Publisher：Journal of Volcanology and Geothermal Research  

Hydrothermal fluids are well known to circulate through fracture zones (e.g., faults) in geothermal areas. Impermeable clay layers can play a role of caprock, retaining geothermal reservoirs underneath. Hydrothermal alteration layers are known to include clay minerals and to have lower hydraulic permeability and higher electrical conductivity than the surrounding rocks. The magnetotelluric (MT) method of geophysical exploration can estimate the resistivity structure below the surface. Therefore, MT method can reveal relations among hydrothermal fluid circulation, impermeable clay layers, and faults. Nevertheless, because of sparseness of observation sites and the resulting low spatial resolution, earlier studies using the MT method have rarely revealed such detailed relations. For this study, high-density audio-frequency MT (AMT) soundings were conducted at 83 sites in the Unzen hot spring area, Japan, with site spacing of approximately 50–150 m to estimate details of the three-dimensional (3-D) resistivity structure near the surface (shallower than 1 km). Consequently, the distribution of conductive bodies was clearly identified in the shallow subsurface. Some conductive bodies are exposed on the surface, where hot springs and fumaroles are distributed. The conductive bodies are regarded as representing hydrothermal alteration layers. However, no shallow conductive body was found on the north side of an active fault (Oshidori-no-ike fault; OF). This feature suggests sharp variation of subsurface temperatures at OF, possibly because of recharging of meteoric water along OF. We conclude that high-density 3-D AMT surveys can reveal shallow subsurface geothermal systems.

DOI： 10.1016/j.jvolgeores.2025.108466

Web of Science

Scopus

Publishing type：Research paper (scientific journal)  

DOI： 10.1029/2025JH000683

Authorship：Lead author,　Corresponding author   Publishing type：Research paper (scientific journal)   Publisher：Society of Exploration Geophysicists  

Blurred resistivity boundaries resulting from smoothness-regularized inversions of electrical resistivity tomography (ERT) data can lead to inaccurate interpretations of sharp boundary structures. To address this issue, various ERT inversion algorithms have introduced localized adjustments (localized discontinuities) in the regularization operator at positions where sharp boundaries are anticipated. Current approaches rely on prior information about sharp boundary locations, obtained from complementary geophysical, geological, and drilling data, to determine the positions and weights for these regularization adjustments. However, such prior information is frequently insufficient, limiting the application of localized regularization adjustments. Accordingly, we developed a sharp boundary inversion (SBI) algorithm using the Akaike Bayesian Information Criterion (ABIC) that determines the optimal positions and weights for localized regularization adjustments by testing various configurations and selecting the one that minimizes ABIC. A synthetic modeling study demonstrated that the SBI algorithm correctly delineated the sharp boundaries of a conductor. Its application to field data demonstrated that it delineated the sharp boundaries of a utility tunnel, and the size and horizontal position of the recovered tunnel were consistent with the estimated dimensions from the blueprint. As it does not rely heavily on prior information, the SBI algorithm can be applied to a wide range of geophysical survey data, even when prior knowledge of sharp boundary locations is limited.

DOI： 10.1190/geo2024-0385.1

Web of Science

Scopus

Language：English   Publisher：Conductivity Anomaly Research Group  

<p>Phreatic eruptions are primarily driven by vapor layers, making the detection of changes in these layers essential for volcanic disaster prevention. Inferno Crater Lake in New Zealand, characterized by its periodic 38-day fluctuations in water level and temperature, is hypothesized to experience vapor layer variations that contribute to these phenomena. To investigate this, a six-month observation campaign was conducted in 2023 using the EM ACROSS method, a geophysical technique sensitive to high-resistivity layers. This method involved continuous transmission of artificial electromagnetic signals, allowing precise monitoring of subsurface resistivity structures. By focusing on frequencies near the transmission frequency, errors in electric field and current measurements were evaluated, enabling observations with a time resolution of one hour. Variations in the amplitude and phase of the apparent resistivity tensor were found to correlate strongly with fluctuations in the lake's water level. However, significant phase variations were not observed below 46.95 Hz, and the phase tensor was undetectable in this frequency range. Resistivity fluctuations at these lower frequencies were attributed to changes at depths of approximately 300 m, suggesting that the sensitivity of the method decreases with depth. To further interpret the observed resistivity changes, a 3-D finite element method was employed to model the subsurface resistivity structure. The results indicate that a vapor layer expanding to a thickness of 180–240 m and rising to 60 m below the surface during high water levels provided the best explanation for the observed phase tensor variations. This finding aligns with previous resistivity surveys that identified a resistivity-altered zone near the lake, although the EM-ACROSS method demonstrated greater sensitivity to deeper regions. These results highlight the potential of the EM-ACROSS method as a highly sensitive tool for monitoring vapor layer dynamics, which are critical to understanding and forecasting phreatic eruption processes. The method’s ability i to provide high-resolution temporal and spatial data makes it particularly valuable for observing phreatomagmatic systems, offering new insights into subsurface resistivity changes and their relationship with surface-level phenomena. Future applications of this method could significantly enhance volcanic monitoring efforts and improve predictive capabilities for eruption-related hazards.</p>

DOI： 10.60410/pcaw.2025.0_52

CiNii Research

Authorship：Lead author,　Corresponding author   Publishing type：Research paper (scientific journal)   Publisher：Oxford University Press (OUP)  

SUMMARY

Although controlled-source electromagnetic (CSEM) methods have higher sensitivity to thin resistive bodies than the magnetotelluric (MT) method, their delineation by the inversion requires CSEM data with high signal-to-noise ratio (SNR). This study aims to enhance the SNR of CSEM data by increasing the number of stacks. To efficiently stack long-term data, we use an EM-accurately controlled, routinely operated signal system (ACROSS), which can transmit accurately controlled waveforms by synchronizing the transmitting waveforms with a 10 MHz Global Positioning System signal. We conducted a CSEM survey using the EM-ACROSS in the Kusatsu-Shirane Volcano to demonstrate that the SNR can be improved by extensive observation data and the CSEM inversion can delineate hydrothermal systems, including resistive bodies of vapour-rich reservoirs. Our EM-ACROSS simultaneously transmitted waveforms from two dipoles during a 192-h of the survey; five-component receivers located 4–6 km away from the transmitter captured EM-ACROSS signals ranging between 146 and 192 h. By stacking extensive observation data using a weighted method, the CSEM responses show minimal error levels, with standard errors &amp;lt;2 per cent for most frequencies. The SNR roughly followed the square root of the stacking times. 3-D inversion of the collected CSEM data delineated a relatively resistive body, interpreted as a vapour-dominated reservoir below a cap-rock layer, while the MT inversion failed to recover the same. This highlights the ability of an EM-ACROSS-based CSEM survey to delineate hydrothermal systems including vapour-dominated reservoirs, and provides a compelling rationale for establishing CSEM as a standard methodology in hydrothermal imaging. Furthermore, this study suggests that the enhanced imaging capabilities of CSEM data can be further improved when integrated with MT data.

DOI： 10.1093/gji/ggae431

Web of Science

Scopus

Other Link： https://academic.oup.com/gji/article-pdf/240/2/1107/60941170/ggae431.pdf

Event date： 2023.11

Language：English   Presentation type：Oral presentation (general)  

Event date： 2022.11

Presentation type：Poster presentation  

Presentation type：Oral presentation (invited, special)  

Language：Japanese   Presentation type：Oral presentation (general)