JOURNAL OF GEOPHYSICAL RESEARCH: SOLID EARTH, VOL. 119, 396–408, doi:10.1002/2013JB010077, 2014
Orthogonal relation between wavefield polarization and fast S wave direction in the Val d’Agri region: An integrating method to investigate rock anisotropy M. Pischiutta,1 M. Pastori,1,2 L. Improta,1 F. Salvini,3 and A. Rovelli 1 Received 6 February 2013; revised 6 November 2013; accepted 12 November 2013; published 15 January 2014.
[1] Wavefield polarization is investigated using 200 seismograms recorded by a network of 20 stations installed on rock outcrops in the Val d’Agri region that hosts the largest oil fields in the southern Apennines (Italy). Polarization is assessed both in the frequency and time domains through the individual-station horizontal-to-vertical spectral ratio and covariance-matrix analysis, respectively. We find that most of the stations show a persistent horizontal polarization of waveforms, with a NE-SW predominant trend. This direction is orthogonal to the general trend of Quaternary normal faults in the region and to the maximum horizontal stress related to the present extensional regime. According to previous studies in other areas, such a directional effect is interpreted as due to the presence of fault-related fracture fields, polarization being orthogonal to their predominant direction. A comparison with S wave anisotropy inferred from shear wave splitting indicates an orthogonal relation between horizontal polarization and fast S wave direction. This suggests that wavefield polarization and fast velocity direction are effects of the same cause: The existence of an anisotropic medium represented by fractured rocks where shear wave velocity is larger in the crack-parallel component and compliance is larger perpendicularly to the crack strike. The latter is responsible for the observed anisotropic pattern of amplitudes of horizontal ground motion in the study area. Citation: Pischiutta, M., M. Pastori, L. Improta, F. Salvini, and A. Rovelli (2014), Orthogonal relation between wavefield polarization and fast S wave direction in the Val d’Agri region: An integrating method to investigate rock anisotropy, J. Geophys. Res. Solid Earth, 119, 396–408, doi:10.1002/2013JB010077.
1.
Introduction
[2] In the top few kilometers of the crust, fault zones are characterized by the presence of systematic brittle deformation [e.g., Ben-Zion and Sammis, 2003, and references therein]. The locally reduced seismic impedance of the damage zone can influence earthquake-induced ground motions as well as ambient noise. The most evident effect is a local increase of ground motion amplitudes (Spudich and Olsen [2001], Cultrera et al. [2003], Peng and Ben-Zion [2006], Karabulut and Bouchon [2007], and Calderoni et al. [2010], to quote only few among many others). Another recurrent effect is the propensity of fault zones to modify wavefield polarization [e.g., Rigano et al. 2008; Di Giulio et al. 2009; Pischiutta et al. 2012, 2013; Di Giulio et al., 2013]. The common results of these papers are the following: (i) waveforms tend to be polarized in the horizontal plane, horizontal motions largely
1
Istituto Nazionale di Geofisica e Vulcanologia, Roma, Italy. Dipartimento di Scienze Geologiche, Università Roma 3, Rome, Italy. 3 Universita Roma Tre, Roma, Italy. 2
Corresponding author: M. Pischiutta, Istituto Nazionale di Geofisica e Vulcanologia, Via di Vigna Murata 605, Roma, IT-00143, Italy. (
[email protected]) ©2013. American Geophysical Union. All Rights Reserved. 2169-9313/14/10.1002/2013JB010077
dominate over the vertical ones; (ii) the most persistent direction of polarization does not fit the expected source mechanism, even in active source-controlled experiments; (iii) polarization azimuths are not random and tend to form a high angle with the fault strike. Due to the decrease of the polarization intensity moving away from the fault trace, Pischiutta et al. [2012, 2013] ascribed these findings to an effect of the locally predominant fracture field. The role of fractures on wavefield polarization is confirmed by Falsaperla et al. [2010], who found clear motion polarizations at stations in the crater area of Mount Etna, with polarization directions varying among sites but everywhere transversal to the orientation of the local fracture field. [3] In the crust, anisotropy of seismic waves is controlled by microcracks aligned by the stress field. However, in fault zones S wave fast direction tends to become nearly fault parallel [Peng and Ben-Zion, 2004; Cochran et al., 2006] due to a combined effect of regional stress and shear fabric of the fault. The goal of the present study is a direct comparison of the effect of fractures on wavefield polarization and S wave fast directions by using the same seismometric data with two different analysis techniques. The data set was recorded in the Val d’Agri region (southern Italy) where abundant subsurface data from hydrocarbon industry provide valuable constraints on the structure of the upper crust, geometry of active faults, characteristics of the fracture systems, and local stress field [Shiner et al., 2004]. [4] The Val d’Agri hosts one of the largest oil fields in Europe, and it has been the target of an intense hydrocarbon
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Figure 1. Geologic map of the Val d’Agri basin and surrounding regions (modified after Lazzari and Lentini [1991] and Maschio et al. [2005]). 1 = Quaternary continental deposits; 2 = terrigenous units (upper Cenozoic); 3 = carbonate clastic units (Cenozoic); 4 = Mesozoic-Tertiary pelagic basin formations (mainly silicic limestones, cherts, and claystones); 5 = detached Mesozoic carbonate platform formations; 6 = Apulian platform carbonates (Mesozoic–Miocene); 7 = main thrusts and overthrusts; 8 = normal faults; 9 = breakout data with blue bars indicating the minimum horizontal stress directions (class quality B and C after Cucci et al. [2004]); 10 = seismic stations with S wave anisotropy and wavefield polarization analysis results; 11 = seismic stations with only wavefield polarization analysis results; 12 = earthquake epicenters of seismic events used in the S wave splitting analysis; 13 = earthquake epicenters used in the wavefield polarization analysis. EAFS = Eastern Agri Fault System; MMFS = Mts. Maddalena Fault System. EAFS dips toward SW [Cello et al., 2003]; MMFS dips toward NE [Maschio et al., 2005]. exploration since the 1980s [Holton, 1999] that confirmed the presence of a wide distribution of intensely fractured rock as a result of the regional extensional stress regime and Quaternary faulting. Pastori et al. [2009, 2012] investigated seismic anisotropy by applying the shear wave splitting method to earthquakes recorded during a dense passive seismic experiment [Valoroso et al., 2009, 2011]. Pastori et al. [2009, 2012] found a dominant fast S wave direction striking NW-SE, perpendicular to the current regional extension that they interpreted as the effect of open and fluid-saturated cracks in fractured carbonate rocks aligned by the active stress field. [5] In the present paper we investigate to what extent S wave splitting and polarization analysis provide consistent results in the Val d’Agri area. In order to make clear the differences between the two methodologies, we begin by describing the methods and also presenting results at a representative station. We proceed showing the ground motion polarization pattern in the area. We anticipate that a large part of seismic stations shows a clear polarization parallel to the local NE trending extension forming a high angle with the strike of the Quaternary normal faults. We demonstrate that at stations where S wave anisotropy is available from Pastori et al.
[2009, 2012], horizontal polarization and fast S wave orientation tend to be orthogonal. This is interpreted as the effect of fracture orientations on both velocity of seismic waves (they travel faster when the direction of propagation is parallel to fractures) and horizontal polarization (medium is more compliant in the direction orthogonal to the fractures).
2.
Geologic and Seismotectonic Setting
[6] The southern Apennines range of Italy is one of the regions with high seismogenic potential in central Mediterranean [CPT1 Working Group, 2004, Figure 1]. Seismicity is characterized by up to magnitude 7 normal-faulting earthquakes occurring along the axial portion of the range [Chiarabba et al., 2005] consistently with a NE-SW oriented extensional regime [Amato and Montone, 1997]. Regional extension is documented by earthquake centroid moment tensor solutions of moderate to large earthquakes [Pondrelli et al., 2006], borehole breakouts [Amato and Montone, 1997; Cucci et al., 2004], and GPS velocities [Serpelloni et al., 2005]. Strain occurs at low rates (2–5 mm/yr according to D’Agostino et al. [2008]) and is mainly accommodated on Quaternary normal faults [Cinque et al., 1993]. Such faults postdate and dissect the Apennine
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thrust-and-fold belt accreted during Mio-Pliocene [Patacca and Scandone, 2001] and locally bound intermontane continental basins. [7] The structural framework of the southern Apennines is typified in the Val d’Agri area where a wide Quaternary graben basin is bordered by two systems of NW-SE trending, highangle normal faults (Figure 1). The basin extends for a total length of 30 km and is filled by continental deposits as thick as 500 m. It is bounded to the east by the Eastern Agri fault system (EAFS) that is composed of subparallel SW dipping strands and has an integrated vertical displacement of ~500 m [Cello et al., 2003]. The EAFS controlled the basin opening and accommodated left-oblique transtension since the lower Pleistocene [Cello et al., 2000; Mazzoli et al., 2000; Maschio et al., 2005]. The western side of the basin is bordered by the NE dipping Monti della Maddalena fault system (MMFS) [Maschio et al., 2005], which is interpreted by some authors as the main structure accommodating active extension in the area [Maschio et al., 2005; Zembo et al., 2009; Improta et al., 2010]. This interpretation is supported by paleoseismological and shallow geophysical surveys (Monte Aquila Fault, see Improta et al. [2010]) and is consistent with the relations between morphology and structural geology as already exploited in the literature for other regions [e.g., Cianfarra et al., 2009]. [8] The EAFS and MMFS dissect a Mio-Pliocene thrustand-fold system that includes Mesozoic-Tertiary carbonate platform and pelagic sedimentary units, stratigraphically covered by Neogene flysch deposits [Patacca and Scandone, 1989, Figure 1]. These sedimentary units form an allochthon overlying the buried Apulian platform that is 6–7 km thick and was involved in the final shortening phase of the Apennines [Menardi Noguera and Rea, 2000]. The Apulian Mesozoic-Tertiary carbonates were folded by thrust-related, long-wavelength anticlines, which host large hydrocarbon reservoirs [Shiner et al., 2004]. [9] Stress indicators observed on both the EAFS and MMFS normal-fault systems are consistent with the active local stress field inferred by seismological, borehole breakout and hydrocarbon production data. The intense microseismicity observed by Valoroso et al. [2009] along the southwestern margin of the basin (Figure 1) is characterized by normalfaulting mechanisms with persistent NE-SW orientation of SHmin. Breakouts from five deep wells drilled in the nearby Monte Alpi and Monte Enoc oil fields [Holton, 1999] provide coherent SHmin directions ranging between N41° and N53° (Figure 1) in the 3000–4900 m depth interval [Cucci et al., 2004]. Such directions are in agreement with results of well logging and borehole imaging surveys that provided valuable information to understand the fracture formation mechanism and its relationship with the local stress field [Trice, 1999; Shiner et al., 2004]. In the Val d’Agri area, oil is produced from limestone and dolomite reservoirs, reached at 2–3 km depth below sea level, with oil columns of 800–1000 m above water [Holton, 1999]. Reservoir properties of the productive Apulian carbonates are excellent due to the presence of large, open fracture systems. The carbonates are cut by a widespread network of fractures that have a scattered pattern in dip, magnitude, and azimuth because of the complex deformation history of the Apulian platform. The high productivity of the reservoirs was related by Trice [1999] to the presence in the network of open and permeable fractures that strike NW-SE, parallel to
the maximum horizontal stress (SHmax) direction. In addition, fault damage zones favor local flow enhancement of hydrocarbons if they are favorably oriented with respect to the regional stress field, as in the case of the NW-SE striking normal faults of the Val d’Agri, where the damage zones are deformed by near-vertical NW-SE fracture systems (i.e., R, R′, and T fractures, see Riedel [1929]).
3.
Data and Methods
[10] During 2005 and 2006, a dense passive seismic experiment was carried out in the area yielding high-resolution images of the background seismicity [Valoroso et al., 2009] and crustal velocity structure [Valoroso et al., 2011]. As expected on the basis of the regional stress regime, focal mechanisms of local earthquakes computed by Valoroso et al. [2009] are consistent with NW-SE striking normal faulting. [11] The seismic network was composed of 20 stations with approximately 5 km spacing (Figure 1). Seismic stations were installed on rock outcrops of the following sedimentary units: pelagic silicic limestones, cherts, and sandstones. They recorded continuously for a period of 13 months between May 2005 and June 2006, and detected almost 2000 lowmagnitude earthquakes ( 0.2 < ML < 2.7). [12] Most of the seismicity occurred in the area between stations AG18, AG14, and AG09, whereas the remaining occurred near stations AG13 and AG11. A minor cluster occurred under station AG04. Large part of these events is concentrated at shallow depth (about 6 km) between the southern margin of the Val d’Agri basin and the Mount Alpi area. Valoroso et al. [2009] also show that seismic events cluster in space and time at greater depths (8–12 km). 3.1. Polarization Analysis [13] The polarization analysis was performed on data from earthquakes with magnitude higher than 1.0 and recorded by more than 10 stations. The selection of the highest magnitude events is driven by the need of a satisfactory signal-to-noise ratio in the frequency band (1 to 9 Hz) of analysis, smaller events having corner frequencies much larger than 10 Hz. The list of selected events is shown in Table 1. [14] Before proceeding with the analysis, signals were detrended and the mean was removed, then they were tapered through a Hanning window for the spectral analysis. No instrumental correction was applied as data are investigated at periods shorter than the eigenperiod (5 s) of the sensor; thus, signals were analyzed in count units. We determined the wavefield polarization through the method of analysis proposed by Pischiutta et al. [2012] that is performed in the frequency domain computing the horizontal-to-vertical spectral ratios (HVSRs) after rotating the horizontal components from 0° to 180° at bins of 10° and in the time domain through diagonalization of the covariance matrix [Jurkevics, 1988]. [15] The use of spectral ratios after rotation of the horizontal components was first introduced by Spudich et al. [1996], to investigate possible directional effects on the horizontal plane. HVSRs show to what extent horizontal motions are amplified, compared to the vertical motion, as a function of frequency and direction of motion. The time windows used for the spectral analysis start from the P waves and include the S and coda waves. After computing the fast Fourier transform, amplitude spectra of the vertical and horizontal components are smoothed
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16/5/2005 14:03 23/5/2005 8:53 23/5/2005 11:24 31/5/2005 13:37 2/6/2005 7:17 28/6/2005 4:35 8/7/2005 5:37 15/7/2005 1:34 19/7/2005 8:26 25/8/2005 2:57 5/11/2005 9:47 11/11/2005 8:21 11/11/2005 9:32 17/11/2005 12:37 5/1/2006 6:35 14/1/2006 2:26 21/1/2006 13:03 5/2/2006 17:00 28/2/2006 2:45 8/3/2006 15:31 11/3/2006 9:01 14/3/2006 13:33 17/3/2006 1:27 15/4/2006 23:26 19/4/2006 4:15 22/4/2006 8:15 22/4/2006 8:19 22/4/2006 18:06 3/6/2006 13:12 4/6/2006 15:19 6/6/2006 19:21 7/6/2006 20:46 7/6/2006 23:16 7/6/2006 23:28 8/6/2006 4:10 8/6/2006 4:55 8/6/2006 8:54 8/6/2006 10:29 8/6/2006 11:21 8/6/2006 13:11 8/6/2006 19:36
Date and Time
40.5577 40.2002 40.2002 40.331 40.335 40.3137 40.264 40.1918 40.428 40.1998 40.1967 40.192 40.2982 40.4002 40.2305 40.2472 40.2392 40.2162 40.2462 40.2722 40.2352 40.8563 40.2393 40.2373 40.2377 40.239 40.2415 40.228 40.2402 40.275 40.2625 40.3155 40.3233 40.319 40.3213 40.3265 40.319 40.3168 40.3188 40.327 40.3287
LAT
16.1355 15.9542 15.9542 15.7413 15.7523 15.8148 15.9012 15.9802 15.7098 15.6692 15.993 15.7527 15.8103 15.7188 15.8867 15.905 15.9295 15.9173 15.9043 15.892 15.9318 15.2777 15.9005 15.9235 15.9242 15.9228 15.9218 15.9067 15.9253 15.8715 15.91 15.986 15.9912 15.9852 15.9892 15.9878 15.9875 15.927 15.9825 16.0007 15.995
LON
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18.5 0.5 0.5 0.4 1.1 11 4.8 0.2 5.5 3.8 9.5 6.1 5.3 3.9 3.3 4.2 3.6 5.3 3.3 4.2 3.8 0.3 3.4 3.8 3.8 4.2 3.8 4 4.3 4.4 4.4 4.6 5.2 4.9 4.7 4.1 4.9 8.8 4.8 4.8 4.2 2.2 2 2.7 2.4 2.1 1.1 1.1 1 1 1.5 1.2 1.2 1.1 1.3 1.8 1.5 1.5 1.5
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Depth (km) M AG01 AG02 AG03 AG04 AG05 AG06 AG07 AG08 AG09 AG10 AG11 AG12 AG13 AG14 AG15 AG16 AG17 AG18 AG19 AG20
For each event, hypocentral coordinates and magnitude are listed. The asterisks indicate the available records. The total number of seismic events used per station is reported in the bottom row. Single asterisks near labels indicate stations discarded because of the low number of events. Double asterisks near labels indicate stations discarded because of showing scattered rose diagrams.
a
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 TOT
Event #
Table 1. Data Set Used for the Polarization Analysis at Each Stationa c
PISCHIUTTA ET AL.: POLARIZATION AND SEISMIC ANISOTROPY
PISCHIUTTA ET AL.: POLARIZATION AND SEISMIC ANISOTROPY
Figure 2. Average horizontal-to-vertical spectral ratios of six representative stations: (a) AG01, (b) AG07, (c) AG08, (d) AG09, (e) AG11, and (f) AG12. The geometric mean is computed over the ensemble of selected seismic events. In Figures 2a–2f (top), average spectral ratios are drawn separately for rotation angle from 0° to 180°. In Figures 2a–2f (bottom), the same spectral ratios are shown in a grey-scale contour representation. with a running 0.5 Hz wide box. The HVSR values are calculated separately for each event; therefore, the geometric mean is computed at each station over the available events. Some representative results of the Val d’Agri stations are illustrated in Figure 2. The average spectral ratios as a function of the rotation angle are shown using contour plots in Figures 2a–2f (top): the y axis and x axis represent rotation angle and frequency, respectively, and the grey scale quantifies the horizontal-to-vertical (H/V) amplitudes. In Figures 2a–2f (bottom) the same average spectral ratios for each rotation angle are drawn separately to better visualize variations of the frequency peak at different azimuths (stations AG01 (Figure 2a)
and AG08 (Figure 2c)). Although stations are installed on rock outcrops, we have found that horizontal motions tend to predominate over vertical ones with HVSR amplitudes up to a factor of 4, a feature that is not common at rock stations. Most of the stations show that HVSRs increase in different frequency bands, but spectral peaks generally fall in the range 1–9 Hz. Thus, we use this frequency band to band-pass filter seismograms to perform the polarization analysis in the time domain. For most of the stations, a single spectral peak predominates (e.g., stations AG01 (Figure 2a) and AG09 (Figure 2d)); for other stations, more than one peak emerges, but consecutive peaks maintain their larger amplitude at similar azimuths (e.g., stations AG08,
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Figure 3. Example of S wave anisotropy and horizontal polarization analysis using the same earthquake (#6 in Table 1). The unfiltered three-component waveforms are shown in the middle. The main steps of splitting analysis, applied to a 0.3 s wide time window centred on the first S wave arrival, are shown in the top: (a) Filtered horizontal seismic waveforms; (b) amplitude of the two horizontal components and particle motion, before and after the rotation and delay time correction; (c) correlation matrix and direction of the fast S wave component. (bottom) Detail of the wavefield polarization analysis is shown, using a 0.5 s long time window sliding with 0.1 s overlap along the entire length of the signals. The two examples of polarization ellipsoid are representative of two different time windows: the first S wave arrivals and coda waves. The former shows lower values of R and I and less elongated ellipsoid; thus, it is associated to a low reliability class. The latter is more horizontal and is associated to the highest reliability class. 401
PISCHIUTTA ET AL.: POLARIZATION AND SEISMIC ANISOTROPY
Figure 4. Results of the covariance matrix analysis at stations AG8 and AG17 for one magnitude 2.7 representative event (#26 in Table 1). Signals recorded at each station are plotted in black, green, and cyan for UP, NS, EW components, respectively. The covariance matrix and subsequently the polarization vector in 3-D are evaluated through a sliding window (0.5 s length, 0.1 s overlap) along signals. Polarization azimuths are plotted versus time using symbols depending on the associated reliability class as defined by Pischiutta et al. [2012]. They are also represented in a planar histogram that is fit with a Gaussian curve in order to estimate mean and standard deviation of the data distribution. We also show the rose diagram obtained aggregating all the analyzed seismic events. AG11, and AG12). There is only one case where two large peaks occur at different azimuths (station AG07). [16] Spectral ratios calculated using the rotated horizontal components are very effective to recognize directional site effects. However, sometimes they may be biased by anomalies in the denominator spectrum. Thus, we apply the covariance matrix method [Jurkevics, 1988] in the time domain to obtain a direct estimate of the ground motion polarization. The covariance matrix is computed along the band-pass filtered signals, beginning few seconds before the P wave arrival and including the late coda. A 0.5 s sliding window with 0.1s overlap is run throughout the seismograms; in each window the polarization ellipsoid is estimated through the eigenvalues and eigenvectors of the covariance matrix by solving the algebraic eigen problem. The eigenvalues and eigenvectors correspond respectively to the length and orientation of the polarization ellipsoid thus defining the polarization vector in 3-D. According to Jurkevics [1988], it is characterized by three parameters: the polarization
angle “AZ” in the horizontal plane (measured from north), rectilinearity “R” (varying from 0 for circular particle motions to 1 for purely rectilinear ones), and the angle “I” of the largest eigenvector from the vertical axis. In order to give major importance to time windows associated with more horizontal and elongated polarization ellipsoids, we apply the hierarchical criterion previously proposed by Pischiutta et al. [2012]. We thus define four classes of increasing reliability as shown in Figures 3 and 4. Two examples of ellipsoid computation are shown in Figure 3 (bottom). They are obtained from two different time windows along the signal of event #5 recorded at station AG13: One ellipsoid is related to the first S wave arrivals, another one is obtained from the coda waves. The former shows lower values of R and I and less elongated ellipsoid; thus, it is associated to a low reliability class. The latter is more horizontal and is then associated to the highest reliability class. [17] Consistently, in Figure 4 we show representative results of the covariance matrix analysis performed for stations AG8
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Figure 5. Horizontal polarization in the Val d’Agri area and the main Quaternary normal faults. Dark circles represent stations showing very scattered rose diagrams. and AG13 using the seismic event #26 of Table 1. For that event, the three components of motion are shown together with polarization azimuths versus time. Azimuth values are plotted using a grey scale representing our reliability classes (light grey to black for increasing reliability). As mentioned above, the class attribution was based on the elongation/flatness and horizontality of the polarization ellipsoid of each time window (details can be found in Pischiutta et al. [2012]). In Figure 4, azimuth values are also represented as a planar histogram that we fit through a Gaussian curve in order to estimate values of mean and standard deviation of each record. The analysis is repeated for all of the events selected in Table 1; therefore, we aggregate the polarization azimuths of each station for the whole data set. Thus, we produce a final circular histogram for each station (the result of stations AG8 and AG13 are shown in the rose diagrams of Figure 4).
3.2. Splitting Analysis [18] The results of seismic anisotropy that will be used in the next sections are taken from Pastori et al. [2012]. In their approach a seismic shear wave propagating in an anisotropic medium is split into two orthogonal components that travel at different velocities. According to the extensive dilatancy anisotropy (EDA), the fast velocity direction is parallel to the SHmax direction that controls the predominant orientation of microcracks [Crampin, 1978]. [19] Here we shortly summarize the main features of Pastori et al. [2012]. These authors assessed seismic anisotropy from local earthquakes estimating S wave splitting with the automatic code Anisomat+ [Piccinini et al., 2013]. The main steps of their computations are shown in Figure 3. They selected seismic events at each station with geometrical incidence angle between
0° and 45°, as measured from the vertical. On each seismic event a 0.3 s wide time window, centered on the S time arrival (Figure 3a, grey box), was selected on band-pass filtered waveforms (1–12 Hz; Figure 3a). A duration of 0.3 s is related to the higher corner frequency of the band-pass filter and is chosen to include at least a complete cycle of the filter corner frequency. The cross-correlation method is applied to the selected window to find the couple of fast direction (θ) and delay time (δt) that maximizes the cross-correlation coefficient (Figure 3c). As expected, the resulting particle motion in the horizontal plane shows a linear trend after the delay time correction (Figure 3b (bottom)).
4.
Results
[20] The pattern of horizontal ground motion inferred from the covariance matrix analysis is shown in Figure 5 where also the basin bounding Quaternary normal faults are drawn. Polarization is estimated for each station as an average over the entire data set and is represented by the rose diagrams. Fifteen stations (AG01, AG02, AG04, AG05, AG06, AG07, AG08, AG09, AG11, AG12, AG13, AG14, AG15, AG17, and AG18) show a narrow distribution of polarization in the rose diagrams with standard deviation lower than 45°, which indicates a fairly narrow distribution. A light grey circle in Figure 5 marks these stations. Predominant polarization is nearly NE-SW, only three stations (AG03, AG10, and AG19) showing scattered rose diagrams (dark grey circles) with standard deviations higher than 45°. Two stations (AG16 and AG20) recorded only five seismic events; thus, they will be no further considered. [21] The polarization pattern is compared with the S fast direction (black rose diagrams in Figure 6) as assessed from shear wave splitting by Pastori et al. [2012]. Five stations
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Figure 6. Horizontal polarization (light rose diagrams) and fast anisotropic direction (black rose diagrams) at stations in the Val d’Agri area that recorded a satisfactory number of seismic events for S wave splitting analysis. The angular relation between the mean polarization and the mean fast S wave orientation is calculated at each station. This relation is quantified through the histogram and the regression curve shown in the insets. The line in the bottom inset represents the orthogonal relation between polarization and fast anisotropic direction. They both suggest a near-orthogonal relation between polarization and anisotropy in the studied area. Equal area projections of the analyzed seismic events visualize azimuth and incidence distribution (black and light dots represent the S wave splitting and the wavefield polarization analysis data sets, respectively). (AG04, AG09, AG13, AG14, and AG18) show a NW-SE dominant fast S wave direction, whereas three stations show a direction that is slightly rotated, to N100° (AG11 and AG17) or N90° (AG05). At station AG01, the fast S wave direction does not show a peaked distribution due to the inconsistent behavior of the small (13) number of available seismic events; thus, this station will be no further considered. The remaining stations did not record a sufficiently large number of earthquakes (more than 10) with vertical incidence angle, this constraint being strictly required in the S wave splitting analysis. However, in the polarization analysis, six of them (AG02, AG06, AG07, AG08, AG12, and AG15) show a narrow polarization distribution (Figure 5). As illustrated by equal area projections in Figure 6, anisotropy estimates are relative to raypaths illuminating the rock volumes beneath the stations, whereas there are no constraints in raypaths for the wavefield polarization estimates. [22] We then calculate the angle Φ between the mean polarization and the fast S wave direction for the eight stations with both these estimates available (AG04, AG09, AG11, AG12, AG13, AG14, AG17, and AG18). The relation polarization anisotropy is visualized in the inset of Figure 6 where in the
bottom we plot the polarization orientation at each station versus fast S wave direction, the line representing their orthogonal relation. In the inset top we show the histogram of Φ. We note that, out of the eight stations considered, seven show a near-orthogonal relation between anisotropy and polarization, only station AG17 differing by 40°. Apart from this station, the difference between the mean polarization and fast S wave direction is comprised in the range 70°–90°.
5.
Discussion
[23] Wavefield polarization is a complex effect that can be caused by different mechanisms. In the direct body waves, it is controlled by the source mechanism, whereas surface waves typically generate particle motions comprised in the radial and transversal plane of propagation (for Rayleigh and Love waves, respectively). In other cases, horizontal wavefield polarization is a site property as first observed by Bonamassa and Vidale [1991] who called it “directional resonance” to indicate narrow-band directional, site-specific amplification. A strong tendency of horizontal ground motion to be amplified in a preferred direction has been frequently found
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Figure 7. Average horizontal-to-vertical spectral ratios of stations AG03, AG06, AG08, and AG13 calculated on a 1 h record of ambient noise and on seismic events. Similar to Figures 2a–2f (bottom), spectral ratios are shown in a grey-scale contour representation. on the top of topographic irregularities where amplification tends to be transversal to the ridge (Buech et al. [2010], Massa et al. [2010], Pischiutta et al. [2010], and Panzera et al. [2011], to quote only a few among many others). Burjànek et al. [2010, 2012] found strongly polarized motions on unstable mountain slopes on Swiss Alps and ascribed the effect to the resonance of rock blocks separated by large open cracks (see also Moore et al. [2011]). Marzorati et al. [2011] too related the observation of directional ground motions on a ridge in the Apennines to large open fractures, polarization direction being transversal to the fractures. There are other cases where directional horizontal motions occur but are not controlled by topography, e.g., those observed in fault zones [Rigano et al., 2008; Di Giulio et al., 2009; Pischiutta et al., 2013]. In these study cases the role of topography was ruled out because of the flat study area (as in the Hayward fault zone, see Pischiutta et al. [2012]) or because of the large site-to-site variability of topography at the scale of hundreds to thousands of meters (as on Mount Etna, see Rigano et al. [2008], Di Giulio et al. [2009], and Pischiutta et al. [2013]). In these cases directional horizontal motions were interpreted as the effect of the larger compliance transversal to fractures in the fault damage zone [Pischiutta et al., 2012, 2013]. [24] In fault zones, also the fast S wave direction is found to be controlled by the crack orientation rather than the regional stress [e.g., Boness and Zoback, 2006; Peng and Ben-Zion, 2004; Syracuse et al., 2012]. Therefore, the comparison between anisotropy inferred from S wave splitting and wavefield polarization can represent a useful test of consistency since these two parameters are estimated in a completely different approach and are relative to different portions of seismograms. The Val d’Agri area is an interesting test site for this check because of the number of previous geological and seismological studies and the huge amount of data collected by the oil industry.
[25] Pastori et al. [2012] interpreted seismic anisotropy for this area in terms of the EDA model [Crampin, 1978]. It considers the rock volume pervaded by fluid-saturated microcracks aligned by the active stress field. These authors showed that the NW-SE fast orientation is parallel to the SHmax direction related to the present regional extension. This finding is also parallel to the general trend of Quaternary normal faults. Their interpretation is supported by data from hydrocarbon exploration and production. Geophysical logging and image logs from deep wells that penetrate the Apulia carbonates between 2–5 km depth reveal a widespread system of fractures developed during the Pliocene contractional tectonics and the Quaternary extension. The present local stress regime plays a primary role in opening different sets of fractures: cracks and fractures which strike NW-SE parallel to the SHmax direction are open and saturated by fluids (water and oil), while those with orthogonal strike tend to be closed [Trice, 1999]. Pastori et al. [2009] proposed that not only the Apulia carbonates but also the upper stack of sedimentary thrust sheets contribute to the shear wave splitting because both basin margins are affected by intense local faulting and by large fracture fields related to the Quaternary normal fault systems [Italiano et al., 2001]. [26] The results of Figure 5 suggest that the shallow Quaternary faults play a major role on the observed wavefield polarization. There are several features in favor of this inference. First, polarization generally tends to be nearly perpendicular to the strike of the large Quaternary normal faults (EAFS and MMFS). Second, seismic stations with isotropic polarization pattern (AG03, AG19, and AG10) are the farthest from the basin-bounding normal faults. Finally, the counterclockwise rotation of the polarization directions agrees with the similar rotation of the strike of the two
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normal-fault bordering systems (see Figure 1). The mean polarization rotates from N56° to N32° along station alignment AG12, AG04, and AG11 on the eastern margin of the basin and from N70° to N35° along alignment AG07, AG13, AG18, AG09, and AG14 on the western margin (Figure 5). [27] Moreover, horizontal polarization is independent of local geology of recording sites, seismic stations with narrow polarization histograms being located on different sedimentary units (Figure 1) including pelagic silicic limestones (AG06), cherts (AG08, AG12, AG15), and upper Miocene sandstones (AG09, AG11, AG14, AG20). Specifically, stations AG10 and AG11 show a very different polarization pattern even though they were both installed on the same geological formation (upper Miocene sandstones). The main difference consists in the distance from the closest Quaternary faults, AG11 being installed very close to a Quaternary normal fault while AG10 being located about 7 km from the eastern termination of the EAFS (Figure 1). [28] Our conclusion is that the primary source of polarization is the shallow, persistent fracture fields of the Quaternary normal faults. The amplified frequency bands are likely related to the wavelengths affected by the size of the fractured volumes, and the H/V amplitude is proportional to the fracture density. Although Pastori et al. [2009, 2012] interpret seismic anisotropy in terms of EDA model, they do not exclude the role of Quaternary normal faults. The common link between the two observed phenomena is the Quaternary extensional regime. It controlled both the evolution of the basin-bounding faults associated to thick damage zones [Cello et al., 2003] and aligns open and fluid-filled cracks that pervade the Apulian carbonates throughout the region [Trice, 1999; Shiner et al., 2004]. [29] Finally, we stress that the two methods are independent and applied to different parts of the seismic signal: S wave splitting uses the direct S arrival (a time window of the order of a fraction of seconds) conveying information on the direct source-to-receiver path, whereas the rose diagrams of polarization are mostly controlled by coda waves, i.e., the scattered wavefield. In a controlled-source experiment, Di Giulio et al. [2013] found that in the fault zone, observed polarization can be different from the one excited by a vibratory machine at distances as small as 50 m. They interpreted the change of polarization as due to shallow mechanisms of scattering and mode conversion related to heterogeneities of the predominantly oriented fracture field. A shallow origin of persistent site polarization is also confirmed by the similarity of results found using earthquake records and ambient noise [see Rigano et al., 2008; Di Giulio et al., 2009; Falsaperla et al., 2010]. Figure 7 suggests that also for the Val d’Agri stations, ambient noise and earthquake records yield consistent results, confirming a shallow origin of the polarization mechanism. In particular, Figure 7 highlights a good consistency in HVSRs between seismic events and ambient noise at stations where a marked directional effect is recognized (AG08 and AG13). HVSRs of ambient noise and seismic earthquakes consistently do not show more than a single peaked direction at station AG03 with isotropic rose diagrams in Figure 5. [30] Thus, S wave splitting and wavefield polarization are sensitive to different rock volumes. Cracks and fractures in the carbonate formations crossed in the direct source-to-receiver path mainly influence S wave splitting; shallow fracture orientation controls horizontal polarization revealed by the scattered wavefield. The finding of a consistent orthogonal relation as
shown by Figure 6 is an indication that shallow fractures of the fault zone and the deeper fractures of carbonate rocks maintain the same attitude.
6.
Concluding Remarks
[31] A polarization analysis on seismograms of rock stations in the Val d’Agri area has revealed a persistent wavefield polarization. The predominant polarization is oriented NE-SW. This direction is orthogonal to the general trend of Quaternary normal faults bordering the graben and to the maximum horizontal stress related to the present extensional regime. Similar to previous studies [Rigano et al., 2008; Di Giulio et al., 2009; Pischiutta et al., 2012, 2013], the strong polarization effect has been interpreted in terms of fracture fields that make the rock more compliant in the strike-transverse direction. [32] In the same area, the fast S wave direction is parallel to the general trend of Quaternary normal faults and to the direction of the maximum horizontal stress as illustrated by Pastori et al. [2009, 2012]. This is consistent with other active stress indicators such as borehole breakout and T axis of focal mechanisms. We have found that in the Val d’Agri area, wavefield polarization and fast S wave direction tend to be orthogonal. We conclude that polarization and shear wave splitting are produced by the same cause: the existence of an anisotropic medium represented by sedimentary rocks with large fracture systems related to the polyphasic tectonic evolution of the southern Apennines. Such fractures make the medium more compliant perpendicularly to their strike. [33] If polarization and S wave splitting analysis give complementary information on crustal anisotropy and local stress field, the study of polarization can be a useful tool when S wave splitting analysis is prevented by the lack of recording with small incidence angles due to an inadequate network-event distribution. Moreover, polarization is faster to be computed, and its estimate is more stable and robust. [34] Acknowledgments. We gratefully acknowledge Luisa Valoroso for providing us seismic data recorded by the temporary network and 3-D hypocentral locations. Special thanks are due to Martha Savage for very useful discussions. Finally, we thank the Guest Editor and two anonymous reviewers for their thorough reviews that improved the manuscript.
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