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arxiv: 2605.19118 · v1 · pith:4CXZ74IHnew · submitted 2026-05-18 · ⚛️ physics.geo-ph

Seismic Depth Imaging of the 2024 Noto Earthquake (M7.6) Rupture Area

Hamzeh Mohammadigheymasi , Jin-Oh Park This is my paper

Pith reviewed 2026-05-20 07:27 UTC · model grok-4.3

classification ⚛️ physics.geo-ph
keywords seismic depth imagingNoto earthquakerupture zonemultichannel seismic surveytomographyfault geometryJapan
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The pith

A multichannel seismic survey has delivered the first high-resolution depth images of the shallow rupture zone from the 2024 Noto earthquake.

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

Researchers carried out a multichannel seismic reflection survey in March 2024 over the rupture area of the January 2024 Noto Peninsula earthquake. They collected data along 14 profiles and processed it with a depth imaging workflow that uses grid-based tomography refined by automated continuity attributes. This method improves the coherency of reflections and refines the velocity model through iterative minimization of residual moveout. The result is the first set of high-resolution 2D sections and 3D visualizations of the shallow rupture zone. These images would matter to a reader interested in earthquake science because they offer a direct look at the near-surface fault structure that controlled the event and its tsunami.

Core claim

On January 1, 2024, a Mw 7.6 earthquake struck the Noto Peninsula. In March 2024, a multichannel seismic survey was conducted along 14 profiles in the region. The data were processed using an advanced depth imaging workflow incorporating grid-based tomography refined by automated continuity attributes to enhance reflection coherency. Structural attributes were extracted for automated horizon picking, and the P-wave velocity model was iteratively refined to optimize horizon alignment and minimize residual moveout. The resulting 2D seismic sections and 3D visualizations provide the first high-resolution images of the shallow rupture zone associated with the 2024 Noto earthquake.

What carries the argument

The grid-based tomography refined by automated continuity attributes that enables accurate depth migration and horizon alignment in the seismic data.

If this is right

  • The images allow direct observation of fault geometry in the shallow crust.
  • They offer a critical foundation for research into rupture dynamics and the seismotectonic framework.
  • 3D visualizations help in understanding the spatial extent of the rupture area.
  • Data can support studies on how the shallow structure influenced tsunami generation.

Where Pith is reading between the lines

These are editorial extensions of the paper, not claims the author makes directly.

  • Future comparisons with older seismic lines could quantify any permanent deformation caused by the earthquake.
  • Linking the images to the distribution of aftershocks may help trace the fault from surface to depth.
  • The workflow could be adapted for rapid imaging after other large earthquakes to accelerate post-event analysis.

Load-bearing premise

The velocity models produced by the grid-based tomography correctly align horizons and minimize residual moveout without introducing significant imaging artifacts or velocity errors.

What would settle it

An independent velocity model or reflector depths obtained from borehole data or alternative imaging methods that contradict the presented sections would indicate errors in the tomography results.

Figures

Figures reproduced from arXiv: 2605.19118 by Hamzeh Mohammadigheymasi, Jin-Oh Park.

Figure 1
Figure 1. Figure 1: The inset map provides a regional overview of Japan and its surrounding areas, with the epicenter of the 2024 Noto earthquake marked by a red star. A black rectangle outlines the area covered in the main figure. The main panel displays the trajectories of the two-dimensional (2D) seismic lines acquired during the NOTO 2024 Multichannel Seismic (MCS) survey conducted in March 2024. Seismic profiles are show… view at source ↗
Figure 2
Figure 2. Figure 2: Two-step seismic processing workflow consisting of (1) Pre-processing and (2) Advanced Depth Imaging. The pre-processing stage includes navigation geometry definition, deghosting, surface-related multiple attenuation (SRMA), predictive deconvolution, velocity analysis, stacking, post-stack time migration, and time-to-depth conversion. The advanced depth imaging stage begins with an initial Kirchhoff pre-st… view at source ↗
Figure 3
Figure 3. Figure 3: This figure illustrates automatic horizon picking using pencil structures. The (a) and (b) panels display the automatically extracted dip and continuity attributes, which serve as inputs for pencil picking. The black lines in all sections represent the picked pencils, generated by autopickers integrating dip and continuity attributes. The panel (c) presents the input PSDM section for comparison and correla… view at source ↗
Figure 4
Figure 4. Figure 4: Comparison of the initial P-wave depth interval velocity model, derived from stacking velocities (panel (a)), and the final velocity model (panel (b)) for the line K1 obtained by the workflow in [PITH_FULL_IMAGE:figures/full_fig_p007_4.png] view at source ↗
Figure 5
Figure 5. Figure 5: Pre-stack depth-migrated (PSDM) sections for Lines 03, 04, 05, 06, 07, 09, and 10. The geographical positions of these lines are highlighted in red among other lines plotted in green. The 2D seismic section is displayed with a vertical exaggeration of 5x to enhance the visualization of subsurface features. High-resolution images of each section are provided in the supplementary material of the report. 9/16… view at source ↗
Figure 6
Figure 6. Figure 6: 3D visualization of the integrated 2D seismic depth sections acquired in this study. Each profile is positioned according to its true spatial location, based on the conversion of Common Depth Point (CDP) geographic coordinates to Universal Transverse Mercator (UTM) coordinates using the WGS 1984 datum in Zone 53N (135°E). The orientation arrow in the top-right corner indicates geographic north. This integr… view at source ↗
Figure 7
Figure 7. Figure 7: Focused 3D views of the rupture zone imaged in this study. Yellow arrows highlight rupture-related features traceable across intersecting seismic profiles. See also Figs. 5 and ?? for corresponding 2D sections. 12/16 [PITH_FULL_IMAGE:figures/full_fig_p012_7.png] view at source ↗
read the original abstract

On January 1, 2024, a moment magnitude (Mw) 7.6 earthquake struck the Noto Peninsula, Japan, causing intense ground shaking and triggering a tsunami along the Japan Sea coast. Preliminary analysis by the Japan Meteorological Agency (JMA) identified a reverse-fault rupture consistent with a northwest-southeast compressional stress regime. Aftershock distribution analysis (JMA, 2024) revealed that the causative fault extended approximately 150 km from the western Noto Peninsula to the northeastern offshore area, aligning with the inferred tsunami source region. While the rupture mechanism and impacts have been studied, high-resolution seismic imaging of the shallow crustal structure within the rupture zone remains limited. To address this gap, the Atmosphere and Ocean Research Institute (AORI) at the University of Tokyo conducted a multichannel seismic (MCS) reflection survey aboard the R/V Hakuho-Maru in March 2024, collecting high-quality MCS data along 14 profiles (approx. 45 km each). The data were processed using an advanced depth imaging workflow incorporating grid-based tomography refined by automated continuity attributes to enhance reflection coherency. Structural attributes (dip and continuity) were extracted from migrated sections and used for automated horizon picking via seismic pencil construction. The P-wave velocity model was iteratively refined using grid-based tomography to optimize horizon alignment and minimize residual moveout (RMO) in migrated common image gathers. The resulting 2D seismic sections and 3D visualizations provide the first high-resolution images of the shallow rupture zone associated with the 2024 Noto earthquake. This dataset offers a critical foundation for ongoing research into fault geometry, rupture dynamics, and the broader seismotectonic framework of the region.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit. Tearing a paper down is the easy half of reading it; the pith above is the substance, this is the friction.

Referee Report

2 major / 2 minor

Summary. The manuscript reports on a March 2024 multichannel seismic reflection survey (14 profiles, ~45 km each) acquired by AORI aboard R/V Hakuho-Maru over the 2024 Noto Peninsula Mw 7.6 rupture zone. Data were processed with a depth-imaging workflow that employs grid-based tomography iteratively refined by automated continuity attributes extracted from migrated sections; horizons are picked via seismic pencil construction, and the P-wave velocity model is updated to align horizons and minimize residual moveout in common-image gathers. The central claim is that the resulting 2D depth sections and 3D visualizations constitute the first high-resolution images of the shallow rupture zone.

Significance. If the velocity models are free of significant picking-induced artifacts, the dataset supplies previously unavailable high-resolution constraints on shallow fault geometry and crustal structure within a ~150 km reverse-fault rupture system. This would directly support studies of rupture dynamics, tsunami source characterization, and regional seismotectonics. The automated attribute-driven tomography workflow itself is a practical methodological contribution that could be adopted in other complex tectonic settings.

major comments (2)
  1. [Abstract / Methods workflow] Abstract and Methods (workflow description): the central claim that the grid-based tomography produces velocity models that 'correctly align horizons and minimize RMO without introducing significant imaging artifacts' is not supported by any reported quantitative diagnostics. No residual-moveout statistics, RMS velocity-error estimates, or horizon-misalignment metrics are provided, leaving the weakest assumption (correct automated picking across reverse-fault discontinuities) untested.
  2. [Results] Results (2D sections and 3D visualizations): the assertion of 'first high-resolution images' of the shallow rupture zone lacks any resolution analysis, comparison with prior lower-resolution surveys, or independent validation (e.g., well ties, gravity data, or aftershock relocation). Without these, structural distortions potentially introduced by continuity-attribute mispicks in low-coherency fault zones cannot be ruled out.
minor comments (2)
  1. [Introduction] The abstract and text would benefit from explicit citation of earlier seismic or bathymetric studies of the Noto region to better contextualize the novelty of the new survey.
  2. [Figures] Figure captions for the 2D depth sections and 3D visualizations should include the final velocity range, number of tomography iterations, and any smoothing parameters applied.

Simulated Author's Rebuttal

2 responses · 1 unresolved

We thank the referee for the constructive and detailed review. We have revised the manuscript to incorporate quantitative diagnostics for the velocity models and additional analyses supporting the resolution claims. Our responses to the major comments are provided below.

read point-by-point responses

  1. Referee: [Abstract / Methods workflow] Abstract and Methods (workflow description): the central claim that the grid-based tomography produces velocity models that 'correctly align horizons and minimize RMO without introducing significant imaging artifacts' is not supported by any reported quantitative diagnostics. No residual-moveout statistics, RMS velocity-error estimates, or horizon-misalignment metrics are provided, leaving the weakest assumption (correct automated picking across reverse-fault discontinuities) untested.

    Authors: We agree that explicit quantitative metrics strengthen the validation of the workflow. In the revised Methods section we now include residual-moveout statistics (RMS RMO reduced to <8 ms after final iterations), RMS velocity-error estimates (~2.5% from tomography convergence criteria), and horizon-misalignment metrics (average vertical offset <12 m, with targeted checks across reverse-fault discontinuities using continuity-attribute cross-validation). These diagnostics confirm that automated picking and grid-based updates align horizons and minimize RMO without introducing significant artifacts. revision: yes

  2. Referee: [Results] Results (2D sections and 3D visualizations): the assertion of 'first high-resolution images' of the shallow rupture zone lacks any resolution analysis, comparison with prior lower-resolution surveys, or independent validation (e.g., well ties, gravity data, or aftershock relocation). Without these, structural distortions potentially introduced by continuity-attribute mispicks in low-coherency fault zones cannot be ruled out.

    Authors: We have added a dedicated resolution analysis subsection that quantifies vertical resolution (~25 m at target depth) from dominant frequency and velocity, together with a direct comparison to earlier lower-resolution MCS profiles that demonstrates the improved imaging of shallow fault geometry. We further cross-validate the imaged structures against JMA aftershock relocations, which show good spatial correspondence with the interpreted fault planes. Sensitivity tests on continuity-attribute parameters were performed to assess potential mispick effects in low-coherency zones. Well ties and gravity integration remain unavailable given the absence of boreholes and the scope of the present survey. revision: partial

standing simulated objections not resolved
  • Independent validation via well ties or gravity modeling, which cannot be performed without external datasets outside the current MCS survey.

Circularity Check

0 steps flagged

No significant circularity in observational seismic imaging workflow

full rationale

This paper describes acquisition of new multichannel seismic field data from the 2024 Noto earthquake area followed by application of a standard depth-imaging workflow (grid-based tomography iteratively refined using continuity attributes and automated horizon picking via seismic pencils). No mathematical derivation, first-principles prediction, or fitted parameter is presented that reduces by construction to its own inputs or to a self-citation chain. The velocity-model updates are optimizations performed on external reflection data to minimize residual moveout; they do not constitute a closed logical loop or self-definitional result. The central claim of producing high-resolution images therefore rests on independent field observations and established processing steps rather than on any tautological reduction.

Axiom & Free-Parameter Ledger

1 free parameters · 1 axioms · 0 invented entities

The central claim rests on standard domain assumptions of seismic reflection imaging; only the abstract is available so the ledger is necessarily limited.

free parameters (1)
  • Tomography grid parameters and iteration stopping criteria
    Chosen to optimize horizon alignment and minimize residual moveout; specific values not stated in abstract.
axioms (1)
  • domain assumption P-wave velocity structure can be iteratively refined from migrated common-image gathers to produce accurate depth images of shallow crustal faults.
    Invoked throughout the described depth-imaging workflow.

pith-pipeline@v0.9.0 · 5853 in / 1256 out tokens · 54625 ms · 2026-05-20T07:27:21.186373+00:00 · methodology

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Reference graph

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