Iterative geostatistical seismic inversion incorporating local anisotropies
Sign Up to like & getrecommendations! Published in 2020 at "Computational Geosciences"
DOI: 10.1007/s10596-020-09966-1
Abstract: Geostatistical seismic inversion methods use stochastic sequential simulation as the model generation and perturbation technique. These stochastic simulation methods use a global variogram model to express the expected spatial continuity pattern of the subsurface elastic… read more here.
Keywords: inversion; variogram; geostatistical seismic; seismic inversion ... See more keywords
Geostatistical Seismic Inversion with Self-Updating of Local Probability Distributions
Sign Up to like & getrecommendations! Published in 2020 at "Mathematical Geosciences"
DOI: 10.1007/s11004-020-09896-9
Abstract: Three-dimensional subsurface elastic models inverted from seismic reflection data are the basis of the geo-modeling workflow. These models are often used to predict the spatial distribution of reservoir rock properties such as porosity, volume of… read more here.
Keywords: self updating; inversion; geostatistical seismic; seismic inversion ... See more keywords
A Hybrid Regularization Operator and Its Application in Seismic Inversion
Sign Up to like & getrecommendations! Published in 2021 at "IEEE Access"
DOI: 10.1109/access.2021.3106912
Abstract: Seismic inversion is an effective tool to estimate the properties of subsurface strata from seismograms. However, the intrinsic ill-posedness of the inversion problem causes the inverted subsurface properties to be easily polluted by inversion errors… read more here.
Keywords: inversion; regularization operator; seismic inversion; regularization ... See more keywords
Hybrid Global Stochastic and Bayesian Linearized Acoustic Seismic Inversion Methodology
Sign Up to like & getrecommendations! Published in 2017 at "IEEE Transactions on Geoscience and Remote Sensing"
DOI: 10.1109/tgrs.2017.2692388
Abstract: Seismic inversion is an important technique for reservoir modeling and characterization due to its potential in inferring the spatial distribution of the subsurface elastic properties of interest. Two of the most common seismic inversion methodologies… read more here.
Keywords: bayesian linearized; methodology; inversion; inversion methodology ... See more keywords
Deep Learning Seismic Inversion Based on Prestack Waveform Datasets
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Geoscience and Remote Sensing"
DOI: 10.1109/tgrs.2022.3195858
Abstract: Prediction of elastic parameters (e.g., P-, S-wave velocity, and density) from observed seismic data is one of the most common means of reservoir characterization. Recently, deep learning (DL), as a data-driven approach, has been attracting… read more here.
Keywords: inversion; seismic inversion; training dataset; data driven ... See more keywords
Seismic Inversion Based on Acoustic Wave Equations Using Physics-Informed Neural Network
Sign Up to like & getrecommendations! Published in 2023 at "IEEE Transactions on Geoscience and Remote Sensing"
DOI: 10.1109/tgrs.2023.3236973
Abstract: Seismic inversion is a significant tool for exploring the structure and characteristics of the underground. However, the conventional inversion strategy strongly depends on the initial model. In this work, we employ the physics-informed neural network… read more here.
Keywords: wave equations; inversion; physics; seismic inversion ... See more keywords
The impact of seismic inversion methodology on rock property prediction
Sign Up to like & getrecommendations! Published in 2020 at "Geophysical Prospecting"
DOI: 10.1111/1365-2478.13044
Abstract: Seismic inversion is a central step within the seismic reservoir characterization workflow. In seismic inversion, seismic amplitudes are inverted to predict the spatial distribution of the subsurface elastic properties. In subsequent steps of the geomodelling… read more here.
Keywords: seismic inversion; rock; methodology; inversion methods ... See more keywords
Two-level uncertainty assessment in stochastic seismic inversion based on the gradual deformation method
Sign Up to like & getrecommendations! Published in 2020 at "GEOPHYSICS"
DOI: 10.1190/geo2019-0492.1
Abstract: Geostatistical seismic inversion can combine seismic data, well data, and spatial continuity of the property of interest to obtain high-resolution reservoir models and evaluate uncertainties. Some workflows estimate global geostatistical parameters, such as correlation length,… read more here.
Keywords: inversion; uncertainty; gradual deformation; method ... See more keywords
A dual formulation of wavefield reconstruction inversion for large-scale seismic inversion
Sign Up to like & getrecommendations! Published in 2021 at "GEOPHYSICS"
DOI: 10.1190/geo2020-0743.1
Abstract: Many of the seismic inversion techniques currently proposed that focus on robustness with respect to the background model choice are not apt to large-scale 3D applications, and the methods that are computationally feasible for industrial… read more here.
Keywords: large scale; inversion; seismic inversion; wavefield reconstruction ... See more keywords
Introduction to special section: Seismic inversion — Conventional seismic impedance inversion and advanced seismic inversion techniques: Developments, workflow, and case studies
Sign Up to like & getrecommendations! Published in 2017 at "Interpretation"
DOI: 10.1190/int-2017-0612-spseintro.1
Abstract: Seismic inversion is a key component of the quantitative seismic interpretation workflows for hydrocarbons exploration and production. In exploration with limited well control, seismic inversion for acoustic impedance helps to understand the spatial variations and… read more here.
Keywords: special section; section seismic; inversion; seismic inversion ... See more keywords
Analysis of Deep Learning Neural Networks for Seismic Impedance Inversion: A Benchmark Study
Sign Up to like & getrecommendations! Published in 2022 at "Energies"
DOI: 10.3390/en15207452
Abstract: Neural networks have been applied to seismic inversion problems since the 1990s. More recently, many publications have reported the use of Deep Learning (DL) neural networks capable of performing seismic inversion with promising results. However,… read more here.
Keywords: neural networks; inversion; learning neural; seismic inversion ... See more keywords