Rayleigh-Wave, Group-Velocity Tomography of the Borborema Province, NE Brazil, from Ambient Seismic Noise

Pure Appl. Geophys. Ó 2014 Springer Basel DOI 10.1007/s00024-014-0982-9 Pure and Applied Geophysics

1 1,2 3 RAFAELA CARREIRO DIAS, JORDI JULIA` , and MARTIN SCHIMMEL

Abstract—Ambient seismic noise has traditionally been Key words: Seismic interferometry, Ambient seismic noise, regarded as an unwanted perturbation that ‘‘contaminates’’ earth- Rayleigh-wave dispersion, surface wave tomography, Borborema quake data. Over the last decade, however, it has been shown that Province. consistent information about subsurface structure can be extracted from ambient seismic noise. By cross-correlation of noise simultaneously recorded at two seismic stations, the empirical Green’s function for the propagating medium between them can be reconstructed. Moreover, for periods less than 30 s the seismic spectrum of ambient noise is dominated by microseismic energy and, 1. Introduction because microseismic energy travels mostly as surface-waves, the reconstruction of the empirical Green’s function is usually pro- Seismic noise has traditionally been regarded as portional to the surface-wave portion of the seismic wavefield. In this paper, we present 333 empirical Green’s functions obtained an unwanted signal in seismic recordings of the from stacked cross-correlations of one month of vertical compo- Earth’s ground motion and has frequently been nent ambient seismic noise for different pairs of seismic stations in omitted from detailed analysis. In recent years, the Borborema Province of NE Brazil. The empirical Green’s however, it has been shown that the empirical functions show that the signal obtained is dominated by Rayleigh waves and that dispersion velocities can be measured reliably for Green’s function of the propagating medium between periods between 5 and 20 s. The study includes permanent stations two points can be reconstructed by cross-correlating from a monitoring seismic network and temporary stations from seismic noise recorded simultaneously at those two past passive experiments in the region, resulting in a combined network of 34 stations separated by distances between approxi- points (LOBKIS and WEAVER 2001;CAMPILLO and PAUL mately 40 and 1,287 km. Fundamental-mode group velocities were 2003;SHAPIRO and CAMPILLO 2004;SNIEDER 2004; obtained for all station pairs and then tomographically inverted to SHAPIRO et al. 2005). Similar to recorded seismo- produce maps of group velocity variation. For short periods (5–10 s) the tomographic maps correlate well with surface geology, grams, cross-correlations of ambient seismic noise with slow velocities delineating the main rift basins (Potiguar, contain information about the distribution of seismic Tucano, and Recoˆncavo) and fast velocities delineating the location velocities within the propagating medium, and ana- of the Precambrian Saõ Francisco craton and the Rio Grande do lysis of ambient noise cross-correlations is now Norte domain. For longer periods (15–20 s) most of the velocity anomalies fade away, and only those associated with the deep routinely used to infer subsurface velocity structure Tucano basin and the Saõ Francisco craton remain. The fading of (SHAPIRO et al. 2005;SABRA et al. 2005;MOTTAGHI the Rio Grande do Norte domain fast-velocity anomaly suggests et al. 2013). Moreover, because ambient noise pro- this is a supracrustal structure rather than a lithospheric terrain, and places new constraints on the Precambrian evolution of the files are dominated by microseismic peaks at Borborema Province. approximately 0.05–0.10 and 0.1–0.2 Hz, and mi- croseisms propagate predominantly as Rayleigh waves (LACOSS et al. 1969;FRIEDRICH et al. 1998; BROMIRSKI 2001;BROMIRSKI and DUENNEBIER 2002; STEHLY et al. 2006), results from cross-correlation of 1 Programa de Po´s-Graduaçaõ em Geodinaˆmica e Geofı´sica, Universidade Federal do Rio Grande do Norte, Natal, Brazil. seismic ambient noise are dominated by the surface- E-mail: [email protected]; jordi@geofisica.ufrn.br wave portion of the Green’s function within those 2 Departamento de Geofı´sica, Universidade Federal do Rio frequency ranges. Dispersion velocities can thus be Grande do Norte, Natal, Brazil. 3 Institut de Cie`ncies de la Terra ‘‘Jaume Almera’’, Centro measured in the cross-correlated time-series and, if Superior de Investigaciones Cientı´ficas, Barcelona, Spain. enough stations are available, tomographic inversion R. C. Dias et al. Pure Appl. Geophys. can be used to develop images of dispersion velocity was considered, which led to the emergence of variation (SHAPIRO et al. 2005;SABRA et al. 2005; Rayleigh waves in the reconstructed empirical VILLASEN˜ OR et al. 2007;BENSEN et al. 2008;MOT- Green’s functions. After obtaining the empirical TAGHI et al. 2013). Green’s functions, group velocities were measured on In the work reported here ambient noise tomog- the cross-correlated time series by using the multiple raphy was used to develop high-resolution filtering analysis (MFA) of DZIEWONSKI et al. (1969) tomographic images of fundamental-mode, Rayleigh- for periods between 5 and 20 s. Tomographic maps wave, group-velocities for the Borborema Province of lateral group-velocity variation were developed by of NE Brazil, with the objective of mapping shallow, using the fast marching surface tomography (FMST) sub-surface velocity variations in the region. Surface- inversion procedure of RAWLINSON (2005), which wave tomographic images of the Borborema Province combines the fast marching method (FMM) of published so far are only available from a few con- RAWLINSON and SAMBRIDGE (2005) for forward com- tinental-scale studies of South America (FENG 2004; putation of surface-wave group delays with the FENG et al. 2007;LLOYD et al. 2010;ASSUMPÇA˜ O iterative subspace inversion scheme of KENNETT et al. et al. 2013), and are of low-resolution in the Province (1988) to map lateral variations in group velocity. because of the limited data available for the region. In Geologically, the Borborema Province is a struc- recent years, however, the Borborema Province has tural domain located in the northeastern-most corner been the focus of large multi-institutional, inter-dis- of South America (Fig. 1). It is characterized by ciplinary projects. Those include the Institutos do complex tectonic evolution that began during Pre- Mileˆnio—Tectonic and Geophysical Studies in the cambrian times and extended into the Cenozoic Borborema Province and the Instituto Nacional de (ALMEIDA et al. 1981, 2000;SANTOS et al. 2000;BRITO Cieˆncia e Tecnologia para Estudos Tectoˆ nicos NEVES and CORDANI 1991;TROMPETTE 1994). The (INCT-ET), both funded by the Brazilian Centro Province is criss-crossed by several east–west and Nacional de Desenvolvimento Cientı´fico e Tec- northeast–southwest trending shear-zones, suggested nolo´gico (CNPq), which deployed several temporary as marking the boundaries of smaller tectonic terrains broadband networks in the region. Moreover, since that amalgamated during the Brasiliano–Pan African 2011, the seismicity in NE Brazil has been monitored orogeny (BRITO NEVES and CORDANI 1991;JARDIM DE by use of the Rede Sismogra´fica do Nordeste SA´ et al. 1992;CORDANI et al. 2003). Some authors, (RSISNE), a permanent network of 16 broadband however, regard them as the surface expression of stations supported by the Brazilian oil company supracrustal deformations overlying a mostly coher- Petrobras. In total, the combined network of perma- ent Early Proterozoic basement (NEVES 2003;NEVES nent and temporary stations now available in the et al. 2000, 2006). Because of extension during con- Borborema Province and surrounding regions continental breakup in Mesozoic times, a number of rift sists of 34 broadband stations with inter-station basins, now aborted, formed in the continental inte- distances between 40 and 1,287 km, approximately. riors. These include the Potiguar basin to the north, the This dramatic increase in the seismic coverage of the Araripe basin to the center-west, and the Tucano, Ja- Borborema Province provides a unique opportunity toba´, and Recoˆncavo basins to the south, with smaller for passive imaging of the Province’s subsurface rift basins scattered throughout the Province (Fig. 1). structure with unprecedented detail. Evolution of the province in the Cenozoic was marked Our study includes 333 cross-correlations by episodes of intraplate volcanism and uplift (MIZU- obtained from 1 month of continuous seismic noise SAKI et al. 2002;MORAIS NETO et al. 2009), which are recordings at several pairs of broadband stations in probably related to magmatic upwellings originating NE Brazil. For each station pair, multiple correlations from upper mantle sources (USSAMI et al. 1999; were obtained at one-day intervals and then stacked KNESEL et al. 2011;OLIVEIRA and MEDEIROS 2012; by using the time–frequency, phase-weighted meth- PINHEIRO and JULIA` 2014). odology of SCHIMMEL and GALLART (2007). Only the For short periods (5–10 s) our tomographic ima- vertical component of the seismic noise recordings ges clearly outline the major intra-continental rift Group-Velocity Tomography of the Borborema Province

Figure 1 Topographic map of the Borborema Province and surrounding physiographic provinces with its Precambrian domains, Mesozoic rift-basins, and shear-zones superimposed. Cenozoic volcanic features along the Fernando de Noronha-Mecejana alignment (FNMA) and the Macau- Queimadas alignment (MQA) are also indicated. Adapted from DE CASTRO et al. (2008), OLIVEIRA (2008), and KNESEL et al. (2011) basins with slower-than-average group velocities. For overall lack of correlation between surface geology longer periods (15–20 s) the anomaly associated with and group velocity variation for longer periods, the Potiguar basin fades away, as expected from the throughout the Province, suggest the Precambrian shallow depth-extent of the basin, whereas the domains making up the Borborema Province may not anomaly associated with the Tucano–Recoˆncavo rift continue at depth. system remains. The Tucano–Recoˆncavo rift system is overlain by a thick layer of slow-velocity sedimentary rocks, and the persistence of the anomaly 2. Geology and Tectonic Setting probably reflects leaking of the sedimentary structure into the longer-period dispersion velocities. Perhaps The Borborema Province is located in the north- more interestingly, high-velocity anomalies are also eastern most corner of the South American continent. observed for shorter periods, approximately coincid- It is limited by the Saõ Francisco craton to the south, ing with the geologic outlines of the Saõ Francisco the Parnaı´ba Basin to the west, and several marginal craton and the Rio Grande do Norte domain of the sedimentary basins to the north and east (ALMEIDA Borborema Province. For longer periods, the high- et al. 1981, 2000; Fig. 1). It is regarded as a complex velocity anomaly associated with the Saõ Francisco orogenic system that was severely affected by craton is still observable, consistent with the litho- deformational, metamorphic, and magmatic pro- spheric scale of this terrain at depth. The high- cesses during the Braziliano/Pan-African orogenic velocity anomaly associated with the Rio Grande do cycle at 850–500 Ma (SANTOS et al. 2010). The Norte domain, on the other hand, fades away com- varying geological and geophysical characteristics of pletely, suggesting this domain does not extend into the crustal blocks that make up the Borborema the deep crust. The fading of this anomaly, with the Province led to its subdivision into five tectonic R. C. Dias et al. Pure Appl. Geophys. domains, separated by shear zones (JARDIM DE SA´ metamorphosed during the Brasiliano orogeny (NE- et al. 1992;CAMPELO 1999;SANTOS and MEDEIROS VES 2003;NEVES et al. 2006). 1999;OLIVEIRA 2008): the External or South Domain, In Paleozoic times, with the Gondwana Super- the Transversal or Central Zone, the Rio Grande do continent already formed, the Parnaı´ba Basin Norte Domain, the Ceara´ Domain, and the Me´dio developed in the interior of the continent, and its area Coreau´ Domain. The boundary between the South of sedimentation expanded on to the Province (OLI- and Central domains is given by the Pernambuco VEIRA 2008). In the Mesozoic, continental breakup led Lineament, and the Patos Lineament separates the to the shaping of the continental margins of the Central Zone from the Rio Grande do Norte Domain. Province and the formation of marginal and interior The limit between the Ceara´ Domain and the Me´dio rift basins (MATOS 1992). A system of rifts in the Coreau´ Domain is given by the Transbrasiliano Lin- Atlantic Ocean gave origin to the marginal basins eament (locally, Sobral-Pedro II Shear Zone), a along the Equatorial and Eastern margins of the continental-scale lineament that can be traced into Province (MATOS 1999), with most of the extensional West Africa in paleo-geographic reconstructions. The events marked by the occurrence of semi-grabens Ceara´ Domain is limited in the east by the Rio distributed along three main axes of deformation: Grande do Norte Domain along the Jaguaribe–Tata- Gabaõ–Sergipe–Alagoas, Cariri–Potiguar, and Rec- juba Lineament, and in the west by the oˆncavo–Tucano–Jatoba´. The final breakup of the Transbrasiliano Lineament (OLIVEIRA 2008). The West African and Saõ Luis cratons caused the Rec- tectonic domains are displayed in Fig. 1. oˆncavo–Tucano–Jatoba´ and Cariri–Potiguar rift The Borborema Province had a complex geo- systems to abort, and the Gabaõ–Sergipe–Alagoas logical evolution in the Precambrian that resulted trend to evolve into a phase of continental breakup from the Brasiliano/Pan-African orogenic cycle. (OLIVEIRA 2008). During this cycle, amalgamation of different conti- After continental breakup, the evolution of the nents and the closing of paleo-oceans led to the Province in the Cenozoic was marked by episodes of formation of Gondwanaland at the end of the Neo- volcanism (ALMEIDA et al. 1988;MIZUSAKI et al. proterozoic and early Paleozoic (*950–450 Ma) 2002;KNESEL et al. 2011) and uplift of the Borbor- (BRITO NEVES and CORDANI 1991;TROMPETTE 1994). ema Plateau (JARDIM DE SA´ et al. 1999; 2005; In particular, West Gondwana was formed by OLIVEIRA 2008;OLIVEIRA and MEDEIROS 2012). Vol- amalgamation of the Amazonian, West-African, Rio canism occurs along two mutually orthogonal de La Plata, Congo-Saõ Francisco and Kalahari alignments: the Fernando de Noronha-Mecejana cratons at *600 Ma. Considering this background, alignment (FNMA), mostly off-shore and trending some authors regard the Borborema Province as the east–west, and the Macau-Queimadas alignment result of amalgamation of several micro-plates and (MQA), on-shore and approximately trending north– oceanic island-arcs that were located between the south. Cenozoic volcanism and uplift was initially West-African craton to the north and the Congo-Saõ explained as resulting from passage of the Province Francisco craton to the south (BRITO NEVES and above one or more mantle plumes (ALMEIDA et al. CORDANI 1991;JARDIM DE SA´ 1994;CORDANI et al. 1988;JARDIM DE SA´ et al. 1999;JARDIM DE SA´ 2001; 2003), with the main shear zones that pervade the MIZUSAKI et al. 2002). The orthogonal arrangement Province marking the boundaries of the accreted of the alignments, the low-volume and long-lived terrains. In contrast with this accretionary model, character of the volcanism, and their lack of a clear some researchers argue that the Borborema Province age progression, however, have led to suggestions was part of a larger tectonic block that remained that such magmatism was the result of small-scale consolidated since 2.0 Ga (NEVES 2003;NEVES et al. convection at the cratonic edge (KNESEL et al. 2011). 2006). In this alternative model, the Borborema The causes of uplift in the Province have been Province would be regarded as a fold belt of the associated with magmatic underplates at the base of Archean and Paleoproterozoic basement overlain by the Borborema crust from melts derived from litho- Neoproterozoic sediments that were deformed and spheric erosion by the small-scale convection cell Group-Velocity Tomography of the Borborema Province

Figure 2 Illustration of pre-processing steps with ambient seismic noise recordings at station LP05. a Raw data (top), one-bit normalization (middle), and spectral whitening (bottom) for a 1-day-long time series recorded on the vertical component of station LP05. Left panels display the time series, and right panels display the corresponding amplitude spectra. The 1-day-long time series was recorded on 01/23/2013. b Comparison of the original (raw) and pre-processed (one bit ? whitening) ambient noise recording at station LP05. Note how the spurious signals (earthquakes) in the original waveform disappear after the pre-processing steps R. C. Dias et al. Pure Appl. Geophys.

(OLIVEIRA and MEDEIROS 2012). Alternative mecha- normalization has been successfully used in seismic nisms for plateau uplift have been proposed, interferometry studies with both coda waves and including thickening of the crust after depth-depen- ambient seismic noise (CAMPILLO and PAUL 2003; dent stretching of the lithosphere (MORAIS NETO et al. SHAPIRO and CAMPILLO 2004;SHAPIRO et al. 2005), 2009) and thermal doming from a low-density body and resulted in a clearly apparent increase in signal- in the upper mantle (USSAMI et al. 1999). to-noise ratio in acoustic laboratory experiments (LAROSE et al. 2004). Spectral whitening consists in normalizing the amplitude spectrum to a unit value without changing the phase of the signal. The purpose 3. Empirical Green’s Functions of spectral whitening is to improve the relative weight of the low-amplitude frequency components. 3.1. Data Pre-Processing Figure 2a shows an example of ambient seismic The purpose of the data pre-processing step is noise recorded at station LP05 on January 23, 2013. removal of unwanted signals, for example earth- The left-hand panels show the raw, one-bit normal- quakes and instrumental artifacts, from the seismic ized, and spectrum-whitened time series, and the recordings, to enhance the proﬁle of ambient seismic right-hand panels display the corresponding ampli- noise. First, for each station, continuous data were cut tude spectra for each of the time-series. The effect of into 24-h long segments and the corresponding time the one-bit normalization is clearly visible in the time series were decimated to 10 samples/s, to reduce data domain, and the effect of spectral normalization size and equalize sampling rates among seismic appears in the frequency domain. The spectral stations. The decimated, 24-h-long segments were normalization reduces imbalances in the amplitude then demeaned, detrended, and tapered with a 5 % spectrum of the cross-correlation that enable the cosine window. As recording equipment varied emergence of an empirical Green’s function with a among the stations, instrument responses were broad frequency content. The raw time series and the removed from continuous waveform data and then time–frequency normalized time series are compared band-pass ﬁltered in the 0.01–1.0 Hz frequency range in Fig. 2b, which reveals removal of the spurious to equalize the time series. Second, time–frequency signals within the 24-h-long time window. normalization (CUPILLARD and CAPDEVILLE 2010) was applied to remove earthquakes, instrumental irregu- 3.2. Cross-Correlation and Stacking larities, and other non-stationary noise sources near the stations that inevitably entered the seismic The next step in the data processing is calculation recordings. Time-domain normalization consisted of of the daily cross-correlations for each station pair in constructing one-bit normalized signals from the 24-h the study area and their stack, to retrieve the long data segments, and the frequency-domain nor- corresponding empirical Green’s functions from the malization consisted of whitening the amplitude ambient seismic noise. Cross-correlation integrals spectrum of the one-bit normalized time series were computed in the frequency domain for each day (LAROSE et al. 2004;SHAPIRO and CAMPILLO 2004; and station pair for time lags between -400 and BENSEN et al. 2007;CUPILLARD and CAPDEVILLE 2010; 400 s, which encloses the dispersed surface-wave SCHIMMEL et al. 2011). train at the longest inter-station distances. All station The one-bit normalization consists in equalizing pairs had 31-days-long time series of overlapping all amplitudes in the time series to a unit value, while ambient seismic noise recordings. keeping the positive or negative polarity of the Stacking of the daily cross-correlations was originally recorded amplitude (CUPILLARD and CAPDE- achieved by use of the time–frequency, phase- VILLE 2010). Even though BENSEN et al. (2007) weighted stacking (tf-PWS) procedure of SCHIMMEL believe one-bit normalization to be the most aggres- and GALLART (2007). This procedure is an extension sive of a range of normalization methods, we found it of the phase-weighted stacking (PWS) of SCHIMMEL worked acceptably well with our dataset. One-bit and PAULSSEN (1997), in which each sample of a Group-Velocity Tomography of the Borborema Province

Figure 3 Examples of 31-day-long stacks of ambient noise cross-correlations between stations NBPE and NBPS (left) and NBLI and NBPI (right). Note how the empirical Green’s function emerges on the causal portion of the time-series. The top traces were obtained by use of the extended phase weight stacking (tf-PWS) procedure of SCHIMMEL and GALLART (2007) whereas the bottom traces correspond to unweighted point-to- point stacks. Note how the tf-PWS procedure improves the signal-to-noise ratio of the empirical Green’s function linear stack is weighted by a coherence measure By analogy, the extended tf-PWS is expressed as: independent of amplitude. The weights of the PWS can be expressed as: ptfðs; f Þ¼S1sðs; f Þctfðs; f Þ m XN ipf s XN m 1 S ðs; f Þe 1 ¼ S ðs; f Þ j ; ð3Þ cðtÞ¼ ei/jðtÞ ; ð1Þ 1s N S ðs; f Þ N J¼1 j j¼1 where S (s, f)istheS-transform (STOCKWELL et al. where c(t) is the phase stack, N the number of traces j 1996;SCHIMMEL and GALLART 2005;SCHIMMEL used, j is an index that enumerates the N traces used, et al. 2011)ofthejth time-series and S1s(s, f)is /(t) the instantaneous phase (BRACEWELL 1965), and m the S-transform of the linear stacking of all the is a variable for tuning the transition between N time-series (cross-correlograms). The phase coherent and less coherent signal summation. The coherence c (s, f) is used to downweight the amplitudes of the weights range between 0 and 1 as a tf incoherent portions of the linear stacking in the function of time. If the instantaneous phases of the time–frequency domain (SCHIMMEL et al. 2011). signals at a given time are coherent, the amplitude of Examples of 31-days-long stacks of ambient noise the weight is equal to unity, and zero amplitude cross-correlations, with and without the phase- means that the signals are incoherent. Stacking is then weighting scheme, are given in Fig. 3.Theﬁgure realized by use of the non-linear relationship: clearly illustrates the dramatic improvement in the m 1 XN 1 XN signal-to-noise ratio of the recovered empirical pðtÞ¼ s ðtÞ ei/jðtÞ ; ð2Þ N k N Green’s function achieved with the tf-PWS k¼1 j¼1 scheme of SCHIMMEL and GALLART (2007). It also where p(t) is the phase-weighted stack, s(t) the seis- displays the strong asymmetry of the empirical mic trace, N the number of traces used, j is an index Green’s functions, which probably reﬂects the that enumerates the N traces used, /(t) is the predominant direction of propagation of the instantaneous phase (BRACEWELL 1965), and m is a microseismic noise from the continental margins variable for tuning the transition between coherent toward the continental interiors (as discussed in and less coherent signal summation. the Sect. 3). R. C. Dias et al. Pure Appl. Geophys.

Figure 4 a Topographic map showing the location of the 34 broadband stations considered in this study. b Ray paths corresponding to the 333 station pairs for which an empirical Green’s function could be reconstructed. c Symmetric empirical Green’s functions (Rayleigh wave) sorted by interstation distance. The symmetric empirical Green’s functions were obtained from the causal and acausal portions after stacking of the forward and time-revered daily cross-correlations by use of the tf-PWS scheme of SCHIMMEL and GALLART (2007). The time series have been ﬁltered between 0.01 and 1.0 Hz for display purposes Group-Velocity Tomography of the Borborema Province

3.3. Empirical Green’s Functions stacked time-series, band-pass filtered in several frequency bands. Note how the wave trains consis- Phase-weighted stacks of daily cross-correlations tently emerge at all periods and that the emerged have been developed from 34 broadband stations in signal is dispersive, as expected. Northeast Brazil, resulting in a total of 333 empir- The cross-correlations displayed in Fig. 4c were ical Green’s functions sampling the Borborema constructed by stacking both the causal and acausal Province and neighboring regions. The broadband portions of the daily cross-correlations together stations are equipped with either RefTek-120A or through the extended phase-weighted procedure Streckheisen STS-2 sensors, with a flat velocity described in the Sect. 3.2, after time-reversing the response between 120 s and 50 Hz, feeding high- acausal portion of the daily cross-correlations. In gain digitizers (Reftek RT-130 or Quanterra Q330), fact, because of their dependence on the location of sampling continuously at 100 samples/s and with the noise sources, the causal and acausal portions GPS timekeeping. The empirical Green’s functions of the cross-correlation differ in amplitude (Fig. 3). are displayed in Fig. 4, with the location of the If the sources of ambient seismic noise were broadband stations and the interstation ray paths homogeneously distributed in azimuth, the causal associated with the empirical Green’s functions. The and acausal parts of the Green’s functions would be cross-correlation stacks were obtained from the symmetric with respect to the arrival time. If, vertical component of the ambient seismic noise however, the density of sources is larger on one of only, and have been band-pass filtered between 0.01 the sides than on the other, the amount of energy and 1.0 Hz for displaying purposes. Distances range propagating in both directions will be different. In from approximately 40 km to slightly over this case, the Green’s functions are asymmetric. 1,287 km. Short-period Rayleigh waves clearly According to SABRA et al. (2005), and given the emerge from the ambient seismic noise, although proximity of our network to the coast, it is the signal is somewhat obscured at long distances expected that the Green’s functions for station because of attenuation. The dispersive character of pairs oriented perpendicular and close to the coast the Rayleigh waves recovered from the cross- will emerge more clearly than those for station correlation stacks is illustrated in Fig. 5 for the pairs oriented parallel and further inland. NBIT–NBPS station pair. The figure shows the

Figure 5 Empirical Green’s functions for the NBIT–NBPS station pair, ﬁltered at different frequency bands. Note the dispersive character of the recovered Rayleigh wave trains. The frequency bands are noted to the right of each frame, in Hz R. C. Dias et al. Pure Appl. Geophys.

4. Measuring Group Velocity the surface waves. To isolate the fundamental mode a phase-matched filter is used (HERRIN and GOFORTH Group velocities for the fundamental mode of the 1977). The isolation filter C(x) is constructed in Rayleigh waves reconstructed in the stacked cross- accordance with the expression: correlations were determined by using the MFA of CðxÞ¼expfihðxÞg; ð4Þ DZIEWONSKI et al. (1969), as implemented in the Computer Programs in Seismology package of where h(x) is the integral of the group delay given HERRMANN and AMMON (2002). The MFA procedure by: analyzes variations of signal amplitudes as a function Zx of velocity and period and it has its theoretical basis hðxÞ¼ tgðxÞdx; ð5Þ in the use of a Gaussian filter to isolate the wave 0 package around the central period of the filter. The width of the Gaussian filter is chosen according to and where tg is the group delay. epicentral distance (or, in our case, inter-station dis- Group velocities were measured for the 333 tance) to minimize the area of the fundamental mode stacked cross-correlations obtained from the ambient in the group velocity-period profile surface (AMMON seismic noise recorded at 34 broadband stations in the 2001). Consequently, this width parameter controls Borborema Province (discussed in the Sect. 3.3). As the resolution of the group velocity measurement, and only the vertical component of the recordings was the group velocity for each frequency can be calcu- used, the dispersion measurements correspond to lated by dividing the distance between the stations by Rayleigh waves. Period was chosen to range from 1 the group delay (maximum of the filtered wave- to 30 s and group velocity between 2 and 5 km/s. package envelope). Inter-station distances ranged from 40 to 1,287 km The group velocity-period profile surface con- and the filter width varied between 3 and 50, in structed by use of the MFA may have contours accordance with the linear relationship given in contaminated, for example, with the higher modes of HERRMANN and AMMON (2002). A first run of

Figure 6 Examples of reliable (left) and unreliable (right) multiple-ﬁlter analysis (MFA) surfaces for empirical Green’s functions obtained in this study. Note how the dispersion curve is clearly delineated along the maximum values of the MFA surface in the left panel for periods under 20 s, whereas no clear maximum can be observed on the MFA surface in the right panel Group-Velocity Tomography of the Borborema Province

Figure 7 Sequential stacks of 10, 20, and 31 daily cross-correlations (left) and corresponding dispersion curves obtained through multiple-filter analysis (MFA) (right) for short (a), intermediate (b), and long (c) interstation distances. Note the rapid convergence of the cross-correlation stacks into the empirical Green’s functions, and the stability of the corresponding dispersion curves in the 5–20 s period range R. C. Dias et al. Pure Appl. Geophys. measurements was done on the raw empirical Green’s are at least three wavelengths long when measuring function waveforms and, using the preliminary fun- dispersion velocities for a given period (FENG et al. damental-mode, group-delays thus obtained, a phase- 2004;VILLASEN˜ OR et al. 2007). Therefore, to ensure matched filter was constructed. The empirical stability of the group-velocity measurements in our Green’s functions were then filtered with the con- study, we adopted the same minimum wavelength structed phase-match filter to isolate the fundamental criterion as in surface-wave tomography studies. mode and a new run was applied to the filtered Finally, the stability of the measured dispersion waveforms to obtain the final set of group velocity curves was further tested by producing empirical measurements. Green’s functions at three select station pairs from A strict quality-control procedure was imple- ambient seismic noise recorded during three different mented to identify and reject bad group-velocity measurements. First, dispersion velocities were measured from the stacked cross-correlations only along well-defined ridges along the MFA contour plots (Fig. 6). Second, the period-range of stability for the measured group velocities was investigated by stacking daily cross-correlations for progressively increasing periods of time of 10, 20, and 31 days at three select station pairs and superimposing the measured dispersion curves. The investigation is shown in Fig. 7, and demonstrates that the empirical Green’s function waveforms stabilize after stacking 20 daily cross-correlations, and that 20 days are generally enough for consistently measuring dispersion velocities up to 20 s for the entire interstation distance range. Recall that microseismic energy decays abruptly for periods longer than 20 s (BRO- MIRSKI 2009), which probably explains why group- velocity measurements for the longer periods are more scattered. Thus, group-velocity measurements for periods longer than 20 s were not considered in our study. Third, we adopted a minimum wavelength criterion for group-velocity measurements. Close inspection of Fig. 7 reveals that the stability of the period range in the dispersion curves is slightly dependent on interstation distance. Note that the period-range of stability seems to grow to 24 s for LP03–NBAN (597 km) and to 27 s for NBIT–NBPS (1,188 km). This dependence probably reflects the increasing separation of the harmonic components making up the surface-wave train with increasing interstation distance, which facilitates their isolation Figure 8 by the narrow-band Gaussian filtering utilized during Dispersion curves measured on 31-day-long cross-correlation the construction of the MFA envelopes. For this stacks for short (a), intermediate (b), and long (c) inter-station distances, superimposed for three different months during 2013. reason, many surface-wave and ambient noise Note the stability of the dispersion curves below 20 s, despite small tomography studies require interstation distances that differences (\0.1 km/s) depending on the time of the year Group-Velocity Tomography of the Borborema Province months of the year. The measured dispersion curves points in the mesh, so there is no need to repeat the are superimposed in Fig. 8, which shows that dis- calculations for every single ray path. To solve the persion velocities up to 20 s period differ slightly inverse problem, a subspace inversion scheme is used (\0.1 km/s) with the month of the year. Because such (KENNETT et al. 1988) that reduces computational differences are likely to result from variations in the effort during the inversion by expansion of the model location of the noise sources during the year, dis- space. Moreover, the inversion strategy follows an persion velocity anomalies that are 0.1 km/s or less in iterative, linear scheme where the ray paths are re- the tomographic maps may not be reliable. computed after each model update, effectively accounting for the non-linearity of the forward problem. The combination of the two steps provides 5. Lateral Variation of Group-Velocity stable and robust results, even in heterogeneous, strongly varying media (RAWLINSON et al. 2010). To obtain tomographic images for fundamental- More specifically, the inverse problem is formu- mode, Rayleigh-wave, group-velocity variations in lated as an optimization problem where it is the Borborema Province we used the FMST scheme necessary to minimize the objective function S(m) given by: of RAWLINSON (2005). The FMST is implemented T 1 iteratively in two steps: (i) prediction of travel-times SðmÞ¼ðgðmÞdobsÞ Cd ðgðmÞdobs (forward problem); and (ii) adjustment of the model T 1 T T þ eðm m0Þ Cm ðm m0Þþgm D Dm; parameters that satisfy the data, with regularization ð6Þ constraints (inverse problem). To solve the forward problem, the FMM (SETHIAN where m is the unknown vector of model parameters,

1996;SETHIAN and POPOVICI 1999;RAWLINSON and dobs the observed travel-time (group-delay) data, SAMBRIDGE 2005) is applied. The method finds the g(m) contains the predicted travel-times, m0 the ini- solution to the eikonal equation using finite differ- tial or reference model, Cd the data covariance ences within a pre-determined grid, to construct the matrix, Cm the model covariance matrix, e the wave fronts from the phase delays (RAWLINSON and damping variable, g the smoothing variable, and SAMBRIDGE 2005). The most important advantage of D the smoothness matrix. The first term in Eq. (6) this method over more traditional ray-tracing meth- represents a weighted misfit between data and ods is that travel-times are computed for all the grid observations, the second term is a regularization term

Figure 9 Trade-off curves between root-mean-square (RMS) misfit and model roughness (a), RMS misfit and model variance (b), and variation of RMS misfit with iteration number (c). The curves show that the optimum balance between RMS misfit and model roughness, and between RMS misfit and model variance is achieved for regularization terms of g = 840 (smoothness) and e = 140 (damping), respectively, and that the tomographic inversions converge after six iterations for the selected regularization terms. All curves are shown for inversions of group- velocities for periods of 5 and 20 s R. C. Dias et al. Pure Appl. Geophys.

Figure 10 Group velocity tomography maps developed for T = 5, 10, 15, and 20 s for the Borborema Province and surrounding areas. Slow-velocity anomalies correlate with Mesozoic rift basins, while fast-velocity anomalies correlate with the Rio Grande do Norte domain and the sampled portion of the Sa˜o Francisco craton for short periods (5–10 s). Note how the fast-velocity anomaly corresponding to the Rio Grande do Norte domain fades away for longer periods (15–20 s), along with the slow-velocity anomalies associated with the rift basins that penalizes models that differ substantially from lateral velocity variations against models with more the initial or reference model (RAWLINSON and SAM- abrupt variations. BRIDGE 2005), and the third term is another The FMST procedure was applied to the selected regularization term to favor models with smooth group-velocity measurements in the 5–20 s period Group-Velocity Tomography of the Borborema Province

Figure 11 Noise-contaminated checkerboard tests for tomographic inversions for periods of 5 s (top) and 20 s (bottom). Ray-path coverage, initial checkerboard models, and recovered models are shown in the left, middle, and right panels, respectively. Note the excellent recovery of the starting checkerboard cells for 5 s and the degradation of the cells for the longest period. All checkerboard inversions were performed with the same node spacing as the 0.5° 9 0.5° grid used in the tomographic maps of Fig. 10 range to produce maps of group velocity variation for 551 velocity nodes, and 2D group-velocity maps the fundamental-mode Rayleigh wave over a grid of were produced for periods of 5, 10, 15, and 20 s, with 0.5° 9 0.5° in the Borborema Province and sur- the damping variable equal to 140 and the smoothing rounding regions. The model is parameterized with variable equal to 840. The regularization terms were R. C. Dias et al. Pure Appl. Geophys. chosen after careful inspection of trade-off curves and 20 s, on the other hand, the well-developed between root-mean-square (RMS) misfit with respect anomalies in the Potiguar basin and the Rio Grande to model roughness and RMS with respect to model do Norte domain completely fade away whereas variance, where model roughness and model variance those in the Saõ Francisco craton and the Recoˆncavo– T T T -1 are defined as m D Dm and (m - m0) Cm (m - Tucano basin remain, although strongly attenuated. A m0), respectively (Eq. 6). The trade-off curves were faster-than-average velocity anomaly also develops at obtained for periods of 5 and 20 s for smoothness 20 s under the western half of the Araripe basin. varying between 1 and 9,000 (Fig. 9a) and damping The robustness of the tomographic maps was varying between 0.5 and 380 (Fig. 9b), and show that checked by use of a checkerboard test, displayed in the selected values (g = 840, e = 140) provide an Fig. 11, for periods of 5 and 20 s. The starting optimum balance between resolution and model checkerboard models were defined through a grid of roughness and model variance, respectively. An nodes with B-spline cubic interpolation, which pro- investigation of the number of iterations required to duces a continuous, smooth, and locally controlled achieve convergence was also performed by velocity medium. The corresponding synthetic inspecting the reduction in RMS misfit with the ‘‘dataset’’ for the starting velocity models was pro- number of iterations. The results are displayed in duced using the FMM procedure with the same inter- Fig. 9c, which shows that the reduction in RMS station ray-path pattern of the observed dataset misfit starts stabilizing after six iterations. Figure 9b (Fig. 11a, d), with addition of 20 % random noise to also shows that model variance decreases to an the synthetic data. The recovery of the starting model, average of *0.03 km2/s2 or, equivalently, an aver- obtained by using the same regularization terms and age standard deviation *0.2 km/s for the selected the same 0.5° 9 0.5° grid as for the tomographic regularization terms after six iterations. Average images in Fig. 10, is quite satisfactory for 5 s and standard deviations in our measured group velocities indicates overall good resolution for short periods. are in the 0.1–0.2 km/s velocity range for periods The recovery of the starting models for 20 s, on the between 5 and 20 s, demonstrating that the inverted other hand, is less satisfactory, especially across the tomography maps are close to the maximum resolv- western and southern portions, despite the increased ing power of the dataset. cell size. Comparing the ray-path coverage for both Tomographic maps of group-velocity variation periods, it seems quite clear that the decrease in are displayed in Fig. 10 for periods of 5, 10, 15, and resolution can be directly attributed to the sparser 20 s. A quick inspection of the maps reveals that the ray-path coverage across the poorly resolved regions variation in group-velocity correlates well with sur- for a period of 20 s. face geology for shorter periods (5–10 s) whereas the correlation degrades substantially for longer periods (15–20 s). In more in detail, tomographic maps for 6. Discussion 5 s show well-defined slow-velocity anomalies coinciding with the Potiguar basin in the north and The most important result revealed by the tomo- the Tucano–Recoˆncavo basins in the south, and well- graphic maps displayed in Fig. 10 is the strong developed fast-velocity anomalies coinciding with correlation of the group-velocity variations with the sampled portion of the Saõ Francisco craton and surface geology for short periods and the degradation with the Rio Grande do Norte domain, north of the of the correlation for longer periods. Part of the Patos Lineament. Weak fast-velocity anomalies also degradation can certainly be attributed to the decrease dominate across the Transversal and South domains, in the number of ray paths at 20 s, which probably and in the Coreau domain of the northwesternmost explains the strong attenuation of the fast-velocity corner of the Borborema Province and in the western anomaly under the Saõ Francisco craton and, perhaps, half of the Ceara´ domain. A similar pattern of slow the development of a fast velocity anomaly under the and fast velocity anomalies is observed in the tomo- western Araripe basin. Close inspection of the graphic maps for periods of 10 s. For periods of 15 checkerboard tests in Fig. 11 shows, nonetheless, that Group-Velocity Tomography of the Borborema Province recovery of the starting model East of the 40°W of surface geologic structures is consistent with the longitude is still good for 20 s, so a more geological association of the slow-velocity anomalies with the explanation must be sought in explain the fading of slow-velocity sediments filling the Potiguar and the slow-velocity anomalies under the rift basins and Recoˆncavo–Tucano basins. The Potiguar basin has the fast-velocity anomaly under the Rio Grande do maximum depths of approximately 6 km (PEDROSA Norte domain. et al. 2010) and its signature in the tomographic maps A possible explanation of the fading of the group- completely disappears for 15 s; the Recoˆncavo–Tu- velocity anomalies at longer periods is that short- cano basin is considerably deeper, approximately period surface-waves sample shallower depths than 12 km in its central portion (DA SILVA et al. 2003), long-period surface-waves. More specifically, sensi- and therefore its signature leaks slightly into the tivity kernels for fundamental-mode, Rayleigh-wave longer periods down to 20 s. The fading of the fast- group-velocities show that peak sensitivity for 5 s velocity anomaly associated with the Rio Grande do occurs at approximately 5 km depth whereas peak Norte domain, on the other hand, is more intriguing sensitivity for 20 s occurs lower—down to 20–25 km and would suggest the Patos Lineament marks the depth (TANIMOTO 1991). Thus, the correlation of the border between two supracrustal structures that do tomographic maps for 5 s with surface geology is not not have a continuation into the deep crust. surprising, because they are mostly sensitive to To further investigate the robustness of the fast- shallow velocity variations; correlation of 15–20 s velocity anomaly in the Rio Grande do Norte domain tomographic images with surface geology, on the for short periods we performed two additional other hand, would require a continuation of the sur- tomographic inversions with a perturbed dataset. face features at upper-to-mid crustal depths. Fading Figure 12a shows the tomographic map for 5 s of the anomalies because of the limited depth-extent obtained after removing the group-velocity

Figure 12 Tomographic maps of group-velocity variation for periods of 5 s on removal of the dispersion curve associated with the ray path connecting the stations on each side of the Rio Grande do Norte, fast-velocity anomaly (a), and on removal of all the dispersion curves associated with ray paths connecting either of the two stations on each side of the Rio Grande do Norte, fast-velocity anomaly (b). Note how the fast-velocity anomaly in the Rio Grande do Norte domain disappears on removal of the ray paths R. C. Dias et al. Pure Appl. Geophys. measurement for the ray path joining the two stations the boundaries of several continental fragments and flanking the fast-velocity anomaly in the Rio Grande microplates that amalgamated during the Pan Afri- do Norte domain to the East and West, respectively can–Brasiliano orogenic cycles. In that context, these (PFBR and SLBR). The anomaly disappears, clearly shear zones must be regarded as major lithospheric indicating that the anomaly is constrained by the boundaries that separate tectonic blocks with inde- empirical Green’s function corresponding to the pendent tectonic evolution during the Precambrian. medium between those two stations. This suggests On the other hand, the single-block model (NEVES that the fast velocity anomaly might be an artifact 2003;NEVES et al. 2006), views the Borborema resulting from a timing problem at one of the stations. Province as a coherent block that has behaved as a This ray path, however, is also included in the group- consolidated tectonic unit for the past 2.0 Ga. In that velocity maps at 15–20 s, where no fast velocity model, the shear zones are regarded as supracrustal anomaly is observed for the Rio Grande do Norte features that mark the boundaries of Neoproterozoic domain (Fig. 10c, d). Realize that if the fast-velocity metasediments that were deformed and metamor- anomaly at 5 s were an artifact because of a timing phosed during the Pan African–Brasiliano orogeny. problem, it should be actually observed for all peri- The fading of the fast velocity anomaly in the Rio ods; as this is not the case, we must conclude that the Grande do Norte domain would thus be better fading of this anomaly for longer periods is not an understood within the framework provided by the artifact. Furthermore, Fig. 12b displays the tomo- single-block model. graphic map for 5 s obtained after removing the two The lack of substantial anomalies for short periods stations that flank the Rio Grande do Norte domain across the other major shear zones, and the overall anomaly. Realize that, in addition to the ray path lack of correlation of the tomographic maps for connecting the stations, this operation will remove all longer periods with surface geology may indeed ray paths having one of the two stations on one side. suggest that the Borborema Province is a single, As expected, the fast velocity anomaly disappears, coherent tectonic block. We must keep in mind, but the rest of the anomalies in the map remain however, that the resolution of the tomographic maps basically the same. Once again, if the anomaly were degrades for longer periods, especially in the south- an artifact, one would expect that removal of all the ern and western portions of the study area. Although ray paths associated with the malfunctioning station the permanence of the fast-velocity anomaly under would have a greater effect on the tomographic maps. the Saõ Francisco craton down to 20 s, which is These additional tomographic inversions thus dem- located within the poorly resolved southwestern onstrate that the Rio Grande do Norte domain portion of the study area, may give some confidence anomaly is well constrained for short periods and that that long-wavelength structures are still resolved, it is not the result of a drifting GPS clock or any other spatial resolution for long periods remains low, so malfunction at the stations flanking the anomaly. interpretation of the Borborema Province as a single, After these additional tests, we conclude that coherent Precambrian block will still require better fading of the fast-velocity anomaly in the Rio Grande sampling of the western and southern portions of the do Norte domain is a well-constrained feature in our Province and the surrounding Parnaı´ba basin and Saõ tomographic maps, and that the anomaly is probably Francisco craton. a supracrustal structure that does not extend into the deep crust. This is an important observation with regard to the Precambrian evolutionary models that 7. Conclusions have been proposed for the Borborema Province (as discussed in the Sect. 2). On one hand, the accre- To summarize, cross-correlation of ambient seis- tionary model (BRITO NEVES and CORDANI 1991; mic noise in the Borborema Province of NE Brazil JARDIM DE SA´ 1994;CORDANI et al. 2003) views the has enabled reconstruction of the Green’s functions main shear zones that traverse the Borborema Prov- for pairs of stations separated by approximately 40 ince—including the Patos Lineament—as marking and 1,287 km. The Green’s functions revealed a clear Group-Velocity Tomography of the Borborema Province dispersive signal, which was identified as the funda- ALMEIDA, F.F.M., HASUI, Y., BRITO NEVES, B.B., FUCK, H.A., mental mode of Rayleigh waves. Group velocities (1981). Brazilian structural provinces: an introduction. Earth- Science Reviews 17 (1–2): 1–29. were measured with success for periods between 5 ALMEIDA, F.F.M., BRITO NEVES, B.B., CARNEIRO, C.D.R., (2000). and 20 s, and the dispersion measurements were The origin and evolution of the South American Platform. Earth- inverted tomographically to map subsurface struc- Science Reviews, 50, 77–111. AMMON, C.J., Notes on Seismic Surface-Wave Processing, Part I, tural features. For short periods, the tomographic Group Velocity Estimation. (2001). Saint Louis University. images correlate well with such surface geological Version 3.9.0. Surface Wave Multiple Filter Analysis Software features as Mesozoic rift basins and the Precambrian Documents. ASSUMPÇA˜ O, M., FENG, M., TASSARA, A., JULIA` , J., (2013). Models of Rio Grande do Norte domain. For longer periods, crustal thickness for South America from seismic refraction, corresponding to upper-to-mid crustal levels, no clear receiver functions and surface wave tomography. Tectonophys- correlation is observed between group-velocity ics, doi:10.1016/j.tecto.2012.11.014. anomalies and surface geology. We conclude that the BENSEN, G.D., M.H. RITZWOLLER, M.P. BARMIN, A.L. LEVSHIN,F. LIN, M.P. MOSCHETTI, N.M. SHAPIRO,Y.YANG (2007), Processing lack of correlation for long periods reveals the Rio seismic ambient noise data to obtain reliable broad-band sur- Grande do Norte domain is likely to be a supracrustal face-wave dispersion measurements, Geophys. J. Int., 169, structure, as predicted by models of Precambrian 1239–1260. BENSEN, G.D., RITZWOLLER, M.H., SHAPIRO, N.M., (2008). Broad- evolution that regard the Borborema Province as a band ambient noise surface wave tomography across the United single, coherent tectonic unit over geologic time. States. J. Geophys. Res. 113 (B5), B05306 doi:10.1029/ Confident interpretation of the depth-extent of other 2007JB005248. BRACEWELL, R.N., (1965). The Fourier transform and its applica- Precambrian domains making up the entire Borbor- tions, McGraw-Hill, New York, NY. ema Province will, however, require better sampling BRITO NEVES, B.B., CORDANI U.G. (1991). Tectonic evolution of of its western and southern portions. South America during the Late Proterozoic. Precambrian Research, 53(191):23–40. BROMIRSKI, P. D. (2001), Vibrations from the ‘‘Perfect Storm,’’ Geochem. Geophys. Geosyst., 2(7), doi:10.1029/2000GC000119. Acknowledgments BROMIRSKI, P., and F. DUENNEBIER, (2002). The near-coastal microseism spectrum: Spatial and temporal wave climate rela- tionships. Journal of Geophysical Research 107, doi:10.1029/ This work was supported in part by the Instituto 2001JB000265. Nacional de Cieˆncia e Tecnologia em Estudos BROMIRSKI, P.D. (2009), Earth vibrations, Science, 324, Tectoˆnicos (INCT-ET) of the Brazilian Centro Nac- 1026–1027. AMPELO ´ ional de Desenvolvimento Cientı´fico e Tecnolo´gico C , R. C. (1999). Analise de Terrenos na Porçaõ Setentrional da Provıńcia Borborema, NE do Brasil: Integraçaõ de Dados (CNPq, grant number 57.3713/2008-01). RCD was Geolo´gicos e Gravime´tricos. Dissertaçaõ de Mestrado, Programa supported by a two-year scholarship from CNPq to de Po´s-Graduaçaõ em Geodinaˆmica e Geofı´sica, Universidade complete her M.Sc. degree at UFRN. JJ thanks CNPq Federal do Rio Grande do Norte, Natal, 130p. CAMPILLO, M., A. PAUL (2003), Long-range correlations in the for his research fellowship (CNPq, grant number diffuse seismic coda, Science, 299, 547–549. 308171/2012-8) and MS acknowledges support by CORDANI U.G., BRITO NEVES B.B. and D’AGRELLA-FILHO M.S. the Brazilian Science Without Border Program (2003). From Rodinia to Gondwana: A review of the available evidence from South America. Gondwana Research, (CNPq, grant number 40.2174/2012-7). M. As- 6(2):275–283. sumpçaõ and an anonymous reviewer are thanked CUPILLARD, P. and CAPDEVILLE Y. (2010). On the amplitude of for thorough review of the original manuscript. Most surface waves obtained by noise correlation and the capability to of the figures were produced with the generic recover the attenuation: a numerical approach. Geophys. J. Int., doi: 10.1111/j.1365-246X.2010.04586.x. mapping tools of WESSEL and SMITH (1998). DA SILVA, A.J.P., LOPES, R.C., VASCONCELOS, A.M., BAHIA, R.B.C. (2003). Paleozoic and Meso-Cenozoic sedimentary basins. In: BIZZI, L.A., SCHOBBENHAUS, C., VIDOTTI, R.M., GONÇ ALVES, J.H. (Eds), Geologia, Tectoˆnica e Recursos Minerais do Brasil, REFERENCES CPRM, Brası´lia, pp. 55–85. DE CASTRO D.L., BEZERRA F.H.R., CASTELO BRANCO R. M. G., ALMEIDA, F.F.M., CARNEIRO, C.D.R., MACHADO Jr., D.L., DEHIRA, (2008). Geophysical evidence of crustal-heterogeneity control of L.K., (1988). Magmatismo Po´s-Paleozoíco no Nordeste Oriental fault growth in the Neocomian Iguatu basin, NE Brazil. Journal do Brasil. Revista Brasileira de Geocieˆncias, 18(4): 451–462. of South American Earth Sciences, v. 26, p. 271–285. R. C. Dias et al. Pure Appl. Geophys.

DZIEWONSKI, A., BLOCH, S., and LANDISMAN, M., (1969). A technique LLOYD, S., VAN DER LEE, S., FRANÇA, G. S., ASSUMPÇA˜ O, M., FENG, for analysis of transient seismic signals. Bull. Seism. Soc. Am., M., (2010). Moho map of South America from receiver functions 59(1):427–444. and surface waves. J. Geophys. Res.-Sol. Ea. 115 (B11), doi:10. FENG, M., 2004. Tomografia de Ondas de Superfıćie na Ame´rica do 1029/2009JB006829. Sul: Inversaõ Conjunta de Velocidade de Grupo e Forma de Onda. LOBKIS, O.I., R.L. WEAVER (2001), On the emergence of the PhD tese, IAG, Universidade de Saõ Paulo, Saõ Paulo, Brasil. Green’s function in the correlations of a diffuse field, J. Acoust. FENG, M., ASSUMPCAO, M., VAN DER LEE, S., (2004). Group-velocity Soc. Am., 110, 3011–3017. tomography and lithospheric S-velocity structure of the South MATOS, R. M.D., (1992). The Northeast Brazilian Rift System. American continent. Physics of the Earth and Planetary Interiors Tectonics, 11(4):766–791. 147(4), 315–331. MATOS, R.M.D., (1999). History of the northeast Brazilian rift FENG, M., LEE, S.V.D., ASSUMPÇA˜ O, M., (2007). Upper mantle system: kinematic implications for the break-up between Brazil structure of South America from joint inversion of waveforms and West Africa. In: CAMERON N.R., BATE R.H. and CLURE V.S. and fundamental mode group velocities of Rayleigh waves. (eds.) The Oil and Gas Habitats of the South Atlantic. Geological Journal of Geophysical Research 112, 1–16. Society, London, Special Publications, 153:55–73. FRIEDRICH, A., F. KRU¨ GER, and K. KLINGE (1998), Ocean generated MIZUSAKI, A.M.P., THOMAS-FILHO, A., MILANI, P. and CE´ SERO,P. microseismic noise located with the Gra¨fenberg array, J. Seis- (2002). Mesozoic and Cenozoic igneous activity and its tectonic mol., 2, 47–64. control in Northeastern Brazil. Journal of South American Earth HERRIN, E., and GOFORTH, T., (1977). Phase-matched filters: Sciences 15, 183–198. Application to the study of Rayleigh waves. Bull. Seism. Soc. MORAIS NETO, J. M., HEGARTY, K. A., KARTER, G. D. and ALKIMIM, Am., 67:1259–1275. F. F., (2009). Timing and mechanisms for the generation and HERRMANN, R. B., and AMMON, C. J., 2002. Computer programs in modification of anomalous topography of Borborema Province, seismology surface waves, receiver functions and crustal struc- northeastern Brazil, Marine and Petroleum Geology 26, ture. St. Louis University, St. Louis, MO. 1070–1086. JARDIM DE SA´ , E.F., FUCK R.A., MACEDO M.H.F. and KAWASHITA K. MOTTAGHI, A. A., REZAPOUR, M., KORN,M.Ambient noise surface (1992). Terrenos Proterozoícos na Provıńcia Borborema e a wave tomography of the Iranian Plateau. Geophys. J. Int. (2013) margem Norte do Cra´ton Saõ Francisco. Revista Brasileira de 193, 452–462. doi:10.1093/gji/ggs134. Geocieˆncias, 22(4):472–480. NEVES, S.P., VAUCHEZ A. and FERAUD G. (2000). Tectono-thermal JARDIM DE SA´ , E.F. (1994). A Faixa Serido´ (Provıńcia Borborema, evolution, magma emplacement, and shear zone development in NE do Brasil) e o seu significado geodinaˆmico na Cadeia Bra- the Caruaru area (Borborema Province, NE Brazil). Pre- siliana/Pan-Africana. Instituto de Geocieˆncias da Universidade cambrian Research, 99: 1–32. de Brası´lia, Brası´lia, Tese de Doutorado, 804 p. NEVES, S.P. (2003). Proterozoic history of the Borborema Province JARDIM DE SA´ , E.F., MATOS, R.M.D., MORAIS NETO, J.M., SAADI, A., (NE Brazil): correlation with neighboring cratons and Pan- (1999). Epirogenia cenozoíca na Provıńcia Borborema: sıńtese e African belts, and implications for the evolution of western discussaõ sobre os modelos de deformaçaõ associados. VII Gondwana, Tectonics, 22:10–31. Simpo´sio Nacional de Estudos Tectoˆnicos, Soc. Bras. de Geol., NEVES, S.P. BRUGUIER, O., VAUCHEZ, A., BOSCH, D., SILVA, J.M.R., Lençoís, Brazil, Boletim de Resumos Expandidos, pp. 58 e 61. MARIANO, G., (2006). Timing of crust formation, deposition of JARDIM DE SA´ , E.F., (2001). Tectoˆnica cenozoíca na margem supracrustal sequences, and Transamazonian and Brasiliano equatorial brasileira da Provıńcia Borborema, Nordeste do Brasil metamorphism in the East Pernambuco belt (Borborema Prov- (A contribuiçaõ da geologia estrutural no continente). VIII ince, NE Brazil): Implications for western Gondwana assembly. Simpo´sio Nacional de Estudos Tectoˆnicos, Soc. Bras. de Geol., Precambrian Research 149, 197–216. Recife, Brazil, Boletim de Resumos Expandidos, pp. 25 e 28. OLIVEIRA, R.G., 2008. Arcabouço Geofı´sico, Isostasia e Causas do JARDIM DE SA´ E.F., VASCONCELOS P.M., SAADI A., GALINDO A.C., Magmatismo Cenozoíco da Provıńcia Borborema e de sua LIMA M.G. and OLIVEIRA M.J. (2005). Marcos temporais para a Margem Continental (Nordeste do Brasil). Tese de Doutorado, evoluçaõ cenozoíca do Planalto da Borborema. In: SBG/Nućleo Programa de Po´s-Graduacao em Geodinaˆmica e Geofı´sica, Parana´, Simpo´sio Nacional de Estudos Tectoˆnicos, 10o, Curitiba, Universidade Federal do Rio Grande do Norte. Boletim de Resumos Expandidos, p. 160–162. OLIVEIRA, R. G. and MEDEIROS,W. E. (2012). Evidences of buried KENNETT, B. L. N., SAMBRIDGE, M. S., and WILLIAMSON, P. R., loads in the base of the crust of Borborema Plateau (NE Brazil) (1988). Subspace methods for large scale inverse problems from Bouguer admittance estimates. J. South. Am. Earth Sci., 37, involving multiple parameter classes: Geophysical Journal, 94, 60–76. 237–247. PEDROSA, N.C., DE CASTRO, D.L., DE MATOS, J.P.L. (2010). Assi- KNESEL, K.M., SOUZA, Z.S., VASCONCELOS, P.M., COHEN, B.E., SIL- naturas magne´ticas e gravime´tricas do arcabouço estrutural da VEIRA, F.V., (2011). Young volcanism in the Borborema bacia Potiguar emersa, NE do Brasil. Rev. Bras. Geof., 28, Province, NE Brazil, shows no evidence for a trace of the Fer- 276–282. nando de Noronha plume on the continent. Earth and Planetary PINHEIRO, A.G. and JULIA` , J. (2014). Normal thickness of the upper Science Letters 302, 38–50. mantle transition zone in NE Brazil does not favour mantle LACOSS, R. T., E. J. KELLY and M. N. TOKSOZ, (1969). Estimation of plumes as origin for intraplate Cenozoic volcanism, Geophys. seismic noise using Arrays. Geophysics 34, No.1: 21–38. J. Int., 199, 996–1005. LAROSE, E., DERODE, A., CAMPILLO, M. and FINK, M., (2004). RAWLINSON, N., 2005. FMST: Fast Marching Surface Tomography Imaging from one bit correlations of wide-band diffuse wave- package, Research School of Earth Sciences, Australian National fields. J. Appl. Phys., 95(12), 8393–8399. University, Canberra ACT 0200. Group-Velocity Tomography of the Borborema Province

RAWLINSON, N. and SAMBRIDGE, M., (2005). The fast marching SETHIAN, J. A., (1996), A fast marching level set method for method: an effective tool for tomographic imaging and tracking monotonically advancing fronts: Proceedings of the National multiple phases in complex layered media, Expl. Geophys., 36, Academy of Science, 93, 1591–1595. 341–350. SETHIAN, J. A. and POPOVICI, A. M., (1999), 3-D traveltime com- RAWLINSON, N., POZGAY S., FISHWICK, S, (2010). Seismic tomogra- putation using the fast marching method: Geophysics, 64, phy: A window into deep Earth. Geoscience. doi:10.1016/j.pepi. 516–523. 2009.10.002. SHAPIRO, N., M. CAMPILLO (2004), Emergence of broadband Ray- SABRA, K. G., P. GERSTOFT,P.ROUX,W.A.KUPERMAN, and M. leigh waves from correlations of the ambient seismic noise, C. FEHLER (2005), Surface wave tomography from microseism in Geophys. Res. Lett., 31, L07614, doi:10.1029/2004GL019491. southern California, Geophys. Res. Lett., 32, L14311, doi:10. SHAPIRO, N. M., M. CAMPILLO,L.STEHLY, and M. RITZWOLLER 1029/2005GL023155. (2005). High-resolution surface-wave tomography from ambient SANTOS, E. J. and MEDEIROS V. C., 1999. Constraints from granitic seismic noise. Science 307, 1,615–1,618. plutonism on proterozoic crustal growth of the Transverse Zone, SNIEDER, R. (2004), Extracting the Green’s function from the cor- Borborema Province, NE-Brazil. Revista Brasileira de Geo- relation of coda waves: A derivation based on stationary phase, cieˆncias, 29:73–84. Phys. Rev. E, 69, 046610, doi:10.1103/PhysRevE.69.046610. SANTOS E.J., BRITO NEVES B.B., VAN SCHMUS W.R., OLIVEIRA R.G. STEHLY, L., CAMPILLO, M. and SHAPIRO, N., (2006). A study of the and MEDEIROS V.C. (2000). An overall view on the displaced seismic noise from its long-range correlation properties. J. Geo- terrane arrangement of the Borborema Province, NE Brazil. In: phys. Res., 111, B10306, doi:10.1029/2005JB004237. International Geological Congress, 31th, Rio de Janeiro, Brazil, STOCKWELL, R. G., L. MANSINHa, and R. P. LOWE (1996), Locali- General Symposia, Tectonic Evolution of South American Plat- zation of the complex spectrum: The S-transform, IEEE Trans. form, 9-5, 1 cd-rom. Signal Process., 44, 998–1001. SANTOS, E.J., SCHMUS, W.R.V., KOZUCH, M., (2010). The Cariris TANIMOTO, T. (1991). Waveform inversion for three-dimensional Velhos tectonic event in Northeast Brazil. Journal of South density and S-wave structure, J. Geophys. Res., 96, 8167–8189. American Earth Sciences, 29, 61–76. TROMPETTE R. (1994). Geology of Western Gondwana SCHIMMEL, M. and PAULSSEN, H., (1997). Noise reduction and (2000–500 Ma): Pan-African–Brasiliano Aggregation of South detection of weak, coherent signals through phase weighted Ame´rica and Africa. A.A. Balkema, Rotterdam, Brookfield, stacks, Geophys. J. Int., 130, 497–505, doi:10.1111/j.1365-246X. 350p. 1997.tb05664.x. USSAMI R., MOLINA E. C. and MEDEIROS W. E. (1999). Novos SCHIMMEL, M. and GALLART, J., (2005). The inverse S Transform in vıńculos sobre a evoluçaõte´rmica da margem continental leste filters with time–frequency localization, IEEE Trans. Signal do Brasil. In: SBG-BA/ABGP, VII Simpo´sio Nacional de Estu- Process., 53(11), 4417–4422, doi:10.1109/TSP.2005.857065. dos Tectoˆnicos, Lençoís, Anais, S3:20–23. SCHIMMEL, M. and GALLART, J., (2007). Frequency-dependent phase VILLASEN˜ OR, A., Y. YANG, M.H. RITZWOLLER,J.GALLART (2007), coherence for noise suppression in seismic array data, J. Geo- Ambient noise surface-wave tomography of the Iberian Penıń- phys. Res., 112, B04303, doi:10.1029/2006JB004680. sula: Implications for shallow seismic structure, Geophys. Res. SCHIMMEL, M., STUTZMANN, E., and GALLART, J., (2011). Using Lett., 34, L11304, doi:10.1029/2007GL030164. instantaneous phase coherence for signal extraction from WESSEL, P., SMITH, W.H.F., (1998). New, improved version of the ambient noise data at a local to a global scale, Geophys. J. Int. generic mapping tools released. Eos Trans. AGU 79, 579. 184, 494–506. doi:10.1111/j.1365-246X.2010.04861.x.

(Received January 28, 2014, revised November 4, 2014, accepted November 4, 2014)