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DOI | 10.1002/2017GL076708 |
Estimating Fault Friction From Seismic Signals in the Laboratory | |
Rouet-Leduc, Bertrand1; Hulbert, Claudia1; Bolton, David C.2; Ren, Christopher X.3; Riviere, Jacques2,4; Marone, Chris2; Guyer, Robert A.1; Johnson, Paul A.1 | |
2018-02-16 | |
发表期刊 | GEOPHYSICAL RESEARCH LETTERS
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ISSN | 0094-8276 |
EISSN | 1944-8007 |
出版年 | 2018 |
卷号 | 45期号:3页码:1321-1329 |
文章类型 | Article |
语种 | 英语 |
国家 | USA; England; France |
英文摘要 | Nearly all aspects of earthquake rupture are controlled by the friction along the fault that progressively increases with tectonic forcing but in general cannot be directly measured. We show that fault friction can be determined at any time, from the continuous seismic signal. In a classic laboratory experiment of repeating earthquakes, we find that the seismic signal follows a specific pattern with respect to fault friction, allowing us to determine the fault's position within its failure cycle. Using machine learning, we show that instantaneous statistical characteristics of the seismic signal are a fingerprint of the fault zone shear stress and frictional state. Further analysis of this fingerprint leads to a simple equation of state quantitatively relating the seismic signal power and the friction on the fault. These results show that fault zone frictional characteristics and the state of stress in the surroundings of the fault can be inferred from seismic waves, at least in the laboratory. Plain Language Summary In a laboratory setting that closely mimics Earth faulting, we show that the most important physical properties of a fault can be accurately estimated using machine learning to analyze the sound that the fault broadcasts. The artificial intelligence identifies telltale sounds that are characteristic of the physical state of the fault, and how close it is to failing. A fundamental relation between the sound emitted by the fault and its physical state is thus revealed. |
领域 | 气候变化 |
收录类别 | SCI-E |
WOS记录号 | WOS:000426161800015 |
WOS关键词 | STICK-SLIP ; ACOUSTIC EMISSIONS ; GRANULAR MATERIAL ; EARTHQUAKES ; VELOCITY ; LAWS ; DEFORMATION ; RELAXATION ; PRECURSORS ; FAILURE |
WOS类目 | Geosciences, Multidisciplinary |
WOS研究方向 | Geology |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://119.78.100.173/C666/handle/2XK7JSWQ/25955 |
专题 | 气候变化 |
作者单位 | 1.Los Alamos Natl Lab, Geophys Grp, Los Alamos, NM 87545 USA; 2.Penn State Univ, Dept Geosci, University Pk, PA 16802 USA; 3.Univ Cambridge, Dept Mat Sci & Met, Cambridge, England; 4.Grenoble Alpes Univ, CNRS, Inst Earth Sci ISTerre, Grenoble, France |
推荐引用方式 GB/T 7714 | Rouet-Leduc, Bertrand,Hulbert, Claudia,Bolton, David C.,et al. Estimating Fault Friction From Seismic Signals in the Laboratory[J]. GEOPHYSICAL RESEARCH LETTERS,2018,45(3):1321-1329. |
APA | Rouet-Leduc, Bertrand.,Hulbert, Claudia.,Bolton, David C..,Ren, Christopher X..,Riviere, Jacques.,...&Johnson, Paul A..(2018).Estimating Fault Friction From Seismic Signals in the Laboratory.GEOPHYSICAL RESEARCH LETTERS,45(3),1321-1329. |
MLA | Rouet-Leduc, Bertrand,et al."Estimating Fault Friction From Seismic Signals in the Laboratory".GEOPHYSICAL RESEARCH LETTERS 45.3(2018):1321-1329. |
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