STUDY OF THE LITHOSPHERIC STRUCTURE
BENEATH NORTHEAST BRAZIL WITH P-WAVE
MULTIPLE FREQUENCY SEISMIC TOMOGRAPHY

Guilherme Manno Penna Crepaldi Affonso, Marcelo Peres Rocha, Jordi Julià, Aderson Farias Do Nascimento, Reinhardt Adolfo Fuck, Eduardo Alexandre Santos de Menezes, Estevão Vasconcello Campos Tadeu, Karin Sigloch, Guust Nolet, Tiago Jalowitzki

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Guilherme Manno Penna Crepaldi Affonso, Marcelo Peres Rocha, Jordi Julià, Aderson Farias Do Nascimento, Reinhardt Adolfo Fuck, et al. STUDY OF THE LITHOSPHERIC STRUCTURE BE-NEATH NORTHEAST BRAZIL WITH P-WAVE MULTIPLE FREQUENCY SEISMIC TOMOG-RAPHY. Geophysical Journal International, inPress, 10.1093/gji/ggaf304/8225767. hal-05209685

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<figure><img src="image_1.png" /></figure>

Distributed under a Creative Commons Attribution 4.0 International License
STUDY OF THE LITHOSPHERIC STRUCTURE BENEATH
NORTHEAST BRAZIL WITH P-WAVE MULTIPLE
FREQUENCY SEISMIC TOMOGRAPHY

Authors: Guilherme Manno Penna Crepaldi Affonso<fnref n="1" />, Marcelo Peres Rocha<fnref n="1" />, Jordi Julià<fnref n="2" />, Aderson Farias do Nascimento<fnref n="2" />, Reinhardt Adolfo Fuck<fnref n="1" />, Eduardo Alexandre Santos de Menezes<fnref n="2" />, Estevão Vasconcello Campos Tadeu<fnref n="1" />, Karin Sigloch<fnref n="3" />, Guust Nolet<fnref n="3" /> & Tiago Jalowitzki<fnref n="1" />

We used the multiple-frequency seismic tomography method to image the upper mantle beneath Northeast Brazil by processing P-wave broadband seismograms in six frequency passbands. The data comprised 87,896 relative traveltime residuals for P and PKIKP phases, simultaneously inverted to obtain 3D models of P-velocity anomalies. We conducted resolution tests using checkerboard patterns with horizontal dimensions of 312 x 312 km and 390 x 390 km. For the 312 x 312 km structures, we observed good horizontal recovery beneath the areas of the Borborema province and northern São Francisco craton at the depths of 136 and 226 km, with the areas of the São Luís craton and Parnaíba basin also presenting recovery, albeit with reduced amplitudes. For the 390 x 390 km structures we observed good horizontal and amplitude recovery throughout the entire study area. Our model was unable to recover the sharp vertical transitions between the anomalies. We present the preferred model for Parnaíba basin and Borborema province. The model shows a fragmented basement for the Parnaíba basin, with two strong high-velocity anomalies consistent with the Parnaíba and Granja blocks, and another slight high-velocity anomaly north of the basin, consistent with the São Luís craton. To the west of the basin, the Parnaíba block appears separate from another high-velocity anomaly associated with the Amazonian craton. A strong high-velocity anomaly south of the Borborema province is interpreted as the northern portion of the São Francisco craton. The São Francisco craton anomaly presents strong high-velocity anomalies, interpreted as a thickening of certain portions of the craton, separated by a weaker positive anomaly, interpreted as the Paramirim Aulacogen. The Borborema province is characterized by a low-velocity anomaly. The central and northeastern portions of this anomaly presented even lower velocities, which was interpreted as lateral flow in the asthenosphere, originating from the passage of a plume to the north of the province. A low-velocity anomaly located west of the Borborema province strikes roughly NE-SW and separates the São Francisco craton from the Parnaíba block and the Amazonian craton. It is interpreted as the Transbrasiliano Lineament. To test the capability of our data to resolve the limits of large-scale structures, we created four synthetic models simulating the presence of different cratonic nuclei. The models show good horizontal recovery, with the fourth model, based on our findings, presenting the best correlation between the real and recovered models. Seismicity in the study region is mainly correlated to low-velocity anomalies.

Keywords: Seismic Tomography, Body waves, Cratons, Hotspots

<footnote n="1">¹University of Brasília, Institute of Geosciences, Graduate Program in Geology, Brazil.</footnote>

<footnote n="2">²Federal University of Rio Grande do Norte, Department of Geophysics.</footnote>

<footnote n="3">³Université Côte d'Azur, Observatoire de la Côte d'Azur, CNRS, IRD, Géoazur, Sophia Antipolis, France</footnote>
# 1. Introduction

The South American Platform (SAP) consists of several Archean and Proterozoic cratonic blocks of varying sizes that coalesced to form part of West Gondwana at the end of the Proterozoic (Brito-Neves et al. 1999; Alkmim et al. 2001). These cratonic blocks are surrounded and interconnected by mobile belts that resulted from the collision process. Most of the SAP is located within Brazil, especially the largest cratonic blocks, such as the Amazon and São Francisco cratons. Much of the SAP is covered by large sedimentary basins that make it difficult to delineate the boundaries between the cratonic blocks and to understand their tectonic evolution during and after amalgamation.

Some areas of the SAP are better understood than others due to a larger number of studies in those areas and availability of denser datasets, particularly on a regional scale. This disparity is particularly evident in seismic and seismological studies, where limited station coverage results in decreased resolution. The establishment of the Brazilian Seismographic Network (RSBR) in 2011 (Bianchi et al., 2018) significantly improved national coverage (see Figure 1) and partly remedied this situation. However, resolution remains poor in certain areas due to the lack of stations, requiring the deployment of temporary networks to address these data gaps and to investigate specific regions more thoroughly.

An example of a region with sparse station coverage is the Parnaíba basin (PBa), which features only a few RSBR stations and some temporary networks, being among the least studied regions using seismological methods. In contrast, the Borborema province, adjacent to the Parnaíba basin, benefits from more extensive and uniform station coverage, primarily due to RSBR stations and local networks operated by the Seismology Laboratory of the Federal University of Rio Grande do Norte (LABSIS/UFRN). Thus, the Borborema province has been the subject of numerous seismological studies (e.g., Pinheiro & Julià, 2014; Simões Neto et al., 2018; Nemocón et al., 2021) but its interactions with adjacent units,
such as the Parnaíba basin and São Francisco craton remain poorly understood. To enhance coverage along the contact between these regions, additional broadband temporary stations were deployed (ZL network - red triangles in Figure 1), supported by funding from the National Institute of Science and Technology for Tectonic Studies (INCT-ET/CNPq) in Brazil. The integration of data from this network with those from the permanent RSBR stations and other, previous temporary deployments, allowed for a more detailed investigation of the upper mantle under the northern and northeastern regions of Brazil using body-wave seismic tomography.

This study applies the Multi-Frequency Seismic Tomography (MFST) method to P-wave arrivals from teleseismic earthquakes (Sigloch et al., 2008), with the goal of mapping the upper mantle beneath the Paranaíba basin and Borborema province. The method considers that relative traveltime measurements are sensitive to velocity heterogeneities in a finite volume around the seismic ray, with the sensitive mantle region resembling a banana in three dimensions, while being hollow along its middle, i.e. resembling a doughnut when sliced perpendicular to the ray path. Marquering et al. (1999) termed these sensitivity kernels of the finite-frequency traveltime measurement “Banana-Doughnut Kernels”, and Dahlen et al. (2000) developed their expression in the Born approximation, with observations on higher-frequency waveforms associated with narrower kernels, and lower-frequency observations with wider kernels. The MFST method thus inverts traveltime residuals within multiple frequency bands simultaneously, each kernel sampling structures at different, complementary scales around the raypath. MFST thus removes the mismatch between real-world data that is bandwidth-limited, and their interpretation by ray theory, which assumes infinite bandwidth content in a seismogram. MFST remains computationally very efficient while fitting traveltime residuals of entire broadband waveforms (Sigloch & Nolet 2006).
The studies conducted in the Parnaíba Basin are consistent with a fractured basement, being limited to the west by the Araguaia fold belt and to the east by the Transbrasiliano lineament (TBL), while disagreeing to the horizontal limits of the cratonic nuclei underneath the basin. The MFST method in conjunction with longer data acquisition periods from RSBR stations and a new temporary network in the southeastern Parnaíba basin should provide tomographic images with improved resolution that allow us to study the upper mantle structure beneath the Parnaíba basin down to sub-lithospheric depths, adding to the tectonic knowledge of the region. The first goal of our study is to investigate the continuity of postulated shallow, buried blocks under the basin at sublithospheric depths through mapping of seismic velocity contrasts. The second goal is to observe the signature of the Transbrasiliano lineament at depth, as there is still no consensus about its trace under the sedimentary conver, especially in the central-eastern dection of the PBa. The third goal is to make use of the ZL temporary network, installed in the southern area of the PBa, to establish the northern and northwestern limits of the São Francisco craton and its relationship with the TBL. The fourth and last goal is to image the upper mantle under the Borborema province and investigate the origin of asynchronous magmatism in the province's north and northeastern portions.

## 2 Geological Summary

### 2.1. Precambrian Framework

Figure 1 summarizes the regional geological framework together with seismological station coverage. The Parnaíba basin (PBa – Figure 1a) is an intracratonic basin of roughly circular shape, with the depocenter reaching a thickness of approximately 3,500 meters (Cordani et al., 1984; Vaz et al., 2007). Its basement comprises Precambrian blocks agglutinated during the Neoproterozoic Brasiliano Orogeny and surrounded by
Neoproterozoic fold belts (Cordani et al., 2009). Cordani et al. (2016) assert the existence of a singular triangular block under the basin, the Parnaíba block (PBI - Figure 1a). Klein & Moura (2008) separate the basement into two separate blocks (Figure 1b): the Parnaíba block (PBI) in the northwest of the basin, and the Granja block (GBI) in the northeast and bordering the Transbrasiliano Lineament.

Bordering the PBa are the Gurupi fold belt (GFB - Figure 1b) to the north and the Araguaia fold belt to the west (AFB - Figure 1b). The GFB separates the PBa from the São Luís craton (SLC - Figure 1a, b), a unit with accretionary and collisional phases dating from 2240-2250 Ma and 2080 ± 20 Ma, respectively, and was once part of the West African craton (Brito-Neves & Cordani, 1991; Klein et al., 2005; Klein & Moura, 2008). The AFB, a unit that underwent severe deformations during the late Brasiliano Orogeny (Cordani et al., 1984; Brito-Neves et al., 1984; Alvarenga et al., 2000), separates the PBa from the Amazonian craton.

East of the PBa is the Neoproterozoic Borborema province (BP – Figure 1a, b) with the TBL marking the separation between both domains (Figure 1). The BP is considered one of the three main structural provinces of the Brasiliano domain together with the Tocantins and Mantiqueira provinces (Almeida et al., 1981; Brito-Neves & Fuck, 2014), with a fourth province, the Pampean province, in Argentina, being added later (Brito-Neves & Fuck, 2013). The basement of the BP is formed of Archean and lower Proterozoic blocks (Vauchez et al., 1995). Two main shear zones include two EW-trending parallel lineaments; Patos (PtL – Figure 1), to the north, and Pernambuco (PeL – Figure 1), to the south, which cross the entire province.

## 2.2 Intraplate Volcanism

Mizusaki et al. (2002) compiled several published and unpublished sources of K/Ar dating of igneous rocks. They concluded that the BP was the site of four events of
magmatism. and postulated their causes: 210-180 Ma, related to the North Atlantic opening, 140-120 Ma, associated with the initial rifting stages of the South Atlantic, 90 Ma, related to the separation of the African and Eastern Brazilian continental crusts, and <50 Ma. The older events are located mainly northeast of the BP, forming the Macau-Queimadas Alignment (MQA - Mizusaki et al., 2002; Knesel et al., 2011). The geochronological ages date as far as 140-120 Ma for the Rio Ceará Mirim Mafic Dikes, and 80-30 Ma for the alkaline volcanism (Mizusaki et al., 2002). The younger volcanism, of <50 Ma, was associated by Mizusaki et al. (2002) with the presence of a plume, with its initial continental expression being the Mecejana volcanism, with ages 34-26 Ma. As the continent drifted to the west, the plume created the Fernando de Noronha-Mecejana Alignment (FNMA – Figure 1b), with the Fernando de Noronha Island having geochronological ages of 22-2 Ma (Knesel et al., 2011).

Knesel et al. (2011) expanded the period of volcanism in the BP based on $^{40}$Ar/$^{39}$Ar dating, extending it from 80-30 million years ago (Ma) to 93 to 7 Ma. They noted that the volcanism in Fernando de Noronha and the BP overlapped by at least 5 Ma. They concluded that these synchronous volcanic events could not be explained by the presence of a mantle plume, suggesting instead an edge-driven convection mechanism. Pinheiro & Julià (2014) examined the thickness of the transition zone using receiver functions and found no anomalous values in the area, which further discouraged the interpretation of a plume. Sleep (2003) proposed that this magmatism was due to lateral lithospheric flow originating from a plume beneath the Paraná basin, which was first imaged by VanDecar et al. (1995) and interpreted as the Tristan da Cunha Fossil Plume. The study by Simões Neto et al. (2018) identified a low-velocity anomaly with a northeast-southwest orientation in the western part of the BP at depths between 200 and 450 km, interpreting this as the conduit proposed by Sleep (2003). While Simões Neto et al. (2018) did detect a shallow low-velocity anomaly located east of the BP and north of the Patos Lineament, which might indicate the presence of the convection cell
proposed by Knesel et al. (2011), the existence of such convection cell was discarded by the
study due to the large temperature contrast associated with the low-velocity anomaly,
suggesting instead the eastward asthenospheric flow.

<figure><img src="image_2.png" /></figure>

Figure 1 - Maps showing the study area and its regional context. a) Geologic-tectonic map of South America, with colors indicating tectonic age (see legend to the bottom right). Key tectonic units are highlighted by dashed lines and outlines. Seismological stations are superimposed as triangles, with fill colors denoting seismic network affiliation (see legend to the right). Dashed red box shows the target area of our tomography study.
Tectonic units outside the study area: AC – Amazonian craton, sub-divided into cratonic provinces according to Macambira et al. (2020). PaBI – Paranapanema block, RDLPC – Rio de la Plata craton, LAC – Luiz Alves cráton, TBL (orange dashed line) –Transbrasiliano Lineament (Cordani et al. 2016). b) Zoom into the study region and its tectonic units of interest. The continuous black line shows the limits of the Parnaíba basin according to the Brazilian National Petroleum Agency (ANP - https://geomaps.anp.gov.br/geoanp/). Units within the basin are Pbl – Parnaíba block, GBI – Granja block, according to Klein & Moura (2008). The blue continuous and dashed lines are the Araguaina fault zone and the Transbrasiliano shear zone (TBSZ) as proposed by Daly et al. (2014), respectively. Orange and green dashed lines are the Transbrasiliano lineament (TBL) as proposed by Cordani et al. (2016) and Castro et al (2014), respectively. SFC is the São Francisco craton (black dashed), and SFPB (solid orange) is the São Francisco Paleocontinental block, as proposed by Rocha et al. (2019b). SLC - São Luís craton. BP - Borborema province, and lineaments within the province: PtL – Patos lineament, PeL – Pernambuco lineament. FNMA – Fernando de Noronha-Mecejana alignment, MQA – Macau-Queimadas alignment (Knesel et al., 2011). MeV, MaV and QV are the Mecejana, Macau and Queimadas volcanic zones, respectively. Red lines are dikes (Cordani et al., 2016). AFB and GFB are the Araguaia and Gurupi fold belts, respectively. Bathymetry was added to maps a and b to show oceanic features

(Available at:

https://www.marinha.mil.br/dhn/sites/www.marinha.mil.br.dhn/files/DTM_Brasil_LatLongProf.zip)

2.3. Geophysical studies

The PBa has also been studied by several geophysical methods. Castro et al. (2014)
used airborne data to obtain gravimetric and magnetic anomaly maps, and a 3D inversion for
Moho depth estimative, helping to understand the crustal structure of the basin. This study
concluded that a roughly triangular-shaped crustal fragment exists beneath the basin and that
it can be separated into two main domains based on their gravimetric and magnetic
signatures: the Teresina block, to the east, and the Parnaíba block, to the west, which can also
be divided in Parnaíba North and South.

The deep seismic reflection profile (DSRP) from Daly et al. (2014) identified three
distinctive crustal units related to the basin’s setting. These are, from west to east, the
Amazonian craton (AC) with the Araguaia fold belt (AFB), the Parnaíba block (PBI), and the
Borborema province (BP). The PBI is separated from the AC and the BP by the Araguaína Fault Zone (AFZ) and the Transbrasiliano Shear Zone (TBSZ), respectively. The study also points to a possible division of the PBI, with the western portion having no distinctive acoustic features. In contrast, the eastern portion has an unusual occurrence of mid-crustal reflectivity, associated by the authors with an igneous intrusion.

The study of Solon et al. (2018) inverted magnetotelluric data to obtain a resistivity model, identifying three major lithospheric blocks with distinct electric properties: one to the west, with higher resistivity values, formed by the eastern portion of the AC and western portion of the PBa; one beneath the basin, characterized by a conductive anomaly associated by the authors to the possible increase in conductive minerals due to Brasiliano orogenic processes or Triassic and Cretaceous igneous intrusions; and one to the east, extending from the eastern margin of the PBa to the BP, being characterized by two distinctive high resistivity vertical anomalies extending from the crust to the upper mantle, with each anomaly coincident with the different Transbrasiliano models proposed by Castro et al. (2014) and Daly et al. (2014). The study also identified two high resistivity anomalies extending from the crust to the upper mantle to the west of the profile, interpreting them as the Quatipuru Suture Zone to the west and Araguaína Fault Zone to the east, marking the limits of the Amazonian craton and Tocantins province.

The wide-angle refraction-reflection (WARR) profile of Soares et al. (2018), following roughly the same path as the DSRP from Daly et al. (2014), also identified the three main crustal domains from the DSRP study, with the PBI being divided into the Grajaú (west) and Teresina (east) domains, confirming the findings of Daly et al. (2014) regarding the differences in mid crust reflectivity between the western and eastern portions of the block.

Soares et al. (2018) characterize the Grajaú Domain by having a transitional layer between the lower crust and upper mantle, marking its separation from the Teresina Domain by a 4 km
step in the Moho. The Teresina Domain is characterized by Soares et al. (2018) by having a higher upper crustal velocity gradient and a flat Moho at a depth of 39 km. Upper mantle velocities were found to be higher beneath the PBI than the adjacent AC and BP. Those results were broadly consistent with the S-velocity model developed in Coelho et al. (2018) from the joint inversion of receiver functions and surface-wave dispersion velocities.

Daly et al. (2018) integrated geophysical and geological studies to discuss the formation and tectonic setting of the PBa, concluding that the findings of Daly et al. (2014), Soares et al. (2018), and Solon et al. (2018) agreed on the existence of two major crustal boundaries: the AFZ, separating the PBI from the AC and Tocantins province, and the Transbrasiliano Lineament, separating the PBI from the BP.

Daly et al. (2018) also concluded that two other minor discontinuities were observed: the Quatipuru Suture Zone, west of the AFZ, and a minor discontinuity within the PBI, differentiating it into western and eastern portions, suggesting that the basement beneath the PBa presents considerable heterogeneity. The study also concluded that the results suggest a thicker crust beneath the basin, reaching up to 45 km compared to those in the AC and BP. This crust is limited to the west and east by increasing crustal thickness associated with the Tocantins-Araguaia and Parnaíba-Borborema suture zones, respectively.

The basement of the PBa was further analyzed by the study of Porto et al. (2022), which used geophysical and geological data in the area to propose a basement formed by four terranes. They observed the existence of two blocks beneath the basin: the Grajaú block, to the west, characterized by a thicker crust, decreased gravity anomaly, a basement with the absence of reflectors and a high velocity lower crust. To the east, they described the Tocantins block by having mid-crustal reflectors, proposed to originate from the suture between the two blocks, a thinner crust, and higher gravity anomaly values. The study still
suggested the existence of a transitional domain between the two blocks, named Barra do Corda Transitional Domain.

## 3 Data

The database used to apply themulti-frequency seismic tomography method is composed by seismograms recorded by 262 broadband seismographic stations from 2009 to 10/08/2023. Eleven temporary stations of the ZL network, funded by INCT—ET (National Institute of Science and Technology—Tectonic Studies) and installed by UFRN (Federal University of Rio Grande do Norte) and UnB (University of Brasília), recorded the main data for our study. This new temporary network was deployed in January 2022 to help sample the southern portion of the Parnaíba basin and it limit with the SFC, which lacked data because no other stations had been installed in the region previously. Most of the permanent stations belong to the RSBR (Bianchi et al., 2018), maintained by a consortium between UFRN, UnB, USP (University of São Paulo), and ON (National Observatory). The RSBR stations can be seen in Figure 1, being composed of four subnets: BR (UnB); NB (UFRN); BL (USP; and ON (ON). Other permanent stations are maintained by ObSis (Seismological Observatory from UnB - OS in Figure 1) and other belong to the global networks (GT and IU). We also include data from temporary deployments throughout Brazil: the XC network (Assumpção & Bianchi, 2016), deployed in the Chaco, Paraná, and Pantanal basins; and the AR, BP, and RF networks, deployed in the northeast region of Brazil with support from CNPq, BP Energy do Brasil and Petrobras, respectively. The subnets of the RSBR are plotted separately in Figure S1.

We chose to process data from 2009 onwards to guarantee the synchronous operation of permanent stations and temporary deployments. This is justified by the finding of Maupin (2021) that relative residuals obtained from networks that did not operate synchronously
might lead to large-scale biases. Such effects should be avoided by using data from
temporary networks that operated simultaneously with the BL network in 2009 and 2010 and
after installing the initial stations of the RSBR, which happened in 2011, thus guaranteeing
synchronous data acquisition.

Data for stations installed outside of the study area were processed to reduce edge
effects and to increase kernel density at all depths. Data recorded by stations outside the study
area can also be affected by heterogeneities beneath the study area due to volumetric
sensitivity around the seismic ray, characteristic of the “Banana-Doughnut Kernels”. There
are few crossing raypaths for some regions outside the study area, so the structures in these
regions are far from being resolved. Data availability for each station during the 2009-
10/08/2023 period is shown in Figure S2 (stations with high data availability (>80%) were
labeled).

The seismograms processed were obtained for the direct P phase and the inner-core
refracted PKIKP phase. We established a minimum magnitude of 5.7 mb for a good signal-
to-noise ratio, and epicentral intervals for each phase in order to avoid triplications and low
energy zones. For the P phase, we choose events from 30°-95° and for which the PKIKP
phase events from 150°-180°. For the PKIKP phase, we also discarded seismograms for
which the inner-core reflected PKP theoretical arrival was calculated to be less than 32
seconds after PKIKP, in order to avoid interference of the two phases on the PKIKP time
picking for lower-frequency filters.

The traveltime relative residuals were obtained by processing the seismograms in six
different frequency bands (center periods of 1, 2, 4, 8, 16, and 32 seconds) with the
semiautomatic method developed by Bonnin et al. (2014), a modification of the Multichannel
Cross Correlation of VanDecar & Crosson (1990). The technique imposes a minimal
correlation coefficient, regularization, and a correlation window, with its length based on the
central frequency, pulse duration, and user-chosen taper. The window start time (WTs – Equation 1) and end time (WTE – Equation 2) are obtained by:

$$WT_s = T_{AK} - \sigma - \tau_1 \quad (\text{Eq. 1})$$
$$WT_E = T_{AK} + \sigma + \tau_2 + T_D + T_{Obs} \quad (\text{Eq. 2})$$

where TAK is the theoretical traveltime computed from the AK135 spherical reference earth model (Kennett et al., 1995), σ is the uncertainty on the time picks, τ1 and τ2 are the start and end tapers, TD is the dominant period of the filter and TObs is the observed duration of the pulse on the broadband seismogram. The filter’s power spectrum theory can be found in Hung et al. (2000). The uncertainty used in equations 1 and 2 is applied to avoid the late start and premature ending of the correlation window, being related exclusively to the sample rate of the seismograms.

All events had the correlation time windows manually assigned, with tapers and TObs defined based on visual inspection of the seismograms. Data with low signal-to-noise ratio or inconsistent waveform were removed in this step. We used a constant uncertainty σ = 0.1 s, equal to the sample interval of the seismograms. Regarding cycle skips, a problem associated with the use of relative residuals when processing higher frequency bands, Mercerat & Nolet (2013) stated that a correlation coefficient of 0.8 is enough to greatly reduce the occurrence of such skips. The following seismic tomography studies used higher coefficients of 0.85 (Sigloch et al. 2008, Bonnin et al., 2014; Costa et al., 2020) and 0.9 (Nolet et al., 2019; Affonso et al., 2021). We decided to establish a minimum correlation coefficient of 0.9 while requiring a minimum of eight intercorrelations between seismograms for at least one frequency band, in order to accept the event and compute its relative residuals.

This processing yielded 52,691 and 35,205 relative residuals for the P and PKIKP phases, respectively. This totaled 87,896 residuals for all six frequency bands, obtained from 687 earthquakes (401 for P and 286 for PKIKP). Figure 2 shows the histogram for our time
residuals database. The difference in standard deviation (StD) observed for the P and PKIKP phases can be attributed to the different raypaths taken by each phase. The P phase path makes it more susceptible to mantle heterogeneities while the PKIKP phase travels through the more homogeneous core. The paths taken by PKIKP are also longer and have a smaller azimuth aperture, meaning mid path heterogeneities will influence residuals equally.

Figure S3 shows the relative residual count throughout all bands and events for each of the stations used. Figure S4a shows the yearly summary for the number of events and average number of residuals per band for all the events of that year. Figure S4b shows the histogram of average residuals per band for each event.

<figure><img src="image_3.png" /></figure>

Figure 2 - Histogram of 87,896 relative traveltime residuals for the processed database. The 52,691 P and 35,205 PKIKP residuals are shown in blue and green, respectively. The best-fitting normal distribution has a mean of 0.0s and a standard deviation of 0.539s for the P phase and a mean of 0.0s and a standard deviation of 0.407s for the PKIKP phase.
## 4 Method

We adopt a cubed-sphere parametrization (Charlèty et al. (2013)) where the earth's mantle is subdivided into six subvolumes, each covering one sixth of the surface with 128x128 curved voxels in the horizontal, with voxel sizes in the vertical dimension decreasing towards the core. This results in a horizontal voxel spacing of roughly 78 km on the surface and 40 km on the core-mantle boundary, and 37 voxels in the vertical dimension. The default vertical spacing of 90 km is refined near to 45 and 23 km near mantle discontinuities.

The basic inverse problem consists of minimizing the linear system $Km = d$, where the [nx1] data vector $d$ contains the P-wave traveltime residuals, matrix $K$ of dimensions [nxm] contains one sensitivity kernel per row, and the [mx1] solution vector $m$ contains a velocity anomaly value $dVp/Vp$ for each voxel. In practice, this inverse problem is underdetermined and its solution $m$ is non-unique; we regularize it using norm damping and smoothing operators. The regularized linear system can be written as (Nolet, 2008), and is shown in Equation 3:

$$ \begin{bmatrix} K \\ \varepsilon_D I \\ \varepsilon_S D \end{bmatrix} \mathbf{m} = \begin{bmatrix} d \\ 0 \\ 0 \end{bmatrix} \quad (\text{Eq. 3}) $$

where $I$ is the identity matrix acting as the norm damping operator, and $D$ is the Laplacian roughening (second derivative) operator, whose action is penalized by the L2 norm minimization, resulting in a smoothed solution. $\varepsilon_D$ and $\varepsilon_S$ are the weights assigned to these respective operators. We use the ratio $\varepsilon_D/\varepsilon_S = 0.35/0.65 \approx 0.54$. We embedded the region of interest into a global model to avoid that anomalies far away from Brazil would unduly influence the local model. Wavefront healing will naturally reduce such influence as the anomalies are at larger distance. We therefore used a higher damping (by a factor of 5)
outside the study area. The study area was defined as a half-sphere with a radius of 2,700 km centered at 14.6°S, 53.9°W (Figures S1 and S3).

The traveltime delays were corrected using the ray tracing algorithm of Tian et al. (2007a) for crustal, topographic, and ellipticity effects. We used the model LITHO1.0 (Pasyanos et al., 2017) for the crustal corrections, available at https://igppweb.ucsd.edu/~gabi/litho1.0.html. LITHO1.0 uses CRUST1.0 (Laske et al., 2013) as starting model, with both not including data from the papers cited in Section 2. The lateral resolution for both models is 1° (roughly 111km), resulting in small scale structures being averaged out of the final model. While this can cause correction errors, it should be noted that the lateral dimensions of the structures interpreted in our study are bigger than 110km. Thus, we consider that artifacts caused by such errors are smoothed out by the inversion's regularization.

During the ray tracing step, 4,134 delays were rejected because the solution did not converge or the PKIKP phase arrivals were too close to the antipode. This resulted in a total of n=83,762 relative residuals used in the inversion. The frequency-dependent banana-doughnut kernels K were computed using the paraxial approach-based algorithm developed by Tian et al. (2007b).

Our data vector d, comprised of 83,762 relative traveltime residuals, had a normalized chi-squared data misfit $X^2/N$ of 46.641 with the spherically symmetric starting model. After a first inversion with minimal regularization (allowing for arbitrary overfitting of the data), 2,032 traveltime residuals that still did not fit to within two standard deviations (2*σ) were considered faulty outliers and removed from further inversions, representing 2.4% of our database. Without these outliers, the data had an almost unchanged $X^2/N$=46.591 with respect to the starting model. Assuming the data errors σ are correctly known, the preferred solution should have a chi-square of (or around) 1.0, indicating that the data on average fit to
within their measurement uncertainties but not over-fit. Our preferred tomographic model has a $X^2/N=1.086$ and a model norm (roughness) $\|m\|_2/\sqrt{M}$ of 0.0468. The trade-off curve between RMS norm of $m$, our proxy for the desired model simplicity, and data misfit $X^2/N$ (on the y-) is presented in Figure 3. It features ten solutions obtained by gradually increasing the action of the regularization operators. We also present the recovered models for a depth of 136 km for the first 8 solutions. We observe that the increase in regularization from Solution 1 to Solution 3 is enough to stabilize the inversion, with further solutions differing mainly in the magnitudes of their dVp/Vp anomaly values, rather than their spatial distributions. Solutions 9 and 10, not shown, strongly resemble Solution 8, but with an even more damped appearance (faintier colors).

<figure><img src="image_4.png" /></figure>

Figure 3—Trade-off curve between the RMS length ("simplicity") of our candidate tomography models (on the x-axis) versus their normalized chi-square misfit $X^2/N$ on the y-axis. The severity of regularization (damping and smoothing) increased from Solution 1 (minimal regularization) to Solution 10. Solution 4, highlighted in red, is our preferred model with a $X^2/N$ very close to 1, as theoretically expected.
# 5 Model Resolution Tests

To evaluate model resolution, we generated synthetic models $m_s$ and computed the corresponding synthetic data $d_s$ by solving the forward problem $d_s = Km_s$. For $m_s$ we used checkerboard patterns, consisting of alternating positive and negative anomalies whose steep gradients are challenging to recover in the inverse step. One checkerboard model featured structures with dimensions of 4x4x4 voxels (approximately 312x312 km horizontally), and another checkerboard model was slightly "easier" with structures of 5x5x5 voxels (390x390 km horizontally). The anomalies had an amplitude of ±2.0%. Gaussian noise with the same standard deviation as the real data (0.49s for P and PKIKP dataset) was added to simulate noise and uncertainties. The synthetic data were then inverted with the same regularization parameters used for the real data, obtaining the recovered model parameters $m_r$.

For the 4x4x4 checkerboard test (Figures 4 and 5), we observe good geometrical recovery at depths of 136 and 226 km (the main interpretable depths) in the Borborema province (BP), at the northern portion of the São Francisco craton (SFC), and the central part of the Parnaíba basin (PBa), although with decreasing resolution in the south of this region. The input checkerboard model changes sign at a depth of 316 km, resulting in a steep gradient that our output model does not fully recover. At 384 km, it is possible to see some recovery beneath the Borborema province and São Francisco craton, with reduced amplitudes. The vertical cross-sections (Figure 5) show that the first checkerboard layer had its original depths smeared downwards, affecting the recovery of the second layer, which starts at 316 km. This smearing is most prevalent along the ray paths. The profiles also show that horizontal limits are generally well recovered by our model.

For the 5x5x5 structures (Figure 6) at depths of 136 and 226 km, geometry and amplitude recovery are very good throughout the entire study area, with the depth of 316 km having reduced amplitude compared to previous depths while maintaining the geometric
characteristics. The signs of the anomalies are inverted at 384 km, with the model unable to
recover the steep gradient generated by this transition.

We estimate that the model can reliably recover structures with horizontal dimensions
between 300x300 km and 400x400 km for the areas of the BP, northern portion of the SFC,
and central and southern portions of the PBa. The eastern region of the São Luís craton also
shows partial recovery. The recovered structures present smearing along the direction of the
ray paths, evidencing reduced vertical resolution throughout the study area. The reduction in
resolution in regions close to the Brazilian coast can be explained especially by the lack of
events east of Brazil, which reduces the amount of ray crossing in these regions.
<figure><img src="image_5.png" /></figure>

Figure 4 Checkerboard model with dimensions of 4x4 (312 km horizontally at the surface) at depths of 136, 225, 316, 384, 429 and 497 km. The blue and red squares indicate horizontal limits for the alternating positive and negative checkerboard anomalies. Black triangles are seismological stations used in this study. The geological features shown are the SLC - São Luís craton, PBI - Parnaíba block and GBI – Granja block,

<figure><img src="image_6.png" /></figure>
according to Klein & Moura (2008), the BP – Borborema province and SFC – São Francisco craton from
Cordani et al. (2016) and the PBa – Parnaíba basin, extracted from https://geomaps.anp.gov.br/geoanp/.

<figure><img src="image_7.png" /></figure>

Figure 5 - Cross-sectional profiles F-F*, G-G*, H-H*, I-I* and J-J* through the 4x4 synthetic checkerboard model (red/blue rectangles) and its recovered model (red/blue color shades). The locations of the cross-sections are indicated on the map, which also shows the input and output models at 136 km depth. Plotting style and labeling as in Figure 4.
<figure><img src="image_8.png" /></figure>

Figure 6 - Checkerboard model with dimensions of 5x5 (390 km horizontally at the surface) at depths of 136, 225, 316, 384, 429 and 497 km. Plotting style and labeling as in Figure 4.
## 6 Results

We present the results as map sections at depths of 135, 226, 316 and 384 km (Figures 7, 8), and as five vertical cross-sections at depths of 0 to 800 km, although we focus interpretations on the upper 400 km (Figure 8). Map sections at 34 and 68 km depth are included in the Supplementary Material (Figure S5). P-velocity anomalies $dVp/Vp$ are presented in a red-blue color scale that saturates at -1.0% and 1.0% deviation from a regional mean (at a given depth), rather than absolute deviation from global reference model AK135 model at that depth.

As in previous tomographic studies from South America (e.g., Rocha et al., 2019a, b; Affonso et al., 2021), we consider that the leading cause for velocity anomaly is temperature difference. Cratonic nuclei are considered older and more stable, having lower temperatures and higher velocities. Collisional areas, such as mobile belts and provinces, are associated with low-velocity anomalies of weak to mean amplitudes, arising from lithospheric thinning. Stronger low-velocity anomalies are associated with plumes, mainly due to higher temperatures.

Beneath the northwestern and northeastern Parnaíba basin (PBa), we observe two high-velocity anomalies at lithospheric depths, named in this study as the WPH - northWestern Parnaíba High-velocity anomaly and the EPH - northEastern Parnaíba High-velocity anomaly (Figure 7). These anomalies are roughly co-located with the outlines of blocks PBI and GBI, respectively. The WPH is connected to another fast anomaly further west, the ArH - Araguaia High-velocity anomaly. The ArH is located beneath the Araguaia fold belt and is indiscernible below 316 km, also presenting some segmentation from the WPH for depths of 136 and 226 km.

Another high-velocity anomaly, relatively weak, is observed north of the PBa and is named as NPH – Northern Parnaíba High-velocity anomaly. The NPH is located within the
limits of the São Luís craton at 136 km depth. It may extend westward beyond the bounds of SLC, where the model shows more slightly fast mantle, associated with an isolated seismic station at ~2.5°S, 48°W. There is a tendency for NPH to connect with EPH at shallower depths (136 and 216 km), with the former having a substantially weaker amplitude than the latter. However, it is possible to observe, even at such depths, that the connection between the two has a smaller amplitude, suggesting a segmentation, which becomes clear at greater depths (>316) when these anomalies appear completely separated. This tendency for connection at shallower depths may be related to the low resolution of the model in the coastal portion of Brazil. The NPH anomaly merges with the EPH, with the former being distinguishable only by having a substantially weaker amplitude, which is roughly homogenous down to a depth of 316 km.

A strong high-velocity anomaly is located beneath the São Francisco craton (SFC) area. This anomaly presents two extensions when compared to the nominal SFC from Cordani et al. (2016), one to the north, to beneath the Borborema province, with the anomaly being given the name nSFC+, and one to the northwest, at the southeastern portion of the Parnaíba basin, referred as the nwSFC+. The nSFC+ presents a weaker amplitude for the depth of 136 km compared to the overall SFC anomaly. At greater depths, the nwSFC+ anomaly reaches even further (more northerly) beneath the Parnaíba basin. The SFC anomaly appears internally segmented, with a reduction in amplitude with roughly NNW-SSE (SFCseg) orientation dividing the craton into the eSFC and wSFC (Figure 7).

The Borborema province is underlain by seismically slow mantle (Figure 7) in its northern (BPn), northeastern (BPne) and central (BPc) region, with a sharply delineated velocity gradient towards the fast nSFC+ anomaly to its south. For the depths of 136 and 226 km it is possible to observe that this slow anomaly is even stronger for the BPc and BPne areas, extending beyond the coastline with NE-SW direction.
A low-velocity anomaly parallel to the TBL can be seen to the northwest of the
Borborema province (Figure 7). This anomaly appears to join another low-velocity anomaly
that cuts through the central portion of the Parnaíba basin, south of the EPH, which no longer
follows the direction of the TBL of Cordani et al. (2016) but instead borders the high-velocity
anomaly under the SFC (nwSFC+). This low-velocity anomaly continues westward to the
area south of the WPH, where it takes an SSW-NNE direction, beneath the Brasilia Belt,
continuing to the boundary of our study area at ~12.5°S, 48.5°W. This anomaly is discernible
in all depths, presenting some differentiation from the low-velocity anomaly beneath the
Borborema province.
<figure><img src="image_9.png" /><figcaption>Figure 7 – Our preferred tomographic P-velocity model, plotted as map sections from 135 km to 497 km depth.</figcaption></figure>

Beneath the PBa- Parnaíba basin: GBI – Granja block, PBI – Parnaíba block, WPH – Western Parnaíba High-velocity anomaly, EPH – Eastern Parnaíba High-velocity anomaly, NPH – Northern Parnaíba High-velocity anomaly, ArH – Araguaia High-velocity anomaly, SLC – São Luís craton, TBL – Transbrasiliano lineament.

Beneath the SFC – São Francisco craton: eSFC - eastern São Francisco craton anomaly, wSFC - western São
Francisco craton anomaly, nwSFC+ - northwestern São Francisco craton anomaly, nSFC+ - northern São Francisco craton anomaly, SFCseg - São Francisco anomaly segmentation. Beneath the BP - Borborema province: BPn - Borborema province northern region, BPc - Borborema province central region, BPne - Borborema province northeastern region

<figure><img src="image_10.png" /></figure>

Figure 8 – Vertical cross-sections through the tomography model, from 0 to 800 km depth. The locations of profiles A-A' to E-E' are plotted on a map (bottom right), which also shows the tomography model at 136 km depth. Plotting style and labeling as in figure 7.
# 7 Resolution of a Synthetic Model of lithospheric blocks

One of the main goals of this work is to define the boundaries of cratonic blocks and other lithospheric structures in our study area. Prior studies have made competing proposals for their locations (Figure 1, e.g. for the TBL or cratonic blocks within the PBa), and our tomography model hints at yet different geometries (e.g. for the SFC). We therefore created additional resolution tests featuring (somewhat simplified) geometric renderings of the competing hypotheses, in order to test how resolvable and distinguishable they are with our data.

We model the different cratonic nuclei with an amplitude of dVp/Vp = +2% (Supplementary Material - Figure S6). We add the same Gaussian noise as in the checkerboard tests of Section 6. It is also important to note that negative anomalies in the recovered model are expected, despite having only positive anomalies as input. By using relative traveltime residuals, we expect to recover the contrasts between the anomalies (Maupin, 2021). This was also observed in previous studies (e.g., Affonso et al., 2021, Rocha et al., 2011). Our synthetic fast anomalies are implemented to start at 34 km and reach to depths between 136 and 226 km, based on the observed fast anomalies.

Due to the parametrization's vertical spacing, it was impossible to vertically resolve and implement craton depths between 136 and 226 km accurately. To get around this limitation, we choose to multiply the synthetic dVp/Vp anomaly for the depth of 226 by a factor *f* determined by the proposed craton depth. For example, if we estimated the craton to have a thickness of 180 km, roughly the mean between the depths of 136 and 226 km, we determined a factor of 0.5. The general expression for the factor *f*, considering a pair of depths *d*₁ < *d*₂ and an estimated depth *d*ₐ is: *f* = (*d*ₐ - *d*₁)/(*d*₂ - *d*₁), which is then multiplied by the dVp/Vp at depth *d*₂.
Since our inversion uses seismic stations throughout Brazil, implementing recognized
cratons outside the target area of our tomography model was necessary. For the
Paranapanema block, we used the limits of Affonso et al. (2021). We used the limits of
Rapela et al. (2011) for the Rio de la Plata craton. The Amazonian craton was also included,
with depths reaching from 136 to 180 km. The horizontal limits were based on those
proposed by Cordani et al. (2016).

We inverted synthetic data of four different synthetic models, in order to further
reinforce our interpretation of the Parnaíba basin having three major cratonic nuclei. The first
three models were based on proposals of previous studies, whereas the fourth synthetic model
was an (idealized) version of our own tomographic model, as presented in Section 6
(Results). The Supplementary Material contains Figure S6, which compares the first three
models for depths of 68, 136, and 226 km. The depth extents of the cratonic nuclei were kept
identical in all three models. The results of the three resolution tests are discussed on Text 1
of the supplement. Crucially, none of the three synthetic output models resembles the results
of our tomography using real data. Side-by-side comparisons between the real data and the
recovered Models 1-3 are presented in the Supplementary Material (Figures S8-S10).

The fourth model (Figure S6 - M-4a, M-4b & M-4c & Figure S7) was constructed
based on the anomalies observed with our data (c.f. Section 6). Craton depths were
implemented based on anomaly strength in our tomography and in the waveform tomography
of Ciardelli et al. (2022). The São Francisco craton was modeled reaching depths of roughly
170 km. Since its northern portion presented an anomaly with reduced amplitude (nSFC+),
and since no expression of a craton is observed on the surface beyond the limits drawn in
Figure 7, we decided to remove the initial 34 km layer of the synthetic model, for the part of
the anomaly that spills into the BP in our model. We also choose to model a thinning in the
area characterized by a reduced amplitude (SFCseg). This thinning was established with a
depth of 120 km.

The Pbl and Gbl blocks were both modeled as reaching depths of 150 km. The
horizontal limits of Pbl were moved slightly south when compared to the model of Klein &
Moura (2008), while also extending further west. Gbl was also expanded compared to Klein
& Moura (2008), reaching farther south and west. Due to sparse station coverage in the SLC,
and therefore lack of constraints, we made only minor adjustments to the horizontal limits of
Klein & Moura (2008) and Cordani et al. (2016), reducing the westerly extent of the craton.
We implemented a depth of 110 km for the SLC.
<figure><img src="image_11.png" /></figure>

Figure 9 – Resolution test results for synthetic block model #4, at depths of 136 to 384 km. Plotting styles as in Figure 7. The input model consisted of fast anomalies mimicking cratonic blocks, whose outlines are shown as blue polygons in the two top panels. These (idealized) cratonic block boundaries were inferred from our actual tomographic model (as shown in Figure 7).
The recovered model (Figures 9, 10) presents good resemblance to the input model and shows good correlation with the real model (Figure S11 presents a side-by-side comparison). The São Francisco craton presents good horizontal recovery, with the anomalies correlating with those described in the results. By expanding the craton northwest, beneath the Parnaíba basin, we could match the anomalies of the recovered model to our observed tomography model (nwSFC+). This adjustments to the northwestern limits provided better results when compared to the São Francisco Paleocontinental block of Rocha et al. (2019b). We were also able to recover the segmentation (SFCseg) between the SFCw and SPCE, evidenced mainly by a reduced amplitude.

The recovered horizontal limits of the Parnaíba block matched those observed in the actual tomography model. We observe a good correlation between the real and recovered anomalies in profiles A-A' and D-D' (Figures 9, 10). It was also possible to recover the segmentation between the WPH and the ArH.

Profiles C-C' and D-D' (Figures 9, 10) show a good correlation between the input and recovered anomalies associated with the Granja block (Gbl). With the horizontal limits being well recovered. The EPH and NPH also smear together in our output model and can only be differentiated by their amplitude. We could not recreate the strong high-velocity anomaly of the Granja block observed in the real model. The amplitude of the synthetic São Luís craton was poorly recovered, mainly due to the lack of stations in the area.

The presence of low-velocity anomalies in the test output is expected due to the use of relative residuals, as explained at the beginning of the section. These low velocities are homogeneous throughout the study, with no spikes that could be associated with data distribution. We consider this an indication that the strong low-velocity anomaly observed in central Borborema province by the real tomographic inversion, instead of the homogeneous one recovered for the synthetic model, should be due to an actual slow mantle feature.
<figure><img src="image_12.png" /><figcaption>Figure 10 - Vertical cross-sections through the input and output model of the resolution test for block model #4. Profiles A-A' to E-E' profiles showing the fast input anomalies as solid blue polygons and the recovered structures in red/blue color shades, for depths between 100 and 800 km. Plotting styles as for fig. 8.</figcaption></figure>

# 8 Discussion

## 8.1 Parnaíba basin and São Francisco craton

The high-velocity anomalies observed in our study generally agree with the cratonic blocks proposed by previous studies. The two pronounced high-velocity anomalies beneath the PBa, WPH and EPH, are consistent with a thick lithosphere, their lateral extents roughly coinciding with the Parnaíba (PBI – Figure 11a) and Granja (GBI – Figure 11a) blocks proposed by Klein & Moura (2008). Our result does not support a single triangular cratonic block as proposed by Cordani et al. (2016). The interpretation of Nascimento et al. (2024), based on fast anomalies obtained by surface-wave tomography, also discouraged the presence of a single triangular block beneath the PBa. This interpretation also correlates with the
transitional zone proposed by Porto et al. (2022), named the Barra do Corda Belt, shown in Figure 11a as shaded area. Schiffer et al. (2021) also proposed a suture in this area, evidenced by the higher Vp/Vs ratios.

While the tomographic study of Chagas de Melo et al. (2025) observed a single, strong high velocity anomaly in the northern portion of the basin, consistent with a single block, it must be noted that the aforementioned study did not have access to data used in our inversion (ZL and BP networks, installed in the central and southern areas of the Parnaíba basin). This could result in a model with low resolution for the area, with the cratonic nuclei not being differentiated. Furthermore, tomography methods that use body waves, as is the case in our study, have better horizontal resolution.

The third anomaly beneath the PBa, referenced as NPH, is a weak high-velocity anomaly related to the São Luís craton (SLC – Figure 11a). This weaker anomaly might be the result of a thin cratonic block. Considering that the lithospheric model of Priestley et al. (2018) obtained high thickness values for the West African craton, we believe that the small fragment suffered intense reworking during breakup, eroding its cratonic roots, resulting in a relatively thin block, as proposed by Klein & Moura (2008) and Chagas de Melo et al. (2025). Another explanation is that the lack of stations affected the model's capacity to recover the craton, reducing the amplitude.

The segmentation between the Parnaíba block and what was interpreted as the Amazonian craton coincides with the Araguaína fault zone (AFZ – Dark green continuous line in Figure 11b) proposed by Daly et al. (2014) and with the high Vp/Vs ratios from Schiffer et al. (2021) characterized as suture zones. While the suture between the two cratonic nuclei is evident by geological mapping and shallow geophysical methods, our model did not have enough resolution to effectively show the separation between the Parnaíba block and Amazonian craton.
The TBL was interpreted as the low-velocity anomaly that starts to the northwest of the Borborema province and east of the EPH, correlating with the models of Castro et al. (2014) and Cordani et al. (2016). The sub-surface expression of the TBL proceeds south of the EPH, under the PBa, diverging from its surface expression, following the limits of the high velocity anomaly related to the São Francisco Paleocontinent at lithospheric depths. Further south, this slow anomaly separates the São Francisco craton from the Amazonian craton and connects with the Brasília Fold Belt, proceeding further south.

The SFC was interpreted as a high-velocity anomaly which showed a resemblance with the São Francisco Paleocontinental block (SFPB – Orange continuous line in Figure 11a) proposed by Rocha et al. (2019b) and with the anomalies from Nascimento et al. (2024). The main difference between our model and the SFPB is located to the northwest, near the previously established TBL. We propose an SFC with limits reaching farther northwest than the SFPB, beneath the Parnaíba basin. It must be noted that the model generated by Rocha et al. (2019b) did not include the stations of the ZL network and have a reduced resolution in the area. Our proposed northwestern limit also correlates with a conductive zone observed by Rocha et al. (2019c) through magnetotelluric imaging, interpreted as the Borborema-São Francisco suture.

Also related to the SFC is the observed low-velocity segmentation with NW-SE orientation inside the craton (dashed orange lines - Figure 11a, b). Our synthetic model (#4) implemented cratonic thinning in this region, which was recovered by our data. We interpret this thinning to be associated with the Paramirim Aulacogen (Figure 11a – PrmA, Pedrosa-Soares et al., 2001). Rocha et al. (2019) also interpreted a low velocity anomaly within the SFC as being the Paramirim Aulacogen.
## 8.2 The Borborema province and its magmatism

Our results showed that at lithospheric depths the Borborema province is characterized mostly by low velocities, suggesting that the lithosphere is thinner and that the asthenosphere is shallower compared to the cratonic regions. The observed lithospheric thinning under the BP was also observed in previous studies. The lithosphere-asthenosphere boundary models of Priestley et al. (2018) and Pasyanos et al. (2017) determine a depth of roughly 70 km for the northeastern portion of the BP, coinciding with the low-velocity anomalies obtained in our results and previous regional tomographic studies (Ciardelli et al., 2022, Nascimento et al., 2024). The stronger slow anomaly, in the BPc and BPnw areas, and distinguishable down to 316 km depth, have a distinct feature from the other regions in PB, and would be related to the Borborema province's magmatism.

The enigmatic nature of the coeval and widespread Cenozoic alkaline magmatism (<35 Ma) in the BP and Fernando de Noronha Archipelago (Northeast Brazil) remains a subject of ongoing debate. Notably, lavas from continental (Mecejana and Macau) and oceanic (Fernando de Noronha) domains display strong geochemical and isotope (Sr-Nd-Pb) affinity (e.g., Gerlach et al., 1987; Kogarko et al., 2007; Knessel et al., 2011; Guimarães et al., 2020). Although this compositional similarity would suggest a common mantle source for both domains, the lack of an apparent age progression besides the longevity of magma generation (mainly between 35.0 and 1.3 Ma, Guimarães et al., 2020 and references therein) attest against the impingement of a deep mantle plume.

Even with this evidence, a mantle plume beneath Northeast Brazil has been widely discussed (e.g., Fodor et al., 1998, 2002; Rivalenti et al., 2007; Mizusaki et al., 2002). Consistent with this model, notably high-³He/⁴He isotope ratios (15.31–17.58 R<sub>A</sub>) were reported for mantle xenoliths from Fernando de Noronha, indicating the existence of a deep
and undegassed, pristine component involved in the formation of this archipelago (Buikin et al., 2022).

An alternative, non-plume model invokes asthenospheric upwelling beneath a thin lithosphere beneath Northeast Brazil (Guimarães et al., 2020). In this scenario, the hot (up to 1280 °C; Rivalenti et al., 2007) and enriched continental lithosphere near the lithosphere-asthenosphere boundary (LAB) acts as an inverted drainage in which the asthenosphere flows towards the thinnest parts of the oceanic lithosphere (Guimarães et al., 2020). In other words, this mechanism is equivalent to the small-scale (edge-driven) convection, which promotes lateral thermal erosion as a response to the rise of the hot asthenosphere (e.g., Knessel et al., 2011).

We suggest that a mantle plume initiated its activity in the continental area (i.e., Northwest Borborema province) during the Oligocene. In contrast, Fernando de Noronha represents its final expression in the Equatorial Atlantic Ocean since the Miocene. Remarkably, excluding the contemporaneous volcanic activity in continental and oceanic regions (~13–7 Ma), a systematic age progression is observed from Mecejana (35.03–30.8 Ma), Macau (34.0–21.1 Ma), and Fernando de Noronha (<12.5 Ma) (Guimarães et al., 2020 and references therein). Regarding the lack of a short duration magmatism, we consider that a long-lived thermal source would explain this magmatism while the South American plate has been moving westward at ~35–20 Ma, where the Borborema province passed south of the region where the Fernando de Noronha hotspot is currently located (e.g., Morgan, 1983; O’Connor and Duncan, 1990). Supplementary Figure S12 shows the paleo reconstruction from Matthews et al. (2016) of the South American continent, using continental structures from Cordani et al. (2016) and the positions of the plumes in the region (Whittaker et al., 2015).
On the other hand, the effect of an edge-driven convection seems improbable as the main source of the low-velocity seismic anomaly beneath Northeast Brazil due to the decreasing of volcanic ages from continent to ocean. However, the edge-driven convection cell would explain the continental volcanism overlapping the ages of Fernando de Noronha (~13–7 Ma, Knessel et al., 2011).

We propose that the plume would not necessarily be directly beneath the province to generate the synchronous volcanisms observed. The existing plume north of the province, combined with the observed lithospheric thinning, would result in the flow of part of this plume’s material to the province as it drifted westward. Barruol et al. (2019) observed a similar occurrence for the Réunion Hotspot and the Central Indian Ridge, proposing the existence of an asthenospheric flow from the hotspot to the ridge (plume-to-ridge). Our proposal is also analogous to the findings of Park & Chang (2025), which suggested that the overlapping ages of the volcanism in the Caroline Islands can be attributed to the bilateral flow of the Caroline plume, identified as a low-velocity anomaly and positive radial anisotropy.

The existing plume north of the Borborema province, in the region of Fernando de Noronha, combined with the lithospheric thinning in that Province, would result in the flow of part of this plume's material to the province as it drifted westward. This plume-to-province flow (Figure 11a) would remain active for an extended period, resulting in the formation of the Fernando de Noronha-Mecejana Alignment (Figure 11 - FNMA) synchronous with the volcanism in the Borborema province. The lateral flow proposition would also explain the lack of deep thermal anomalies within the mantle discontinuities that would be associated with the presence of a plume directly beneath the Borborema province (Pinheiro & Julià, 2014).
Simões Neto et al. (2018) observed a low-velocity anomaly originating south of the Borborema province. They proposed this could be evidence for lateral flow along sublithospheric channels originating from a plume beneath the Paraná basin, as proposed by Sleep (2003). According to the studies, this would explain the Borborema province's volcanism younger than 85 Ma. We did not observe this feature in our results; however, Simões Neto et al. (2018) included short-period stations in their study that provided a significantly denser sampling of the eastern Borborema Province and, therefore, higher resolution in that region. We believe that it would be more reasonable that a flow coming from the Fernando de Noronha Plume be responsible for the magmatism observed in PB, both due to the age of magmatism and the distance for the displacement of the asthenospheric flow.

The red circles in Figure 11b show events of the Brazilian Seismic Catalog published in April 2024. Assumpção et al. (2004) concluded that areas underlain by slow mantle, interpreted as areas of lithospheric thinning, have a higher occurrence of events due to stress concentration. This same behavior was observed by Rocha et al. (2016) in Central Brasil. Our study corroborates these findings, as the areas of the Borborema province and Transbrasiliano Lineament have a significantly higher number of events in Figure 11b when compared to high-velocity zones, interpreted as cratons. The lack of earthquakes in the central and southern portions of the Parnaíba basin may be an observational blind spot caused by the lack of permanent stations in the area.

## 9 Conclusions

We successfully imaged the upper mantle beneath the Parnaíba basin, Borborema province and adjacent regions, providing a tomographic model for structures extending to sublithospheric depths beneath Northeast Brazil. Stations of the temporary ZL network
provided important new data for better imaging resolution in the southern portion of the Parnaíba basin and its limit with the Borborema province and São Francisco craton

The high velocities observed for the Parnaíba basin were consistent with two cratonic nuclei proposed Klein & Moura (2008), the Granja and Parnaíba blocks. To the north of these anomalies, the São Luís craton was observed as a weak high-velocity anomaly, probably due to the action of metasomatism during breakup from the West African craton and low station coverage in the area. We also concluded that the São Francisco craton extends farther northwest than previously suggested, beneath the Parnaíba basin. We credit this observation to the improved resolution in the area due to the installation of the ZL network.

The low-velocity anomaly beneath the Borborema province presents a certain degree of correlation with previous seismic tomography studies (Ciardelli et al., 2022, Nascimento et al., 2024). This anomaly also coincided with increased seismicity. This strong low-velocity anomaly in the center of the BP is interpreted as the result of a lateral flow of asthenosphere from a plume beneath the oceanic lithosphere to the north, which would explain the intraplate volcanism observed in the BP.

We determined the northeastern expression of the Transbrasiliano Lineament (TBL), observed as a low-velocity anomaly with high occurrence of events. The proposed model is parallel, but with lateral offset, to previous studies (Castro et al., 2014, Cordani et al., 2016). Increased seismicity is observed along the southern expression of the TBL (~12.5°S, 48.5°W), which is associated with lithospheric thinning.
<figure><img src="image_13.png" /></figure>

Figure 11 – Tomographic image at 136 km depth, with anomaly contours on 0.1% intervals. Both figures include the limits proposed by this study: Dark green is the São Luís craton (SLC), magenta is the Granja block (GBI), blue is the Parnaíba block (PBI) and dark yellow is the São Francisco craton (SFC), with the Paramirim Aulacogen (PrmA) region being delimited by the dashed lines. a: comparison between the limits inferred from tomographic model and those proposed by previous studies: PBI, Gbl and SLC as extracted from Klein & Moura (2008). The orange line is the São Francisco Paleocontinental block (Rocha et al., 2019b). FNMA and MQA are the Fernando de Noronha-Mecejana and Macau-Queimados alignments (Knesel et al., 2011). The shaded area is the Barra do Corda Belt from Porto et al. (2022). b: The orange and green dashed lines are the proposed Transbrasiliano Lineament from Cordani et al. (2016) and Castro et al (2014), respectively. The green line is the Araguaína Fault Zone (Daly et al., 2014). The red circles are events from the Brazilian Seismic Catalog of 2024 (Available at: https://seiscode.iag.usp.br/CSUSP/sisbra/releases/tag/v2024May09). The purple arrows indicate the proposed plume-to-province flow between the Fernando de Noronha plume and the BP.

## Author Contributions

Guilherme Affonso (Conceptualization, Data curation, Investigation, Validation, Visualization, Writing – original draft), Marcelo P. Rocha (Conceptualization, Funding acquisition, Project administration, Supervision, Writing – review & editing), Jordi Julià (Conceptualization, Data curation, Funding acquisition, Investigation, Project administration, Resources, Writing – review & editing), Aderson F. do Nascimento (Data curation, Validation, Writing – review & editing), Reinhardt A. Fuck (Funding acquisition, Project
administration, Validation, Writing – review & editing), Eduardo A.S. de Menezes (Data curation, Investigation), Estevão V. C. Tadeu (Data curation, Resources, Writing – review & editing), Karin Sigloch (Methodology, Software, Visualization, Writing – review & editing), Guust Nolet (Methodology, Software, Visualization, Writing – review & editing) & Tiago Jalowitzki (Investigation, Validation, Writing – original draft, Writing – review & editing).

## Acknowledgments

This study was financed in part by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior – Brasil (CAPES) – Finance Code 001. We thank INCT - ET (National Institute of Science and Technology – Tectonic Studies) for funding the ZL network. We also thank Petrobras for funding initial infra-structure of the Brazilian Seismographic Network (RSBR), and the SGB (Geological Survey of Brazil) for its maintenance in the last years. Stations from the BP network, deployed in the Parnaíba basin, were installed with resources from BP Energy Brazil. We thank CNPq for the research fellow grants 315613/2021-1 (M.P. Rocha), 310261/2023-6 (J. Julià), 312884/2021-4 (A.F. do Nascimento), and 301065/2016-0 (R. Fuck). K. Sigloch was supported by the French government through the UCAJEDI Investments in the Future project, reference number ANR-15-IDEX-01. We thank all staff and students that helped in the station installation. We thank the editor, Professor Ian Bastow, and the anonymous reviewer for their valuable comments and suggestions, which have greatly helped improve the quality of this paper.

## Data Availability

Waveform data can be downloaded via FDSN (Federation of Digital Seismographic Networks) web services by using ObsPy (Beyreuther et al., 2010) to access the data repository of University of São Paulo (client name: USP). Waveform data for stations of the AR, BP, RF and ZL networks are currently restricted due to ongoing studies. Waveform data for the 7A network is currently restricted due to commercial interests. The software used in this study can be found at https://www.geoazur.fr/GLOBALSEIS/Soft.html. Tomographic models will be available at https://doi.org/10.5281/zenodo.15113922.

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