Название: Muography
Автор: Группа авторов
Издательство: John Wiley & Sons Limited
Жанр: Физика
isbn: 9781119723066
isbn:
22 Saito, T., Takahashi, S., & Wada H. (2003). 14C ages of Omuroyama volcano, Izu Peninsula, Bulletin of the Volcanological Society of Japan, 48, 2, 215–219. (in Japanese) https://doi.org/10.5026/jgeography.105.4_475
23 Schofield, R., King, L., Tayal, U., Castellano, I., Stirrup, J., Pontana, F., et al. (2020). Image reconstruction: Part 1—understanding filtered back projection, noise and image acquisition. Journal of Cardiovascular Computed Tomography, 14(3), 219–225. https://doi.org/10.1016/j.jcct.2019.04.008
24 Tanaka, H. K. M., Nakano, T., Takahashi, S., Yoshida, J., Takeo, M., Oikawa, J. et al. (2007). High resolution imaging in the inhomogeneous crust with cosmic‐ray muon radiography: The density structure below the volcanic crater floor of Mt. Asama, Japan. Earth and Planetary Science Letters, 263, 1, 104–113. doi:10.1016/j.epsl.2007.09.001
25 Tanaka, H. K. M., Taira, H., Uchida, T., Tanaka, M., Takeo, M., Ohminato, T., et al. (2010). Three‐dimensional computational axial tomography scan of a volcano with cosmic ray muon radiography. Journal of Geophysical Research, 115, B12332. https://doi.org/10.1029/2010JB007677
26 Tarantola, A. (2005). Inverse Problem Theory and Methods for Model Parameter Estimation. Philadelphia: Society for Industrial and Applied Mathematics. https://doi.org/10.1137/1.9780898717921
3 Joint Inversion of Muography and Gravity Data for 3D Density Imaging of Volcanoes
Ryuichi Nishiyama
Earthquake Research Institute, The University of Tokyo, Tokyo, Japan
ABSTRACT
Muography is surely one way to shed light on the density structure of the underground, but it is not the only one. Classical gravity surveys also provide information on the mass distribution of the entire Earth. Although these two methods differ in sensitivity, combining the two (joint inversion) would combat the weaknesses of each method and improve the resolution of three‐dimensional imaging. This chapter introduces one formulation of the joint inversion following an early work done by the author’s group, and tries to review further technical developments and applications by other researchers. Future technical prospects are discussed at the end.
3.1 INTRODUCTION
Muography has been established as a tool for mapping the subsurface density profile over the past decade. The application of the technology originated from volcanology (Gibert et al., 2021; Lo Presti et al., 2021; Macedonio et al., 2021; Oláh & Tanaka, 2021; Tanaka, 2021; Tioukov et al., 2021) and it has spread to various targets: natural caves (Hamar et al., 2021); glaciers (Scampoli et al., 2021); underground monitoring (Thompson et al., 2021); mining (Schouten et al., 2021); block landslides (Hernández et al., 2016); etc. Muography is based on the attenuation of the flux of cosmic‐ray muons when they traverse the surveyed targets. The rate of attenuation yields the information on the density distribution, specifically the density integrated along the lines of sight, which is referred to as density length or opacity (Tanaka, 2021). When a measurement is performed with a single detector, it only provides a two‐dimensional map in an angular space, which lacks the resolution along the depth dimension. In the case of volcano monitoring, such a two‐dimensional map can be used to specify on which lines of sight a volcanic conduit may exist. However, the exact location on the line or the size of the conduit cannot be determined from single‐detector measurements.
Tanaka et al. (2010) demonstrated that the limitations of single‐detector muography can be overcome by surrounding the mountain with multiple detectors. They installed two scintillation‐type detectors on the northern and eastern flank of Asama Volcano, Japan, and solved the three‐dimensional density distributions with a scheme of a regularized linear inversion. This sort of measurement is analogous to a medical computed tomography scan, where X‐rays pass through the patient's body from multiple projections. However, in the case of muography, it is often difficult to fully cover the mountain, due mainly to practical reasons, such as cost, logistics, and labor.
Surface gravity data can complement the weaknesses of muography. The measurement of gravity acceleration on the Earth’s surface has been used for multiple purposes. The surface gravity data has been used to determine the shape of the geoid, the equipotential surface of the Earth (e.g., Hoffmann‐Wellenhof & Moritz, 2006). Surface gravity data takes an important role in the exploration of mineral deposits and oil accumulation (e.g., Parasnis, 1976). Gravity anomaly maps provide knowledge of the internal structure of volcanoes and calderas (e.g., Scandone, 1990; Yokoyama & Ohkawa, 1986). Temporal gravity changes are used to study the movement of mass associated with volcanic eruptions (e.g., Battaglia et al., 2008; Van Camp et al., 2017; Carbone et al., 2007; Okubo, 2020).
Since the gravity acceleration on the surface reflects the gravitational attraction by mass of the Earth, it contains the information on the density distribution in the near‐surface. The information, whose sensitivity is different from the one of muography, could be used to improve the resolution of muography imaging. The idea was formulated in a scheme of linear inversion by Davis & Oldenburg (2012) and Nishiyama et al. (2014) performed the demonstration with an actual observation. Simultaneously, a non‐linear and exact formulation was provided by Jourde et al. (2015). Rosas‐Carbajal et al. (2017) performed a linear inversion to a huge gravity/muography dataset taken on La Soufrière de Guadeloupe lava dome. Cosburn et al. (2019) applied the joint inversion to the gravity data taken underground. The formulation of the joint inversion was further developed by Lelièvre et al. (2019), which allows the use of unstructured (tetrahedral) meshes and takes a density bias (discussed later) into account. Methodology for choosing hyper‐parameters was investigated by Barnoud et al. (2019). This chapter introduces a simple formulation by Davis and Oldenburg (2012) and Nishiyama et al. (2014) and reviews the aforementioned technical developments.
Figure 3.1 (Left) Gravity observation. The white instrument in front of the operator is a Lacoste & Romberg relative gravimeter. Behind the operator stands the antenna for Global Positioning System. (Right) Muography observation at Mt. Showa‐Shinzan lava dome (Japan) with nuclear emulsion films.
3.2 GRAVITY MEASUREMENTS
Gravity acceleration on the Earth is produced by the gravitational attraction of the mass of the Earth and the centrifugal acceleration due to the rotation of the Earth. In most cases of gravity measurements, gravimeters determine the magnitude of the gravity acceleration along the local plumb line at each gravity station. There are two mechanisms employed in modern gravimeters: the free‐fall method and the spring method. The former is based on measuring the absolute acceleration of a test mass falling in a vacuum chamber, in which the air drag is reduced. The FG5 absolute gravimeters produced by Micro‐g Lacoste Inc. have become the de facto standard of absolute measurements (Niebauer et al., 1995). As a test mass, the use of laser‐cooled atoms has been proposed and recently commercialized (Ménoret et al., 2018). These instruments are costly and require delicate handling of vacuums, lasers, atomic clocks, electronics, etc. The absolute measurement, therefore, has been performed mostly indoors where benchmarks can be maintained. СКАЧАТЬ