 km and nearly homogeneous middle and lower parts with minimal velocity contrasts in the corresponding layers. Velocity inversion zones are virtually absent in the final variant of the velocity structure. [21] Previously we presented and discussed the velocity structure beneath RUKSA obtained from a receiver function alone, without invoking data on surface waves and traveltimes of converted waves from the 410-km boundary [Sharov, 2004]. The main features of the structure, the Moho depth and average velocities in the crust and the mantle, are close to those inferred in our study. Distinctions are mainly observed in the upper part of the section and can be attributed to the instability of the inversion using data of the receiver function alone. The extent of misfit (the rms deviation) between the synthetic and observed waveforms of the published structure is 1.5 times greater than in our present work. [22] Reliable features of the presented models (Figure 4) are the presence of a sharp boundary at a depth of about 40 km (the Moho), anomalously low velocities in the depth interval 0-3 km that are untypical of ancient shields, a rapid rise in the velocity with depth in the upper crust, and weak differentiation in velocities of the middle and lower crust. Significant heterogeneities in the upper part of the crystalline crust to depths of 12-15 km were previously noted in studies of the fine structure of seismic wavefields from small aperture array data [Nevsky and Riznichenko, 1980]. [23] Thus, using data of short-period instrumentation with improved characteristics, a detailed velocity structure is obtained beneath the RUKSA small aperture array. These data are necessary for remote location of seismic events. They can also be used for the construction of a 3-D lithosphere model of the European part of the Russian Federation. This approach is promising if mobile small-aperture arrays and natural sources (remote earthquakes) are used for local mapping of crustal boundaries from seismic data of relatively short period instrumentation. Acknowledgments[24] We are grateful to M. Bruneton, who kindly provided us with data on phase velocities of surface waves. Data on tps410 traveltimes from SVEKALAPKO records were obtained by I. M. Aleshin and G. L. Kosarev during their visit to Oulu University at the invitation of E. Kozlovskaya (research grant of the Finnish Academy of Sciences, 2004). Experimental observations with the RUKSA array were supported by the INTAS grant 97-0936 and the Zurich ETH Institute (Switzerland). This work was supported by the Russian Foundation for Basic Research, projects nos. 03-05-64654, 04-05-64634, and 04-07-90362-B. ReferencesAmmon, C. J. (1990), On the nonuniqueness of receiver function inversions, J. Geophys. Res., 95, 2504. Bashilov, I. P., T. N. Ershova, M. M. Krekov, M. V. 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Nauk SSSR (in Russian), 261, (5), 1091. Vinnik, L. P., S. Roecker, G. L. Kosarev, S. I. Oreshin, and I. Yu. Kulakov (2002), Crustal structure and dynamics of the Tien Shan, Geophys. Res. Lett., 29, (22), 94. Vinnik, L. P., Ch. Reigber, I. M. Aleshin, G. L. Kosarev, M. K. Kaban, S. I. Oreshin, and S. W. Roecker (2004), Receiver function tomography of the central Tien Shan, Earth Phys. Sci. Lett., 225, 131. Received 15 February 2006; revised 1 March 2006; accepted 9 March 2006; published 14 March 2006. Keywords: Earth's crust, small aperture array, method of the receiver function. Index Terms: 7205 Seismology: Continental crust; 7255 Seismology: Surface waves and free oscillations; 7294 Seismology: Seismic instruments and networks. ![]() Citation: 2006), Crustal velocity structure under the RUKSA seismic array (Karelia, Russia), Russ. J. Earth Sci., 8, ES1003, doi:10.2205/2006ES000194. (Copyright 2006 by the Russian Journal of Earth SciencesPowered by TeXWeb (Win32, v.2.0). |