4.7 Article

Geophysical Inversion Using a Variational Autoencoder to Model an Assembled Spatial Prior Uncertainty

Related references

Note: Only part of the references are listed.
Article Environmental Sciences

Deep Convolutional Autoencoders for Robust Flow Model Calibration Under Uncertainty in Geologic Continuity

Anyue Jiang et al.

Summary: This paper introduces a deep learning architecture called variational auto-encoder for robust dimension-reduced parameterization of spatially distributed aquifer properties under uncertain geostatistical models.

WATER RESOURCES RESEARCH (2021)

Article Geochemistry & Geophysics

3D Carbonate Digital Rock Reconstruction Using Progressive Growing GAN

Nan You et al.

Summary: The development of digital rock physics relies on high-quality 3D digital rock images, which can be obtained using X-ray micro-Computed Tomography (mu CT). A machine learning method is proposed to reconstruct 3D digital rocks from 2D cross-section images, saving imaging cost and improving image quality. The method was successfully applied to an Estaillades carbonate rock sample, achieving nine times speedup of the imaging process and more than 4,500 times compression of image data. The Progressive Growing Generative Adversarial Network (PG-GAN) used in the method can expand the digital rock repository and enable efficient imaging editing in its linear latent space.

JOURNAL OF GEOPHYSICAL RESEARCH-SOLID EARTH (2021)

Article Computer Science, Interdisciplinary Applications

Deep generative models in inversion: The impact of the generator's nonlinearity and development of a new approach based on a variational autoencoder

Jorge Lopez-Alvis et al.

Summary: In this study, the authors review the conceptual framework of inversion with DGMs and point out that the nonlinearity in generative mapping between latent and original representations is mainly caused by changes in topology and curvature. They identify a conflict between the accuracy of generated patterns and the feasibility of gradient-based inversion, and propose a method that achieves a tradeoff between these two goals for better inversion results.

COMPUTERS & GEOSCIENCES (2021)

Article Geosciences, Multidisciplinary

Linear Waveform Tomography Inversion Using Machine Learning Algorithms

Tue Holm-Jensen et al.

MATHEMATICAL GEOSCIENCES (2020)

Article Computer Science, Interdisciplinary Applications

Hybrid geological modeling: Combining machine learning and multiple-point statistics

Tao Bai et al.

COMPUTERS & GEOSCIENCES (2020)

Article Computer Science, Interdisciplinary Applications

Towards a robust parameterization for conditioning facies models using deep variational autoencoders and ensemble smoother

Smith W. A. Canchumuni et al.

COMPUTERS & GEOSCIENCES (2019)

Review Computer Science, Interdisciplinary Applications

Gradient-based deterministic inversion of geophysical data with generative adversarial networks: Is it feasible?

Eric Laloy et al.

COMPUTERS & GEOSCIENCES (2019)

Article Environmental Sciences

Cross-borehole tomography with full-decay spectral time-domain induced polarization for mapping of potential contaminant flow-paths

Thue Sylvester Bording et al.

JOURNAL OF CONTAMINANT HYDROLOGY (2019)

Article Physics, Fluids & Plasmas

Nested multiresolution hierarchical simulated annealing algorithm for porous media reconstruction

Laurent Lemmens et al.

PHYSICAL REVIEW E (2019)

Article Computer Science, Artificial Intelligence

A Learning-Based Method for Solving III-Posed Nonlinear Inverse Problems: A Simulation Study of Lung EIT

Jin Keun Seo et al.

SIAM JOURNAL ON IMAGING SCIENCES (2019)

Article Geochemistry & Geophysics

Mapping sand layers in clayey till using crosshole ground-penetrating radar

Majken Caroline Looms et al.

GEOPHYSICS (2018)

Article Environmental Sciences

Training-Image Based Geostatistical Inversion Using a Spatial Generative Adversarial Neural Network

Eric Laloy et al.

WATER RESOURCES RESEARCH (2018)

Article Computer Science, Hardware & Architecture

ImageNet Classification with Deep Convolutional Neural Networks

Alex Krizhevsky et al.

COMMUNICATIONS OF THE ACM (2017)

Article Computer Science, Interdisciplinary Applications

A fast marching algorithm for the factored eikonal equation

Eran Treister et al.

JOURNAL OF COMPUTATIONAL PHYSICS (2016)

Article Mathematics

TESTING THE MANIFOLD HYPOTHESIS

Charles Fefferman et al.

JOURNAL OF THE AMERICAN MATHEMATICAL SOCIETY (2016)

Article Geosciences, Multidisciplinary

Quantifying natural delta variability using a multiple-point geostatistics prior uncertainty model

Celine Scheidt et al.

JOURNAL OF GEOPHYSICAL RESEARCH-EARTH SURFACE (2016)

Review Water Resources

Geological realism in hydrogeological and geophysical inverse modeling: A review

Niklas Linde et al.

ADVANCES IN WATER RESOURCES (2015)

Article Multidisciplinary Sciences

scikit-image: image processing in Python

Stefan van der Walt et al.

PEERJ (2014)

Article Water Resources

Connectivity metrics for subsurface flow and transport

Philippe Renard et al.

ADVANCES IN WATER RESOURCES (2013)

Article Computer Science, Interdisciplinary Applications

History matching and uncertainty quantification of facies models with multiple geological interpretations

Hyucksoo Park et al.

COMPUTATIONAL GEOSCIENCES (2013)

Article Geosciences, Multidisciplinary

Modeling Fine-Scale Geological Heterogeneity-Examples of Sand Lenses in Tills

Timo Christian Kessler et al.

GROUND WATER (2013)

Article Water Resources

Sparse geologic dictionaries for subsurface flow model calibration: Part I. Inversion formulation

Mohammadreza Mohammad Khaninezhad et al.

ADVANCES IN WATER RESOURCES (2012)

Article Computer Science, Interdisciplinary Applications

Inverse problems with non-trivial priors: efficient solution through sequential Gibbs sampling

Thomas Mejer Hansen et al.

COMPUTATIONAL GEOSCIENCES (2012)

Article Geography, Physical

Characterization of sand lenses embedded in tills

T. C. Kessler et al.

QUATERNARY SCIENCE REVIEWS (2012)

Article Geochemistry & Geophysics

Fast solution of geophysical inversion using adaptive mesh, space-filling curves and wavelet compression

Kristofer Davis et al.

GEOPHYSICAL JOURNAL INTERNATIONAL (2011)

Article Geochemistry & Geophysics

Wavelet Reconstruction of Geologic Facies From Nonlinear Dynamic Flow Measurements

Behnam Jafarpour

IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING (2011)

Article Geosciences, Multidisciplinary

An Improved Parallel Multiple-point Algorithm Using a List Approach

Julien Straubhaar et al.

MATHEMATICAL GEOSCIENCES (2011)

Article Environmental Sciences

The Direct Sampling method to perform multiple-point geostatistical simulations

Gregoire Mariethoz et al.

WATER RESOURCES RESEARCH (2010)

Article Geochemistry & Geophysics

Transform-domain sparsity regularization for inverse problems in geosciences

Behnam Jafarpour et al.

GEOPHYSICS (2009)

Article Geosciences, Multidisciplinary

Kernel principal component analysis for efficient, differentiable parameterization of multipoint geostatistics

Pallav Sarma et al.

MATHEMATICAL GEOSCIENCES (2008)

Article Geosciences, Multidisciplinary

The necessity of a multiple-point prior model

Andre Journel et al.

MATHEMATICAL GEOLOGY (2006)

Article Geosciences, Multidisciplinary

The probability perturbation method: A new look at Bayesian inverse modeling

Jef Caers et al.

MATHEMATICAL GEOLOGY (2006)

Article Geochemistry & Geophysics

Applying petrophysical models to radar travel time and electrical resistivity tomograms: Resolution-dependent limitations

FD Day-Lewis et al.

JOURNAL OF GEOPHYSICAL RESEARCH-SOLID EARTH (2005)

Article Geosciences, Multidisciplinary

Conditional simulation of complex geological structures using multiple-point statistics

S Strebelle

MATHEMATICAL GEOLOGY (2002)

Article Geosciences, Multidisciplinary

Gradual deformation and iterative calibration of sequential stochastic simulations

LY Hu et al.

MATHEMATICAL GEOLOGY (2001)