# Fine-Scale Crustal Velocity Structure at the Lucky Strike Segment of Mid-Atlantic Ridge From Full Waveform Inversion of Wide-Angle Seismic Data

Zhikai Wang, Satish C. Singh, Timothy A. Minshull, Wayne C. Crawford

► To cite this version:

Zhikai Wang, Satish C. Singh, Timothy A. Minshull, Wayne C. Crawford. Fine-Scale Crustal Velocity Structure at the Lucky Strike Segment of Mid-Atlantic Ridge From Full Waveform Inversion of Wide-Angle Seismic Data. Journal of Geophysical Research: Solid Earth, 2025, 130, pp.2024JB029982. 10.1029/2024JB029982 . insu-05080921

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Submitted on 23 May 2025

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Distributed under a Creative Commons Attribution 4.0 International License
# JGR Solid Earth

## RESEARCH ARTICLE

10.1029/2024JB029982

**Key Points:**

* Crust thins by 4.3–4.7 km from the center to the ends of the Lucky Strike segment, indicating a focused melt supply to the segment center

* Large variation in crustal thickness along-axis is mainly accommodated by a significant thinning of the lower crust toward the segment ends

* Small variation in crustal structure across the ridge axis suggests the current magmatic accretion mode has lasted for 3 Myr

**Supporting Information:**

Supporting Information may be found in the online version of this article.

**Correspondence to:**

Z. Wang,
zw1m23@soton.ac.uk

**Citation:**

Wang, Z., Singh, S. C., Minshull, T. A., & Crawford, W. C. (2025). Fine-scale crustal velocity structure at the lucky strike segment of Mid-Atlantic ridge from full waveform inversion of wide-angle seismic data. *Journal of Geophysical Research: Solid Earth, 130*, e2024JB029982. https://doi.org/10.1029/2024JB029982

Received 22 JUL 2024
Accepted 15 FEB 2025

**Author Contributions:**

**Conceptualization:** Zhikai Wang, Satish C. Singh

**Data curation:** Satish C. Singh, Wayne C. Crawford

**Funding acquisition:** Zhikai Wang, Timothy A. Minshull

**Methodology:** Zhikai Wang

**Project administration:** Zhikai Wang, Timothy A. Minshull

**Software:** Zhikai Wang, Satish C. Singh

**Validation:** Zhikai Wang

**Visualization:** Zhikai Wang

**Writing – original draft:** Zhikai Wang

**Writing – review & editing:**

Zhikai Wang, Satish C. Singh, Timothy A. Minshull, Wayne C. Crawford

© 2025. The Author(s).
This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

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# Fine-Scale Crustal Velocity Structure at the Lucky Strike Segment of Mid-Atlantic Ridge From Full Waveform Inversion of Wide-Angle Seismic Data

Zhikai Wang¹, Satish C. Singh², Timothy A. Minshull¹, and Wayne C. Crawford²

¹School of Ocean and Earth Science, University of Southampton, Southampton, UK, ²Université Paris Cité, Institut de Physique du Globe de Paris, CNRS, Paris, France

**Abstract** The Lucky Strike segment at the Mid-Atlantic ridge, characterized by a well-defined median valley with a central volcano, is an archetypical slow-spreading ridge segment and hence an ideal site for studying magmatic and tectonic processes at slow-spreading ridges. Here we present fine-scale velocity models of this segment, by applying full waveform inversion to wide-angle seismic data, that allows characterization of crustal accretion processes along the entire segment. Along ridge axis, the crust thins from ~8.4 km at the center of the segment to ~3.7–4.1 km at the segment ends. This large variation in crustal thickness is mainly accommodated by lower crustal thinning toward the segment ends. The ratio of the lower/upper crust thickness varies from 2.2 at the segment center to 0.1 at the segment ends, so upper crust at segment ends accounts for ~90% of the crustal thickness, suggesting that the lateral dyking is the primary crustal accretion mechanism. The reduction of lower crustal velocity at the segment center indicates the presence there of melt within the lower crust, which is the source of melt delivery for dyke propagation. The upper crustal velocity gradually decreases from the segment center to segment ends, consistent with an increase in faulting and the presence of more evolved magma toward the segment ends. These observations demonstrate the presence of focused magma supply to the segment center. Off-axis, the upper crustal thickness shows little variation over ~30 km on both flanks, suggesting the current magmatic accretion mode could have been active for 3 Myr.

**Plain Language Summary** The Lucky Strike segment at 37°N on the Mid-Atlantic ridge is characterized by a well-defined median valley and a volcano at the segment center. Studying the structure of crust formed along this segment is critical for understanding the magmatic and tectonic processes at slow-spreading ridges. We present fine-scale crustal structures of the Lucky Strike segment obtained by performing full waveform inversion (FWI) of controlled-source seismic data recorded by oceanic bottom seismometers. FWI is an advanced seismic imaging technique that constrains the velocity of subsurface by fitting the modeled waveform with the waveform of field data. The crustal thickness along axis decreases from ~8.4 km at segment center to ~3.7–4.1 km at segment ends. This variation is mainly due to the thinning of lower crust toward segment ends. This observation demonstrates that the melt is focused to the Lucky Strike segment center and the crust at segment ends is mainly composed of upper crust formed by lateral dyking of melt from the segment center. The across-axis crustal structure shows little variations over ~30 km distance on both flanks, suggesting that enhanced melt supply at segment center is not a transient feature on slow-spreading ridges but can persist for several million years.

## 1. Introduction

Oceanic crust covers over 60% of the Earth's surface and is being continuously created along mid-ocean ridges (MORs) (Searle, 2013). As the two plates move apart at MORs, the mantle upwells and produces basaltic melt by decompression melting (Cann, 1970; McKenzie & Bickle, 1988). The basaltic melt migrates upward and accumulates within the crust. A portion of this accumulated melt erupts to the surface to form lava flows on the seafloor and dykes underneath, forming the upper crust (Cann, 1970; Karson, 1998; Sinton & Detrick, 1992; Vine & Moores, 1972). The remainder of the melt cools and crystallizes in situ, forming the gabbroic lower crust (Guo et al., 2022; Karson, 1998; Kelemen et al., 1997; Vine & Moores, 1972). The crust is separated from the underlying residual mantle by the Mohorovičić boundary (Moho) (Aghaei et al., 2014; Boudier & Nicolas, 1995; Christeson et al., 2019; Nedimović et al., 2005). Across the Moho, the crust and the underlying mantle show significant differences in physical properties and chemical compositions (Christeson et al., 2019; Grevemeyer
et al., 2018; Searle, 2013; White et al., 1992). This crustal accretion pattern has been designated as the “Penrose” model (Conference Participants, 1972). Although this basic model is widely accepted, the crustal accretion process and the resultant crustal structures show large differences at MORs of different spreading rates.

Axis melt lenses have been widely imaged beneath fast- and intermediate-spreading centers, with their top at 0.8–2.5 km depth below the seafloor (Arnulf et al., 2014; Blacic et al., 2004; Canales et al., 2006; Carbotte et al., 2021; Detrick et al., 1987; Kent et al., 1993; Marjanović et al., 2023; Tolstoy et al., 1997). Below the axial melt lens, a broader low velocity zone is observed in the lower crust and upper mantle, indicating the presence of partial melt and hot rocks (Arnulf et al., 2018; Dunn, 2022; Dunn et al., 2000; Harding et al., 1989; West et al., 2001). Crust formed at fast- and intermediate-spreading ridges shows little variation in thickness with slightly thinner crust formed at segment ends at the oceanic transform faults and the overlapping spreading centers (Canales et al., 2003; Roland et al., 2012; Van Avendonk et al., 1998). These observations suggest that the mantle upwelling and melt delivery from the mantle is relatively uniform and sheet-like along fast- and intermediate-spreading centers (Lin & Morgan, 1992) and that magmatic processes are dominant in the crustal accretion.

In contrast, the accretion process and structure of the oceanic crust are more complicated at slow-spreading ridges, such as the Mid-Atlantic ridges (MARs). Axial melt lenses have only been observed at three sites beneath slow-spreading ridges (Alfaro et al., 2007; Combier et al., 2015; Navin et al., 1998; Singh et al., 2006; Sinha et al., 1998) and two of these sites are influenced by hot spots (Alfaro et al., 2007; Navin et al., 1998; Sinha et al., 1998). Below these axial melt lenses, a low velocity zone in the lower crust is observed (Dunn et al., 2005; Seher et al., 2010; Sinha et al., 1998). The crust formed along slow-spreading ridges (e.g., MARs) generally shows a large reduction in crustal thickness from the segment center to the distal ends (Detrick et al., 1995; Dunn et al., 2005; Hooft et al., 2000; Tolstoy et al., 1993), indicating a focused mantle upwelling and melt supply to the center of segment (Lin & Morgan, 1992; Magde & Sparks, 1997), even though uniform crustal thickness is observed along several ridge segments (Christeson et al., 2020; Wang & Singh, 2022). Excess melt delivery to the segment center generally leads to a crust that is locally thicker than the global average of 6.2 km (Dannowski et al., 2011; Dunn et al., 2005; Hooft et al., 2000; Minshull et al., 1991, 1998; Seher et al., 2010; Tolstoy et al., 1993). In contrast, limited melt supply makes the segment ends magmatically starved, forming anomalously thin crust (Dunn et al., 2005; Hooft et al., 2000; Minshull et al., 1991; Tolstoy et al., 1993). The plate separation at the magma-starved slow-spreading ridges could be dominantly accommodated by tectonic extension, exposing lower crustal and upper mantle rocks to the seafloor forming oceanic core complexes (Cann et al., 1997; Cannat et al., 1995).

The Lucky Strike segment at the MAR (Figure 1) is an archetypical example of slow-spreading ridge, with a well-developed axial valley, central volcano and active hydrothermal vent fields, and hence is an ideal site for studying the magmatic, tectonic and hydrothermal processes on slow-spreading ridges (Singh et al., 2006). However, the crustal structure of the whole Lucky Strike segment has not been well constrained. In this paper, we present high-resolution velocity models along and across the Lucky Strike segment obtained by performing two-dimensional (2-D) full waveform inversion (FWI) of wide-angle seismic data. The FWI models allow us to study the changes in crustal accretion mode along the ridge axis and over a ~3 Myr timescale on the Lucky Strike segment.

## 2. Geological Background

The Lucky Strike segment locates at 37°N the MAR, approximately 360 km southwest of the Azores triple junction (Figure 1a). This ridge segment is a part of the plate boundary between the African and the North American plates (Bird, 2003), and is currently spreading at a full rate of ~20 mm/year (DeMets et al., 2010). The Lucky Strike segment is ~70 km long, and is bounded to the south by a non-transform offset (NTO) and the North Famous segment and to the north by another NTO and the Menez Gwen segment (Figure 1a; Parson et al., 2000).

The seafloor within the median valley is shallowest (~1.6 km) at the summit of the central volcano and gradually deepens to ~3.7 km at the nodal basins near the segment ends. A ~7 km long and ~4 km wide axial melt lens reflector (Figure 1b) has been imaged at 3.0–3.4 km depth below seafloor (Combier et al., 2015; Singh et al., 2006) and further below is a broader partially molten zone with low seismic velocity (Seher et al., 2010). A young frozen lava lake and very fresh lavas at the volcanic summit indicate recent magmatism (Fouquet et al., 1995; Humphris et al., 2002). A hydrophone array deployed in the North Atlantic Ocean between 15°N and 35°N (Smith et al., 2002) detected an earthquake swarm in 2001 on the Lucky Strike segment, which was interpreted to result from a dyke intrusion event (Dziak et al., 2004). In addition, the continued microseismicity
<figure><img src="image_3.png" /><figcaption>**Figure 1.** Study area. (a) Bathymetry map showing the Lucky Strike ridge segment in the North Atlantic Ocean and the seismic profiles used in this study. The Lucky Strike segment is bounded to the south and north by non-transform offset (NTOs). The two seismic profiles intersect on the summit of the Lucky Strike central volcano. Lines 201, 301, 212 and 313 were collected during the 2-D data acquisition, while L101 and 112 were collected during 3-D data acquisition. The shot locations on the across-axis profile are shown as black, light gray and gray lines. The shot locations on the along-axis profile are shown as magenta, pink and brown lines. Labels L#a and L#b represent the start and end points of shot lines. The locations of oceanic bottom seismometers are marked by cyan dots. The red curves and the blue star in the globe inset show the global mid-ocean ridges and the position of the Lucky Strike segment. (b) Close-up of the Lucky Strike central volcano. The white inverted triangles show the locations of active hydrothermal vents on the flank of the central volcano (Escartín et al., 2015). The black dashed curves show the fault scarps (Bohidar et al., 2024; Escartín et al., 2014). The magenta curve outlines the extent of the axial melt lens (Combier et al., 2015; Singh et al., 2006).</figcaption></figure>

after the 2001 earthquake swarm indicated possible small vertical dyke intrusions from 2015 to 2019 (Bohidar et al., 2024).

The median valley of the Lucky Strike segment is 15–20 km wide, bounded by two major ridge-ward dipping normal faults (Figure 1a). The bounding faults have vertical throws of 500–900 m and extend in depth close to or into the axial magma chamber (Combier et al., 2015; Singh et al., 2006). Other ridge-ward dipping normal faults have also been imaged within the median valley and some of them cut through the volcanic edifice (Combier et al., 2015; Humphris et al., 2002). Away from the median valley, the seafloor morphology is dominated by fault-controlled ridge-parallel abyssal hills (Figure 1a). These observations suggest that here, tectonic processes play an important role in the formation of oceanic crust, accounting for at least 10% of the plate separation at the central portion of this segment (Combier et al., 2015).

The summit of the Lucky Strike central volcano sustains one of the world's largest hydrothermal fields (Figure 1b; Escartín et al., 2015; Langmuir et al., 1997); and a deep-sea hydrothermal ecosystem (Desbruyères et al., 2001). Some of the hydrothermal vents have been active for hundreds to thousands of years (Langmuir et al., 1997). Near-surface heat flow measurements in the axial domain suggested that the on-axis discharge of water is fed by off-axis recharge (Lucazeau et al., 2006), while a microseismicity study and numerical modeling suggest a component of on-axis recharge (Crawford et al., 2013; Fontaine et al., 2014). Hydrothermal activity can extract heat from the crust, cool the lithosphere and subsequently affect the crustal accretion. Therefore, the accretion of crust at the Lucky Strike ridge segment is controlled by a combined effect of magmatic, tectonic and hydrothermal processes.

# 3. Data and Methods

## 3.1. Wide-Angle Seismic Data

The 2005 SISMOMAR experiment took place onboard the French research vessel “L’Atalante” where wide-angle active-source seismic data were acquired at the Lucky Strike ridge segment (Crawford et al., 2010). Two ~115 km-long 2-D profiles (Figure 1a) were acquired along and across the ridge axis to study the changes in tectonism
and magmatism along the ridge axis and with time. The along-axis profile was at the center of the median valley and covered the whole Lucky Strike segment. The across-axis profile crossed the Lucky Strike central volcano and extended ~50 km on both flanks. Ten oceanic bottom seismometers (OBSs) were deployed along each profile. Each of these OBSs were equipped with a hydrophone and a vertical geophone. The 2-D seismic profiles were first shot at 425 m interval (L201 and L212 in Figure 1a) and then their central parts were re-shot at a shorter interval of 150 m (L301 and L312 in Figure 1a). During the SISMOMAR experiment, a three-dimensional (3-D) seismic refraction survey was also carried out around the central volcano using 25 OBSs and 150 m shot interval to image the crustal structure of the central region of the Lucky Strike segment (Crawford et al., 2010; Seher et al., 2010). Profiles L101 and L112 from the 3-D seismic refraction survey were collocated with the along- and across 2-D profiles, respectively (Figure 1a).

We performed 2-D FWI of the combined data collected along the 2-D seismic profiles (L201, L301, L212 and L312) and the collocated profiles (L101 and L112) from the 3-D seismic refraction survey. We inverted the along- and the across-axis velocity structures separately. The OBS spacings ranged from 4.5 to 12.5 km for both profiles with a denser deployment around the Lucky Strike central volcano (Figure 1a). The seismic source was an airgun array of 8,410 in³ volume deployed at 25 m depth below sea level. Although the total volume and the depth of the airgun source were the same for the 2-D and 3-D seismic data acquisitions, some configurations of the airgun array were different. Therefore, we separately estimated source wavelets for the 2-D and 3-D seismic data. One OBS (A10 in Figure 1a) on the across-axis profile was deployed 900 m above the seafloor in the water column to record the far field signature of the source. Only data recorded on the hydrophone channel were used in the FWI. The seismic data were corrected for linear clock drift, and the shot and OBS locations were determined from direct arrivals (Seher et al., 2010).

## 3.2. First-Arrival Traveltime Tomography of OBS Data

The implementation of FWI requires a starting estimate of the subsurface velocity. The starting model should contain the long-wavelength velocity structure of the subsurface so that no cycle-skipping occurs between the modeled and observed seismic data for the minimum frequency band used in FWI. Seher et al. (2010) performed a 3-D traveltime tomographic inversion of the 3-D SISMOMAR OBS data to constrain crustal velocity structure around the Lucky Strike central volcano. The 3-D tomographic model shows a crustal thickness of ~7.0–7.5 km beneath the central volcano that decreases to 5–6 km over ~15–20 km distance in both along axis directions. However, this model covers only the region within 20 km of the central volcano and does not constrain the crustal structure for the whole ridge segment. Furthermore, mantle refracted arrivals were not used in the 3-D traveltime tomography, so the resulting model provides no information on the mantle velocity. We, therefore, performed 2-D traveltime tomography to obtain starting velocity models for FWI. In our 2-D traveltime tomography, we only used the traveltime of crustal and mantle first arrivals, so it is a first arrival traveltime tomography (FATT). We did not include Moho reflections in tomography because traveltime tomography would require a sharp interface for Moho (e.g., (Seher et al., 2010; Wang & Singh, 2022)), which would need to be smoothed for FWI. Furthermore, we wanted the Moho structure to be constrained by FWI rather than being inherited from the starting model.

To identify the first arrivals and pick their travel times, we filtered the seismic data using a minimum-phase Butterworth band-pass filter with corner frequencies of 3.5 and 20.0 Hz. The seismic data after band-pass filtering show clear first arrivals which can be traced to a maximum offset of ~50 km (Figure 2). We picked the traveltime of first arrivals on the OBS gathers for both along- and across-axis profiles (red dots in Figure 2). We assigned an uncertainty of 36 ms to all the picks, which is the root sum square of the uncertainties associated with errors in shot locations (~3 ms), errors in receiver locations (~2 ms), uncertainty related to the bathymetry (~16 ms), uncertainty related to seismic raypath calculations (~10 ms) (Seher et al., 2010) and the uncertainty in manually picking (~30 ms).

FATT also requires an initial estimate of the subsurface velocity. The initial models for FATT were built by hanging a one-dimensional (1-D) velocity profile below the seafloor. Seafloor depth along the two profiles was extracted from a combined bathymetry data set using the high-resolution (40 × 40 m grid) bathymetry data from the SISMOMAR experiment and the Global Multi-Resolution Topography Synthesis (Ryan et al., 2009) elsewhere. The P-wave velocity in the water column was set to 1.5 km/s and was not updated in FATT. The crustal part of the 1-D velocity profile is based on the prior information from the 3-D traveltime tomographic model
<figure><img src="image_4.png" /><figcaption>**Figure 2.** Examples of oceanic bottom seismometer (OBS) data after band-pass filtering between 3.5 and 20.0 Hz from (a) the along-axis profile and (b) the across-axis profile. The locations of OBSs are marked in Figure 1a. The traveltimes of the data are reduced by a velocity of 7.5 km/s for better display. The red dots mark hand-picked first arrivals. The dashed white and solid black curves show the top and bottom of time windows used in the full waveform inversion of data with offset <25 km and <50 km, respectively. Pg: Crustal refractions; PmP: Moho reflections; Pn: Mantle refractions.</figcaption></figure>

(Seher et al., 2010) and contains an upper crust where velocity increases from 4.0 to 6.5 km/s within 2.5 km depth range and a lower crust where velocity further increases to 7.3 km/s at the bottom of the crust. The thickness of the lower crust in the starting model is 3.5 km for the along-axis profile and 5.0 km for the across-axis profile, respectively. Below the crust, the velocity increases with depth at a gradient of 0.2 s⁻¹ to make sure that rays can penetrate and turn back from the mantle. The starting velocity models for FATT were discretized at 150 m grid spacing horizontally and 50 m vertically.

We applied a least-squares tomographic inversion method developed by Van Avendonk et al. (2004) and parallelized by Jian et al. (2017) to invert the picked first arrival traveltimes. Ray paths and the corresponding traveltimes were calculated using a shortest path method (Moser, 1991). To obtain a smooth velocity model and to avoid the introduction of artifacts, we applied first- and second-order velocity regularizations (Van Avendonk et al., 2004), and the regularization parameters were tested and selected in each iteration step. The standard χ² value was used to measure the mismatch between the modeled and picked traveltimes. We performed 7 and 4 iterations in FATT of the along- and across-axis data, respectively, and we stop the inversion when the χ² value approaches 1. The resulting along- and across-axis velocity models are shown in Figures 3a and 3b, respectively. After FATT, the residuals between the picked and modeled traveltimes are significantly reduced (Figure 4).

### 3.3. Full Waveform Inversion of OBS Data

Taking the velocity model from FATT as the initial model, we performed 2-D time domain elastic FWI to further update the velocity structures along and across the Lucky Strike segment. FWI updates the velocity of subsurface by iteratively minimizing a misfit function defined as the mismatch between the observed and modeled waveforms (Tarantola, 1984). It has higher resolution than traveltime tomography because it compares not only the traveltime information but also the seismic waveform. Theoretically, FWI can reach a resolution of half of the
<figure><img src="image_5.png" /><figcaption>**Figure 3.** Velocity models from first arrival traveltime tomography (FATT) for (a) the along-axis profile and (b) the across-axis profile. The red inverted triangles mark the locations of oceanic bottom seismometers (OBSs). The OBS at ~4.3 km horizontal distance on the across-axis profile was deployed in the water at ~1 km depth below sea level and ~900 m above seafloor to record the far field signature of the airgun array source. The two dashed curves from top to bottom are the 6.5 and 7.5 km/s velocity contours, respectively. The vertical to horizontal exaggeration is 2:1.</figcaption></figure>

propagated wavelength (Virieux & Operto, 2009). The elastic FWI algorithm used in this work was originally developed by Shipp and Singh (2002) for marine streamer data with constant shot and receiver intervals. We modified the code to accommodate seismic data recorded by OBSs with arbitrary shot and receiver intervals in 2-D space. In the following subsections, we describe the details of applying FWI to the OBS data, including seismic data pre-processing, finite-difference waveform modeling, source wavelet estimates, and FWI misfit function and gradient calculation.

### 3.3.1. Seismic Data Pre-Processing

In a real active-source seismic experiment, the seismic wave propagates in the 3-D Earth, but our FWI algorithm is in 2-D. Therefore, a correction must be made to account for the difference between spherical and cylindrical spreading before performing FWI. We carried out this transformation in two steps following the workflow proposed by Pica et al. (1990): (a) multiply the amplitude of the data by $\sqrt{t}$ to correct the amplitude, where $t$ is the traveltime and (b) convolve the data with $1/\sqrt{t}$ to adjust the phase. In this work, we progressively inverted the seismic data of three frequency bands (3.5–6.5 Hz, 3.5–8.0 Hz and 3.5–10.0 Hz), and the seismic data after geometry correction were band-pass filtered correspondingly in the inversion of each frequency band.

We focused on inverting the seismic first arrivals and some later wide-angle reflections from the Moho. The direct arrivals propagating in the water column, the near-offset reflections and the seismic multiples were muted. These arrivals are excluded from inversion because the near-offset reflections and seismic multiples can significantly increase the nonlinearity of inversion leading FWI converge to local minimum. The velocity in the water column is not updated in FWI. We designed a 1.0 s time window starting from 0.1 s prior to first picked arrival that includes the seismic first arrivals and the wide-angle reflections (see examples in Figure 2).
<figure><img src="image_6.png" /><figcaption>**Figure 4.** Comparison of traveltime residuals before and after the first arrival traveltime tomography. (a) For the along-axis profile and (b) for the across-axis profile.</figcaption></figure>

### 3.3.2. Time-Domain Finite Difference Waveform Modeling

An accurate and efficient waveform modeling method is critical for performing FWI. Firstly, waveform modeling is used to generate synthetic seismic data for the comparison with the observed data to obtain seismic residuals. Secondly, the seismic residuals are back projected into model space by simulating wave propagation in the subsurface to estimate the velocity gradient for updating the velocity model (Shipp & Singh, 2002; Tarantola, 1984). Here, we simulated wave propagation by solving the 2-D elastic-wave equation using a time domain finite-difference (FD) approach proposed by Levander (1988). This FD approach has 2nd-order accuracy temporally and 4th-order accuracy spatially. It requires at least 5 grid points within the shortest wavelength to avoid numerical dispersion and in our case, the shortest wavelength of P-wave occurs in the water column. Therefore, we interpolated the velocity model to 40, 30 and 25 m grid spacings, respectively, in the waveform modeling of 3.5–6.5 Hz, 3.5–8.0 Hz and 3.5–10.0 Hz data. Correspondingly, we used time steps (Δt) of 2, 2 and 1 ms to ensure that the waveform modeling is stable (Δt < 0.606h/Vmax, where h is the grid spacing and Vmax is the maximum value in the P-wave velocity model (Levander, 1988)). We applied an absorbing boundary condition (Clayton & Engquist, 1977) to attenuate the reflections from all model boundaries.

### 3.3.3. Source Wavelet Estimate

The synthetic waveform modeling requires a source wavelet to represent the source signature generated by the airgun array. An accurate source wavelet is important for FWI because errors in seismic waveform difference due
<figure><img src="image_7.png" /><figcaption>**Figure 5.** (a) Aligned seismic traces showing the near-offset direct wave extracted from OBS-A10 gathers from 2-D data acquisition. The seismic data has been band-pass filtered between 3.5 and 20.0 Hz. The dashed line shows the time of 0.1 s. (b) Stack of traces in panel (a). (c) The estimated source wavelets for full waveform inversion of 2-D collected seismic data by filtering the stacked signal in panel (b) to 3.5–6.5 Hz (in gray), 3.5–8.0 Hz (in black) and 3.5–10.0 Hz (in brown), respectively. (d) Comparisons of synthetic (in black) and observed (in red) near-offset water wave for OBH-A10 using 3.5–10.0 Hz source wavelet in panel (c).</figcaption></figure>

to an inaccurate source wavelet will introduce artifacts into the velocity model. To characterize the source signature of the airgun array used in data collection, an OBS on the across-axis profile (OBS-A10 in Figure 1a) was deployed at 1.0 km depth in the water column, which is ~900 m above the seafloor. This OBS recorded high-quality near-offset direct water-wave arrivals which are not contaminated by the later arrivals (Figure 5a). These water-wave arrivals propagated directly from the airgun array to the OBS, preserving the source signature, since there is negligible attenuation in the water column at the frequencies used. Therefore, we estimated the source wavelets by stacking the near-offset water-wave arrivals recorded by the OBS-A10.

The source wavelet estimation was carried out in the following steps: (a) we extracted five near-offset traces from the OBS-A10 seismic gather after band-pass filtering between 3.5 and 20 Hz and aligned the extracted traces to the same starting time of 0.1 s. These aligned traces show high similarity in waveform of water-wave arrivals (Figure 5a). (b) We muted the signals after 0.5 s to exclude the influence of seismic multiples and later reflections. (c) We stacked the aligned traces (Figure 5b) and filtered the stacked signal using the same band-pass filters (3.5–6.5 Hz, 3.5–8.0 Hz or 3.5–10.0 Hz; Figure 5c) as applied to seismic data in FWI. (d) We determined the starting time of the source wavelets by performing finite difference waveform modeling and comparing the modeled and observed near-offset water arrivals (Figure 5d).

We used a FWI misfit function comparing the modeled and observed seismic data after trace-by-trace normalization (see Section 3.3.4), which primarily fit the traveltime or phase information. Therefore, the precise amplitude of the source wavelet is not needed. Figure 5d shows the comparisons of the observed and modeled near-offset water arrivals for OBS-A10 using 3.5–10.0 Hz source wavelet. The good match between the modeled and observed water arrivals demonstrates that the estimated source wavelets are sufficiently accurate for performing FWI.

### 3.3.4. Misfit Function and Gradient Calculation

FWI updates the velocity of the subsurface by iteratively minimizing a misfit function defined as the mismatch between the observed and modeled seismic data. The choice of the misfit function is critical for the successful application of FWI. The FWI algorithm originally proposed by Tarantola (1984) directly compares the difference
between the modeled and synthetic seismic data sample by sample under L₂-norm context (true-amplitude FWI). However, the field-collected seismic data are contaminated by noise. Moreover, the Earth's intrinsic attenuation effect can distort the seismic waveform (Toksoz & Johnston, 1981). The seismic attenuation could be strong at spreading centers due to the high temperature and the presence of melt (Dunn et al., 2005; Wilcock et al., 1995). However, neither field noise nor seismic attenuation can be modeled using our elastic FWI method. In this work, we applied a modified version of the trace-normalized misfit function proposed by Liu et al. (2016).

$$S = \frac{1}{2} \sum_{i=1}^{Ns} \sum_{j=1}^{Nr} \left( \frac{d(i,j)}{\|d(i,j)\|} - \frac{u(i,j)}{\|u(i,j)\|} \right)^2 w(i,j), \quad (1)$$

where, S denotes the FWI misfit function. d(i,j) and u(i,j) represent the j-th trace of the i-th observed and modeled OBS seismic gathers, respectively. Ns is the total number of OBS gathers and Nr is the trace number within each OBS gather. w(i,j) is a weighting factor (see below). || || represents the L₂-norm of a vector.

The trace-normalized misfit function in Equation 1 is equivalent to the normalized zero-lag cross-correlation measuring the similarity between the modeled and observed seismic data after trace-by-trace normalization (Tao et al., 2017)

$$S = \sum_{i=1}^{Ns} \sum_{j=1}^{Nr} \left( 1 - \frac{d(i,j)^T u(i,j)}{\|d(i,j)\| \|u(i,j)\|} \right) w(i,j), \quad (2)$$

therefore, it is not sensitive to the absolute amplitude of seismic data. Tao et al. (2017) shows that this misfit function can decouple the composite waveform such as the triplications of crustal and mantle refractions and Moho reflections around the critical angle. Furthermore, the trace-normalized FWI is less sensitive to the errors in the source wavelet than is the true-amplitude FWI, allowing it to produce a reasonable velocity model when the source wavelet is not precise (Liu et al., 2016). The disadvantages of the trace-normalized misfit function are that it increases the nonlinearity of inversion (Liu et al., 2016), and that it discards important information carried by amplitudes of seismic data. In the practical implementation of FWI, we introduced a weighting factor $w(i,j) = \|d(i,j)\|$ to mitigate the nonlinearity of FWI by highlighting the near-offset seismic data which constrains the shallow crust. In general, the amplitude of OBS data should be scaled, for example, by the root mean square (RMS) amplitude of the entire gather, to guarantee they have similar contribution to the FWI gradient, which is used for updating the velocity model. However, we did not scale the OBS data in this work as they have similar RMS amplitude.

Starting from the velocity model obtained from FATT, FWI gradually updates the velocity model by iteratively decreasing the FWI misfit function

$$m_{n+1} = m_n + \lambda_n g_n, \quad (3)$$

where m is the model parameter, λ is the step length, g is the gradient of the FWI misfit function and n is the iteration number. A constant step-length of 30 m/s was used in all iterations. We only inverted the P-wave velocity of the subsurface (not the water column), that is, m represents P-wave velocity. The OBS data do not show clear S-wave arrivals (Figure 2). Therefore, the S-wave velocity and density models were calculated from the starting P-wave velocity using the empirical relationships given in Brocher (2005) and were fixed throughout the inversion. We computed the FWI gradient g by zero-lag cross-correlating the source generated forward-propagated wavefield and the adjoint source generated wavefield by back projecting the seismic residuals (Shipp & Singh, 2002; Tarantola, 1986). The residual R corresponding to the misfit function in Equation 1 can be derived using the adjoint-state method (Plessix, 2006)

$$R(i,j) = \frac{1}{\|u(i,j)\|} \left( \frac{\int d(i,j) u(i,j) dt}{\|u(i,j)\|^2} u(i,j) - d(i,j) \right) \quad (4)$$

Some pre-conditioning processes were applied to the FWI gradient before using it to update the velocity model. The gradient of the water column is muted so that the velocity of the water column is not updated. We tapered the
gradient within 200 m distance from OBSs. Considering the sparse deployment of OBSs, we smoothed the ve-
locity gradient over 0.5 km depth vertically and 2.5 km distance horizontally to mitigate artifacts introduced by
insufficient data coverage. A conjugate-gradient method (Scales, 1987) was adopted to speed up the convergence
of FWI.

4. Results

**4.1. Full Waveform Inversion Results**

In the practical implementation of FWI, we adopted the multi-scale inversion strategy (Bunks et al., 1995) to ensure FWI converge to the global minimum. The inversion started by using 3.5–6.5 Hz data and then proceeded to 3.5–8.0 Hz data followed by the inversion of 3.5–10.0 Hz data. The multi-stage strategy for offset (Shipp & Singh, 2002) was introduced in the inversion of each frequency-band data, where we first inverted the near-offset data within 25 km offset and then increased the offset to 50 km. We performed 50 iterations in the inversion of each frequency band data, including 30 iterations for the near-offset data and 20 iterations for the far-offset data. In each step, the misfit function gradually decreased with increasing iterations, for both along- and across-axis data (Figures 6a and 6b). A large reduction in misfit was achieved in the inversion of near-offset (<25 km) data for each frequency band due to the inclusion of new frequency components in inversion. Meanwhile, the misfits for most OBS gathers were reduced to 40%–70% after FWI for both along- and across-axis profiles (Figures 6c and 6d). The synthetic data after FWI have a better match with the observed seismic data, both in traveltime and trace-by-trace normalized amplitude (Figure 7 and Figures S1 and S2 in Supporting Information S1), demonstrating the velocity models from FWI is closer to the real subsurface velocity than the tomographic models. Waveform mismatch at large offsets is observed in some OBSs, which could be due to insufficient velocity updating at relatively great depth. Compared with the velocity models from FATT (Figures 3a and 3b), the models from FWI (Figures 8a and 9a) show more fine-scale structure.

4.2. Resolution Tests

We performed a checkerboard test to assess the resolution of the FWI results (Guo et al., 2022; Jian et al., 2021). We built checkerboard models by adding 2-D sinusoidal anomalies with maximum velocity perturbations of ±5% into the final models from the FWI of OBS data. Synthetic seismic data were generated by performing time-domain FD modeling using these checkerboard models and the same source wavelets and data acquisition geometry as those used in FWI of OBS data. Taking the final models from the FWI of the OBS data as starting models, we inverted the synthetic seismic data following the same workflow as that for the inversion of OBS data and using the same inversion parameters and time window for data selection.

We tested checkerboard patterns with size of 0.75 × 7.5 km (vertical × horizontal) and 0.5 × 5.0 km for the along-axis model. The checkerboard pattern of 0.75 × 7.5 km size is well recovered after FWI between −35 and 35 km horizontal distance (Figure 10a). When the size of the checkerboard pattern reduces to 0.5 × 5.0 km, only anomalies at the central part of the model between −20 and 10 km horizontal distance are partially recovered (Figure 10b). For the across-axis model, we tested checkerboard patterns with size of 1.0 × 10.0 km and 0.75 × 7.5 km. The checkerboard pattern of 1.0 × 10.0 km size is recovered between −30 and 30 km horizontal distance after FWI (Figure 11a). When the size of the checkerboard pattern reduces to 0.75 × 7.5 km, the anomalies within the upper crust between −20 and 20 km horizontal distance are recovered (Figure 11b).

Here, we interpret the velocity model between −30 and 33 km horizontal distance for the along-axis profile, which covers the whole Lucky Strike segment. We only interpret the velocity structure between −30 and 30 km horizontal distance for the across-axis profile - the region constrained by the OBS data. Considering a full spreading rate of ~20 mm/year and assuming symmetric spreading of the Lucky Strike segment (DeMets et al., 2010), the across-axis profile constrains the structure of crust up to the age of ~3 Myr.

**4.3. Crustal-Mantle Boundary and Crustal Thickness**

The FWI models do not show a sharp Moho boundary between the crust and mantle (Figures 8a and 9a). This could be either due to the limited vertical resolution (500–750 m) of our FWI method or because the Moho is a transition zone (MTZ) between the crust and mantle (Dhabaria & Singh, 2024; Vera & Diebold, 1994; Wang et al., 2023). A recent FWI study reveals that the MTZ beneath the 70-Ma crust in the equatorial Atlantic Ocean is
<figure><img src="image_8.png" /><figcaption>**Figure 6.** (a, b) Variations of normalized misfit function of full waveform inversion (FWI) with iterations for along- and across-axis profiles, respectively. (c, d) Normalized misfit for each oceanic bottom seismometer gather (3.5–10.0 Hz) from first arrival traveltime tomography and FWI models for the along- and across-axis profiles, respectively.</figcaption></figure>
<figure><img src="image_9.png" /><figcaption>**Figure 7.** Comparisons of observed (in red) and synthetic (in black) seismic data before and after full waveform inversion (FWI). (a) For OBS-A16 on L201 and (b) for OBS-A13 on L212. The observed data have been filtered between 3.5 and 10.0 Hz and the synthetic data are modeled using 3.5–10.0 Hz source wavelet. Upper panels compare the observed data with synthetic data modeled using the velocity model from first arrival traveltime tomography. Lower panels compare the observed data with synthetic data modeled using the velocity model from FWI. The locations of oceanic bottom seismometers are marked on Figure 1a. For better visibility, the seismic data has been normalized trace by trace and their traveltime is reduced using a reduction velocity of 7.5 km/s.</figcaption></figure>
<figure><img src="image_10.png" /><figcaption>**Figure 8.** (a) Velocity model from full waveform inversion (FWI) for the along-axis profile. The brown and magenta curves are the interpreted upper-lower crust boundary and the Moho boundary in this work, respectively. The red curve marks the location of the axial melt lens reflection from Combier et al. (2015). The blue dashed curve is the Moho boundary constrained by 3-D traveltime tomography form Seher et al. (2010). The two black dashed curves are the 6.5 and 7.5 km/s velocity contours. The red inverted triangles mark the locations of oceanic bottom seismometers. The vertical to horizontal exaggeration is 2:1. (b) Vertical velocity gradient of the inverted model. The black dashed curves are the 0.5 s⁻¹ contour. The thick black dashed curves outline the two interpreted Moho transition zones (MTZ-A and MTZ-B). (c) Along-axis variations of crustal thickness from traveltime tomography (in blue (Seher et al., 2010);) and from FWI (in magenta), upper crustal thickness (UCT) (in brown) and lower crustal thickness (LCT) (in black). The brown circle shows the UCT from the across-axis velocity model at the intersection of the along- and across-axis profiles. (d) Along-axis variations of the ratio between LCT and UCT. The black dashed line demarcates LCT/UCT = 2. (e) Along-axis variations in the upper crustal velocity at 1.0, 1.5 and 2.0 km depth below the seafloor. The black, blue and green circles show the velocity at 1.0, 1.5 and 2.0 km depth from the across-axis velocity model at the intersection of the along- and across-axis profiles.</figcaption></figure>
<figure><img src="image_11.png" /><figcaption>**Figure 9.** Velocity model from full waveform inversion for the across-axis profile. The brown curve is the interpreted upper-lower crust boundary. The red curve marks the location of the axial melt lens reflection from Combier et al. (2015). The blue dashed curve is the Moho boundary constrained by 3-D traveltime tomography from Seher et al. (2010). The two black dashed curves in are the 6.5 km/s and 7.5 km/s velocity contours. The red inverted triangles mark the locations of oceanic bottom seismometers (OBSs). The OBS at –4.3 km horizontal distance on the across-axis profile was deployed in the water at ~1 km depth below sea level and ~900 above seafloor. The vertical to horizontal exaggeration is 2:1. (b) Vertical velocity gradient of the inverted model. The black dashed curves are the 0.5 s⁻¹ contour. (c) Upper crustal thickness (in brown) and seafloor depth (in black). Only the upper crust thickness between –30 and 30 km horizontal distance is plotted, which is constrained by the data.</figcaption></figure>

1.0 ± 0.5 km thick and is characterized by a high velocity-gradient of >0.5 s⁻¹ (Dhabaria & Singh, 2024). We observed high-velocity gradient zones that could be interpreted as MTZs at two locations in the along-axis FWI model (MTZ-A and MTZ-B in Figure 8b). The MTZ-A is ~9 km wide, ~1 km thick and locates at 9–10 km depth below the Lucky Strike central volcano (Figure 8b). The velocity of MTZ-A increases with depth from ~6.8 km/s to ~7.6 km/s (Figure 12a). The MTZ-B spans between –20 and –10 km horizontal distance at 8–9 km depth (Figure 8b) and its velocity increases from ~7.2 km/s to ~7.9 km within ~1 km depth range (Figure 12b). High velocity-gradient zones indicating rapid changes from crustal to mantle velocities are not observed elsewhere in the along-axis model, which could be due to the MTZ is locally narrower in these regions that is not resolved in the FWI result.

To investigate crustal thickness variations along the entire ridge segment, we used the 7.1 km/s velocity contour as a proxy for the base of the oceanic crust, corresponding to the global mean velocity at the oceanic crustal base (Christeson et al., 2019). We extracted the depth of the 7.1 km/s velocity contour and smoothed it using a 7.5 km-wide moving Gaussian window and then took it as the crust–mantle boundary (magenta curve in Figure 8a). Along the axis of the Lucky Strike segment, the FWI model shows large variations in the crustal thickness (magenta curve in Figure 8c). The thickest crust of ~8.4 km is observed at the center of the segment beneath the central volcano. The crustal thickness decreases abruptly to ~4.6–4.9 km at ~10 km from the segment center, and then more gradually to ~3.7 km at the northern end and to ~4.1 at the southern end of the segment. The mean
<figure><img src="image_12.png" /><figcaption>**Figure 10.** Checkerboard tests for the along-axis profile. Panels on the top are the input checkerboard patterns, and panels on the bottom are the recovered models. The size of the input checkerboard pattern is (a) 0.75 × 7.5 km (vertical × horizontal) and (b) 0.5 × 5.0 km, respectively. The maximum velocity perturbations in the input checkerboard pattern are ±5%. The red inverted triangles mark the locations of the oceanic bottom seismometers. The vertical to horizontal exaggeration is 2:1.</figcaption></figure>

crustal thickness along the ridge axis is ~5.2 km with a standard deviation of 1.3 km. If we use the 7.0 km/s or 7.2 km/s velocity contour to represent the depth of the crust-mantle boundary, the mean crustal thickness differs by 0.35 km.
<figure><img src="image_13.png" /><figcaption>**Figure 11.** Checkerboard tests for the across-axis profile. Panels on the top are the input checkerboard patterns, and panels on the bottom are the recovered models. The size of the input checkerboard pattern is (a) 1.0 × 10.0 km (vertical × horizontal) and (b) 0.75 × 7.5 km, respectively. The maximum velocity perturbations in the input checkerboard pattern are ±5%. The red inverted triangles mark the locations of the oceanic bottom seismometers. The vertical to horizontal exaggeration is 2:1.</figcaption></figure>

4.4. Upper Crustal Structure

For both along- and across-axis profiles, the velocity models show large velocity gradient in the upper crust (Figures 8b and 9b) indicating a rapid velocity increase with depth. We smoothed the depth of the 6.5 km/s velocity contour using a 7.5 km-wide moving Gaussian window and took it as the boundary between the upper and lower
<figure><img src="image_14.png" /><figcaption>**Figure 12.** Average 1-D velocity-depth profiles. (a) At segment center between -1 and 1 km distance. (b) Between -14 and -16 km distance. (c) At southern segment end between -24 and -26 km distance. (d) At northern segment end between 29 and 31 km distance. The horizontal black dashed lines show depths of the base of the upper crust. The blue dashed box in panels (a, b) outline the velocity-depth range of the interpreted Moho transition zones.</figcaption></figure>

crust (brown curves in Figures 8a and 9a). The 6.5 km/s velocity is the global mean velocity at the base of the upper crust (Christeson et al., 2019). The upper crust shows velocity gradient dominantly >0.5 s⁻¹ and a clear decrease in velocity gradient is observed at the interpreted upper/lower crustal boundary (Figures 8b and 9b).

The thickness of the upper crust ranges between 2.5 and 3.6 km along the ridge axis (brown curve in Figure 8c), with a mean thickness of 3.0 ± 0.3 km. The upper crust is slightly thinner (<3.0 km) around the segment center and is thicker (3.3–3.6 km) at the segment ends. This slightly increased upper crustal thickness (UCT) could be due to slightly reduced velocity in the lower crust at the segment ends below, where a part of the lower crust could have been accounted in the UCT estimation. To investigate the lateral variations in the upper crustal velocity, we plot the velocity at 1.0, 1.5 and 2.0 km depth below the seafloor (Figure 8e). The upper crustal velocity decreases along the ridge axis from the segment center to both segment ends. At the same depth below the seafloor, the upper crustal velocity at the segment ends is up to 2.5 km/s lower than that at the segment center (Figure 8e). The upper crust velocity at the northern segment end is up to 1.0 km/s higher than that at the southern segment end (Figure 8e).

Off-axis, the upper crust is generally 1.8–2.8 km thick (brown curve in Figure 9c). Thicker upper crust of 3.2 km is only observed beneath the western bounding wall of the median valley. The mean thickness of the upper crust is
2.4 ± 0.3 km across axis, ~600 m thinner than the mean thickness of the upper crust in the along-axis direction. Variations in the across-axis UCT are small, corresponding to a standard deviation of 0.3 km. At the intersection (horizontal distance of 0 km) with the along-axis profile, the upper crust is ~2.7 km thick, consistent with that (2.6 km) estimated from the along-axis velocity model.

## 4.5. Lower Crustal Structure

The lower crust shows significant variations in thickness along the ridge axis, thinning rapidly from ~6.3 km at the segment center to ~2.3 km over ~10 km distance and then further thinning slowly to ~0.5–0.7 km at the segment ends (black curve in Figure 8c). The variation of the lower crustal thickness (LCT) mimics the variation of crustal thickness along the ridge axis, indicating the large variation in the crustal thickness is mainly due to the significant thinning of lower crust toward the segment ends (Mutter & Mutter, 1993). Previous compilations, which mostly include estimates from segment centers of slow-spreading ridges, have indicated that the oceanic lower crust has a small velocity gradient (<0.2 s⁻¹) with velocity ranging between ~6.5 and ~7.1 km/s (Christeson et al., 2019; Spudich & Orcutt, 1980; White et al., 1992). However, the velocity at the Lucky Strike segment ends increases rapidly (at a gradient >0.5 s⁻¹) from ~2.5 km/s at seafloor to 7.1 km/s at ~3.6–4.0 km depths (Figures 12c and 12d), supporting a thin or absent lower oceanic crust at the segment ends.

At the same depth, the lower crust at the segment center shows reduced velocity, starting approximately from the depth of the axial magma chamber reflector (Combier et al., 2015; Singh et al., 2006) and extending to the base of the crust (Figures 8a and 9a). The lower crust with reduced velocity extends ~5–7 km away from the segment center along the ridge axis while it extends ~10–15 km across axis. At 4–5 km depth below the seafloor, the velocity within the low-velocity zone is ~0.5 km/s lower than the average velocity of crust at 15–20 km distance east of the spreading center. This difference is consistent with the estimate from the 3-D tomography study (Seher et al., 2010). The analysis of Seher et al. (2010) suggests that the velocity reduction within the low velocity zone cannot be solely explained by the elevated temperature at the spreading center but requires the presence of 0.2%–1.2% of melt.

# 5. Discussion

## 5.1. Strong Melt Focusing to the Center of the Lucky Strike Segment

The FWI result shows a thick crust—up to 8.4 km—at the center of the Lucky Strike segment, which is ~1.0–1.5 km thicker than the estimate from the 3-D traveltime tomography of Seher et al. (2010) and more than 2.0 km thicker than the global average of 6.2 km for slow-spreading crust (Christeson et al., 2019). Crust with comparable thickness to that at the center of the Lucky Strike segment is also observed at other slow-spreading ridge locations that are distant from hotspot influences (Dannowski et al., 2011; Hooft et al., 2000; Tolstoy et al., 1993). For example, the OH-1 segment at 35°N the MAR has 8.1 km-thick crust at the segment center (Dunn et al., 2005; Hooft et al., 2000) and the 33°S segment on the MAR shows 7.8 km-thick crust at its center (Tolstoy et al., 1993). The crust at the center of the propagating TAMMAR segment at 21.5°N on the MAR is 8.0 km thick (Dannowski et al., 2011). Some magmatically robust ultraslow-spreading ridges also show thick crust at the segment center, such as the Southwest Indian Ridge segment at 50°28'E (full rate of 13 mm/yr) where 9.5–10.0 km-thick crust is observed at its center (Jian et al., 2017; Li et al., 2015; Niu et al., 2015). The thick crust at segment center indicates a more 3-D mantle upwelling beneath these ridges with enhanced melt delivery to the segment center (Hooft et al., 2000; Li et al., 2015; Seher et al., 2010). An axial melt lens is imaged at 3.0–3.4 km depth at the center of the Lucky Strike segment (Combier et al., 2015; Singh et al., 2006), underlain by a broader partially molten zone within the lower crust (Figures 8a and 9a and Seher et al., 2010). These observations demonstrate that the magmatism is the dominant process for crustal accretion at the center of the Lucky Strike segment.

Along the ridge axis, the crust thins rapidly by 3.5–4.0 km (or by ~45 ± 3%) over 10 km away from the segment center. Further toward the segment ends, the crustal thinning is up to 4.7 km, which means the crust is less than half as thick at the segment ends than at the segment center. A gravity study of the Lucky Strike segment suggests ~3.0 km crustal thinning from the segment center to the segment ends (Detrick et al., 1995) and the 3-D traveltime tomographic model suggests ~2.0 km reduction in along-axis crustal thickness over 15–20 km distance away from segment center (Seher et al., 2010), but our FWI model indicates a much stronger melt focusing effect. Crustal thinning toward the ends of segments is widely observed along slow-spreading (Dannowski et al., 2011; Hooft et al., 2000; Tolstoy et al., 1993) and ultraslow-spreading ridges (Jian et al., 2017; Li et al., 2015; Minshull et al., 2006). A compilation from Wang and Singh (2022) shows that the crust formed at the segment center of slow-
<figure><img src="image_15.png" /><figcaption>**Figure 13.** A schematic diagram showing the main crustal features in the full waveform inversion models with the bathymetry capped on the top. The crust formed at the Lucky Strike segment is divided into upper crust and lower crust. The upper crust is composed of lava flow on the top (black ovals) and dykes underneath. The upper crustal thickness shows small variations in both along- and across-axis directions. In contrast, the lower crustal thickness shows large reduction from the segment center to the segment ends. An axis melt lens (AML) is located at ~3.4 km depth below the seafloor and is confined to the segment center (Combier et al., 2015; Singh et al., 2006). The lower crust below the AML is partially molten with 0.2%–1.2% of melt (this work and Seher et al., 2010). The dashed black arrows represent the lateral dyking with melt from the AML at the segment center, which is the main process forming the upper crust along the entire segment. The melt gets more evolved during the lateral transport through dyke. The thin solid black arrows represent the dyking-fissure eruption. Away from the ridge axis, ridge-dipping faults (dashed black lines) cut the crust (Combier et al., 2015; Singh et al., 2006).</figcaption></figure>

spreading ridges is generally 2.8–5.7 km thicker than that formed at the corresponded segment ends. The large reduction in crust thickness along axis of the Lucky Strike segment is primarily accommodated by the thinning of the lower crust, suggesting a highly focused melt supply to the segment center and significantly reduced melt supply to the segment ends. Detachment faulting might occur at the Lucky Strike segment ends as it is common at the magmatically-limited ends of the MAR segments (Escartín et al., 2008). There is no evidence in swath bathymetric data (Escartín et al., 2014) for the corrugated surfaces that are often diagnostic of such faulting (Cann et al., 1997).

## 5.2. Upper Crustal Accretion Through Lateral Dyking on the Lucky Strike Segment

In contrast to the thinning of the crust toward the segment ends, the upper crust shows very little variation in thickness along the whole ridge segment. Similarly, seismic layer 2A within the axial valley shows a nearly constant thickness of ~600–700 m within 20 km distance from the segment center (Crawford et al., 2010). The layer 2A/2B boundary has been interpreted as a lithologic boundary because the seismic event representing the layer 2A/2B boundary on the depth-converted migration image is sub-parallel with the 4.5 km/s velocity (Crawford et al., 2010). Further toward the northern segment end, the seismic layer 2A thins to ~300 m while toward the southern segment end, the layer 2A/2B boundary reflection event becomes distorted (Crawford et al., 2010). These observations indicate the presence of a magmatic upper crust along the whole Lucky Strike segment. Taking the 6.5 km/s velocity contour as a proxy of the base of upper crust might over-estimate the UCT at segment ends. Using the 6.2 km/s velocity contour as a proxy of the upper and lower crustal boundary (Guo et al., 2022) at segment ends will decrease the UCT only by ~200 m, which would not affect our conclusions.

Since the axial melt lens and the partially molten lower crust are observed only in the very central portion of the Lucky Strike segment, we propose that the oceanic upper crust along the whole ridge segment is mainly formed by the volcanic eruption and/or by the redistribution of melt from the segment center through lateral dyke injection (Figure 13). This mechanism means that most of the upper crust on the Lucky Strike segment is not formed by a
magma reservoir underneath, but by a magma reservoir below the central volcano. In this case, the northern and southern portions of the Lucky Strike segment can be treated as the rift zones of the Lucky Strike central volcano, similar to those observed on other volcanos, such as the north and south rift zones on the Axial Seamount (Embley et al., 1990). Side-scan sonar data and swath bathymetric data have shown volcanic morphologies along the entire Lucky Strike segment within the median valley and un-faulted sheet flows overlapping sediment at the segment ends (Parson et al., 2000). The collected basalts are highly enriched at the center of the Lucky Strike segment and get more evolved toward the segment ends, indicating preferential melt focusing to the segment center and melt delivery to the segment ends through lateral dyking (Gale et al., 2011).

Lateral dyke propagation over long distance has been observed at several volcanic sites with focused melt supply. At the Axial Seamount on the intermediate-spreading Juan de Fuca ridge, the dyke propagated ~50 km distance along the south rift zone during the 1998 eruption (Dziak & Fox, 1999) and propagated at least 19 km along the north rift zone during the 2015 eruption (Chadwick Jr et al., 2016). On a segment of the slow-spreading MAR at 53.3°–54.3°N, a seismic swarm reveals a dyke propagation over ~60 km distance along the ridge axis (Cesca et al., 2023). Similarly, lateral dyking over 45–60 km distances is also observed on a magmatic segment at the Afar rift (Wright et al., 2006) and on the volcanic systems in Iceland (Gudmundsson et al., 2016; Sigmundsson et al., 2015). The melt stored away from the Lucky Strike segment center (if present) could be tapped by the lateral propagation of dyke fed by the segment center reservoir, leading to a mixture of compositionally different melt and contributing to lateral dyke propagations. The tapping of locally stored melt by propagating dykes has been observed during several Axial Seamount eruptions (Chadwick et al., 2005; Lee et al., 2022) and the 2018 Kīlauea eruption (Gansecki et al., 2019). Furthermore, the later-stage lateral dyke could intrude into the pre-existing lower crustal gabbro, producing a heterogeneous crust and reducing the lower crustal velocity. Although we cannot preclude that some melt is delivered directly from the mantle to the crust without focusing to the segment center (Gale et al., 2011), the observations from other sites support that lateral dyking with melt from the reservoir at segment center can build up the upper crust along the entire Lucky Strike segment, where the distance between the segment center and ends is ~30 km.

### 5.3. More Faulting and More Evolved Melt Toward the Segment Ends

Along the ridge axis, the upper crustal velocity shows a clear decrease from the segment center to the segment ends. Similar variations in upper crustal velocity are also observed along the axis of other slow-spreading segments, such as the OH-1 and OH-3 segments in the north Atlantic Ocean (Hooft et al., 2000; Hosford et al., 2001). The decrease in upper crustal velocity toward the segment ends can be attributed to the development of more faults due to less frequent melt injection toward segment ends. Faulting can decrease the crustal velocity by creating more fractures and fissures and increasing the porosity of the crust. The upper crustal velocity is lower at the southern segment ends than at the northern segment ends, implying the melt injection through lateral dyking might be asymmetric.

The basalts collected from the Lucky Strike spreading center show a nearly symmetrical decrease in MgO from the segment center to the distal ends (Gale et al., 2011). This is due to the cooling and fractionation of melt as it migrates toward the segment ends. Excluding the influence of crack and porosity, the velocity of volcanic rocks gradually decreases as it contains less fraction of MgO at a constant pressure-temperature condition (Kelemen & Holbrook, 1995; Korenaga et al., 2002). Therefore, move evolved melt with less MgO content toward segment ends could contribute to the gradual decrease in the upper crustal velocity, but itself cannot explain the up to 1.0 km/s difference in upper crustal velocity between segment center and ends (Kelemen & Holbrook, 1995; Korenaga et al., 2002).

### 5.4. Lower-Upper Crustal Thickness Ratio as Indicator for Crustal Accretion Pattern

Various parameters have been proposed to characterize the crustal accretion pattern at MORs. Numerical modeling of crustal accretion assuming vertical dyke intrusion suggests that the fault development at MOR is primarily controlled by the rate of dyke intrusion (M parameter (Behn & Ito, 2008; Buck et al., 2005). The extension is more magmatism-dominated when M > 0.5, forming normal abyssal hills on the seafloor (Behn & Ito, 2008; Buck et al., 2005), while detachment faulting occurs when M falls in 0.3 and 0.5 range (Tucholke et al., 2008). However, this modeling is carried out in 2-D space and only considers vertical dyke injection. Therefore, it cannot describe fully the crustal accretion of a segment with focused melt supply where the upper
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<figure><img src="image_22.png" /></figure>

<figure><img src="image_23.png" /><figcaption>Figure 14.</figcaption></figure>
crust is dominant formed by lateral dyking, such as the Lucky Strike segment. Thermal modeling in 2-D ignoring lateral dyking suggests that melt flux (product of spreading rate and crustal thickness) controls the variations in depth of axial melt lenses from fast-to ultraslow-spreading ridges (Chen et al., 2023). However, to explain the axial melt lens at ~3.0–3.4 km depth on the Lucky Strike segment, their model requires inefficient hydrothermal cooling and a melt flux much higher than that calculated using the crustal thickness at the center and the spreading rate of the Lucky Strike segment (Chen et al., 2023). The observation of vigorous hydrothermal venting on the summit of the Lucky Strike volcano (Escartin et al., 2015; Langmuir et al., 1997) excludes the inefficient hydrothermal cooling as a plausible interpretation. A possible explanation is that the melt flux is much higher than estimated from the crustal thickness, and a significant amount of this melt builds the crust away from the segment center. A modeling approach involving dyking in 3-D space is needed to explore this issue further.

The fraction of tectonically accommodated plate separation (T parameters) has been adopted to characterize the tectonic extension along MOR (Escartín et al., 1999; Howell et al., 2016). Here we estimated the T parameter over 20 km distance from the ridge axis along three profiles crossing different parts of the Lucky Strike segment (Figure 14a). The scarps of ridge-dipping faults within ~10 km distance from the ridge axis were taken from Bohidar et al. (2024) and of ridge-dipping faults between ~10 and 20 km distance were identified on 100 m resolution bathymetry data from Global Multi-Resolution Topography Synthesis (Ryan et al., 2009). The interpreted ridge-dipping faults show continuous high slopes (Figure 14b). We calculated the horizontal offset of a fault using the measured fault heave and a fault dip of 45° (Figures 14c–14e; Howell et al., 2016; Olive et al., 2024). The T parameter is obtained by calculating the ratio between the cumulative horizontal offset of faults and the measured distance away from ridge axis using a least-squares fitting approach. The results shows that the plate separation accommodated by tectonic extension is ~8.3% at the center of the Lucky Strike segment and gradually decreases to ~6.1%–6.5% at 10 km distance away from the central volcano (Figures 14f–14h). This variation does not show more faulting and increasing in tectonic extension toward the Lucky Strike segment ends. Our calculation demonstrates that the T parameter estimated from bathymetric profiles cannot correctly describe variations of tectonic extension within an individual ridge segment, because the influences of temporal and spatial variations of faults are not considered in the estimate of fault offsets using bathymetry data (Chen et al., 2025).

We propose to use the ratio between the LCT and UCT (LCT/UCT ratio) to quantify the melt focusing effect and crustal accretion mode along a ridge segment. The global synthesis shows that, on average, the young oceanic crust formed at slow-spreading ridges consists of a ~2.1 km upper crust and ~4.2 km lower crust (Christeson et al., 2019), that is, the LCT/UCT is 2.0. Along the Lucky Strike segment, the LCT/UCT is ~2.2 at the segment center and decreases to 0.1–0.2 at the segment ends (Figure 8d). An LCT/UCT larger than the global average value of 2.0 only occurs at the very central portion of the Lucky Strike segment where the axial melt lens is imaged. Similarly, the slow-spreading Reykjanes ridge at 57°45′N on the MAR shows a crustal thickness of ~7.5 km and an axial melt lens at ~2.5 km depth below the seafloor (Navin et al., 1998; Sinha et al., 1998), giving an LCT/UCT of ~2.0 (Figure 15).

We compiled the thicknesses of upper crust and whole crust for some ridge segments where axial melt lenses are imaged (Table 1 and Figure 15). In this compilation, we used the depth of axial melt lens below seafloor to represent the UCT. For a ridge segment not influenced by a hot spot, the UCT increases as the spreading rate of ridge decreases (Figure 15a) while the lower crust below the axial melt lens thickens as well (Figure 15b), leading to an LCT/UCT ratio close to 2.4 (Figure 15c), the global average of LCT/UCT ratio estimated for ultraslow-to fast-spreading ridges (Christeson et al., 2019). The LCT/UCT ratio shows no clear correlation with the spreading rate of a ridge, although it is slightly higher (up to 3.8) at some fast-spreading ridge segments, such as the East Pacific Rise at 17°15′S (Figure 15c). Based on these observations, we argue that for a crust with LCT/UCT ratio around 2.4, the upper crust is formed by a magma reservoir underneath within the mid-crust. At some hotspot-influenced ridge segments, such as the Axial Seamount (West et al., 2001) and the Galápagos Ridge segment

**Figure 14.** (a) Bathymetry map of the Lucky Strike segment and (b) seafloor slope. The black lines in panel (a) show profiles A-C along which topographic cross-sections are extracted. The magenta line marks the center of the ridge axis. The red curves represent scarps of ridge-ward dipping faults. (c-e) Topographic cross-sections along the profiles A-C in panel (a). The identified fault scarps are shown in red and cyan, respectively, on the western and eastern flanks. (f-h) Plot of the cumulative horizontal offset of faults versus the measured distance on the western (in red) and eastern (in cyan) flanks for profiles A-C, respectively. The fraction of fault-accommodated plate separation (T) is calculated using a least-squares approach to fit a linear function between the cumulative horizontal offset of faults and the measured distance.
<figure><img src="image_24.png" /><figcaption>**Figure 15.** (a) Upper crustal thickness (UCT) and (b) crustal thickness of ridge segments where axial melt lens (AML) has been observed. The UCT is defined as the depth of the top of AML below seafloor. Data and references are listed in Table 1. (c) Ratio between the lower and upper crustal thicknesses (lower crustal thickness (LCT)/UCT). The Axial Seamount on the Juan de Fuca ridge is influenced by the Cobb hotspot (West et al., 2001) while the Galápagos Ridge segment at 92°W (Gala-3) is influenced by the Galápagos hotspot (Canales et al., 2002). The horizontal gray dashed lines in panels (a–c) represent the global average of UCT (~1.8 km), crustal thickness (~6.2 km) and LCT/UCT (~2.4) (Christeson et al., 2019), respectively. The thin dashed vertical lines mark the boundaries of fast-, intermediate- and slow-spreading ridges (Perfit and Chadwick, 1998). EPR: East Pacific Rise; SEIR: Southeast Indian Ridge; Gala-2: Galápagos Ridge at 94°W. Axial and Endeavor: Axial and Endeavor segments on the Juan de Fuca Ridge; RR: Reykjanes Ridge; LS: Lucky Strike ridge.</figcaption></figure>
<table><caption>**Table 1**
Compilation of Spreading Rate, Upper Crustal Thickness, and Crustal Thickness Along Ridge Segments Where Axial Melt Lenses Are Imaged</caption><thead><tr><th>Ridge segment</th><th>Half-spreading rate (mm/year)</th><th>Crustal thickness (km)</th><th>Upper crustal thickness (AML depth below seafloor) (km)</th></tr></thead><tbody><tr><td>17°15'S East Pacific Rise (EPR)</td><td>77.5</td><td>5.2 (Bazin et al., 1998)</td><td>1.1–1.3 (Mutter et al., 1995)</td></tr><tr><td>9°45'N EPR</td><td>55</td><td>5.7 (Aghaei et al., 2014)</td><td>1.4–1.6 (Carbotte et al., 2013)</td></tr><tr><td>P2 segment on the Southeast Indian Ridge (SEIR-P2)</td><td>36</td><td>6.8 (Holmes et al., 2008)</td><td>2.0–2.2 (Baran et al., 2005)</td></tr><tr><td>Endeavor segment on Juan de Fuca Ridge (Endeavor)</td><td>28.5</td><td>7.0 (Arnoux et al., 2019)</td><td>2.1–3.3 (Ark et al., 2007)</td></tr><tr><td>Axial Seamount (Axial)</td><td>28</td><td>11 (West et al., 2001)</td><td>1.1–2.3 (Arnulf et al., 2014)</td></tr><tr><td>Galápagos Ridge at 92°W (Gala-3)</td><td>27</td><td>7.45 (Canales et al., 2002)</td><td>1.0–2.5 (Blacic et al., 2004)</td></tr><tr><td>Galápagos Ridge at 94°W (Gala-2)</td><td>26.5</td><td>5.9 (Canales et al., 2002)</td><td>2.5–4.5 (Blacic et al., 2004)</td></tr><tr><td>Reykjanes Ridge (RR)</td><td>11</td><td>7.5 (Sinha et al., 1998)</td><td>2.0–2.5 (Sinha et al., 1998)</td></tr></tbody></table>

at 92°W (Canales et al., 2002), the excess melt supply leads to extremely thick crust while the axial magma lens occurs at shallow depth (Figures 15a and 15b). For example, at the Axial Seamount, influenced by the Cobb hotspot, the crust is ~11 km thick (West et al., 2001) and the top of the axial melt lens lies at 1.1–2.3 km depth below seafloor, resulting a LCT/UCT ratio of 4.0–9.0. On the other hand, the LCT/UCT ratio of 0.1–0.2 at the ends of the Lucky Strike segment indicates the upper crust accounts for ~90% of the total thickness of the crust. This upper crust here is primarily formed by lateral dyking and the thin lower crust indicates that very little melt is delivered from below at the segment ends. Therefore, an LCT/UCT ratio approaching 0 represents crustal accretion by lateral dyking with melt sourced from the reservoir at segment center.

### 5.5. Temporal Variation in Magmatic Accretion Pattern

The across-axis velocity model allows us to study variations in magmatic accretion with time. Across the ridge axis, the upper crust shows small variations in its thickness between –30 and 30 km horizontal distance. The thickness of the upper crust is anti-correlated with the seafloor depth, suggesting that variations in the UCT are mainly due to the short-wavelength variations in seafloor depth related to faults. It has been difficult to define the crust-mantle boundary using the 7.1 km/s velocity contour (Christeson et al., 2019) for the across-axis model, because the lower crustal velocity increases as it moves away from the spreading center and cools. The 3-D tomographic model from Seher et al. (2010) shows that the lower crustal velocity can reach 7.3–7.4 km/s beyond ~10 km distance from the spreading center, consistent with our FWI result. Meanwhile, the 3-D tomographic model shows that the across-axis variation in crustal thickness is small (<1.3 km) over 15–20 km distance on both flanks (Seher et al., 2010). Collectively, these observations demonstrate that the current magmatic accretion mode with enhanced melt supply at the segment center could have been going for 3 Myr.

The crustal thickness of the OH-1 segment shows <500 m variations in the spreading direction over 25 km distance away from spreading center, suggesting a relatively continuous melt supply over the last 2.5 Myr (Dunn et al., 2005). The gravity and bathymetry data suggest that thick crust and more abundant magmatism could have lasted for 6 Myr on the OH-1 segment (Rabain et al., 2001). These observations suggest that the enhanced melt supply at segment center is not a transient feature on slow-spreading ridges but can persist for several million years.

## 6. Conclusions

By performing 2-D FWI to wide-angle seismic data recorded by OBSs, we have constrained the high-resolution velocity structures along the entire Lucky Strike ridge segment and to 30 km distance away from the spreading center. Based on the fine-scale velocity models from FWI, the following conclusions can be made:

1. Along the ridge axis, the crustal thickness reduces from ~8.4 km at the center to ~3.7–4.1 km at the distal ends, indicating very focused melt supply to the segment center. The mean crustal thickness for the entire segment is ~5.2 km.
2. The lower crust thins from 6.3 km at the segment center to 0.5–0.7 km at the segment ends while the upper crust shows small variations in thickness, demonstrating that the large variations in the crustal thickness along the ridge axis is mainly related to thinning of the lower crust.

3. The upper crust accounts for nearly 90% of the total thickness of the crust at the segment ends, suggesting the igneous crust at the segment ends is formed primarily by lateral dyking from the segment center to segment ends.

4. The velocity of the upper crust is lower at the segment ends than at the segment center, suggesting that more faulting at segment ends due to less frequent melt injection and the presence of more evolved melt toward segment ends.

5. Across the ridge axis, the small variations in the thicknesses of upper crust and crust suggest the current magmatic accretion mode could have persisted for 3 Myr.

## Conflict of Interest

The authors declare no conflicts of interest relevant to this study.

## Data Availability Statement

The wide-angle seismic data and the full waveform inversion code are archived at the Institut de Physique du Globe de Paris (IPGP) Research Collection (Wang et al., 2024).

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## Acknowledgments

We thank the captain, crew and scientific team of the SISMOMAR cruise for data collection. Z. Wang is funded by the Royal Society—Newton International Fellowship 2022 (NIFR1\221849). Full waveform inversion results presented in this paper were performed on the IRIDIS5 High Performance Computing Facility of the University of Southampton, and we thank Jeff Blundell for his help in software installation. We thank Mathilde Cannat, Jie Chen and Soumya Bohidar for useful discussions and help. We thank the two anonymous reviewers, the editor and associate editor for their constructive comments that helped to improve the manuscript. Institut de Physique du Globe de Paris contribution number 4295.
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