3-D inversion of magnetic data based on the L1–L2 norm regularization

• 資料種別: 記事
• タイトル: 3-D inversion of magnetic data based on the L1–L2 norm regularization
• 著者・編者: Mitsuru Utsugi
• 出版事項: 日本 : Springer Nature
• 出版年月日等: 2019-07-03
• 出版年（W3CDTF）: 2019-07-03
• タイトル（掲載誌）: EPS : Earth, Planets and Space
• 巻号年月日等（掲載誌）: 71(73)
• 掲載巻: 71(73)
• ISSN（掲載誌）: 1880-5981
• ISSN-L（掲載誌）: 1343-8832
• 本文の言語コード: eng
• DOI: 10.1186/s40623-019-1052-4; https://doi.org/10.1186/s40623-019-1052-4
• 国立国会図書館永続的識別子: info:ndljp/pid/11377498; https://dl.ndl.go.jp/pid/11377498
• コレクション（共通）: 障害者向け資料
• コレクション（障害者向け資料：レベル1）: テキストデータ
• コレクション（個別）: 国立国会図書館デジタルコレクション > 電子書籍・電子雑誌 > その他; https://dl.ndl.go.jp/collections/B00035
• 収集根拠: オンライン資料収集制度
• 受理日（W3CDTF）: 2019-10-28T20:45:15+09:00
• 保存日（W3CDTF）: 2019-10-28
• 記録形式（IMT）: application/pdf
• オンライン閲覧公開範囲: 国立国会図書館内限定公開
• デジタル化資料送信: 図書館・個人送信対象外
• 遠隔複写可否（NDL）: 可
• 掲載誌（URI）: https://earth-planets-space.springeropen.com/articles
• 掲載誌（国立国会図書館永続的識別子）: info:ndljp/pid/11245705; https://dl.ndl.go.jp/pid/11245705
• 連携機関・データベース: 国立国会図書館 : 国立国会図書館デジタルコレクション; https://dl.ndl.go.jp

• 要約等: Magnetic inversion is one of the popular methods to obtain information about the subsurface structure. However, many of the conventional methods have a serious problem, that is, the linear equations to be solved become ill-posed, under-determined, and thus, the uniqueness of the solution is not guaranteed. As a result, several different models fit the observed magnetic data with the same accuracy. To reduce the non-uniqueness of the model, conventional studies introduced regularization method based on the quadratic solution norm. However, these regularization methods impose a certain level of smoothness, and as the result, the resultant model is likely to be blurred. To obtain a focused magnetic model, I introduce L1 norm regularization. As is widely known, L1 norm regularization promotes sparseness of the model. So, it is expected that, the resulting model is constructed only with the features truly required to reconstruct data and, as a result, a simple and focused model is obtained. However, by using L1 norm regularization solely, an excessively concentrated model is obtained due to the nature of the L1 norm regularization and a lack of linear independence of the magnetic equations. To overcome this problem, I use a combination of L1 and L2 norm regularization. To choose a feasible regularization parameter, I introduce a regularization parameter selection method based on the L-curve criterion with fixing the mixing ratio of L1 and L2 norm regularization. This inversion method is applied to a real magnetic anomaly data observed on Hokkaido Island, northern Japan and reveals the subsurface magnetic structure on this area.
• DOI: 10.1186/s40623-019-1052-4; https://doi.org/10.1186/s40623-019-1052-4
• オンライン閲覧公開範囲: インターネット公開
• 著作権情報: © The Author(s) 2019. This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
• 関連情報（URI）: http://hdl.handle.net/2433/243098; http://id.ndl.go.jp/digimeta/11377498; https://dl.ndl.go.jp/pid/11377498; http://link.springer.com/content/pdf/10.1186/s40623-019-1052-4.pdf; http://link.springer.com/article/10.1186/s40623-019-1052-4/fulltext.html
• 参照: Magnetic inversion to recover the subsurface block structures based on<i>L</i>1 norm and total variation regularization; https://cir.nii.ac.jp/crid/1360013168799766656; Magnetization structure of Nishinoshima volcano, Ogasawara island arc, obtained from magnetic surveys using an unmanned aerial vehicle; https://cir.nii.ac.jp/crid/1360857593678453120; Aeromagnetic survey in Kusatsu-Shirane volcano, central Japan, by using an unmanned helicopter; https://cir.nii.ac.jp/crid/2051714792011293312
• 参照: Temporal variation in the resistivity structure of the first Nakadake crater, Aso volcano, Japan, during the magmatic eruptions from November 2014 to May 2015, as inferred by the ACTIVE electromagnetic monitoring system; https://cir.nii.ac.jp/crid/1050001338207908480; Airborne electromagnetic and magnetic surveys for long tunnel construction design; https://cir.nii.ac.jp/crid/1360001114160731136; Lunar Magnetic Field Observation and Initial Global Mapping of Lunar Magnetic Anomalies by MAP-LMAG Onboard SELENE (Kaguya); https://cir.nii.ac.jp/crid/1360002215432243712; Analysis of Discrete Ill-Posed Problems by Means of the L-Curve; https://cir.nii.ac.jp/crid/1360011142938948992; Convergence of a Block Coordinate Descent Method for Nondifferentiable Minimization; https://cir.nii.ac.jp/crid/1360011144572274688; High-resolution velocity gathers and offset space reconstruction; https://cir.nii.ac.jp/crid/1360011144737915776; Joint inversion of surface and three-component borehole magnetic data; https://cir.nii.ac.jp/crid/1360011145771030016; A regularized three-dimensional magnetotelluric inversion with a minimum gradient support constraint; https://cir.nii.ac.jp/crid/1360285710546317824; Compact gravity inversion; https://cir.nii.ac.jp/crid/1360292619422278272; A comparison of automatic techniques for estimating the regularization parameter in non-linear inverse problems; https://cir.nii.ac.jp/crid/1360292621089176192; Seismic impedance inversion using <i>l</i> ₁-norm regularization and gradient descent methods; https://cir.nii.ac.jp/crid/1360298342874215040; The inversion of deep‐sea magnetic anomalies using Akaike's Bayesian information criterion; https://cir.nii.ac.jp/crid/1360565166662469376; Wavelet-based double-difference seismic tomography with sparsity regularization; https://cir.nii.ac.jp/crid/1360574094454660480; 3-D inversion of magnetic data; https://cir.nii.ac.jp/crid/1360845539090830720; Orogeny and relative plate motions: Example of the Japanese Islands; https://cir.nii.ac.jp/crid/1360855571434302080; Three-dimensional regularized focusing inversion of gravity gradient tensor component data; https://cir.nii.ac.jp/crid/1361137043652502528; 3-D magnetic imaging using conjugate gradients; https://cir.nii.ac.jp/crid/1361137046103370112; Electromagnetic inversion using quasi-linear approximation; https://cir.nii.ac.jp/crid/1361418519896781824; Regularization and Variable Selection Via the Elastic Net; https://cir.nii.ac.jp/crid/1361418520582715776; Partialling out the Spatial Component of Ecological Variation; https://cir.nii.ac.jp/crid/1361418521187751808; A computationally efficient scheme for the inversion of large scale potential field data: Application to synthetic and real data; https://cir.nii.ac.jp/crid/1361699994396642304; The lasso problem and uniqueness; https://cir.nii.ac.jp/crid/1361699996125546496; Quasi-analytical approximations and series in electromagnetic modeling; https://cir.nii.ac.jp/crid/1361981468496453632; 3-D magnetic inversion with data compression and image focusing; https://cir.nii.ac.jp/crid/1361981468781390976; A two-dimensional magnetotelluric inversion assuming Gaussian static shift; https://cir.nii.ac.jp/crid/1361981470277954816; Spline Models for Observational Data; https://cir.nii.ac.jp/crid/1362825893615676032; 3D magnetic data-space inversion with sparseness constraints; https://cir.nii.ac.jp/crid/1362825895879964672; Analysis of depth resolution in potential-field inversion; https://cir.nii.ac.jp/crid/1363107368659481216; Magnetic anomalies due to prism-shaped bodies with arbitrary polarization; https://cir.nii.ac.jp/crid/1363107369411872256; A new 3-D inversion algorithm for magnetic total field anomalies; https://cir.nii.ac.jp/crid/1363107370677674880; Regression Shrinkage and Selection Via the Lasso; https://cir.nii.ac.jp/crid/1363388844124986368; Impedance inversion based on L1 norm regularization; https://cir.nii.ac.jp/crid/1363388844377211648; Robust 3D gravity gradient inversion by planting anomalous densities; https://cir.nii.ac.jp/crid/1363388844581287680; Tomographic inversion using ℓ₁-norm regularization of wavelet coefficients; https://cir.nii.ac.jp/crid/1363670318350683520; Small-scale mélange fabric between serpentinite block and matrix: Magnetic evidence from the Mitsuishi ultramafic rock body, Hokkaido, Japan; https://cir.nii.ac.jp/crid/1363670318810510464; Variable Selection via Nonconcave Penalized Likelihood and its Oracle Properties; https://cir.nii.ac.jp/crid/1363670318986366336; Generalized Convexity and Optimization; https://cir.nii.ac.jp/crid/1363670319284485248; Regularization Paths for Generalized Linear Models via Coordinate Descent; https://cir.nii.ac.jp/crid/1363670320333519232; Pathwise coordinate optimization; https://cir.nii.ac.jp/crid/1363951796201746304; Focusing geophysical inversion images; https://cir.nii.ac.jp/crid/1364233269679067520; 3D gravity data-space inversion with sparseness and bound constraints; https://cir.nii.ac.jp/crid/1370013168799766656; Regularized magnetotelluric inversion based on a minimum support gradient stabilizing functional; https://cir.nii.ac.jp/crid/2050870367053035520
• 参照（URI）: https://cir.nii.ac.jp/crid/1370849946839464325
• 連携機関・データベース: 国立情報学研究所 : CiNii Research; https://cir.nii.ac.jp/
• 提供元機関・データベース: 学術機関リポジトリデータベース; https://irdb.nii.ac.jp; 雑誌記事索引データベース; https://ndlsearch.ndl.go.jp; Crossref; https://www.crossref.org; CiNii Articles; 科学研究費助成事業データベース; https://kaken.nii.ac.jp/ja
• 書誌ID（NDLBibID）: 11377498; http://id.ndl.go.jp/bib/11377498
• NII論文ID: 120006653084