[S-EM14] 電気伝導度・地殻活動電磁気学

[SEM14-03] メッシュ状に配置した新旧Network-MTダイポールデータによる阿蘇カルデラ地下の3次元比抵抗分布

*畑 真紀¹、上嶋 誠¹、宇津木 充²、松島 喜雄³、田中 良和、橋本 武志⁴、吉村 令慧⁵、大志万 直人⁵ (1.東京大学地震研究所、2.京都大学大学院理学研究科附属地球熱学研究施設火山研究センター、3.産業技術総合研究所、4.北海道大学大学院理学研究院附属地震火山研究観測センター 、5.京都大学防災研究所 )

キーワード：3次元比抵抗モデル、ネットワークMT法データ、阿蘇カルデラ、マグマ供給系

Mt. Aso, an active Quaternary volcano, with a large caldera lie at the Beppu-Shimabara graben in the island of Kyushu. Aso caldera was formed at the central part of the graben by a series of huge eruptions, with a volcanic explosivity index of 7, during 270–90 ka. A post-caldera cone of Naka-dake in Aso caldera is a quite active volcano, at which magmatic and phreatomagmatic eruptions occurred during 2014–2016 and ash eruptions (emissions) have continued since July 2019. In and around Aso caldera, network-MT surveys for measuring the electric potential difference (the electric field) were carried out during 1993–1998 by using long metallic wires/dipoles of the commercial telephone company's networks [e.g., Uyeshima et al., 1995; Tanaka et al., 1998; Hashimoto et al., 1999; Hata et al., 2015]. We determined two components of network-MT response functions between the potential differences for respective dipoles and the two horizontal components of the magnetic field at the Kanoya Geomagnetic Observatory. On the other hand, we newly performed network-MT surveys at Aso caldera during 2019–2020 and determined response functions. Three-dimensional (3-D) inversion analyses were performed by using two data sets in a period up to tens of thousands s for obtaining resistivity models beneath Aso caldera in a crustal depth scale. In the inversion analyses, we used a data-space inversion code, which can be considered the length and direction of respective dipoles [e.g., Siripunvaraporn et al., 2004]. Moreover, the dipoles are distributed as to cover Aso caldera into reticular formation in order to obtain well-resolved 3-D models. In this presentation, we discuss a magma supply system beneath Aso caldera, which are inferred from the two 3-D resistivity models based on the new and old Network-MT data.