[go: up one dir, main page]
More Web Proxy on the site http://driver.im/

Li et al., 2022 - Google Patents

Digital Rock Reconstruction Using Wasserstein GANs with Gradient Penalty

Li et al., 2022

View PDF
Document ID
8736619583139765604
Author
Li Y
He X
Zhu W
AlSinan M
Kwak H
Hoteit H
Publication year
Publication venue
International Petroleum Technology Conference

External Links

Snippet

Due to the scarcity and vulnerability of physical rock samples, digital rock reconstruction plays an important role in the numerical study of reservoir rock properties and fluid flow behaviors. With the rapid development of deep learning technologies, generative …
Continue reading at repository.kaust.edu.sa (PDF) (other versions)

Classifications

    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS
    • G01V99/00—Subject matter not provided for in other groups of this subclass
    • G01V99/005—Geomodels or geomodelling, not related to particular measurements
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T17/00—Three dimensional [3D] modelling, e.g. data description of 3D objects
    • G06T17/05—Geographic models
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS
    • G01V1/00—Seismology; Seismic or acoustic prospecting or detecting
    • G01V1/28—Processing seismic data, e.g. analysis, for interpretation, for correction
    • G01V1/30—Analysis
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/10—Complex mathematical operations
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS
    • G01V2210/00—Details of seismic processing or analysis
    • G01V2210/60—Analysis
    • G01V2210/66—Subsurface modeling
    • G01V2210/665—Subsurface modeling using geostatistical modeling
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T17/00—Three dimensional [3D] modelling, e.g. data description of 3D objects
    • G06T17/20—Finite element generation, e.g. wire-frame surface description, tesselation
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T11/00—2D [Two Dimensional] image generation
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/30—Information retrieval; Database structures therefor; File system structures therefor
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS
    • G01V3/00—Electric or magnetic prospecting or detecting; Measuring magnetic field characteristics of the earth, e.g. declination, deviation
    • G01V3/38—Processing data, e.g. for analysis, for interpretation, for correction
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS
    • G01V11/00—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS prospecting or detecting by methods combining techniques covered by two or more of main groups G01V1/00 - G01V9/00

Similar Documents

Publication Publication Date Title
Santos et al. PoreFlow-Net: A 3D convolutional neural network to predict fluid flow through porous media
Tahmasebi et al. Pore-scale simulation of flow of CO2 and brine in reconstructed and actual 3D rock cores
Silin et al. Robust determination of the pore space morphology in sedimentary rocks
Tahmasebi et al. Image‐based modeling of granular porous media
Latief et al. Continuum reconstruction of the pore scale microstructure for Fontainebleau sandstone
Emerick et al. Combining the ensemble Kalman filter with Markov chain Monte Carlo for improved history matching and uncertainty characterization
Li et al. Digital Rock Reconstruction Using Wasserstein GANs with Gradient Penalty
Janssens et al. Computed tomography 3D super-resolution with generative adversarial neural networks: Implications on unsaturated and two-phase fluid flow
Liu et al. Multiscale fusion of digital rock images based on deep generative adversarial networks
Li et al. Patch‐based iterative conditional geostatistical simulation using graph cuts
Xiao et al. Conditioning of deep-learning surrogate models to image data with application to reservoir characterization
Zhang et al. 3D porosity modeling of a carbonate reservoir using continuous multiple-point statistics simulation
Gerke et al. Multi-scale image fusion of X-ray microtomography and SEM data to model flow and transport properties for complex rocks on pore-level
Phan et al. Size-invariant 3D generation from a single 2D rock image
Li et al. Permeability-porosity relations from single image of natural rock: Subsampling approach
Kim et al. Fast and scalable earth texture synthesis using spatially assembled generative adversarial neural networks
Xiao et al. Deep-learning-generalized data-space inversion and uncertainty quantification framework for accelerating geological CO2 plume migration monitoring
Cui et al. Characterization of subsurface hydrogeological structures with convolutional conditional neural processes on limited training data
Jiang et al. Upscaling Permeability Using Multiscale X‐Ray‐CT Images With Digital Rock Modeling and Deep Learning Techniques
Misra et al. Massive Geomodel Compression and Rapid Geomodel Generation Using Advanced Autoencoders and Autoregressive Neural Networks
Zhang et al. Multiscale Carbonate Rock Reconstruction Using a Hybrid WGAN-GP and Super-Resolution
Ma et al. Enhancing the resolution of micro-CT images of rock samples via unsupervised machine learning based on a diffusion model
Tang et al. History matching complex 3D systems using deep-learning-based surrogate flow modeling and CNN-PCA geological parameterization
Abdollahifard et al. Reconstruction of binary geological images using analytical edge and object models
Rizk et al. A Critical Literature Review on Rock Petrophysical Properties Estimation from Images Based on Direct Simulation and Machine Learning Techniques