X-ray computed tomography, or XCT, has become a routine first step in core processing on board the Chikyu. The method is non-destructive, which makes it ideal for an early look at the three-dimensional structure of rocks and sediments before anyone commits to cutting, sampling, or splitting them. A medical-grade scanner, a GE Healthcare Discovery CT 750HG, is installed on the vessel. Core sections of roughly 1.5 meters are laid on a translating table and advanced through the scanner while an emitter-receiver pair rotates around them. The X-ray beam is attenuated as it passes through the sample through a combination of Compton scattering and the photoelectric effect, and the resulting attenuation coefficient is almost proportional to density. From hundreds of projections acquired at 360 degrees around the core axis, a computer reconstructs a full 3D volume that maps the density of the rock, slice by slice, from top to bottom.

The raw data, however, are unwieldy. Each core section produces DICOM files, the standard format for medical tomography, weighing several hundred megabytes apiece. Horizontal slices have a pixel size of roughly 175 micrometers, while consecutive slices are spaced 625 micrometers apart along the core axis. On board the ship, these volumes could only be explored with specialized software running on a handful of dedicated Macintosh computers located several meters from the core description tables. Scientists found themselves walking back and forth between the cores and the workstations, and checking whether a fracture or boundary was truly planar meant endlessly scrolling through parallel slices. The XCT images, in principle the most continuous and undisturbed record of the recovered material, had become a source of friction in a workflow that runs around the clock during an expedition.

Doan and colleagues propose a visual summary that strips away this friction. Their method, which they describe as unwrapping, converts the cylindrical 3D volume into a single flat 2D image, in much the same way that the Shroud of Turin is said to record a body wrapped around a cylinder. For every iso-Z slice perpendicular to the core axis, the XCT values are interpolated along a circular path centered on the core, traveling counter-clockwise to match the conventions used in borehole imaging. The circle radius is typically set to 64 pixels so that the path stays inside the core liner and samples only rock material. Recording the attenuation values along this circle for every depth produces an image in which the horizontal axis is angle around the core and the vertical axis is depth. Planar features such as fractures and lithological boundaries, which appear as complicated curves in individual slices, unfold into characteristic sinusoidal traces that trained eyes can measure directly.

The implementation was deliberately low-tech in spirit. The team wrote Python scripts embedded in Jupyter Notebook files that read the DICOM data and generate the summary figures. On a 2020 MacBook Pro laptop, producing both the unwrapped image and the longitudinal slices of a core section took less than three minutes. The outputs were then printed on paper and delivered to two key groups: the XCT watchdog scientist, who selects whole-round core intervals for priority sampling before the cores are split, and the structural geology and sedimentology teams who conduct visual core description. Because a single color range, spanning XCT values from 0 to 3000, was applied to all cores during the expedition, the printed images also allowed scientists to track how attenuation, and therefore density, changed with depth across the entire drilled sequence.

The test bed for the method was the first window of IODP Expedition 405, carried out in late 2024 as part of the JTRACK project tracking tsunamigenic slip across the Japan Trench. The unwrapped images quickly proved their worth across the scientific party. The structure team used them to identify and measure the orientation of planar features that were difficult or impossible to distinguish from the cut surface of the core. The sedimentology team relied on them as a continuous reference for tracing fine-scale lithofacies variations, defining interval boundaries, and choosing spots for smear-slide sampling. In one striking case, a thick clast of ash resting at the bottom of the archive half, entirely hidden from the surface, would have gone unnoticed without the XCT summary. The physical properties team found that subtle variations in XCT values flagged heterogeneities throughout the core, and that distinct mineral phases such as pyrite and calcite stood out as bright, strongly absorbing regions.

Beyond the immediate operational gains, the unwrapped images opened a door to more rigorous quantitative analysis. Because they are constructed along a cylinder, they resemble the electrical and acoustic borehole images produced by downhole logging tools, and they can be loaded directly into software such as TechLog that picks sinusoidal features automatically. This allowed the team to measure the dip and relative azimuth of planar structures along the borehole faster and more precisely than manual measurements on the split working halves. Crucially, the XCT scans were collected before the cores were split, preserving the geometry of structures with minimal disturbance and yielding more reliable orientation data. Comparing unwrapped core images with borehole images also helped reorient cores where bedding could be recognized and facilitated correlating structural features between core and log, even though each dataset has limitations: borehole images are oriented and quasi-continuous but lower in resolution, while cores are high-resolution but incomplete, since recovery is rarely a full 100 percent.

The authors are careful to note that the printed XCT summaries complement rather than replace direct observation of the cores. Fine features such as slickensides, the polished fault surfaces that record slip, are invisible on X-ray images, and different lithologies can share similar densities and therefore similar XCT values, making them hard to tell apart. Visual core description at the table remains a necessity. What the unwrapping method changes is the efficiency and continuity of that description: scientists no longer need to interrupt their work to consult a distant workstation, and they can annotate a paper summary with measurements as they go, keeping the digital 3D volumes available for later, more detailed analysis.

The expedition also exposed practical hurdles. Unwrapping was not originally part of the Expedition 405 workflow, and early access to the DICOM files was not planned. Generating the images required lengthy manual copying operations so that data could be processed on an external computer disconnected from the onboard laboratory network, and this maintenance burden was high enough that usage of the summaries tended to lapse during the second window of the expedition. The authors argue that installing the Python scripts directly on a dedicated computer on board would turn XCT unwrapping into an almost real-time service running between scanning and visual core description, automatically producing depth-referenced unwrapped images and combined summaries that could also incorporate data from the Multi-Sensor Core Logger to cross-validate measurements and guide sampling.

If that integration succeeds, the humble printed image may become a standard tool of scientific ocean drilling. The method’s code and notebooks have been released openly through a Zenodo archive, lowering the barrier for other drilling platforms and even land-based core repositories to adopt the approach. For a discipline in which decisions about irreplaceable samples must often be made within hours of the core arriving on deck, a technique that turns a half-gigabyte 3D scan into a sheet of paper in under three minutes is more than a convenience. It is a way of putting the invisible interior of the Earth, quite literally, into the hands of the scientists who need to read it first.

Subject of Research: Real-time unwrapping of 3D X-ray CT scans of scientific drilling cores for visual core description

Article Title: Real-time unwrapping of 3D X-ray CT scans for visual core description

Article References: Doan, M.-L., Brunet, M., Pizer, C., Okuda, H., Chang, Y.-C., Satolli, S., Nicholson, U., Yamamoto, Y., Conin, M., Fukuchi, R., Kirkpatrick, J., Toczko, S., & the IODP Expedition 405 Scientists (2026). Real-time unwrapping of 3D X-ray CT scans for visual core description. Scientific Drilling, 35(1), 55-60. https://doi.org/10.5194/sd-35-55-2026

Image Credits: AI Generated

DOI: 10.5194/sd-35-55-2026

Keywords: X-ray computed tomography, scientific ocean drilling, IODP Expedition 405, D/V Chikyu, visual core description, core scanning, image unwrapping, structural geology, sedimentology, borehole imaging, Scientific Drilling, Japan Trench

Arias intensity and cumulative absolute velocity, often abbreviated as Ia and CAV, are not the household names of earthquake science that peak ground acceleration has become, but among engineers they are prized quantities. Arias intensity, introduced by the Chilean engineer Arturo Arias in 1970, measures the cumulative energy per unit weight absorbed by a simple oscillator subjected to a ground motion record, effectively capturing the total energy content of shaking over its entire duration. Cumulative absolute velocity, developed in the United States in the late 1980s as a criterion for judging whether a nuclear facility had experienced an earthquake exceeding its operating basis, sums the absolute acceleration over time and has proven a robust indicator of structural damage potential. Both measures are central to assessing landslide triggering, liquefaction, and the performance of buildings and infrastructure during prolonged shaking.

Despite their importance, most prediction equations for these intensity measures were built from onshore data. Offshore ground motions, recorded on the seafloor rather than on land, follow different propagation and site amplification rules, and treating them as interchangeable with onshore shaking can lead to serious misestimates of hazard for submarine cables, ports, coastal cities, and offshore infrastructure. The new study, led by Jingyang Tan and Xialei Zhu of China Three Gorges University together with Jinjun Hu and Yinan Zhao of the Institute of Engineering Mechanics, China Earthquake Administration, set out to close that gap for the Japan Trench region using data from the Seafloor Observation Network for Earthquakes and Tsunamis along the Japan Trench, known as S-net.

S-net, operated by the National Research Institute for Earth Science and Disaster Resilience, is the world’s largest cabled ocean-bottom monitoring network, spanning the trench that produced the devastating magnitude 9.0 Tohoku earthquake of 2011. The researchers assembled an exceptionally large dataset for offshore ground motion modeling: 28,950 three-component records from 150 ocean-bottom stations. These records captured 553 earthquakes across three tectonic families, including 130 subduction interface events, where the Pacific plate grinds beneath the Okhotsk plate; 243 slab earthquakes, occurring within the descending plate at depth; and 180 shallow crustal and upper mantle earthquakes. This breadth allowed the team to develop models covering the full range of earthquake mechanisms that threaten the region.

A central innovation of the study lies in how it characterizes the ground beneath each station. Rather than relying on geological maps, the team classified sites using the horizontal-to-vertical spectral ratio technique, or HVSR, which compares the amplitude of horizontal and vertical shaking at a site to reveal its resonant frequency, a fingerprint of soil stiffness and sediment thickness. This site classification scheme, applied uniformly across the ocean-bottom network, allowed the researchers to incorporate site effects directly into their prediction equations. The models account for the key explanatory variables that govern shaking: moment magnitude, rupture distance, focal depth, site class, and, uniquely for offshore settings, the installation condition of the seafloor instruments.

That last variable turned out to matter far more than anyone might have guessed. S-net stations come in different flavors: some instruments are buried in the sediment, while others sit unburied on the seafloor inside pressure vessels. The analysis revealed that the installation method significantly influences recorded Arias intensity and cumulative absolute velocity, with unburied stations exhibiting notably higher values. The likely culprit is the natural vibration of the instrument housing and its coupling with the soft seafloor, which can introduce amplification that is not representative of the true ground motion. For engineers using offshore records, this finding is a caution: ignoring installation conditions could inflate or deflate energy estimates and skew hazard calculations.

The site classification itself proved to be the study’s most valuable uncertainty-reducing tool. When site classes were explicitly included in the models, the model uncertainty, expressed statistically as the standard deviation of the residuals, dropped substantially compared with models that omitted site effects. By contrast, two other candidate explanatory variables, water depth and sedimentary thickness, had only negligible effects on model uncertainty. This is a practically important result, because it suggests that a relatively simple HVSR-based site classification captures most of the site-related variability in offshore energy measures, sparing modelers the difficulty of obtaining detailed sediment profiles from the deep ocean floor.

Comparing their offshore models with existing onshore equations revealed a systematic and physically meaningful difference. Offshore Arias intensity and cumulative absolute velocity exhibit a substantially greater energy accumulation effect than onshore ground motions at comparable distances and magnitudes. The researchers attribute this to amplification by soft seafloor sediments, the water-saturated, low-velocity materials that blanket much of the Japan Trench margin. Soft sediments lengthen the duration of shaking and concentrate seismic energy at low frequencies, inflating cumulative measures even when instantaneous peaks remain moderate. The finding echoes earlier comparisons of peak ground acceleration and response spectra between land and ocean-bottom stations in northeast Japan, but extends the picture to energy-based measures that are more directly tied to damage in flexible structures and to soil failure phenomena such as liquefaction.

Beyond the prediction equations themselves, the team developed spatial correlation models for offshore Arias intensity and cumulative absolute velocity. These geostatistical tools quantify how similar the shaking is at two sites separated by a given distance during the same earthquake, a quantity known as spatial correlation. In seismic risk analysis, spatial correlation governs whether damage concentrates in one neighborhood or spreads across an entire region, which is critical for estimating losses to distributed systems like power grids, pipelines, and transportation networks. By characterizing the spatial dependence of offshore energy measures for the first time in this region, the models enable more realistic simulations of earthquake scenarios that span both land and sea.

The practical reach of the new models extends across the earthquake engineering pipeline. Arias intensity feeds into empirical methods for predicting earthquake-induced landslide displacements through Newmark’s sliding block analysis, while cumulative absolute velocity underpins thresholds for structural damage and liquefaction assessment, including criteria originally developed for nuclear facilities and more recent applications to lateral spreading evaluation. With reliable offshore predictions of both measures, engineers can now assess hazards to submarine infrastructure, evaluate the seismic performance of coastal facilities, and refine probabilistic seismic hazard analyses for the densely populated Pacific coast of northern Japan. The researchers note that the models are applicable to the Japan Trench region and can serve as a reference for seismic hazard assessment in offshore areas more broadly, offering a template for other subduction zones, from Cascadia to Nankai, where ocean-bottom networks are expanding and the seafloor is no longer a blind spot in earthquake science.

Subject of Research: Development of offshore ground motion prediction models for Arias intensity and cumulative absolute velocity in the Japan Trench region using HVSR-based site classification

Article Title: A new ground motion prediction model for Arias intensity and cumulative absolute velocity in the Japan Trench region based on HVSR site classification

Article References: A new ground motion prediction model for Arias intensity and cumulative absolute velocity in the Japan Trench region based on HVSR site classification. (n.d.). https://doi.org/10.1007/s10518-026-02683-7

Image Credits: AI Generated

DOI: 10.1007/s10518-026-02683-7

Keywords: Arias intensity, cumulative absolute velocity, ground motion prediction, Japan Trench, S-net, ocean-bottom seismology, HVSR site classification, seismic hazard assessment, subduction earthquakes, site amplification, spatial correlation, offshore ground motion