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Joint Impedance and Facies Inversion – Seismic inversion redefined
First Break, 2014In this paper we will first review the industry-standard simultaneous inversion method (which derives continuous impedances) and subsequently identify some pitfalls. We will then introduce our new Joint Impedance and Facies Inversion technology (which we call Ji-Fi for short in this paper), which overcomes these pitfalls by recasting the seismic ...
Michael Kemper, James Gunning
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A hybrid joint‐inversion scheme
SEG Technical Program Expanded Abstracts 2011, 2011s, 719–723. Backus, G. E., 1962, Long-wave elastic anisotropy produced by horizontal layering: Journal of Geophysical Research, 67, no. 11, 4427–4440, doi:10.1029/JZ067i011p04427. Chen, J., and T. A. Dickens, 2009, Effects of uncertainty in rock-physics models on reservoir parameter estimation using seismic amplitude variation with angle and controlled-
Charlie Jing +7 more
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2022
<div> <p><span>The Earth crust represents less than 1% of the volume of our planet but is exceptionally important as it preserves the signs of the geological events that shaped our planet. This thin layer is the place where the natural resources we need can be accessed (e.g.&#160; critical raw materials,
Martina Capponi, Daniele Sampietro
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<div> <p><span>The Earth crust represents less than 1% of the volume of our planet but is exceptionally important as it preserves the signs of the geological events that shaped our planet. This thin layer is the place where the natural resources we need can be accessed (e.g.&#160; critical raw materials,
Martina Capponi, Daniele Sampietro
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Joint Inversion on Irregular Meshes
24th European Meeting of Environmental and Engineering Geophysics, 2018The design of structural coupling operators for joint inversion on irregular meshes is a non-trivial task. We propose to use a neighbourhood approach to calculate the model-gradients that are needed for the cross-gradients coupling constraints. Our joint inversion algorithm is applied to 3D synthetic crosshole GPR traveltime and apparent resistivity ...
C. Jordi +3 more
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Model Fusion and Joint Inversion
Surveys in Geophysics, 2013Inverse problems are inherently non-unique, and regularization is needed to obtain stable and reasonable solutions. The regularization adds information to the problem and determines which solution, out of the infinitely many, is obtained. In this paper, we review and discuss the case when a priori information exists in the form of either known ...
Eldad Haber, Michal Holtzman Gazit
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3D Joint hydrogeophysical inversion using similarity measures
Applied Mathematics and Computation, 2019zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Steklova, Klara, Haber, Eldad
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Joint Inversion of Multiple Observations
2018Joint inversion becomes increasingly important with the availability of various types of measurements related to the same quantity. Questions arising in this context are how to combine the different data sets in the first place and, secondly, how to choose the multiple parameters that naturally occur in such a combination.
Christian Gerhards +2 more
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Joint Inversion: One Mans Perspective
81st EAGE Conference and Exhibition 2019 Workshop Programme, 2019Summary Tremendous advances have been made in the last two decades in joint inversion of multiple data sets. Coupling of all forms of geophysical data and flow data have been demonstrated. Advances in methods to link the data sets and associated parameters, both by structural and rock-physics coupling approaches have been key to the impressive results ...
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2002
Ambiguous dependence of observed data related to lithologic parameters suggests that both deterministic mechanism and statistical behaviour characterize practical lithologic inversion problems. The Caianiello neural network method is presented in this paper, including neural wavelet estimation, input signal reconstruction, and nonlinear factor ...
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Ambiguous dependence of observed data related to lithologic parameters suggests that both deterministic mechanism and statistical behaviour characterize practical lithologic inversion problems. The Caianiello neural network method is presented in this paper, including neural wavelet estimation, input signal reconstruction, and nonlinear factor ...
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Bayesian Joint Inversion of Geophysical Data
63rd EAGE Conference & Exhibition, 2001P220 BAYESIAN JOINT INVERSION OF GEOPHYSICAL DATA Summary 1 A new method for the joint inversion of geophysical data based on the Bayesian framework has been developed. Contrary to the traditional joint inversion that simply incorporates two different kinds of observed data into one sensitivity matrix a probabilistic approach has been devised to infer ...
O.S. Hoon, B.D. Kwon, J.C. Nam, D. Lee
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