Open AccessBook
The Rock Physics Handbook: Tools for Seismic Analysis of Porous Media
TLDR
In this article, the authors present basic tools for elasticity and Hooke's law, effective media, granular media, flow and diffusion, and fluid effects on wave propagation for wave propagation.Abstract:
Preface 1. Basic tools 2. Elasticity and Hooke's law 3. Seismic wave propagation 4. Effective media 5. Granular media 6. Fluid effects on wave propagation 7. Empirical relations 8. Flow and diffusion 9. Electrical properties Appendices.read more
Citations
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Journal ArticleDOI
Analysis of fluid substitution in a porous and fractured medium
TL;DR: In this article, the effect of porosity and water saturation on elastic properties and reflection coefficients in transversely isotropic media with a horizontal symmetry axis (HTI) was analyzed.
Proceedings ArticleDOI
Petrophysical properties prediction from pre-stack seismic data using convolutional neural networks
Vishal Das,Tapan Mukerji +1 more
Journal ArticleDOI
Deriving microstructure and fluid state within the Icelandic crust from the inversion of tomography data
TL;DR: In this paper, an effective medium model was developed for estimating velocities in porous media including both pores and cracks and use it to derive the distribution of crack density beneath the Reykjanes Peninsula from accurate tomography data.
Journal ArticleDOI
Seismo-hydro-mechanical modelling of the seismic cycle: Methodology and implications for subduction zone seismicity
Claudio Petrini,Taras Gerya,Viktoriya Yarushina,Ylona van Dinther,Ylona van Dinther,James A. D. Connolly,Claudio Madonna +6 more
TL;DR: In this article, a fully coupled poro-visco-elasto-plastic seismo-hydro-mechanical numerical model was developed for coupled modeling of tectonic and seismic processes in the presence of fluids.
Journal ArticleDOI
Improvement of petrophysical workflow for shear wave velocity prediction based on machine learning methods for complex carbonate reservoirs
TL;DR: In this paper, a machine learning method (Long Short Term Memory Neural Network, LSTM) is proposed to improve the traditional petrophysical workflow, which can deeply mine the rich information in the wireline logs and then establish the relationships between S-wave velocity and wireline log.
References
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Book
An introduction to the bootstrap
Bradley Efron,Robert Tibshirani +1 more
TL;DR: This article presents bootstrap methods for estimation, using simple arguments, with Minitab macros for implementing these methods, as well as some examples of how these methods could be used for estimation purposes.
Book
Pattern Recognition and Machine Learning
TL;DR: Probability Distributions, linear models for Regression, Linear Models for Classification, Neural Networks, Graphical Models, Mixture Models and EM, Sampling Methods, Continuous Latent Variables, Sequential Data are studied.
Book
Theory of elasticity
TL;DR: The theory of the slipline field is used in this article to solve the problem of stable and non-stressed problems in plane strains in a plane-strain scenario.
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