論文 / 著書情報
Article / Book Information
Title

Estimation of spatial distribution and fluid fraction of a potential
supercritical geothermal reservoir by magnetotelluric data: a case study
from Yuzawa geothermal field, NE Japan

Author

Keiichi Ishizu, Yasuo Ogawa, Keishi Nunohara, Noriyoshi Tsuchiya,
Masahiro Ichiki, Hideaki Hase, Wataru Kanda, Shinya Sakanaka,
Yoshimori Honkura, Yuta Hino, Kaori Seki, Kuo Hsuan Tseng, Yusuke
Yamaya, Toru Mogi

Journal/Book name

Journal of Geophysical Research: Solid Earth, Volume 127, Issue 2

Issue date2022, 2

DOI

https://doi.org/10.1029/2021JB022911

Creative Commons

Information is in the article.

Powered by T2R2 (Science Tokyo Research Repository)RESEARCH ARTICLE
10.1029/2021JB022911
Key Points:• A supercritical geothermal reservoirof 3 km (width) × 5 km (length) isimaged using the magnetotelluric
method at a depth of 2.5–6.0 km• The fluid fraction of the supercriticalreservoir is estimated to be 0.1%–4.2%
with salinity of 5–10 wt%• Upwelling supercritical fluids
supplied from the melt are trapped
under a less-permeable silica sealing
Supporting Information:

Supporting Information may be found in
the online version of this article.
Correspondence to:K. Ishizu,
ishizu.k.ab@m.titech.ac.jp;
ishizu.keiichi.n30@kyoto-u.jp

Citation:

Ishizu, K., Ogawa, Y., Nunohara, K.,
Tsuchiya, N., Ichiki, M., Hase, H., et al.
(2022). Estimation of spatial distribution
and fluid fraction of a potential
supercritical geothermal reservoir bymagnetotelluric data: A case study from
Yuzawa geothermal field, NE Japan.
Journal of Geophysical Research: Solid
Earth, 127, e2021JB022911. https://doi.
org/10.1029/2021JB022911
Received 10 AUG 2021
Accepted 4 FEB 2022

© 2022. The Authors.
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.

ISHIZU ET AL.

Estimation of Spatial Distribution and Fluid Fractionof a Potential Supercritical Geothermal Reservoir by
Magnetotelluric Data: A Case Study From Yuzawa
Geothermal Field, NE Japan
Keiichi Ishizu1 , Yasuo Ogawa1 , Keishi Nunohara2, Noriyoshi Tsuchiya2, Masahiro Ichiki3,
Hideaki Hase1,4, Wataru Kanda1 , Shinya Sakanaka5, Yoshimori Honkura1, Yuta Hino1,
Kaori Seki1,6, Kuo Hsuan Tseng1,7 , Yusuke Yamaya8 , and Toru Mogi1
Volcanic Fluid Research Center, Tokyo Institute of Technology, Tokyo, Japan, 2Graduate School of Environmental Studies,
Tohoku University, Miyagi, Japan, 3Graduate School of Science, Tohoku University, Miyagi, Japan, 4Now at Geothermal
Energy Research & Development Co., Ltd., Tokyo, Japan, 5Graduate School of International Resource Sciences, Akita
University, Akita, Japan, 6Now at Groundwater and Hydrology Group, Kokusai Kogyo Co., Ltd., Tokyo, Japan, 7Now at
Sumiko Resources Exploration & Development Co., Ltd., Tokyo, Japan, 8Fukushima Renewable Energy Institute, National
Institute of Advanced Industrial Science and Technology, Fukushima, Japan
1

Abstract Fluids within the Earth's crust may exist under supercritical conditions (i.e., >374°C and>22.1 MPa for pure water). Supercritical geothermal reservoirs at depths of 2–10 km below the surface innortheastern (NE) Japan mainly consist of magmatic fluids that exsolved from the melt during the courseof fractional crystallization. Supercritical geothermal reservoirs have received attention as next-generation
geothermal resources because they can offer significantly more energy than that obtained from conventional
geothermal reservoirs found at temperatures <350°C. However, the spatial distribution and fluid fraction ofsupercritical geothermal reservoirs, which are required for their resource assessment, are poorly understood.
Here, the magnetotelluric (MT) method with electrical resistivity imaging is used in the Yuzawa geothermal
field, NE Japan, to collect data on the fluid fraction and spatial distribution of a supercritical geothermal
reservoir. The collected MT data reveal a potential supercritical geothermal reservoir (>400°C) withdimensions of 3 km (width) × 5 km (length) at a depth of 2.5–6.0 km below the surface. The estimated fluid
fraction of the reservoir is 0.1%–4.2% with salinity values of 5–10 wt%. The melt is also imaged below thereservoir, and based on the resistivity model; we develop a mechanism for the evolution of the supercritical
geothermal reservoir, wherein upwelling supercritical fluids supplied from the melt are trapped under lesspermeable silica sealing and accumulate there.
Plain Language Summary As the demand for sustainable energy solutions has increased
worldwide, geothermal energy has emerged as a clean and renewable energy source that comes fromreservoirs of hot water beneath the Earth's surface. Subsurface fluids in a supercritical state (high temperatureand pressure) have received attention as the next-generation geothermal resources because they can offer
significantly more energy than that obtained from conventional geothermal fluids found at temperatures<350°C. Supercritical geothermal fluids are located in various volcanic areas in the world. However,understanding of the spatial distribution and fluid fraction of supercritical fluids, which is necessary for theirresource assessment, is limited. Therefore, we use the magnetotelluric (MT) method to obtain information on
the spatial distribution and fluid fraction of a supercritical geothermal reservoir in the Yuzawa geothermal fieldin northeastern Japan. The MT method is sensitive to the subsurface electrical resistivity distribution, which
in turn can be used as a proxy for the presence of supercritical fluids. The collected MT data reveal a potential
supercritical geothermal reservoir of 3 km (width) × 5 km (length) at a depth of 2.5–6 km below the surface
with a fluid fraction of 0.1%–4.2% and salinity of 5–10 wt%.
1. Introduction
Magmatic fluids exsolved from melt in the crust during the course of fractional crystallization may exist in a supercritical state (i.e., >374°C and >22.1 MPa for pure water, and >406°C and >29.8 MPa for seawater salinity)
at a depth of about 2–10 km beneath volcanic areas (Bali et al., 2020; Fournier, 1999; Friðleifsson et al., 2020;

1 of 21

Journal of Geophysical Research: Solid Earth

10.1029/2021JB022911

Ikeuchi et al., 1998; Reinsch et al., 2017; Scott et al., 2015; Tsuchiya et al., 2016). Supercritical geothermal
reservoirs at a depth of 2–10 km in northeastern (NE) Japan, which is the subject of this study, are considered toconsist mainly of magmatic fluids (Tsuchiya et al., 2016). In fact, several deep drilling expeditions have foundmagmatic fluid in a supercritical state. An exploration well (WD-1a) in the Kakkonda geothermal area in NE
Japan found magmatic fluid at 500°C at a depth of 3,729 m (Doi et al., 1998; Ikeuchi et al., 1998), and the fluid
was in a supercritical state (Saishu et al., 2014; Tsuchiya & Hirano, 2007). Similarly, an exploratory well drilledby the Iceland Deep Drilling Project (IDDP) also encountered a supercritical fluid (450°C) in the Krafla volcanic
system, Iceland (Elders et al., 2014; Scott et al., 2015).
Supercritical geothermal reservoirs have recently gained attention as next-generation geothermal resources(Friðleifsson et al., 2020; Okamoto et al., 2019; Parisio et al., 2019; Reinsch et al., 2017; Stimac et al., 2017;
N. Watanabe et al., 2017). Various countries, including Japan, the USA, New Zealand, and Italy, are beginningto consider the development of power plants using supercritical fluids (Reinsch et al., 2017). This newfoundattention comes from the fact that supercritical fluids have significant advantages as a source of energy: a higher
enthalpy per unit mass and a lower fluid viscosity than conventional geothermal fluids with temperatures <350°C(Reinsch et al., 2017). Power generation systems using supercritical fluids are therefore able to achieve a large
output from a single power plant. A test of the capacity of supercritical fluids (wellhead temperature of 450°C)
from IDDP-1 in Krafla (Iceland) revealed that the energy output was 10-fold higher than that of conventional
wells (Elders et al., 2014).
Gaining an in-depth understanding of the spatial distribution and fluid fraction of supercritical geothermal reservoirs is necessary for their assessment as a next-generation energy resource (Reinsch et al., 2017; Stimac
et al., 2017). Deep drilling can be used to estimate the number of available resources of supercritical fluids (Doiet al., 1998; Elders et al., 2014; Fournier, 1999; Friðleifsson et al., 2020; Ikeuchi et al., 1998). However, as amethod to assess supercritical geothermal reservoirs, deep drillings are expensive (Elders et al., 2014). Owing
to the limited number of deep drilling points, the distribution and fluid fraction of supercritical geothermal reservoirs remain poorly understood. Therefore, geophysical methods (e.g., electromagnetic and seismic methods)
are required to gain insights into the spatial distribution and fluid fraction of supercritical geothermal reservoirs(Piana Agostinetti et al., 2017; Reinsch et al., 2017).
In this study, we use the magnetotelluric (MT) method with electrical resistivity imaging to estimate the spatial
distribution and fluid fraction of a supercritical geothermal reservoir in NE Japan. The MT method is suitable
for measuring the spatial distribution and fluid fraction of subsurface fluids because electrical resistivity is sensitive to the existence of fluids (Comeau et al., 2020; Ogawa et al., 2014; Unsworth et al., 2005; Wannamaker
et al., 2009). The fluid fraction of a supercritical geothermal reservoir can be obtained from a resistivity modelusing MT data. For the estimation of the fluid fraction, we consider a two-phase mixing law (Hashin & Shtrikman, 1962), assuming that the supercritical geothermal reservoir consists of solid rock and supercritical fluid in
the solid-rock pore space and that the supercritical fluid saturates the pore space. The resistivity obtained using
the MT method is bulk resistivity, which includes contributions from the solid rock and supercritical fluid in thepore space (Chave & Jones, 2012; Hashin & Shtrikman, 1962). We can obtain the fluid fraction of a supercritical
geothermal reservoir from the bulk resistivity using the mixing law if the resistivities of a supercritical fluid anda solid rock are known.
We consider magmatic supercritical fluids as NaCl-H2O fluids because magmatic fluids mainly consist of waterand chloride salts (Blundy et al., 2021; Heinrich, 2005; Monecke et al., 2018; Richards, 2011; Sillitoe, 2010). The
electrical resistivity of NaCl-H2O fluids has been studied extensively in the relationship between subsurface resistivity models and geological structures (Bannard, 1975; Nono et al., 2020; Quist & Marshall, 1968; Sakuma &Ichiki, 2016; Sinmyo & Keppler, 2016). Bannard (1975) reported that the electrical conductivity (the reciprocal
quantity of resistivity) of NaCl-H2O fluids strongly depends on NaCl concentrations, temperature, and pressure
based on measurements of NaCl-H2O fluids for a wide range of pressure, temperature, and NaCl conditions,
including supercritical conditions (up to 200 MPa, 525°C, and 25 wt% NaCl concentration). The measurements
showed that the conductivity of the NaCl-H2O fluid increases with increasing NaCl concentration under a fixed
temperature and pressure condition (e.g., 0.6 S/m and 115 S/m for 0.06 wt% and 24.6 wt% NaCl concentrations,
respectively at 25 MPa and 290°C). The measurements also revealed that the conductivity of NaCl-H2O fluids
under a fixed NaCl concentration and pressure condition increases with increasing temperature between 0°C
and 300°C, reaches a maximum near 300°C, and decreases as temperature increases between 300°C and 525°C
ISHIZU ET AL.

2 of 21

Journal of Geophysical Research: Solid Earth

10.1029/2021JB022911(Bannard, 1975). This result indicates that supercritical fluids tend to be more electrically resistive compared
to fluids at 300°C. Recent studies have also confirmed the decrease in conductivity in the supercritical region(Kummerow et al., 2020; Nono et al., 2020). N. Watanabe et al. (2021) developed a viscosity-dependent empiricalmodel to calculate the conductivity of NaCl-H2O fluids based on Bannard (1975) measurements. We use thisviscosity-dependent empirical model to calculate the conductivity of supercritical fluids. The solid rock in supercritical geothermal reservoirs in NE Japan is considered to be granite (Doi et al., 1998; Pastor-Galán et al., 2021).
We use the resistivity of dry granite reported by Kariya and Shankland (1983) for the resistivity of the solid rock.
NE Japan can be classified as a typical subduction zone, where the Pacific plate subducts beneath the land area at
a rate of ∼10 cm/year (Hasegawa et al., 1991). The dehydration of the subducting slab in the mantle wedge resultsin the upward migration of fluids (Tatsumi, 1989). Since the presence of water lowers the melting temperature ofrocks, the upwelling hot fluids can result in partial melting of the mantle wedge and the crust (Iwamori, 1998).
The partial melting in NE Japan was detected by low-velocity anomalies of S wave (so-called “hot fingers”) andthese hot fingers are distributed over NE Japan at intervals of several tens of kilometers (Tamura et al., 2002).
Magmatic fluids exsolved from the melt are considered to contribute to the formation of supercritical geothermal
reservoirs at a depth of 2–10 km in NE Japan (Tsuchiya et al., 2016). Therefore, the existence of these hot fingers
indicates that a large number of supercritical geothermal reservoirs may exist in NE Japan (Okamoto et al., 2019).
We select the Yuzawa geothermal field in NE Japan as the target area. Hot fingers exist around this geothermal
field (Tamura et al., 2002). Other geophysical and geochemical data (e.g., thermoluminescence, borehole temperature, and seismic data) also suggest that supercritical fluids may exist at a depth of a few kilometers (New
Energy and Industrial Technology Development Organization, 1990; Nunohara et al., 2021; Okada et al., 2014).
We conducted an MT survey to reveal the spatial distribution and fluid fraction of a potential supercritical geothermal reservoir in this field. Any information obtained on a supercritical geothermal reservoir in this field is
likely to be useful for the estimation of spatial distribution and fluid fraction of other supercritical geothermal
reservoirs in NE Japan (e.g., Naruko, Onikobe, and Kakkonda areas). Here, we first provide a brief introductionof the Yuzawa geothermal field, MT method, and a two-phase mixing law. Then, we present our findings on theestimation of the spatial distribution of a potential supercritical reservoir and its fluid fraction.

2. Yuzawa Geothermal Field in NE JapanThe Yuzawa geothermal field in NE Japan contains Wasabizawa geothermal power plant, the fourth-largest geothermal power plant in Japan (Nunohara et al., 2021). This field is located in the inner part of the Sanzugawa
caldera (Figures 1a and 1b). The Sanzugawa caldera, which was first formed ca. 3 Myr ago, has a size of 30 km
north-south and 20 km east-west (Takeno, 2000). A Quaternary volcano, the Takamatsu volcano, or Takamatsu-dake, is found in this geothermal field (red triangle in Figures 1b and 1c). The Takamatsu volcano is located
40 km west of the volcanic front (Tamanyu et al., 1998). The volcano is composed of calc-alkaline andesite todacite. The age of this volcano was estimated to be 0.2–0.3 Myr by thermo-luminescence and K-Ar methods(Umeda et al., 1999). The magma below the volcano is considered to be the heat source of this geothermal field(Takeno, 2000). Geothermal features, such as hot springs and hydrothermally altered rocks, have been observed
extensively at the surface in this geothermal field, indicative of a well-developed hydrothermal system (Nunohara
et al., 2021). Two geothermal power plants (Uenotai: 28,500 kW and Wasabizawa: 46,200 kW) are currently inoperation using a hydrothermal system at temperatures <300°C (magenta stars in Figure 1c).
Seismic imaging of NE Japan suggests that upwelling fluids exist beneath this geothermal field at a depth of up to
several kilometers (Nakajima et al., 2001; Okada et al., 2014; Tamura et al., 2002). The high He3/He4 in this fieldalso indicates that fluids upwell to the surface from the upper mantle (Horiguchi et al., 2010; Kita et al., 1992).
The temperature profile of a well, N63-MS-6 (blue square in Figure 1c) drilled by the New Energy and Industrial
Technology Development Organization (NEDO), is a conduction-dominated type with a temperature gradientof 170°C/km (New Energy and Industrial Technology Development Organization, 1990). This thermal gradientsuggests that temperatures can reach >400°C at a depth of 2.5 km below ground surface (bgs). These geophysicalobservations and borehole temperature measurements strongly indicate the possible existence of a supercritical
geothermal reservoir (>400°C) in this field.

ISHIZU ET AL.

3 of 21

Journal of Geophysical Research: Solid Earth

10.1029/2021JB022911

Figure 1. Maps of the study area. (a) Location of the Yuzawa geothermal field, NE Japan (yellow star). (b) Regional map
around the Yuzawa geothermal field. Black dotted lines follow the outline of the calderas (Yoshida et al., 2014). Red triangles
denote the major Quaternary volcanoes. (c) Local map of the Yuzawa geothermal field. White triangles denote MT sites.
Blue circles denote hot springs. Magenta stars denote power plants (Uenotai: 28,500 kW and Wasabizawa: 46,200 kW). The
red triangle in (c) denotes the Takamatsu volcano. The light blue square denotes the New Energy and Industrial Technology
Development Organization drilling site (N63-MS-6), reaching a depth of 1,500 m (New Energy and Industrial Technology
Development Organization, 1990).

3. Methods
3.1. MT Method
The MT method is a geophysical tool used to map the electrical resistivity structure of subsurfaces (Araya Vargas et al., 2019; Árnason et al., 2010; Becken et al., 2011; Bedrosian et al., 2018; Di Paolo et al., 2020; Heinson
et al., 2018; Heise et al., 2008; Hyndman & Shearer, 1989; Ichihara et al., 2016; Ingham et al., 2009; Le Papeet al., 2015; Moorkamp et al., 2019; Wise & Thiel, 2020). This method uses surface measurements of naturally
occurring low-frequency electromagnetic variations to investigate underground resistivity structures (Chave &Jones, 2012). Each MT station records two components of the electric field (Ex and Ey) and three components ofthe magnetic field (Hx, Hy, and Hz). The x-, y-, and z-directions respectively correspond to the geographic north,
ISHIZU ET AL.

4 of 21

Journal of Geophysical Research: Solid Earth

10.1029/2021JB022911

east, and vertical depths. The z-direction is pointing down. The orthogonal components of the horizontal electricand magnetic fields are linearly related by the complex-valued impedance tensor Z in the frequency domain as
follows:
⎤⎡ ⎤
⎤ ⎡
⎡
(1)
⎢ 𝐸𝑥 ⎥ = ⎢𝑍𝑥𝑥 𝑍𝑥𝑦 ⎥ ⎢𝐻𝑥 ⎥ .
⎢ 𝐸𝑦 ⎥ ⎢𝑍𝑦𝑥 𝑍𝑦𝑦 ⎥ ⎢𝐻𝑦 ⎥
⎦⎣ ⎦
⎦ ⎣
⎣

The tipper T (or vertical magnetic field transfer function) relates the vertical magnetic fields (Hz) to the horizontal
magnetic field components in the frequency domain with the following relation:[] ⎡𝐻 ⎤𝑥
(2)𝐻𝑧 = 𝑇𝑧𝑥 𝑇𝑧𝑦 ⎢ ⎥ ,
⎢𝐻𝑦 ⎥
⎣ ⎦

and T is dimensionless. Z and T carry information about underground resistivity structures and therefore dependon the measurement location r (x, y, z) and frequency f in Hz (Chave & Jones, 2012). The Z can be expressedin terms of the apparent resistivity and phase for data interpretation (Chave & Jones, 2012). The Z can also
be expressed as a phase tensor and phase tensor is independent of the distorting effects produced by localizednear-surface resistivity heterogeneities (Caldwell et al., 2004):⎤⎡
Φ𝑥𝑥 Φ𝑥𝑦 ⎥(3)𝚽 = 𝐗−1 𝐘 = ⎢,⎢Φ𝑦𝑥 Φ𝑦𝑦 ⎥⎦⎣where X and Y are the real and imaginary parts of the Z, respectively. The phase tensor Φ can be graphically
represented as an ellipse with principal (ellipse) axes, Φmax and Φmin (Caldwell et al., 2004):√(4)Φ2 = Φmax Φmin .

The Φ2 indicates the magnitude of the phase tensor response. In a one-dimensional subsurface resistivity structure, the decrease in resistivity with increasing depth is indicated by a value of Φ2 > 45° and the increase inresistivity with increasing depth is indicated by a value of Φ2 < 45°.
The observed MT data can be converted into an underground resistivity model using inversion analysis (Constable et al., 1987; Farquharson, 2008; Kelbert et al., 2014; Newman, 2014; Ogawa & Uchida, 1996; Siripunvaraporn & Egbert, 2009). We use WSINV3DMT for the three-dimensional (3-D) inversion of the observed data
(Siripunvaraporn & Egbert, 2009). WSINV3DMT searches for the smoothest model subject to the desired levelof data misfit χ*. Mathematically, this equals to searching for the stationary point of an unconstrained functional
U(m, λ):{}−1
2
𝑈𝑈 (𝐦𝐦, 𝜆𝜆) = (𝒎𝒎 − 𝒎𝒎0 )𝑇𝑇 𝐂𝐂−1
(𝐝𝐝 − 𝐅𝐅[𝐦𝐦])𝑇𝑇 𝐂𝐂−1(5)𝑚𝑚 (𝐦𝐦 − 𝐦𝐦0 ) + 𝜆𝜆𝑑𝑑 (𝐝𝐝 − 𝐅𝐅[𝐦𝐦]) − 𝜒𝜒∗ ,where m is the resistivity model, m0 is the prior model, d is the observed data, F[m] is the forward response, Cm
is the model covariance, Cd is the data covariance matrix, and λ−1 is the Lagrange multiplier. The first term in thefunction U is the model roughness and the second term is the data misfit weighted by the Lagrange multiplier λ−1.
Since U is a function of both m and λ, the search for the stationary points is not straightforward (Siripunvaraporn& Egbert, 2009). Alternatively, WSINV3DMT minimizes a penalty functional Wλ:𝑇𝑇 −1−1
𝑊𝑊𝜆𝜆 = (𝒎𝒎 − 𝒎𝒎0 )𝑇𝑇 𝐂𝐂−1(6)𝑚𝑚 (𝐦𝐦 − 𝐦𝐦0 ) + 𝜆𝜆 (𝐝𝐝 − 𝐅𝐅[𝐦𝐦]) 𝐂𝐂𝑑𝑑 (𝐝𝐝 − 𝐅𝐅[𝐦𝐦]).

𝐴𝐴

ISHIZU ET AL.

𝜕𝜕𝜕𝜕This is because when λ is𝐴𝐴fixed, 𝐴𝐴and 𝜕𝜕𝜕𝜕
obtain the same result (Siripunvaraporn & Egbert, 2009). By minimiz𝜕𝜕𝜕𝜕𝜕𝜕𝜕𝜕ing Wλ with a series of λ, the stationary point of U can be found (i.e., λ can be found such that the data misfit is𝐴𝐴∗2). For further details on WSINV3DMT, see Siripunvaraporn and Egbert (2009).

5 of 21

Journal of Geophysical Research: Solid Earth

10.1029/2021JB022911

3.2. Two-Phase Mixing Law
We consider a two-phase mixing law proposed by Hashin and Shtrikman (1962) to estimate the fluid fraction of
a potential supercritical geothermal reservoir from an electrical resistivity model. To apply the mixing law, we
assume that the supercritical geothermal reservoir consists of solid rock and supercritical fluid in the solid-rockpore space and that the supercritical fluid saturates the pore space. Hashin and Shtrikman (1962) proposed theupper and lower bounds for effective conductivity. The Hashin-Shtrikman upper bound model (HS+; Hashin &Shtrikman, 1962), which assumes complete connectivity:)(
3 (1 − 𝜒𝜒2 ) (𝜎𝜎2 − 𝜎𝜎1 ),𝜎𝜎bulk+ = 𝜎𝜎2 1 −(7)3𝜎𝜎2 − 𝜒𝜒2 (𝜎𝜎2 − 𝜎𝜎1 )where 𝐴𝐴1 is the conductivity of the solid𝐴𝐴rock, 𝐴𝐴2 is the conductivity of the supercritical fluid,𝐴𝐴
𝐴𝐴 and 𝐴𝐴2 is the volumetric fluid fraction of the supercritical fluid (i.e., porosity). Equation 7 indicates that we can obtain the fluid
fraction of a supercritical geothermal reservoir from the bulk conductivity using the mixing law if conductivity
values of a supercritical fluid and a solid rock are known. With the HS+ model, the contribution of solid rockconductivity to bulk resistivity is limited if the conductivity of the solid rock is much smaller than the conductivity of the fluid (Ogawa et al., 2014). The Hashin-Shtrikman lower bound model (HS‒; Hashin & Shtrikman, 1962)
is presented as follows:()
3𝜒𝜒2 (𝜎𝜎2 − 𝜎𝜎1 )𝜎𝜎bulk− = 𝜎𝜎1 1 +.
(8)3𝜎𝜎1 + (1 − 𝜒𝜒2 ) (𝜎𝜎2 − 𝜎𝜎1 )The HS‒ model assumes that the fluid is included in isolated pockets. This study only considers the Hashin-Shtrikman upper bound model (HS+) because the HS+ has provided a reasonable estimation of a fluid fractionof crustal rocks in NE Japan (Ogawa et al., 2014). We use a viscosity-dependent empirical model developed by N.
Watanabe et al. (2021) to calculate the conductivity of supercritical fluids(𝐴𝐴2). We consider that the solid rock in𝐴𝐴supercritical geothermal reservoirs in NE Japan consists of granite (Doi et al., 1998) and use the conductivity ofdry granite reported by Kariya and Shankland (1983) for the conductivity of the solid𝐴𝐴rock (𝐴𝐴1).

4. Results
We collected MT data at 30 measurement sites to image resistivity structures in the Yuzawa geothermal field(Figure 1c). Since the objective of this study is to image supercritical geothermal reservoirs at depths of several
kilometers, the range of the MT measurement area is 15 km in the horizontal direction. The Φ2 is higher than 45°
at 20 Hz and lower than 45° at 2.5 Hz around Takamatsu volcano and power plants (Figures 2a and 2b), suggesting the existence of near-surface conductors and resistors below the near-surface conductors. Apparent resistivity
data at MT sites around Takamatsu volcano and power plants exhibit low values <50 Ωm at a high frequency of
100 Hz, which also suggests the existence of the near-surface conductors around Takamatsu volcano and power
plants (Figures S1, S2, and S4 in Supporting Information S1). The Φ2 is higher than 45° at 0.3 Hz around thenorthwest of the Takamatsu volcano, which implies the presence of a deep conductor (Figure 2c). The impedance
and tipper data for each observation site are shown in Figures S1–S6 in Supporting Information S1.
Inverse modeling with WSINV3DMT can convert the observed MT data into 3-D resistivity structures (Siripunvaraporn & Egbert, 2009; Siripunvaraporn et al., 2005). The initial resistivity model for inverse modeling consistsof the subsurface (100 Ωm), ocean (0.3 Ωm), and air (1010 Ωm). We tested other initial models with homogeneous
subsurface structures of 1, 10, and 1,000 Ωm. The initial model with homogeneous subsurface structures of 100
Ωm obtained the lowest root-mean-square (RMS) final misfit (the final RMS misfit = 6.37, 3.33, 2.34, and 3.55
for the initial models of 1, 10, 100, and 1,000 Ωm, respectively). The prior resistivity model was set to be the sameas the initial resistivity model. The model mesh is discretized into 74 × 74 × 70 cells in the x-, y-, and z-directions,
respectively, containing boundary cells. The horizontal cell size is kept constant at 300 m inside the area of interest (−10 km < x and y < 10 km) and then is increased toward the boundary. For depths between −1.3 km below
sea level (bsl) and 0 km bsl (depths <0 km bsl indicate above the sea level in our definition), the vertical cell size
is set to values ranging from 20 to 50 m. For depths >0 km bsl, the vertical cell size is increased as the depth
increases. We performed the inverse modeling on a computer (@Xeon 3.10 GHz Gold 6254 central processing

ISHIZU ET AL.

6 of 21

Journal of Geophysical Research: Solid Earth

10.1029/2021JB022911

Figure 2. Phase tensor ellipses of observed MT data for (a) 20, (b) 2.5, (c) 0.3, and 0.02 Hz. The phase tensor ellipses arefilled by
𝐴𝐴 tan−1 (Φ2 ) defined in Equation 4 (Caldwell et al., 2004). Phase tensor ellipses have been normalized by the maximum
phase value. Magenta stars denote power plants. The red triangle denotes Takamatsu volcano. Note that x- and y-directions
respectively correspond to the geographic north and east. The black dashed line indicates the outline of C1 at a depth of
2.5 km bsl in Figure 3.

unit; Intel Corp.) with 3 TB of RAM. The impedance tensor and tipper between frequencies of 0.001–100 Hz (17frequencies) are used for inverse modeling.
Error floors for the impedance tensor are set to 𝐴𝐴
5% of |𝒁𝒁 𝑥𝑥𝑥𝑥 𝒁𝒁 𝑦𝑦𝑦𝑦 | ∕ ; error floors for the tipper are set to 15% ofeach component. The smoothing parameters for Cm are𝐴𝐴set to 𝐴𝐴
𝐴𝐴 = 5, 𝐴𝐴𝑥𝑥 = 0.1, 𝑑𝑑𝑦𝑦 = 0.1, and 𝑑𝑑𝑧𝑧 = 0.3. We selected
these smoothing parameters because the inverse modeling with these smoothing parameters obtained the lowest
final RMS misfit compared to other smoothing parameters. For details on the smoothing parameters of Cm, see
Siripunvaraporn and Egbert (2009). The RMS misfit for the initial model was 10.2. The inversion analysis obtained a resistivity model with an RMS misfit of 2.34 after three iterations (Figure 3). The data fits are good foralmost all sites and frequencies (Figures S1–S6 in Supporting Information S1).
1 2

3-D resistivity structures obtained from the inverse modeling identify near-surface conductors at a depth between−1.3 and 0.5 km bsl, as well as a deep conductor C1 at a depth between 1 and 12 km bsl (Figure 3). The resistivity of the near-surface conductors is 5–20 Ωm, which is lower than that of the surrounding rock of 100 Ωm.
ISHIZU ET AL.

7 of 21

Journal of Geophysical Research: Solid Earth

10.1029/2021JB022911

Figure 3. (a) 3-D view with vertical slice at x = 0.5 km; (b) horizontal slice at a depth of 2.5 km bsl; (c) vertical slice at x = 0.5 km; (d) vertical slice at y = 0.5 km of
the inverted resistivity model from the MT data. C1 denotes conductive zones, which imply a supercritical fluid and partial melting. Black triangles denote MT sites.
Magenta stars denote power plants. The red triangle denotes Takamatsu volcano. The light blue square denotes the New Energy and Industrial Technology Development
Organization drilling sites (N63-MS-6). Contours of Vp/Vs ratio (Okada et al., 2014) are superimposed on the sections in (c and d). Note that depth is indicated as thedepth below sea level, and x- and y-directions denote the geographic north and east, respectively. Black triangles denote MT sites within ±1 km of each profile line.
Black dots denote the relocated hypocenters of earthquakes within ±150 m of each profile line (Okada et al., 2014). White lines denote the depth of a minimum of silica
solubility in pure H2O under hydrostatic conditions (DSi_h: the depth is 1.3 km bsl and 1.9 km bgs at the drilling site N63-MS-6), as presented in Figure 6a.

The near-surface conductors are widely distributed in this area. The resistivity of C1 is 5–15 Ωm. The size of
C1 is 3 km (width) × 5 km (length) × 10 km (height). The existence of the near-surface conductors is consistent
with the features of the observed data where the Φ2 is higher than 45° at 20 Hz and low apparent resistivity data
<100 Ωm is observed at a frequency of 100 Hz (Figure 2 and Figure S1–S6 in Supporting Information S1). The
existence of deep conductor C1 is supported by the feature of the observed data where the Φ2 is higher than 45°
at 0.3 Hz around the northwest of the Takamatsu volcano (Figure 2). Conductive zones extend from the east andwest ends of deep conductor C1 to the near-surface conductors (Figure 3c). The conductive zone extending fromthe west end of C1 extends toward the Wasabizawa power plant (Figure 3c). Although a deep conductor is imaged
at y = 9 km outside the coverage area of the MT measurements (Figure 3c), the MT data do not sufficiently constrain resistivity structures outside the coverage area of the measurements. Therefore, we exclude this conductorfrom our discussions in this study.
ISHIZU ET AL.

8 of 21

Journal of Geophysical Research: Solid Earth

10.1029/2021JB022911

The deep conductor C1 may be associated with a supercritical geothermal reservoir and melt. Therefore C1 is an
important feature in the presented model. It is known that the inverse solution of MT data is non-unique, meaningthat many models can fit the observed data equally well (Constable et al., 1987; Ishizu et al., 2021). We calculate
the MT responses for models where the resistivity values of C1 are replaced by values between 1 and 100 Ωm(1, 3, 10, 30, and 100 Ωm) to determine how well the resistivity values are constrained by the data (Figure S7 in
Supporting Information S1). The RMS misfit is minimum for 10 Ωm and increases away from 10 Ωm (Figure
S7 in Supporting Information S1). We measure the reliability of the resistivity values of C1 based on F values
with a 95% confidence interval (Gresse et al., 2021; Yamaya et al., 2017). The threshold RMS misfit with a 95%
confidence interval is 2.392. Forward models associated with C1: 6.5 Ωm < C1 < 35 Ωm obtain an RMS misfit<2.392. Forward models associated with low and high resistivities (i.e., <6.5 Ωm and >35 Ωm) show RMS
values higher than FRMS = 2.392. In other words, these forward models are statistically rejected with a 95% confidence interval. Hence, we conclude that the resistivity range of C1 is 6.5 Ωm < C1 < 35 Ωm.

5. Discussion
5.1. Shallow Hydrothermal System
First, a shallow geothermal system is investigated using the obtained resistivity model. The resistivity model reveals the near-surface conductors at depths between −1.3 and 0.5 km bsl (Figure 3). Similar near-surface conductors found in various volcanic areas have been interpreted as smectite-rich zones (Cherkose & Saibi, 2021; Kanda
et al., 2019; Ledo et al., 2021; Pellerin et al., 1992; Tseng et al., 2020; Yoshimura et al., 2018). Drilling confirmed
the smectite-rich zones in this field (New Energy and Industrial Technology Development Organization, 1990).
Moreover, the distribution of near-surface conductors is consistent with the distribution of smectite-rich hydrothermal alteration zones at the surface (Nunohara et al., 2021). These results indicate that the near-surface conductors are smectite-rich zones. Smectite under moisture-rich conditions can be converted to illite at temperatures
exceeding 200°C (Pytte & Reynolds, 1989; Wersin et al., 2007; Yamaya et al., 2013). Rocks containing illite haveresistivity values 6–10 times higher than those of rocks with a similar proportion of smectite under the same temperature, porosity, and salinity conditions (Ussher et al., 2000). We set the boundaries of the smectite and illite
zones at 50 Ωm because the depth at which the smectite-rich near-surface conductors reach a resistivity value of
50 Ωm is roughly consistent with the isotherm at 200°C (Figure 3). Hence, we interpret the resistive zone of >50
Ωm below the near-surface conductors as an illite-rich zone transformed from smectite above 200°C.
Conductive zones are found to extend from the east and west ends of deep conductor C1 to the near-surface
conductors (Figure 3c). The conductive zone extending from the west end of C1 extends toward the Wasabizawa
power plant (Figure 3c). The 3He/4He and 4He/20Ne ratios of the fumarolic gas at the Kawarage hot spring, located
3 km west of the Wasabizawa power plant, were 9.5 × 10−6 and 180, respectively (Kita et al., 1992). This indicates that the helium at the Kawarage hot spring originates from magmatic gas. These results suggest that these
conductive zones act as a path for magmatic fluid ascending from C1, resulting in anomalies in the helium ratios
at the Kawarage hot spring. A conductor extending from the deep parts (25 km depth) to the surface at Naruko
volcano also represents a path for ascending magmatic fluid (Ogawa et al., 2014).
5.2. Supercritical Geothermal Reservoir
The low resistivity of C1 suggests that it includes magmatic fluids and melt. C1 is imaged in the low Vp and Vs
region, supporting that C1 contains magmatic fluids and melt (Figure S8 in Supporting Information S1). The low
Vp and Vs zones extend west compared to C1 (Figure S8 in Supporting Information S1). We consider that thegeometry difference largely comes from the model grid difference between the presented resistivity model andthe velocity model (horizontal cell size is 300 m in the resistivity model and 6 km in the velocity model). The
temperature of C1 is estimated to be above 400°C based on the temperature profile (Figure 4a). While few seismic
events occurred inside C1, most occurred around the edge of C1 (Figure 3), indicating that seismic events may
have resulted from fluid migration around the edge of C1. The depth of the seismicity cut-off is consistent withthe top of C1, and it is known that the depth of the seismicity cut-off roughly corresponds to 400°C (Mitsuhata
et al., 2001; Ogawa et al., 2001; Okada et al., 2014). The correspondence between the top of C1 and the seismicity
cut-off also supports that C1 is >400°C.
ISHIZU ET AL.

9 of 21

Journal of Geophysical Research: Solid Earth
(b)

(c)
-1

0

0

0

1

1

1

2

5
0

250 500 750 1000
Temperature (°C)

025 50 75 100
Pressure (MPa)

3

4

150

atic
ost
Lith

5

2

tatic

4

Sealing

s
Hydro

3

tatic

4

2

atic
ost
Lith

3

Depth (km bsl)

-1

Depth (km bsl)

-1

s
Hydro

Depth (km bsl)

(a)10.1029/2021JB022911

50

25 50 75 100
Pressure (MPa)150

Figure 4. (a) Temperature profile as a function of depth at the New Energy and Industrial Technology Development
Organization drilling site (N63-MS-6) presented in Figure 1b (New Energy and Industrial Technology Development
Organization, 1990). The solid line denotes logging data and the dashed line denotes the extrapolated profile. (b) The pressure
profile is a function of depth under hydrostatic pressure (black line) and lithostatic pressure (gray line), respectively. We
calculate the hydrostatic pressure assuming a water density of 1,000 kg/m3 and lithostatic pressure assuming a rock densityof 2,700 kg/m3 (Saishu et al., 2014). (c) The pressure path of ascending magmatic fluids assuming that the sealing exists at a
depth of DSi_h = 1.3 km bsl and the sealing separates the hydrostatic and lithostatic regions.

Similar conductors at depths of 2–15 km in other volcanoes have been interpreted as magmatic fluids andmelt (e.g., Mount St Helens: Bedrosian et al., 2018, Geysers: Peacock et al., 2020, Laguna del Maule: Cordell
et al., 2020, Kirishima: Aizawa et al., 2014; Taupo: Bertrand et al., 2012, Krafla: Lee et al., 2020). A minimum
solidus temperature of 725°C at a pressure of 100 MPa (Bowles-Martinez & Schultz, 2020; Tuttle & Bowen, 1958), suggests that the part of C1 at a temperature lower than 725°C is mostly crystallized and high conductivity values of the part of C1 <725°C is derived from the existence of magmatic fluids, rather than melt. A depthof 3.5 km bsl (or 4.1 km bgs at the drilling site N63-MS-6) corresponds to a temperature of 725°C and a pressureof 107 MPa for the lithostatic conditions (Figure 4a). Therefore, we consider the upper part of C1 at a depth
shallower than 3.5 km bsl as a potential supercritical geothermal reservoir (>400°C). The Vp/Vs ratio (Okada
et al., 2014) is lower than 1.65 in the upper parts of C1 (Figure 3 and Figure S8 in Supporting Information S1).
The low Vp/Vs ratio in the upper crust in NE Japan cannot be explained by the presence of melt but can be explained by the presence of a few volume percent of H2O with a large aspect ratio due to a higher bulk modulus ofmelt than a bulk modulus of H2O (Nakajima et al., 2001). Thus, the low Vp/Vs ratio in the upper parts of C1 also
supports that the upper parts of C1 might contain a certain fraction of magmatic fluids. An increased Vp/Vs ratio
is observed in the lower parts of C1, supporting the existence of melt in the lower parts of C1.
The typical NaCl content of magmatic fluids was estimated to be 5–10 wt%, based on fluid inclusion analysisof porphyry ore samples collected in various regions of the world (Heinrich, 2005). We assume that the magmatic fluid in our study area (subduction zone of NE Japan) also has the typical NaCl content of 5–10 wt%. The
validity of the assigned 5–10 wt% NaCl content of magmatic fluids in our study area is supported by the resultof the fluid inclusion analysis of Kofu Granite samples in central Japan (Kurosawa et al., 2010). Recent mantle
xenolith studies reported the NaCl content of fluids in the mantle wedge beneath the Pinatubo volcano, Philippines (subduction zone) to be 5.1 wt% (Kawamoto et al., 2013). The reported value of 5.1 wt% NaCl content
also supports that the assigned 5–10 wt% NaCl content is reasonable as an NaCl content of magmatic fluids insubduction zones. Phase states of NaCl-H2O fluids are different depending on the pressure, temperature, andsalinity conditions (Afanasyev et al., 2018; Driesner & Heinrich, 2007; Sillitoe, 2010; Weis et al., 2012). We
consider the phase states of the potential supercritical reservoir at a depth of 1.8 km bsl (temperature of 450°C)
because shallow parts are easier to exploit than deeper parts. The pressure at the potential supercritical reservoir is
ISHIZU ET AL.

10 of 21

Journal of Geophysical Research: Solid Earth

10.1029/2021JB022911

Figure 5. (a) Pressure-temperature diagram of NaCl-H2O solution for 5 wt% NaCl equivalent, calculated using AqSo_NaCl software (Bakker, 2018). The magenta
circle denotes the critical point (422°C and 34 MPa). Red, blue, and black crosses denote the pressure-temperature points at a temperature of 450°C (a depth of 1.8 kmbsl) under lithostatic pressure, hydrostatic pressure, and average of lithostatic and hydrostatic pressure, respectively. (b) Isothermal pressure-composition sections for
450°C. The red and blue lines denote pressure at a depth of 1.8 km bsl under hydrostatic and lithostatic conditions. In the phase state of vapor-halite coexistence, solid
halite and vapor coexist (Driesner & Heinrich, 2007). In the phase state of the liquid-vapor coexistence, the fluid exists as low-salinity vapor in equilibrium with a small
fraction of hypersaline brine. In the F domain at pressures above the liquid-vapor surface, fluid properties can continuously vary between vapor- and liquid-like without
any heterogeneous phase change (Driesner & Heinrich, 2007; Scott et al., 2015). The supercritical fluid in this domain is often called “single-phase fluid” (Driesner &Heinrich, 2007). We also use the term of single-phase fluid for the supercritical fluid in this region.

expected to be hydrostatic or lithostatic, or somewhere between the two (Figure 4b). We calculate the hydrostaticpressure assuming a water density of 1,000 kg/m3 and lithostatic pressure assuming a rock density of 2,700 kg/
m3 (Saishu et al., 2014).
The phase state of the supercritical fluid at 450°C and with a 5 wt% NaCl equivalent is a vapor-halite coexistence
if the pressure is in the hydrostatic condition (Figure 5). In the phase state of vapor-halite coexistence, solid halite
and vapor coexist (Driesner & Heinrich, 2007). The supercritical fluid in the pore space exists as vapor withsolid halite in this phase state. Although only a very small fraction of interstitial fluid in the halite can reduce
electrical resistivity by orders of magnitude (T. Watanabe & Peach, 2002), the halite exists with vapor in this case.
Therefore, we consider that the halite is dry. The resistivity of dry halite is reported as >108 Ωm (T. Watanabe &Peach, 2002). We assume that the vapor is resistive at 1,000 Ωm (Peacock et al., 2020). As a result, the resistivityof the vapor-halite coexistence in the pore space is estimated to be more resistive than 1,000 Ωm. Dry granite
resistivity at a temperature of 450°C is 105 Ωm (Kariya & Shankland, 1983). These resistivity values suggest thatthe bulk resistivity of the supercritical geothermal reservoir with the phase state of vapor-halite coexistence is
expected to be much more than 10 Ωm of C1. Thus, the phase state of vapor-halite coexistence would not apply
to the supercritical geothermal reservoir.
The phase state of the supercritical fluid is liquid-vapor coexistence at 450°C if the pressure is below the average
between hydrostatic and lithostatic conditions (e.g., 35 MPa; Figure 5). In the phase state of the liquid-vapor coexistence, the fluid exists as low-salinity vapor in equilibrium with a small fraction of hypersaline brine (Driesner& Heinrich, 2007). Laboratory measurement data reported that the conductivity of volcanic rock samples withsteam in the pore space decreased by a factor of 20 compared to the conductivity of the rock samples with only
liquid in the pore space (Milsch et al., 2010). In fact, the bulk resistivity of 100–1,000 Ωm has been reported forrocks with supercritical fluids of liquid-vapor coexistence (Gresse et al., 2021; Samrock et al., 2018), which aremuch more resistive than 10 Ωm of C1, indicating that the phase state of liquid-vapor coexistence would not also
apply to the supercritical geothermal reservoir.

ISHIZU ET AL.

11 of 21

Journal of Geophysical Research: Solid Earth

10.1029/2021JB022911

Figure 6. Quartz solubility profiles as a function of depth, calculated using Loner AP software (Akinfiev & Diamond, 2009).
The solubility of quartz in pure H2O under hydrostatic conditions (salinity = 0 wt%; black line) and the solubility of quartz
in saline fluid under lithostatic conditions (5 wt% NaCl equivalent; gray line) are shown. The red line denotes the depthof the top of C1 at the drilling point N63-MS-6, as shown in Figure 3. The quartz solubility has a minimum at a depth of
DSi_h = 1.3 km bsl for hydrostatic pressure (green star). DSi_h = 1.3 km bsl occurs at a temperature of 364.14°C and a pressureof 18.44 MPa. (b) Temperature profile and (c) pressure profile used to calculate the quartz solubility. (b and c) are the same as
Figure 4 and for explanations on (b and c), see the caption in Figure 4.

If the pressure is >42 MPa for the temperature of 450°C and 5 wt% NaCl content, no clear distinction between liquidand vapor is possible for the supercritical fluid in this condition (Driesner & Heinrich, 2007). Supercritical fluids inthis state are often referred to as “single-phase fluids” (Driesner & Heinrich, 2007). In this article as well, supercritical fluids in this region will be referred to as “single-phase fluids”. If the pressure is in the lithostatic condition, fluids
in the supercritical geothermal reservoir exist as a “single-phase fluid” (Figure 5). A single-phase supercritical fluid>400°C is more electrically resistive compared to fluids at 300°C (Bannard, 1975; Kummerow et al., 2020; Nonoet al., 2020). However, the conductivity of a single-phase supercritical fluid under the lithostatic pressure (64 MPa)and for 450°C and 5 wt% NaCl content shows a high value of 17.6 S/m even under a supercritical condition (N.
Watanabe et al., 2021). This high conductivity (17.6 S/m) of a single-phase supercritical fluid under the lithostaticpressure implies that the supercritical fluid can reasonably explain 10 Ωm of C1. Therefore, we consider the fluid in
the supercritical geothermal reservoir as a single-phase fluid under pressure close to the lithostatic pressure.
If a connection exists to the surface from the supercritical geothermal reservoir, the pressure should be under hydrostatic conditions in the supercritical geothermal reservoir and supercritical fluids move to the surface without theaccumulation. Moreover, the above discussion suggests that pressures close to the lithostatic pressure are expectedin the supercritical geothermal reservoir to explain the low resistivity (10 Ωm) of C1. Hence, sealing to weaken theconnections should be considered as an explanation for the accumulation of supercritical fluids and the lithostaticpressure of the reservoir (Scholz, 2019; Sibson, 2020). Silica sealing has been found above potential supercriticalreservoirs and may separate the hydrostatic and lithostatic regions (Fournier, 1999; Ingebritsen & Manning, 2010;
Lowell et al., 1993; Manning, 1994; Saishu et al., 2014; Weatherley & Henley, 2013). To consider the potential ofsilica sealing in this field, we calculate the silica solubility using Loner AP software (Akinfiev & Diamond, 2009).
Two general mechanisms have been proposed for the occurrence of silica sealing above supercritical geothermal
reservoirs. The development of silica sealing by the first mechanism occurs when upwelling magmatic fluids underlithostatic pressure encounter fluids under hydrostatic pressure (Fournier, 1999; Saishu et al., 2014). The first mechanism can be explained by the fact that at depths >1 km bsl, the solubility of silica in H2O under the hydrostatic pressure (black line in Figure 6a) is much smaller than the solubility under the lithostatic pressure (gray line in Figure 6a).
When silica-rich magmatic fluids under lithostatic pressure encounter fluids under hydrostatic pressure, silica precipitates due to the difference in solubility. The development of silica sealing by the second mechanism occurs when

ISHIZU ET AL.

12 of 21

Journal of Geophysical Research: Solid Earth

10.1029/2021JB022911

meteoric water under the hydrostatic pressure moves downward (surface to deeppart) driven by hydrothermal convection (Saishu et al., 2014). Silica solubility
in water under the hydrostatic pressure increases with increasing depth, up to adepth of 1.2 km bsl (black line in Figure 6a). Then, the solubility decreases andhas a minimum at a depth of DSi_h = 1.3 km bsl for the hydrostatic pressure indicating that silica precipitation can occur at a depth of DSi_h = 1.3 km bsl fromdownward-moving fluids (black line and green star in Figure 6a). DSi_h = 1.3 km
bsl occurs at a temperature of 364.14°C and pressure of 18.44 MPa and coincides with the point of change from the liquid phase to the vapor phase for the
downward-moving fluids (Figure 7). The solubility of silica in water depends
on the density of the water (Tsuchiya & Hirano, 2007). The fluid flow from thehigher density liquid region into the lower density vapor region causes a drop in
silica solubility at DSi_h = 1.3 km bsl (Tsuchiya & Hirano, 2007).

Figure 7. The relationship between the minimum point of solubility of silica
and the point of change from the liquid phase to the vapor phase. The blackline denotes the pressure-temperature profile under hydrostatic conditions in
the Yuzawa geothermal field. The blue line denotes the vapor pressure curveof pure H2O (salinity = 0 wt%). The solubility of silica in pure H2O underhydrostatic conditions has a minimum DSi_h = 1.3 km below sea level at364.14°C and 18.44 MPa (green star). This minimum point of silica solubility
coincides with the point where the vapor pressure curve and the temperaturepressure profile intersect (i.e., the point of change from the liquid phase to
the vapor phase). The magenta circle denotes the critical point (374.15°C and22.12 MPa).

To explain the silica precipitation caused by the first mechanism, the hydrostatic-lithostatic pressure boundary should exist before the first mechanism
occurs. Therefore, we consider that the second mechanism occurred first,
and the second mechanism would have caused the quartz precipitation at a
depth of DSi_h = 1.3 km bsl and separates the hydrostatic and lithostatic regions at DSi_h. This interpretation is supported by correspondence between
DSi_h and the depth of the top of C1 at the drilling point N63-MS-6. Afterthe development of the silica sealing at DSi_h by the second mechanism, thefirst mechanism also contributes to enhancing the silica sealing at DSi_h. The
silica-rich magmatic fluids under lithostatic pressure encounter fluids under
the hydrostatic pressure at DSi_h, and the difference in silica solubility causes
silica precipitation at DSi_h. Therefore, two mechanisms are currently contributing to the development of silica sealing at a depth of DSi_h = 1.3 km
bsl (Figure 4c). The silica sealing also plays a role in trapping the upwellingsupercritical fluids due to its low permeability.

We estimate the fluid fraction of a potential supercritical reservoir using the obtained resistivity model. The resistivity of dry granite is reported to be about 105 Ωm at a temperature of 400°C–550°C (Kariya & Shankland, 1983).
The solid-phase resistivity for the supercritical geothermal reservoir is fixed at 105 Ωm. Reservoir pressure is assumed to be under the lithostatic condition (Figure 4c). The resistivity of supercritical fluid at a depth of 1.8 km
bsl (450°C and 64 MPa) are 17.6 and 36.0 S/m for 5 wt% and 10 wt% NaCl equivalent, respectively (N. Watanabe
et al., 2021). The HS+ model suggests that 10 Ωm resistivity of C1 requires a fluid fraction of 0.9% and 0.4% for 5
wt% and 10 wt% NaCl equivalent, respectively (Figure 8 and Table 1). Considering the resistivity range of C1 (6.5Ωm < C1 < 35 Ωm), the fluid fraction of the potential supercritical reservoir at a depth of 1.8 km bsl is estimatedto be 0.1%–1.3% (Figure 8 and Table 1). We also estimate the fluid fraction of the supercritical reservoir at a depthof 2.4 km bsl (550°C and 79 MPa). The resistivity of supercritical fluid is 5.4 and 11.5 S/m for 5 wt% and 10 wt%
NaCl equivalent, respectively (N. Watanabe et al., 2021). Considering the resistivity range of C1 (6.5 Ωm < C1 < 35Ωm), the fluid fraction of a potential supercritical reservoir at a depth of 2.4 km bsl is 0.4%–4.2% (Figure 8 and Table 1). Therefore, the fluid fraction of the supercritical reservoir is estimated to be 0.1%–4.2% with a salinity of 5–10
wt%. The 0.1%–4.2% fluid fraction of the supercritical reservoir estimated by the resistivity model is consistent
with the porosity (1.7%) of the core sample of the Kakkonda granite near the bottom of the WD-1a well (Muraoka
et al., 1998). A recent investigation of plagioclase alteration in mafic schists in NE Japan reported that significant
nano-to micro-scale pores were generated in plagioclase during the alteration of 400°C–570°C, which resulted in
the whole-rock porosity of 1.3% ± 0.2% (Nurdiana et al., 2021). The porosity values obtained by investigation ofplagioclase alteration also support that our estimation of the fluid fraction of the supercritical reservoir is reasonable.
5.3. Partial Melt
The temperature of C1 at a depth >4 km bsl is estimated to be above 800°C (Figure 4). This temperature of 800°C
is over the minimum solidus temperature of 725°C at a pressure of 100 MPa for silicic melt (Bowles-Martinez &Schultz, 2020; Tuttle & Bowen, 1958). Therefore, C1 at a depth >4 km bsl can contain melt. Resistivity models
ISHIZU ET AL.

13 of 21

Journal of Geophysical Research: Solid Earth

10.1029/2021JB022911

Figure 8. (a) The bulk resistivity of the potential supercritical geothermal reservoir at 450°C and 60 MPa (depth of 1.8 km bsl) as a function of fluid fraction and of
NaCl content in the supercritical fluid. The assigned conductivity values of supercritical fluid resistivity are 17.6 and 36.0 S/m for 5 wt% and 10 wt% NaCl equivalent,
respectively (N. Watanabe et al., 2021). (b) The bulk resistivity of the potential supercritical geothermal reservoir at 550°C and 79 MPa (depth of 2.4 km bsl) as afunction of fluid fraction and of NaCl content in the supercritical fluid. The assigned conductivity values of supercritical fluid resistivity are 5.4 and 11.5 for 5 wt%
and 10 wt% NaCl equivalent, respectively (N. Watanabe et al., 2021). Bulk resistivity is calculated using Hashin-Shtrikman upper bound model (HS+; Hashin &Shtrikman, 1962). Solid-phase resistivity is fixed at 105 Ωm (Kariya & Shankland, 1983). The gray zone denotes the resistivity range with a 95% confidence interval forC1 based on F-test (6.5 Ωm < C1 < 35 Ωm).

are useful for inferring the melt fraction in the subsurface (Feucht et al., 2017; Hata et al., 2015; Hill et al., 2009;
Ichiki et al., 2021; Lee et al., 2020; Peacock et al., 2015; Piña-Varas et al., 2018; Samrock et al., 2018). The resistivity of the melt has been well studied in the literature (Gaillard & Marziano, 2005; Guo et al., 2017; Laumonier
et al., 2015; Pommier & Le-Trong, 2011). Here, we assume that the part of C1 with a temperature above 800°C
consists of melt and solid rock and estimate the melt fraction using the obtained resistivity model.
Table 1
Summary of Fluid Fraction Estimation of the Supercritical Geothermal Reservoir
Temperature and pressure conditions
450°C and 64 MPa (depth of 1.8 km bsl)

NaCl content
5 wt%

10 wt%

550°C and 79 MPa (depth of 2.4 km bsl)

5 wt%

10 wt%𝐴𝐴

𝐴𝐴2

Bulk resistivity of the supercritical geothermal reservoir

Fluid fraction

17.6 S/m

6.5 Ωm (lower bound)

1.3%

36.0 S/m

5.4 S/m

11.5 S/m

10 Ωm

0.9%

35 Ωm (upper bound)

0.3%

6.5 Ωm (lower bound)

0.6%

10 Ωm

0.4%

35 Ωm (upper bound)

0.1%

6.5 Ωm (lower bound)

4.2%

10 Ωm

2.8%

35 Ωm (upper bound)

0.8%

6.5 Ωm (lower bound)

2.0%

10 Ωm

1.3%

35 Ωm (upper bound)

0.4%

Notes. We consider two different depths of the supercritical geothermal reservoir. The conductivity of supercritical fluids is calculated using a viscosity-dependent
empirical model by N. Watanabe et al. (2021). Bulk resistivity of the supercritical geothermal reservoir represents the resistivity range of C1 determined by F values
with a 95% confidence interval. The fluid fraction represents an estimated fluid fraction of the supercritical geothermal reservoir using the HS+ model. The resistivityof the solid phase is fixed at 105 Ωm (Kariya & Shankland, 1983).

ISHIZU ET AL.

14 of 21

Journal of Geophysical Research: Solid Earth

10.1029/2021JB022911

Table 2
Conductivity of Dacitic Melt at 900°C and 150 MPa (at a Depth of 5 km bsl) and Andesitic Melt at 1,050°C and 250 MPa (at a Depth of 9 km bsl)
Melt
Dacitic melt

Andesitic melt

Temperature and pressure conditions

Water content

Conductivity of melt

900°C and 150 MPa (at a depth of 5 km bsl)

2 wt%

0.13 S/m

3 wt%

0.23 S/m

4 wt%

0.40 S/m

5 wt%

0.70 S/m

2 wt%

0.65 S/m

3 wt%

1.13 S/m

4 wt%

1.85 S/m

5 wt%

2.94 S/m

1,050°C and 250 MPa (at a depth of 9 km bsl)

Note. We use the conductivity values reported by Laumonier et al. (2015) for dacitic melt and those reported by Guo et al. (2017) for andesitic melt.

A petrologic study found dacitic and andesitic rocks in the Yuzawa geothermal field (Ban et al., 2007). Note thatbasaltic magmas can transform to andesite, dacite, and rhyolite through fractional crystallization (Wilson, 1989).
The dacitic melt has a shallower origin than the andesitic melt (Ban et al., 2007; Tatsumi et al., 2008). We assume
that conductor C1 at a depth of 5 km bsl consists of dacitic melt and solid rock, and use the resistivity value reported by Laumonier et al. (2015) for dacitic melt. Table 2 describes the resistivity values of dacitic melt. Bulk resistivity is calculated using the Hashin-Shtrikman upper bound model (HS+; Hashin & Shtrikman, 1962), which
predicts well-connected melt fractions (Naif et al., 2013). The resistivity of dry granite is reported to be about
1,000 Ωm at a temperature of 900°C–1,050°C (Kariya & Shankland, 1983). Thus, the solid-phase resistivity isfixed at 1,000 Ωm. The bulk resistivity of the dacitic melt and solid rock at 900°C and 150 MPa (at a depth of
5 km bsl) suggests that an 80% melt fraction with 2 wt% H2O is required to explain the 10 Ωm of C1 (Figure 9a).
If we consider the lower bound of C1 (6.5 Ωm), the 100% melt fraction is considered for 2 wt% H2O (Figure 9a).
However, these melt fractions are not reasonable. The water content in the dacitic melt can range up to 5.5 wt%,
which is the water saturation condition (Wallace, 2005). If the dacitic melt is almost water-saturated (5 wt% H2O),

Figure 9. (a) The bulk resistivity of the dacitic melt and solid rock at 900°C and 150 MPa (a depth of 5 km bsl) as a function of melt fraction and water content in the
dacitic melt. The resistivity of the dacitic melt is calculated based on Laumonier et al. (2015). Solid rock resistivity is fixed at 1,000 Ωm (Kariya & Shankland, 1983).
Bulk resistivity is calculated using Hashin-Shtrikman upper bound model (HS+). (b) The bulk resistivity of the andesitic melt and solid rock at 1,050°C and 250 MPa(a depth of 9 km bsl) as a function of melt fraction and water content in the andesitic melt. The resistivity of the andesitic melt is calculated based on Guo et al. (2017).
The gray zones denote the resistivity range with a 95% confidence interval for C1 based on the F-test (6.5 Ωm < C1 < 35 Ωm).

ISHIZU ET AL.

15 of 21

Journal of Geophysical Research: Solid Earth

10.1029/2021JB022911

a 20% melt fraction can explain 10 Ωm (Figure 9a). Even if we consider the lower bound of C1 (6.5 Ωm), a 30%
melt fraction is considered for 5 wt% H2O. Therefore, we consider that water content in the dacitic melt is 5 wt%
H2O. The upper bound of C1 (35 Ωm) requires a 6% melt fraction for 5 wt% H2O. These findings suggest that C1
at a depth of 5 km bsl is a dacitic melt with 5 wt% H2O and a melt fraction of 6%–30%.
The andesitic melt is expected to be located in the deep zones of this field (Ban et al., 2007). The conductor C1 at
a depth of 9 km bsl is assumed to consist of andesitic melt and solid rock. The resistivity of the andesitic melt is
calculated according to Guo et al. (2017). Table 2 describes the resistivity values of andesitic melt. The water content in the andesitic melt can range up to 5.5 wt% for 1,100°C–1,300°C and 200 MPa (Botcharnikov et al., 2006).
Water is enriched in the melt during fractional crystallization, and therefore the dacitic melt should have a higher
water content than the andesitic melt. This suggests that the water content in the andesitic melt is lower than theestimated value of 5 wt% H2O in the dacitic melt. To explain 10 Ωm of C1 at 1,050°C and 250 MPa (at a depthof 9 km bsl), the melt fraction is estimated to be 20% and 8% for 2 wt% and 4 wt% H2O contents, respectively(Figure 9b). The lower bound of C1 (6.5 Ωm) requires 30% and 12% melt fractions for 2 wt% and 4 wt% H2O
contents, respectively. The upper bound of C1 (35 Ωm) requires 6% and 2% melt fractions for 2 wt% and 4 wt%
H2O content, respectively. Hence, our resistivity model suggests that C1 at a depth of 9 km bsl consists of andesitic melt with a melt fraction of 2%–30% and 2–4 wt% H2O in the melt.
5.4. Mechanism of Evolution of a Supercritical Geothermal Reservoir
Our MT data reveal a potential supercritical geothermal reservoir, melt, and a shallow geothermal system in
the Yuzawa geothermal field in NE Japan (Figure 3). Based on our resistivity model, we propose a mechanism
for the evolution of a supercritical geothermal reservoir (Figure 10). The dacitic and andesitic melt below thesupercritical geothermal reservoir may supply magmatic fluids to the supercritical geothermal reservoir (Blundy
et al., 2021; Heinrich, 2005; Sillitoe, 2010). Upwelling supercritical fluids
supplied from the melt are found to become trapped under a less-permeablesilica sealing, and supercritical fluids accumulated below the silica sealing
as a result (Figure 10). Silica sealing separates the hydrostatic and lithostatic regions (Figure 4c). Hence, the supercritical geothermal reservoir below
the silica sealing is under lithostatic pressure, and fluids in the supercritical
geothermal reservoir are interpreted as single-phase supercritical fluids. The
supercritical geothermal reservoir is imaged as a low resistivity anomaly of
C1 (Figure 3). The fluid fraction of the supercritical reservoir is estimated tobe 0.1%–4.2% (Figure 8). Episodic supplies of magmatic fluids from the melt
increase the pressure of the supercritical geothermal reservoir, with high levels of pressure subsequently breaking the silica sealing. Fluids leaking fromthe silica sealing moved to the surface (Figure 10). The fluids are detected as
conductive zones extending from the deep conductor C1 to the near-surface
conductors (Figure 3c). The smectite-rich zones near the surface act as acap layer owing to their low permeability (Revil et al., 2019). The upwelling
fluids that leak from the silica sealing mixes with the meteoric water during
the ascent, and the mixed hydrothermal fluids are trapped below the cap layer. Power plants in operation in the area use hydrothermal fluids (<300°C)
trapped below the impermeable cap of smectite to generate electric energy(New Energy and Industrial Technology Development Organization, 1990).
Since our MT data reveal a potential supercritical geothermal reservoir in thisgeothermal field, power plants in this field potentially may use supercritical
geothermal reservoirs to increase their power generation in the future.

6. Conclusions
Figure 10. (a) West-east cross-section at x = 0.5 km of the inverted resistivity
model. This cross-section is the same as Figure 3c. Symbols are the same as
in Figure 3. (b) Schematic model of a geothermal system inferred from ourresistivity model.

ISHIZU ET AL.

Supercritical geothermal reservoirs are next-generation energy resourcesthat yield higher productivity than those obtained from conventional geothermal reservoirs at temperatures <350°C. Although understanding thefluid fraction and spatial distribution of supercritical geothermal reservoirs
16 of 21

Journal of Geophysical Research: Solid Earth

10.1029/2021JB022911

is necessary for their assessment as next-generation geothermal resources, these characteristics remain poorly
understood. In this study, we applied the MT method to the Yuzawa geothermal field in NE Japan to estimate thefluid fraction and spatial distribution of a potential supercritical geothermal reservoir. Our main findings can besummarized as follows:
1. The MT data reveal a supercritical geothermal reservoir, melt, and shallow geothermal system in the Yuzawa
geothermal field
2. The supercritical geothermal reservoir (>400°C) with a size of 3 km (width) × 5 km (length) is located at
a depth of 2.5–6.0 km below the surface. The fluid fraction of the supercritical reservoir is estimated to be
0.1%–4.2% with salinity of 5–10 wt%
3. Silica sealing may exist above the potential supercritical geothermal reservoir, separating the hydrostatic andlithostatic regions. The supercritical geothermal reservoir is under lithostatic pressure, and fluids in the reservoir exist as single-phase supercritical fluids
4. Dacitic and andesitic melt exist below the supercritical geothermal reservoir. The melt supplies magmatic
fluid to the supercritical geothermal reservoir
5. We develop a mechanism to explain the evolution of a supercritical geothermal reservoir, wherein upwellingsupercritical fluids supplied by the melt are trapped under less permeable silica sealing and accumulated there
6. The supercritical fluid breaking from the silica sealing provides upward-moving fluids to the surface

Data Availability Statement
The MT data used in this study (Ogawa et al., 2011–2020) were archived at the Data Management Center of
the Incorporated Research Institutions for Seismology SPUD EMTF database (http://ds.iris.edu/spud/emtf). The
following two formats are available for all MT data: electrical data interchange (EDI) format and electromagnetictransfer function extensible markup language (EMTF XML) format. The EDI format is a standard MT data format constructed by the Society of Exploration Geophysicists (Wight, 1988) and the description of EDI format
is provided at the following website: https://www.seg.org/Portals/0/SEG/News%20and%20Resources/Technical%20Standards/seg_mt_emap_1987.pdf. The EMTF XML format is a new, self-describing, searchable, andextensible way to store MT data (Kelbert, 2020). The open-source Python package MTpy can be used to analyze
the MT data (Kirkby et al., 2019; Krieger & Peacock, 2014). The quartz solubility, pressure, and temperature data
for Figure 6 are available on the Zenodo open-access repository operated by the CERN: https://doi.org/10.5281/
zenodo.5952138.

Acknowledgments
This work was supported by the Japan
Society for the Promotion of Science
KAKENHI (20K22326 and 21109003).
One of the authors (K. Ishizu) would liketo acknowledge the support from the Hiki
Foundation, Tokyo Institute of Technology. The authors thank W. Siripunvaraporn
for allowing us to use WSINV3DMT, andT. Okada for providing seismic data andvelocity models. The authors are grateful
to N. Watanabe for helpful discussions
on the resistivity of supercritical fluids,
Y. Kawada for meaningful discussions
on supercritical fluids, R. Yamada for his
help with the geological interpretationof the resistivity model and A. Kelbert
for her help in archiving our MT data.
The authors would like to thank two
anonymous reviewers, the associate editor
M. Moorkamp and the editor D. Schmitt
for their detailed and helpful commentsthat led to significant improvements inthis article.

ISHIZU ET AL.

References
Afanasyev, A., Blundy, J., Melnik, O., & Sparks, S. (2018). Formation of magmatic brine lenses via focussed fluid flow beneath volcanoes. Earthand Planetary Science Letters, 486, 119–128. https://doi.org/10.1016/j.epsl.2018.01.013
Aizawa, K., Koyama, T., Hase, H., Uyeshima, M., Kanda, W., Utsugi, M., et al. (2014). Three-dimensional resistivity structure and magma
plumbing system of the Kirishima volcanoes as inferred from broadband magnetotelluric data. Journal of Geophysical Research: Solid Earth,119(1), 198–215. https://doi.org/10.1002/2013JB010682
Akinfiev, N. N., & Diamond, L. W. (2009). A simple predictive model of quartz solubility in water-salt-CO2 systems at temperatures up to
1,000°C and pressures up to 1,000 MPa. Geochimica et Cosmochimica Acta, 73(6), 1597–1608. https://doi.org/10.1016/j.gca.2008.12.011
Árnason, K., Eysteinsson, H., & Hersir, G. P. (2010). Joint 1-D inversion of TEM and MT data and 3-D inversion of MT data in the Hengill area,
SW Iceland. Geothermics, 39(1), 13–34. https://doi.org/10.1016/j.geothermics.2010.01.002
Araya Vargas, J., Meqbel, N. M., Ritter, O., Brasse, H., Weckmann, U., Yáñez, G., & Godoy, B. (2019). Fluid distribution in the Central
Andes subduction zone imaged with magnetotellurics. Journal of Geophysical Research: Solid Earth, 124(4), 4017–4034. https://doi.
org/10.1029/2018JB016933
Bakker, R. J. (2018). AqSo_NaCl: Computer program to calculate p-T-V-x properties in the H2O-NaCl fluid system applied to fluid inclusion
research and pore fluid calculation. Computers & Geosciences, 115, 122–133. https://doi.org/10.1016/j.cageo.2018.03.003
Bali, E., Aradi, L. E., Zierenberg, R., Diamond, L. W., Pettke, T., Szabó, Á., et al. (2020). Geothermal energy and ore-forming potential of 600°C
mid-ocean-ridge hydrothermal fluids. Geology, 48(12), 1221–1225. https://doi.org/10.1130/G47791.1
Ban, M., Hirotani, S., Wako, A., Suga, T., Iai, Y., Kagashima, S., et al. (2007). Origin of felsic magmas in a large-caldera-related stratovolcano
in the central part of NE Japan—Petrogenesis of the Takamatsu volcano. Journal of Volcanology and Geothermal Research, 167(1), 100–118.
https://doi.org/10.1016/j.jvolgeores.2007.05.008
Bannard, J. E. (1975). Effect of density on the electrical conductance of aqueous sodium chloride solutions. Journal of Applied Electrochemistry,5(1), 43–53. https://doi.org/10.1007/BF00625958
Becken, M., Ritter, O., Bedrosian, P. A., & Weckmann, U. (2011). Correlation between deep fluids, tremor, and creep along the central San Andreas fault. Nature, 480(7375), 87–90. https://doi.org/10.1038/nature10609
Bedrosian, P. A., Peacock, J. R., Bowles-Martinez, E., Schultz, A., & Hill, G. J. (2018). Crustal inheritance and a top-down control on arc magmatism at Mount St Helens. Nature Geoscience, 11(11), 865–870. https://doi.org/10.1038/s41561-018-0217-2

17 of 21

Journal of Geophysical Research: Solid Earth

10.1029/2021JB022911

Bertrand, E. A., Caldwell, T. G., Hill, G. J., Wallin, E. L., Bennie, S. L., Cozens, N., et al. (2012). Magnetotelluric imaging of upper-crustal convection plumes beneath the Taupo Volcanic Zone, New Zealand. Geophysical Research Letters, 39(2). https://doi.org/10.1029/2011GL050177
Blundy, J., Afanasyev, A., Tattitch, B., Sparks, S., Melnik, O., Utkin, I., & Rust, A. (2021). The economic potential of metalliferous sub-volcanicbrines. Royal Society Open Science, 8(6), 202192. https://doi.org/10.1098/rsos.202192
Botcharnikov, R. E., Behrens, H., & Holtz, F. (2006). Solubility and speciation of C-O-H fluids in andesitic melt at T = 11,00°C –1,300°C
and P = 200 and 500 MPa. Physics, Chemistry, and Rheology of Silicate Melts and Glasses, 229(1), 125–143. https://doi.org/10.1016/j.
chemgeo.2006.01.016
Bowles-Martinez, E., & Schultz, A. (2020). Composition of magma and characteristics of the hydrothermal system of Newberry volcano, Oregon,from Magnetotellurics. Geochemistry, Geophysics, Geosystems, 21(3), e2019GC008831. https://doi.org/10.1029/2019GC008831
Caldwell, T. G., Bibby, H. M., & Brown, C. (2004). The magnetotelluric phase tensor. Geophysical Journal International, 158(2), 457–469.
https://doi.org/10.1111/j.1365-246X.2004.02281.x
Chave, A. D., & Jones, A. G. (2012). Introduction to the magnetotelluric method. In The magnetotelluric method: Theory and practice (pp. 1–18).
Cambridge University Press. https://doi.org/10.1017/CBO9781139020138.002
Cherkose, B. A., & Saibi, H. (2021). Investigation of the Ayrobera geothermal field using 3-D magnetotelluric data inversion, Afar depression,
NE Ethiopia. Geothermics, 94, 102114. https://doi.org/10.1016/j.geothermics.2021.102114
Comeau, M. J., Becken, M., Connolly, J. A. D., Grayver, A. V., & Kuvshinov, A. V. (2020). Compaction-driven fluid localization as an explanation for lower crustal electrical conductors in an intracontinental setting. Geophysical Research Letters, 47(19), e2020GL088455. https://doi.
org/10.1029/2020GL088455
Constable, S., Parker, R. L., & Constable, C. G. (1987). Occam’s inversion: A practical algorithm for generating smooth models from electromagnetic sounding data. Geophysics, 52(3), 289–300. https://doi.org/10.1190/1.1442303
Cordell, D., Unsworth, M. J., Lee, B., Díaz, D., Bennington, N. L., & Thurber, C. H. (2020). Integrating magnetotelluric and seismic images ofsilicic magma systems: A case study from the Laguna del Maule Volcanic Field, central Chile. Journal of Geophysical Research: Solid Earth,125(11), e2020JB020459.
Di Paolo, F., Ledo, J., Ślęzak, K., Martínez van Dorth, D., Cabrera-Pérez, I., & Pérez, N. M. (2020). La Palma Island (Spain) geothermal system
revealed by 3-D magnetotelluric data inversion. Scientific Reports, 10(1), 18181. https://doi.org/10.1038/s41598-020-75001-z
Doi, N., Kato, O., Ikeuchi, K., Komatsu, R., Miyazaki, S., Akaku, K., & Uchida, T. (1998). Genesis of the plutonic-hydrothermal system aroundquaternary granite in the Kakkonda geothermal system, Japan. Geothermics, 27(5), 663–690. https://doi.org/10.1016/S0375-6505(98)00039-X
Driesner, T., & Heinrich, C. A. (2007). The system H2O-NaCl. Part I: Correlation formulae for phase relations in temperature-pressure-composition space from 0°C to 1,000°C, 0 to 5,000 bar, and 0 to 1 XNaCl. Geochimica et Cosmochimica Acta, 71(20), 4880–4901. https://doi.
org/10.1016/j.gca.2006.01.033
Elders, W. A., Friðleifsson, G. Ó., & Albertsson, A. (2014). Drilling into magma and the implications of the Iceland Deep Drilling Project (IDDP)
for high-temperature geothermal systems worldwide. Geothermics, 49, 111–118. https://doi.org/10.1016/j.geothermics.2013.05.001
Farquharson, C. G. (2008). Constructing piecewise-constant models in multidimensional minimum-structure inversions. Geophysics, 73(1), K1–
K9. https://doi.org/10.1190/1.2816650
Feucht, D. W., Sheehan, A. F., & Bedrosian, P. A. (2017). Magnetotelluric imaging of lower crustal melt and lithospheric hydration in the
Rocky Mountain Front transition zone, Colorado, USA. Journal of Geophysical Research: Solid Earth, 122(12), 9489–9510. https://doi.
org/10.1002/2017JB014474
Fournier, R. O. (1999). Hydrothermal processes related to movement of fluid from plastic into brittle rock in the magmatic-epithermal environment. Economic Geology, 94(8), 1193–1211. https://doi.org/10.2113/gsecongeo.94.8.1193
Friðleifsson, G. Ó., Elders, W. A., Zierenberg, R. A., Fowler, A. P. G., Weisenberger, T. B., Mesfin, K. G., et al. (2020). The Iceland Deep Drilling
Project at Reykjanes: Drilling into the root zone of a black smoker analog. Journal of Volcanology and Geothermal Research, 391, 106435.
https://doi.org/10.1016/j.jvolgeores.2018.08.013
Gaillard, F., & Marziano, G. I. (2005). Electrical conductivity of magma in the course of crystallization controlled by their residual liquid composition. Journal of Geophysical Research: Solid Earth, 110(B6). https://doi.org/10.1029/2004JB003282
Gresse, M., Uyeshima, M., Koyama, T., Hase, H., Aizawa, K., Yamaya, Y., et al. (2021). Hydrothermal and magmatic system of a volcanic island
inferred from magnetotellurics, seismicity, self-potential, and thermal image: An example of Miyakejima (Japan). Journal of GeophysicalResearch: Solid Earth, 126(6), e2021JB022034. https://doi.org/10.1029/2021JB022034
Guo, X., Li, B., Ni, H., & Mao, Z. (2017). Electrical conductivity of hydrous andesitic melts pertinent to subduction zones. Journal of Geophysical Research: Solid Earth, 122(3), 1777–1788. https://doi.org/10.1002/2016JB013524
Hasegawa, A., Zhao, D., Hori, S., Yamamoto, A., & Horiuchi, S. (1991). Deep structure of the northeastern Japan arc and its relationship toseismic and volcanic activity. Nature, 352(6337), 683–689. https://doi.org/10.1038/352683a0
Hashin, Z., & Shtrikman, S. (1962). A variational approach to the theory of the effective magnetic permeability of multiphase materials. Journalof Applied Physics, 33(10), 3125–3131. https://doi.org/10.1063/1.1728579
Hata, M., Oshiman, N., Yoshimura, R., Tanaka, Y., & Uyeshima, M. (2015). Three-dimensional electromagnetic imaging of upwelling fluids
in the Kyushu subduction zone, Japan. Journal of Geophysical Research: Solid Earth, 120(1), 1–17. https://doi.org/10.1002/2014JB011336
Heinrich, C. A. (2005). The physical and chemical evolution of low-salinity magmatic fluids at the porphyry to epithermal transition: A thermodynamic study. Mineralium Deposita, 39(8), 864–889. https://doi.org/10.1007/s00126-004-0461-9
Heinson, G., Didana, Y., Soeffky, P., Thiel, S., & Wise, T. (2018). The crustal geophysical signature of a world-class magmatic mineral system.
Scientific Reports, 8(1), 10608. https://doi.org/10.1038/s41598-018-29016-2
Heise, W., Caldwell, T. G., Bibby, H. M., & Bannister, S. C. (2008). Three-dimensional modeling of magnetotelluric data from the Rotokawa geothermal field, Taupo Volcanic Zone, New Zealand. Geophysical Journal International, 173(2), 740–750. https://doi.
org/10.1111/j.1365-246X.2008.03737.x
Hill, G. J., Caldwell, T. G., Heise, W., Chertkoff, D. G., Bibby, H. M., Burgess, M. K., et al. (2009). Distribution of melt beneath Mount St Helens
and Mount Adams inferred from magnetotelluric data. Nature Geoscience, 2(11), 785–789. https://doi.org/10.1038/ngeo661
Horiguchi, K., Ueki, S., Sano, Y., Takahata, N., Hasegawa, A., & Igarashi, G. (2010). Geographical distribution of helium isotope ratios in northeastern Japan. Island Arc, 19(1), 60–70. https://doi.org/10.1111/j.1440-1738.2009.00703.x
Hyndman, R. D., & Shearer, P. M. (1989). Water in the lower continental crust: Modeling magnetotelluric and seismic reflection results. Geophysical Journal International, 98(2), 343–365. https://doi.org/10.1111/j.1365-246X.1989.tb03357.x
Ichihara, H., Mogi, T., Tanimoto, K., Yamaya, Y., Hashimoto, T., Uyeshima, M., & Ogawa, Y. (2016). Crustal structure and fluid distribution
beneath the southern part of the Hidaka collision zone revealed by 3-D electrical resistivity modeling. Geochemistry, Geophysics, Geosystems,
17(4), 1480–1491. https://doi.org/10.1002/2015GC006222

ISHIZU ET AL.

18 of 21

Journal of Geophysical Research: Solid Earth

10.1029/2021JB022911

Ichiki, M., Kaida, T., Nakayama, T., Miura, S., Yamamoto, M., Morita, Y., & Uyeshima, M. (2021). Magma reservoir beneath Azumayama Volcano, NE Japan, as inferred from a three-dimensional electrical resistivity model explored by means of magnetotelluric method. Earth, Planets,
and Space, 73(1), 150. https://doi.org/10.1186/s40623-021-01451-y
Ikeuchi, K., Doi, N., Sakagawa, Y., Kamenosono, H., & Uchida, T. (1998). High-temperature measurements in well WD-1A and the thermal
structure of the Kakkonda geothermal system, Japan. Geothermics, 27(5), 591–607. https://doi.org/10.1016/S0375-6505(98)00035-2
Ingebritsen, S. E., & Manning, C. E. (2010). Permeability of the continental crust: Dynamic variations inferred from seismicity and metamorphism. Geofluids, 10(1–2), 193–205. https://doi.org/10.1111/j.1468-8123.2010.00278.x
Ingham, M. R., Bibby, H. M., Heise, W., Jones, K. A., Cairns, P., Dravitzki, S., et al. (2009). A magnetotelluric study of Mount Ruapehu volcano,
New Zealand. Geophysical Journal International, 179(2), 887–904. https://doi.org/10.1111/j.1365-246X.2009.04317.x
Ishizu, K., Ogawa, Y., Mogi, T., Yamaya, Y., & Uchida, T. (2021). Ability of the magnetotelluric method to image a deep conductor: Explorationof a supercritical geothermal system. Geothermics, 96, 102205. https://doi.org/10.1016/j.geothermics.2021.102205
Iwamori, H. (1998). Transportation of H2O and melting in subduction zones. Earth and Planetary Science Letters, 160(1), 65–80. https://doi.
org/10.1016/S0012-821X(98)00080-6
Kanda, W., Utsugi, M., Takakura, S., & Inoue, H. (2019). Hydrothermal system of the active crater of Aso volcano (Japan) inferred from athree-dimensional resistivity structure model. Earth, Planets, and Space, 71(1), 37. https://doi.org/10.1186/s40623-019-1017-7
Kariya, K. A., & Shankland, T. J. (1983). Electrical conductivity of dry lower crustal rocks. Geophysics, 48(1), 52–61. https://doi.
org/10.1190/1.1441407
Kawamoto, T., Yoshikawa, M., Kumagai, Y., Mirabueno, M. H. T., Okuno, M., & Kobayashi, T. (2013). Mantle wedge infiltrated with saline fluids from dehydration and decarbonation of subducting slab. Proceedings of the National Academy of Sciences of the United States of America,
110(24), 9663–9668. https://doi.org/10.1073/pnas.1302040110
Kelbert, A. (2020). EMTF XML: New data interchange format and conversion tools for electromagnetic transfer functions. Geophysics, 85(1),F1–F17. https://doi.org/10.1190/geo2018-0679.1
Kelbert, A., Meqbel, N., Egbert, G. D., & Tandon, K. (2014). ModEM: A modular system for inversion of electromagnetic geophysical data.
Computers & Geosciences, 66, 40–53. https://doi.org/10.1016/j.cageo.2014.01.010
Kirkby, A. L., Zhang, F., Peacock, J., Hassan, R., & Duan, J. (2019). The MTPy software package for magnetotelluric data analysis and visualisation. Journal of Open Source Software, 4(37), 1358. https://doi.org/10.21105/joss.01358
Kita, I., Nagao, K., Nakamura, Y., & Taguchi, S. (1992). Information on geothermal system obtained by chemical and isotropic characteristic ofsoil and fumarolic gases from the Doroyu-Kawarage geothermal field, Akita, Japan. Journal of the Geothermal Research Society of Japan,
14(2), 115–128. (in Japanese). https://doi.org/10.11367/grsj1979.14.115
Krieger, L., & Peacock, J. R. (2014). MTpy: A Python toolbox for magnetotellurics. Computers & Geosciences, 72, 167–175. https://doi.
org/10.1016/j.cageo.2014.07.013
Kummerow, J., Raab, S., Schuessler, J. A., & Meyer, R. (2020). Non-reactive and reactive experiments to determine the electrical conductivities
of aqueous geothermal solutions up to supercritical conditions. Journal of Volcanology and Geothermal Research, 391, 106388. https://doi.
org/10.1016/j.jvolgeores.2018.05.014
Kurosawa, M., Ishii, S., & Sasa, K. (2010). Trace-element compositions of single fluid inclusions in the Kofu granite, Japan: Implications forcompositions of granite-derived fluids. Island Arc, 19(1), 40–59. https://doi.org/10.1111/j.1440-1738.2009.00702.x
Laumonier, M., Gaillard, F., & Sifre, D. (2015). The effect of pressure and water concentration on the electrical conductivity of dacitic melts:
Implication for magnetotelluric imaging in subduction areas. Chemical Geology, 418, 66–76. https://doi.org/10.1016/j.chemgeo.2014.09.019
Ledo, J., García-Merino, M., Larnier, H., Slezak, K., Piña-Varas, P., Marcuello, A., et al. (2021). 3-D electrical resistivity of Gran Canaria islandusing magnetotelluric data. Geothermics, 89, 101945. https://doi.org/10.1016/j.geothermics.2020.101945
Lee, B., Unsworth, M., Árnason, K., & Cordell, D. (2020). Imaging the magmatic system beneath the Krafla geothermal field, Iceland: A new
3-D electrical resistivity model from inversion of magnetotelluric data. Geophysical Journal International, 220(1), 541–567. https://doi.
org/10.1093/gji/ggz427
Le Pape, F., Jones, A. G., Unsworth, M. J., Vozar, J., Wei, W., Jin, S., et al. (2015). Constraints on the evolution of crustal flow beneath Northern
Tibet. Geochemistry, Geophysics, Geosystems, 16(12), 4237–4260. https://doi.org/10.1002/2015GC005828
Lowell, R. P., Van Cappellen, P., & Germanovich, L. N. (1993). Silica precipitation in fractures and the evolution of permeability in hydrothermal
upflow zones. Science, 260(5105), 192–194. https://doi.org/10.1126/science.260.5105.192
Manning, C. E. (1994). The solubility of quartz in H2O in the lower crust and upper mantle. Geochimica et Cosmochimica Acta, 58(22), 4831–
4839. https://doi.org/10.1016/0016-7037(94)90214-3
Milsch, H., Kristinsdóttir, L. H., Spangenberg, E., Bruhn, D., & Flóvenz, Ó. G. (2010). Effect of the water-steam phase transition on the electricalconductivity of porous rocks. Geothermics, 39(1), 106–114. https://doi.org/10.1016/j.geothermics.2009.09.001
Mitsuhata, Y., Ogawa, Y., Mishina, M., Kono, T., Yokokura, T., & Uchida, T. (2001). Electromagnetic heterogeneity of the seismogenic region of 1962 M6.5 Northern Miyagi Earthquake, northeastern Japan. Geophysical Research Letters, 28(23), 4371–4374. https://doi.
org/10.1029/2001GL013079
Monecke, T., Monecke, J., Reynolds, T. J., Tsuruoka, S., Bennett, M. M., Skewes, W. B., & Palin, R. M. (2018). Quartz solubility in the H2O-NaCl system: A framework for understanding vein formation in porphyry copper deposits. Economic Geology, 113(5), 1007–1046. https://doi.
org/10.5382/econgeo.2018.4580
Moorkamp, M., Fishwick, S., Walker, R. J., & Jones, A. G. (2019). Geophysical evidence for crustal and mantle weak zones controlling intra-plate seismicity—The 2017 Botswana earthquake sequence. Earth and Planetary Science Letters, 506, 175–183.
https://doi.org/10.1016/j.epsl.2018.10.048
Muraoka, H., Uchida, T., Sasada, M., Yagi, M., Akaku, K., Sasaki, M., et al. (1998). Deep geothermal resources survey program: Igneous, metamorphic and hydrothermal processes in a well encountering 500°C at 3,729 m depth, Kakkonda, Japan. Geothermics, 27(5), 507–534. https://doi.org/10.1016/S0375-6505(98)00031-5
Naif, S., Key, K., Constable, S., & Evans, R. L. (2013). Melt-rich channel observed at the lithosphere-asthenosphere boundary. Nature, 495(7441),
356–359. https://doi.org/10.1038/nature11939
Nakajima, J., Matsuzawa, T., Hasegawa, A., & Zhao, D. (2001). Seismic imaging of arc magma and fluids under the central part of northeasternJapan. Tectonophysics, 341(1), 1–17. https://doi.org/10.1016/S0040-1951(01)00181-0
New Energy and Industrial Technology Development Organization. (1990). Final report on survey to identify and promote geothermal development at Minase field (p. 1121). (in Japanese). Retrieved from https://geothermal.jogmec.go.jp/report/nedo/file/30.pdf
Newman, G. A. (2014). A review of high-performance computational strategies for modeling and imaging of electromagnetic induction data.
Surveys in Geophysics, 35(1), 85–100. https://doi.org/10.1007/s10712-013-9260-0

ISHIZU ET AL.

19 of 21

Journal of Geophysical Research: Solid Earth

10.1029/2021JB022911

Nono, F., Gibert, B., Parat, F., Loggia, D., Cichy, S. B., & Violay, M. (2020). Electrical conductivity of Icelandic deep geothermal reservoirs up
to supercritical conditions: Insight from laboratory experiments. Journal of Volcanology and Geothermal Research, 391, 106364. https://doi.
org/10.1016/j.jvolgeores.2018.04.021
Nunohara, K., Okano, H., Yamada, R., Hirano, N., & Tsuchiya, N. (2021). Geothermal potentiality in southern part of the Sanzugawa caldera, Akita prefecture, northeast Japan. Journal of the Geothermal Research Society of Japan, 24(4), 313–314. (in Japanese). https://doi.org/10.11367/
grsj.43.65
Nurdiana, A., Okamoto, A., Yoshida, K., Uno, M., Nagaya, T., & Tsuchiya, N. (2021). Multi-stage infiltration of Na- and K-rich fluids from pegmatites at mid-crustal depths as revealed by feldspar replacement textures. Lithos, 388–389, 106096. https://doi.org/10.1016/j.lithos.2021.106096
Ogawa, Y., Ichiki, M., Kanda, W., Mishina, M., & Asamori, K. (2014). Three-dimensional magnetotelluric imaging of crustal fluids and seismicity around Naruko volcano, NE Japan. Earth, Planets, and Space, 66(1), 158. https://doi.org/10.1186/s40623-014-0158-y
Ogawa, Y., Mishina, M., Goto, T., Satoh, H., Oshiman, N., Kasaya, T., et al. (2001). Magnetotelluric imaging of fluids in intraplate earthquake
zones, NE Japan Back Arc. Geophysical Research Letters, 28(19), 3741–3744. https://doi.org/10.1029/2001GL013269
Ogawa, Y., Nunohara, K., Tsuchiya, N., Ichiki, M., Hase, H., Kanda, W., et al. (2011–2020). Magnetotelluric transfer functions in the Yuzawa
geothermal field. NE Japan. https://doi.org/10.17611/DP/EMTF/YUZAWASGR
Ogawa, Y., & Uchida, T. (1996). A two-dimensional magnetotelluric inversion assuming Gaussian static shift. Geophysical Journal International,
126(1), 69–76. https://doi.org/10.1111/j.1365-246X.1996.tb05267.x
Okada, T., Matsuzawa, T., Nakajima, J., Uchida, N., Yamamoto, M., Hori, S., et al. (2014). Seismic velocity structure in and around the
Naruko volcano, NE Japan, and its implications for volcanic and seismic activities. Earth, Planets, and Space, 66(1), 114. https://doi.
org/10.1186/1880-5981-66-114
Okamoto, K., Asanuma, H., Ishibashi, T., Yamaya, Y., Saishu, H., Yanagisawa, N., et al. (2019). Geological and engineering features of developing ultra-high-temperature geothermal systems in the world. Geothermics, 82, 267–281. https://doi.org/10.1016/j.geothermics.2019.07.002
Parisio, F., Vilarrasa, V., Wang, W., Kolditz, O., & Nagel, T. (2019). The risks of long-term re-injection in supercritical geothermal systems.
Nature Communications, 10(1), 4391. https://doi.org/10.1038/s41467-019-12146-0
Pastor-Galán, D., Spencer, C. J., Furukawa, T., & Tsujimori, T. (2021). Evidence for crustal removal, tectonic erosion, and flare-ups from theJapanese evolving forearc sediment provenance. Earth and Planetary Science Letters, 564, 116893. https://doi.org/10.1016/j.epsl.2021.116893
Peacock, J. R., Earney, T. E., Mangan, M. T., Schermerhorn, W. D., Glen, J. M., Walters, M., & Hartline, C. (2020). Geophysical characterization of the Northwest Geysers geothermal field, California. Journal of Volcanology and Geothermal Research, 399, 106882. https://doi.
org/10.1016/j.jvolgeores.2020.106882
Peacock, J. R., Mangan, M. T., McPhee, D., & Ponce, D. A. (2015). Imaging the magmatic system of Mono Basin, California, with magnetotellurics in three dimensions. Journal of Geophysical Research: Solid Earth, 120(11), 7273–7289. https://doi.org/10.1002/2015JB012071
Pellerin, L., Johnston, J. M., & Hohmann, G. W. (1992). Evaluation of electromagnetic methods in geothermal exploration. In SEG Technical
Program Expanded Abstracts 1992 (Vol. 1, pp. 405–408). Society of Exploration Geophysicists. https://doi.org/10.1190/1.1822102
Piana Agostinetti, N., Licciardi, A., Piccinini, D., Mazzarini, F., Musumeci, G., Saccorotti, G., & Chiarabba, C. (2017). Discovering geothermal
supercritical fluids: A new frontier for seismic exploration. Scientific Reports, 7(1), 14592. https://doi.org/10.1038/s41598-017-15118-w
Piña-Varas, P., Ledo, J., Queralt, P., Marcuello, A., & Perez, N. (2018). On the detectability of Teide volcano magma chambers (Tenerife, CanaryIslands) with magnetotelluric data. Earth, Planets, and Space, 70(1), 14. https://doi.org/10.1186/s40623-018-0783-y
Pommier, A., & Le-Trong, E. (2011). “SIGMELTS”: A web portal for electrical conductivity calculations in geosciences. Computers & Geosciences, 37(9), 1450–1459. https://doi.org/10.1016/j.cageo.2011.01.002
Pytte, A. M., & Reynolds, R. C. (1989). The thermal transformation of smectite to illite. In N. D. Naeser, & T. H. McCulloh (Eds.), Thermal
history of sedimentary basins (pp. 133–140). Springer New York. https://doi.org/10.1007/978-1-4612-3492-0_8
Quist, A. S., & Marshall, W. L. (1968). Electrical conductances of aqueous sodium chloride solutions from 0° to 800° and at pressures to 4,000
bars. The Journal of Physical Chemistry, 72(2), 684–703. https://doi.org/10.1021/j100848a050
Reinsch, T., Dobson, P., Asanuma, H., Huenges, E., Poletto, F., & Sanjuan, B. (2017). Utilizing supercritical geothermal systems: A review of past
ventures and ongoing research activities. Geothermal Energy, 5(1), 16. https://doi.org/10.1186/s40517-017-0075-y
Revil, A., Qi, Y., Ghorbani, A., Coperey, A., Ahmed, A. S., Finizola, A., & Ricci, T. (2019). Induced polarization of volcanic rocks. 3. Imaging
clay cap properties in geothermal fields. Geophysical Journal International, 218(2), 1398–1427. https://doi.org/10.1093/gji/ggz207
Richards, J. P. (2011). Magmatic to hydrothermal metal fluxes in convergent and collided margins. Ore Geology Reviews, 40(1), 1–26. https://doi.org/10.1016/j.oregeorev.2011.05.006
Saishu, H., Okamoto, A., & Tsuchiya, N. (2014). The significance of silica precipitation on the formation of the permeable-impermeable boundary within Earth’s crust. Terra Nova, 26(4), 253–259. https://doi.org/10.1111/ter.12093
Sakuma, H., & Ichiki, M. (2016). Electrical conductivity of NaCl-H2O fluid in the crust. Journal of Geophysical Research: Solid Earth, 121(2),577–594. https://doi.org/10.1002/2015JB012219
Samrock, F., Grayver, A. V., Eysteinsson, H., & Saar, M. O. (2018). Magnetotelluric image of transcrustal magmatic system beneath the Tulu
Moye geothermal prospect in the Ethiopian Rift. Geophysical Research Letters, 45(23), 12847–12855. https://doi.org/10.1029/2018GL080333
Scholz, C. H. (2019). The mechanics of earthquakes and faulting. The mechanics of earthquakes and faulting (3rd ed.). Cambridge University
Press. https://doi.org/10.1017/9781316681473
Scott, S., Driesner, T., & Weis, P. (2015). Geologic controls on supercritical geothermal resources above magmatic intrusions. Nature Communications, 6(1), 7837. https://doi.org/10.1038/ncomms8837
Sibson, R. H. (2020). Preparation zones for large crustal earthquakes consequent on fault-valve action. Earth, Planets, and Space, 72(1), 31.
https://doi.org/10.1186/s40623-020-01153-x
Sillitoe, R. H. (2010). Porphyry copper systems. Economic Geology, 105(1), 3–41. https://doi.org/10.2113/gsecongeo.105.1.3
Sinmyo, R., & Keppler, H. (2016). Electrical conductivity of NaCl-bearing aqueous fluids to 600°C and 1 GPa. Contributions to Mineralogy andPetrology, 172(1), 4. https://doi.org/10.1007/s00410-016-1323-z
Siripunvaraporn, W., & Egbert, G. (2009). WSINV3DMT: Vertical magnetic field transfer function inversion and parallel implementation. Physics of the Earth and Planetary Interiors, 173(3), 317–329. https://doi.org/10.1016/j.pepi.2009.01.013
Siripunvaraporn, W., Egbert, G., Lenbury, Y., & Uyeshima, M. (2005). Three-dimensional magnetotelluric inversion: Data-space method. Physics
of the Earth and Planetary Interiors, 150(1–3), 3–14. https://doi.org/10.1016/j.pepi.2004.08.023
Stimac, J., Wilmarth, M., Mandeno, P. E., Dobson, P., & Winick, J. (2017). Review of exploitable supercritical geothermal resources to 5 km
at Geysers-Clear Lake, Salton Sea, and Coso. GRC Transactions, 41, 806–835. Retrieved from https://publications.mygeoenergynow.org/
grc/1033767.pdf
Takeno, N. (2000). Thermal and geochemical structure of the Uenotai geothermal system, Japan. Geothermics, 29(2), 257–277. https://doi.
org/10.1016/S0375-6505(99)00062-0

ISHIZU ET AL.

20 of 21

Journal of Geophysical Research: Solid Earth

10.1029/2021JB022911

Tamanyu, S., Fujiwara, S., Ishikawa, J., & Jingu, H. (1998). Fracture system related to geothermal reservoir based on core samples of slim
holes. Example from the Uenotai geothermal field, northern Honshu, Japan. Geothermics, 27(2), 143–166. https://doi.org/10.1016/
S0375-6505(97)10012-8
Tamura, Y., Tatsumi, Y., Zhao, D., Kido, Y., & Shukuno, H. (2002). Hot fingers in the mantle wedge: New insights into magma genesis in subduction zones. Earth and Planetary Science Letters, 197(1), 105–116. https://doi.org/10.1016/S0012-821X(02)00465-X
Tatsumi, Y. (1989). Migration of fluid phases and genesis of basalt magmas in subduction zones. Journal of Geophysical Research: Solid Earth,94(B4), 4697–4707. https://doi.org/10.1029/JB094iB04p04697
Tatsumi, Y., Takahashi, T., Hirahara, Y., Chang, Q., Miyazaki, T., Kimura, J.-I., et al. (2008). New insights into andesite genesis: The role ofmantle-derived calc-alkalic and crust-derived tholeiitic melts in magma differentiation beneath Zao volcano, NE Japan. Journal of Petrology,49(11), 1971–2008. https://doi.org/10.1093/petrology/egn055
Tseng, K. H., Ogawa, Y., Nurhasan Tank, S. B., Ujihara, N., Honkura, Y., Honkura, Y., et al. (2020). Anatomy of active volcanic edifice at theKusatsu-Shirane volcano, Japan, by magnetotellurics: Hydrothermal implications for volcanic unrests. Earth, Planets, and Space, 72(1), 161.
https://doi.org/10.1186/s40623-020-01283-2
Tsuchiya, N., & Hirano, N. (2007). Chemical reaction diversity of geofluids revealed by hydrothermal experiments under sub- and supercriticalstates. Island Arc, 16(1), 6–15. https://doi.org/10.1111/j.1440-1738.2007.00554.x
Tsuchiya, N., Yamada, R., & Uno, M. (2016). Supercritical geothermal reservoir revealed by a granite-porphyry system. Geothermics, 63,
182–194. https://doi.org/10.1016/j.geothermics.2015.12.011
Tuttle, O. F., & Bowen, N. L. (1958). Origin of granite in the light of experimental studies in the system NaAlSi3O8-KAlSi3O8-SiO2-H2O. In O. F.
Tuttle, & N. L. Bowen (Eds.), GSA Memoirs (Vol. 74, p. 146). Geological Society of America. https://doi.org/10.1130/MEM74-p1
Umeda, K., Hayashi, S., & Ban, M. (1999). K-Ar ages of Zarumori, Takamatsu, Funagata, and Sankichi-Hayama volcanoes, NE Japan. Bulletinof the Volcanological Society of Japan, 44(4), 217–222. (in Japanese). https://doi.org/10.18940/kazan.44.4_217
Unsworth, M. J., Jones, A. G., Wei, W., Marquis, G., Gokarn, S. G., Spratt, J. E., & Spratt, J. E. (2005). Crustal rheology of the Himalaya andSouthern Tibet inferred from magnetotelluric data. Nature, 438(7064), 78–81. https://doi.org/10.1038/nature04154
Ussher, G., Harvey, C., Johnstone, R., & Anderson, E. (2000). Understanding the resistivities observed in geothermal systems. In Proceedings
World Geothermal Congress (pp. 1915–1920). Kyushu. Retrieved from https://www.geothermal-energy.org/pdf/IGAstandard/WGC/2000/
R0279.PDF
Wallace, P. J. (2005). Volatiles in subduction zone magmas: Concentrations and fluxes based on melt inclusion and volcanic gas data. Journal ofVolcanology and Geothermal Research, 140(1), 217–240. https://doi.org/10.1016/j.jvolgeores.2004.07.023
Wannamaker, P. E., Caldwell, T. G., Jiracek, G. R., Maris, V., Hill, G. J., Ogawa, Y., et al. (2009). Fluid and deformation regime of an advancing
subduction system at Marlborough, New Zealand. Nature, 460(7256), 733–736. https://doi.org/10.1038/nature08204
Watanabe, N., Numakura, T., Sakaguchi, K., Saishu, H., Okamoto, A., Ingebritsen, S. E., & Tsuchiya, N. (2017). Potentially exploitable supercritical geothermal resources in the ductile crust. Nature Geoscience, 10(2), 140–144. https://doi.org/10.1038/ngeo2879
Watanabe, N., Yamaya, Y., Kitamura, K., & Mogi, T. (2021). Viscosity-dependent empirical formula for electrical conductivity of H2O-NaClfluids at elevated temperatures and high salinity. Fluid Phase Equilibria, 549, 113187. https://doi.org/10.1016/j.fluid.2021.113187
Watanabe, T., & Peach, C. J. (2002). Electrical impedance measurement of plastically deforming halite rocks at 125°C and 50 MPa. Journal ofGeophysical Research: Solid Earth, 107(B1), ECV2-1–ECV2-12. https://doi.org/10.1029/2001JB000204
Weatherley, D., & Henley, R. (2013). Flash vaporization during earthquakes evidenced by gold deposits. Nature Geoscience, 6, 294–298. https://doi.org/10.1038/ngeo1759
Weis, P., Driesner, T., & Heinrich, C. A. (2012). Porphyry-copper ore shells form at stable pressure-temperature fronts within dynamic fluid
plumes. Science, 338(6114), 1613–1616. https://doi.org/10.1126/science.1225009
Wersin, P., Johnson, L. H., & McKinley, I. G. (2007). Performance of the bentonite barrier at temperatures beyond 100°C: A critical review.
Physics and Chemistry of the Earth, 32(8), 780–788. https://doi.org/10.1016/j.pce.2006.02.051
Wight, D. E. (1988). SEG standard for MT and EMAP data. In SEG Technical Program Expanded Abstracts 1988 (Vol. 1, pp. 249–251). Societyof Exploration Geophysicists. https://doi.org/10.1190/1.1892244
Wilson, M. (Ed.). (1989). Partial melting processes in the Earth’s upper mantle. In Igneous petrogenesis (pp. 37–72). Springer Netherlands.
https://doi.org/10.1007/978-1-4020-6788-4_3
Wise, T., & Thiel, S. (2020). Proterozoic tectonothermal processes imaged with magnetotellurics and seismic reflection in southern Australia.
Geoscience Frontiers, 11(3), 885–893. https://doi.org/10.1016/j.gsf.2019.09.006
Yamaya, Y., Alanis, P. K. B., Takeuchi, A., Cordon, J. M., Mogi, T., Hashimoto, T., et al. (2013). A large hydrothermal reservoir beneath Taal
Volcano (Philippines) revealed by magnetotelluric resistivity survey: 2-D resistivity modeling. Bulletin of Volcanology, 75(7), 729. https://doi.
org/10.1007/s00445-013-0729-y
Yamaya, Y., Mogi, T., Honda, R., Hase, H., Hashimoto, T., & Uyeshima, M. (2017). Three-dimensional resistivity structure in Ishikari Lowland,
Hokkaido, northeastern Japan—Implications to strain concentration mechanism. Geochemistry, Geophysics, Geosystems, 18(2), 735–754.
https://doi.org/10.1002/2016GC006771
Yoshida, T., Kimura, J.-I., Yamada, R., Acocella, V., Sato, H., Zhao, D., et al. (2014). Evolution of late Cenozoic magmatism and the crust-mantle
structure in the NE Japan Arc. Geological Society, London, Special Publications, 385(1), 335. https://doi.org/10.1144/SP385.15
Yoshimura, R., Ogawa, Y., Yukutake, Y., Kanda, W., Komori, S., Hase, H., et al. (2018). Resistivity characterization of Hakone volcano, Central Japan, by three-dimensional magnetotelluric inversion. Earth, Planets, and Space, 70(1), 66. https://doi.org/10.1186/s40623-018-0848-y

ISHIZU ET AL.

21 of 21