Advances in Geological Science – serie

On the basis of thermodynamic considerations and the Earth’s historical processes, this book argues the physical inevitability of life’s generation and evolution, i.e., Why did life generate?

This publication shows the three-dimensional configuration of the gigantic tectonic sag of the Osaka Bay sedimentary basin on the eastern Eurasian margin based on reflection seismic data never before published. The basin has developed relatively quickly since the dawn of the Quaternary. High-resolution subsurface images on the profiles provide highly valuable information about the architecture of active faults, paleoenvironmental changes, and mass balance on the convergent margin. The book presents an excellent case study of a tectonically controlled basin because morphologies and evolutionary processes of such basins show an enormous diversity, reflecting spatiotemporal variation in tectonic stress. Furthermore, this volume provides insight into the general mechanism of sedimentary basin formation.The quantitative analyses contained here will be thought-provoking for industry experts, academics, and graduate and undergraduate students engaged in geologic survey and civil engineering. The contents will be especially useful to professionals in the fields of Quaternary geology, neotectonics, and active fault research.

On the basis of thermodynamic considerations and the Earth’s historical processes, this book argues the physical inevitability of life’s generation and evolution, i.e., Why did life generate?

This publication shows the three-dimensional configuration of the gigantic tectonic sag of the Osaka Bay sedimentary basin on the eastern Eurasian margin based on reflection seismic data never before published.

The recent explosion of global and regional seismicity data in the world requires new methods of investigation of microseismicity and development of their modelling to understand the nature of whole earth mechanics. In this book, the author proposes a powerful tool to reveal the characteristic features of global and regional microseismicity big data accumulated in the databases of the world. The method proposed in this monograph is based on (1) transformation of stored big data to seismicity density data archives, (2) linear transformation of microseismicity density data matrixes to correlated seismicity matrixes by means of the singular value decomposition method, (3) time series analyses of globally and regionally correlated seismicity rates, and (4) the minimal non-linear equations approximation of their correlated seismicity rate dynamics. Minimal non-linear modelling is the manifestation for strongly correlated seismicity time series controlled by Langevin-type stochastic dynamicequations involving deterministic terms and random Gaussian noises. A deterministic term is composed minimally with correlated seismicity rate vectors of a linear term and of a term with a third exponent. Thus, the dynamics of correlated seismicity in the world contains linearly changing stable nodes and rapid transitions between them with transient states. This book contains discussions of future possibilities of stochastic extrapolations of global and regional seismicity in order to reduce earthquake disasters worldwide. The dataset files are available online and can be downloaded at springer.com.

The recent explosion of global and regional seismicity data in the world requires new methods of investigation of microseismicity and development of their modelling to understand the nature of whole earth mechanics. In this book, the author proposes a powerful tool to reveal the characteristic features of global and regional microseismicity big data accumulated in the databases of the world. The method proposed in this monograph is based on (1) transformation of stored big data to seismicity density data archives, (2) linear transformation of microseismicity density data matrixes to correlated seismicity matrixes by means of the singular value decomposition method, (3) time series analyses of globally and regionally correlated seismicity rates, and (4) the minimal non-linear equations approximation of their correlated seismicity rate dynamics. Minimal non-linear modelling is the manifestation for strongly correlated seismicity time series controlled by Langevin-type stochastic dynamicequations involving deterministic terms and random Gaussian noises. A deterministic term is composed minimally with correlated seismicity rate vectors of a linear term and of a term with a third exponent. Thus, the dynamics of correlated seismicity in the world contains linearly changing stable nodes and rapid transitions between them with transient states. This book contains discussions of future possibilities of stochastic extrapolations of global and regional seismicity in order to reduce earthquake disasters worldwide. The dataset files are available online and can be downloaded at springer.com.

This book explains the physics behind seismic ground motions and seismic waves to graduate and upper undergraduate students as well as to professionals.

This book explains the physics behind seismic ground motions and seismic waves to graduate and upper undergraduate students as well as to professionals.

The Mj 7.3 (Mw 7.0) mainshock produced extensive and complex surface ruptures in and around the active Futagawa-Hinagu fault zone, including primary right-lateral faulting, slip-partitioned normal faulting, and distributed and triggered surface breaks, as well as minor surface ruptures associated with the foreshocks of up to Mj 6.5 (Mw 6.2).

The Mj 7.3 (Mw 7.0) mainshock produced extensive and complex surface ruptures in and around the active Futagawa-Hinagu fault zone, including primary right-lateral faulting, slip-partitioned normal faulting, and distributed and triggered surface breaks, as well as minor surface ruptures associated with the foreshocks of up to Mj 6.5 (Mw 6.2).

The recent understandings about global earth mechanics are widely based on huge amounts of monitoring data accumulated using global networks of precise seismic stations, satellite monitoring of gravity, very large baseline interferometry, and the Global Positioning System. New discoveries in materials sciences of rocks and minerals and of rock deformation with fluid water in the earth also provide essential information. This book presents recent work on natural geometry, spatial and temporal distribution patterns of various cracks sealed by minerals, and time scales of their crack sealing in the plate boundary. Furthermore, the book includes a challenging investigation of stochastic earthquake prediction testing by means of the updated deep machine learning of a convolutional neural network with multi-labeling of large earthquakes and of the generative autoencoder modeling of global correlated seismicity. Their manifestation in this book contributes to the development of human societyresilient from natural hazards. Presented here are (1) mechanics of natural crack sealing and fluid flow in the plate boundary regions, (2) large-scale permeable convection of the plate boundary, (3) the rapid process of massive extrusion of plate boundary rocks, (4) synchronous satellite gravity and global correlated seismicity, (5) Gaussian network dynamics of global correlated seismicity, and (6) prediction testing of plate boundary earthquakes by machine learning and generative autoencoders.

The recent understandings about global earth mechanics are widely based on huge amounts of monitoring data accumulated using global networks of precise seismic stations, satellite monitoring of gravity, very large baseline interferometry, and the Global Positioning System. New discoveries in materials sciences of rocks and minerals and of rock deformation with fluid water in the earth also provide essential information. This book presents recent work on natural geometry, spatial and temporal distribution patterns of various cracks sealed by minerals, and time scales of their crack sealing in the plate boundary. Furthermore, the book includes a challenging investigation of stochastic earthquake prediction testing by means of the updated deep machine learning of a convolutional neural network with multi-labeling of large earthquakes and of the generative autoencoder modeling of global correlated seismicity. Their manifestation in this book contributes to the development of human societyresilient from natural hazards. Presented here are (1) mechanics of natural crack sealing and fluid flow in the plate boundary regions, (2) large-scale permeable convection of the plate boundary, (3) the rapid process of massive extrusion of plate boundary rocks, (4) synchronous satellite gravity and global correlated seismicity, (5) Gaussian network dynamics of global correlated seismicity, and (6) prediction testing of plate boundary earthquakes by machine learning and generative autoencoders.

This book presents a summary of high-pressure phase transitions of minerals and related inorganic compounds.

This book presents a summary of high-pressure phase transitions of minerals and related inorganic compounds.

This book is a product of the joint efforts of interdisciplinary academic fields under the integrative framework of human geoscience. Human geoscience is a new genre of geoscience concerned with the natural phenomena that occur on the surface of the Earth and their relations with human activities. It therefore has connections with many fields of geoscience, namely, physical geography, geomorphology, geology, soil science, sedimentology, seismology, volcanology, meteorology, climatology, oceanography, and hydrology. It also has strong links to the humanities, social sciences, agricultural sciences, and engineering related to disaster prevention or mitigation. All these disciplines are important fields for understanding disasters and global environmental problems and for evaluating the associated risks comprehensively, then proposing mitigation strategies.The volume is designed for those who may not necessarily have a geoscience background but have broad scientific interest inunderstanding the causes, mechanisms, and consequences of geo-disasters and global environmental problems and wish to make the world more sustainable on that basis. The book consists of six parts: I. Introduction, II. Earth Surface Realms, III. Natural Resources and Society, IV. Natural Hazards and Society, V. Global Environmental Problems, and VI. Global Sustainability Programmes and Human Geoscience, which discusses the contribution of this field of science to a new comprehensive framework for global sustainability.

This book is a product of the joint efforts of interdisciplinary academic fields under the integrative framework of human geoscience.

This book provides a comprehensive characterization of high-temperature geothermal fields worldwide, encompassing diverse geological settings such as extensional and contractional　tectonics, silicic and mafic crustal regions, hypersaline and low-salinity fluid environments, and both brittle and ductile lithospheric layers. It also details current geothermal exploration and development efforts in Japan.Emerging exploration technologies, including Full-waveform Inversion (FWI), Distributed Temperature Sensing (DTS), and Distributed Acoustic Sensing (DAS), are introduced and discussed in the context of their practical applications. A central challenge in geothermal development remains the accurate identification of viable targets for production and reinjection wells, as exploratory drilling entails significant costs. Accordingly, this book places special emphasis on target identification strategies, setting it apart from other works in the field.While global in scope, this book primarily focuses on geothermal development in Japan and features field-based case studies related to well targeting. Authored and reviewed by experienced geothermal engineers, it serves as a valuable resource for professionals engaged in geothermal exploration and reservoir engineering.

This book provides a new data augmentation method based on the local stochastic distribution patterns in natural time series data of global and regional seismicity rates and their correlated seismicity rates.

This book provides a new data augmentation method based on the local stochastic distribution patterns in natural time series data of global and regional seismicity rates and their correlated seismicity rates. The augmentation procedure is called the diffusion – denoising augmentation method from the local Gaussian distribution of segmented data of long time series. This method makes it possible to apply the deep machine learning necessary to neural network prediction of rare large earthquakes in the global and regional earth system.The book presents the physical background of the processes showing the development of characteristic features in the global and regional correlated seismicity dynamics, which are manifested by the successive time series of 1990–2023. Physical processes of the correlated global seismicity change and the earth’s rotation, fluctuation of plate motion, and the earth’s ellipsoid ratio (C20 of satellite gravity change) are proposed in this book. The equivalency between Gaussian seismicity network dynamics and the minimal nonlinear dynamics model of correlated seismicity rates is also provided. In addition, the book contains simulated models of the shear crack jog wave, precipitation of minerals in the jog, and jog accumulation inducing shear crack propagation which leads to earthquakes in the plate boundary rocks under permeable fluid flow.

This book presents the mechanism of in-situ radon volatilization and outlines the geological requisites to site a radon monitoring well for earthquake warning. A small fractured aquifer under undrained conditions is an effective natural strain meter for earthquake prediction. It shows significant merit on a local basis, and most importantly, the analysis can also be applied globally in subduction zones with similar tectonic settings and physical–chemical relationships.Between 2003 and 2010, anomalous declines in groundwater radon concentration were recurrently recorded at Antung, Taiwan, which are considered as precursory to local major earthquakes. The correlations between radon decline and earthquake magnitude are useful for early warning of local main earthquakes. The book consists of 7 chapters. Chapter 1 presents background information and the objectives of the book. Chapter 2 illustrates the methods of monitoring groundwater radon and a brief review of earthquake prediction research using groundwater radon. Chapter 3 provides the details of anomalous decrease in groundwater radon before the Taiwan Mw 6.8 Chengkung Earthquake of 2003. Chapter 4 provides the description of the mechanism of groundwater-radon volatilization. Chapter 5 shows the recurrent anomalous declines in groundwater radon concentration consistently recorded at Antung, Taiwan, prior to local main earthquakes that occurred between 2003 and 2010. Monitoring groundwater radon in small, unconfined fractured aquifers is explained in Chapter 6, followed by an analysis of correlating precursory declines in groundwater radon, precursory time with earthquake magnitudes for small, confined fractured aquifers in Chapter 7.

This book presents the mechanism of in-situ radon volatilization and outlines the geological requisites to site a radon monitoring well for earthquake warning.

Different physical or geophysical methods provide information about distinctive physical properties of the objects, e.g., rock formations and mineralization. In many cases, this information is mutually complementary, which makes it natural for consideration in a joint inversion of the multiphysics data. Inversion of the observed data for a particular experiment is subject to considerable uncertainty and ambiguity. One productive approach to reducing uncertainty is to invert several types of data jointly. Nonuniqueness can also be reduced by incorporating additional information derived from available a priori knowledge about the target to reduce the search space for the solution. This additional information can be incorporated in the form of a joint inversion of multiphysics data.Generally established joint inversion methods, however, are inadequate for incorporating typical physical or geological complexity. For example, analytic, empirical, or statistical correlations between different physical properties may exist for only part of the model, and their specific form may be unknown. Features or structures that are present in the data of one physical method may not be present in the data generated by another physical method or may not be equally resolvable.This book presents and illustrates several advanced, new approaches to joint inversion and data fusion, which do not require a priori knowledge of specific empirical or statistical relationships between the different model parameters or their attributes. These approaches include the following novel methods, among others: 1) the Gramian method, which enforces the correlation between different parameters; 2) joint total variation functional or joint focusing stabilizers, e.g., minimum support and minimum gradient support constraints; 3) data fusion employing a joint minimum entropy stabilizer, which yields the simplest multiphysics solution that fits the multi-modal data. In addition, the book describes the principles of using artificial intelligence (AI) in solving multiphysics inverse problems. The book also presents in detail both the mathematical principles of these advanced approaches to joint inversion of multiphysics data and successful case histories of regional-scale and deposit-scale geophysical studies to illustrate their indicated advantages.