We describe a two-step Bayesian algorithm for seismic-reservoir characterization, which, thanks to some simplifying assumptions, is computationally very efficient. The applicability and reliability of this method are assessed by comparison with a more sophisticated and computer intensive Markov Chain Monte Carlo (MCMC) algorithm, which in a single-loop directly estimates petrophysical properties and litho-fluid facies from pre-stack data. The two-step method first combines a linear rock-physics model with the analytical solution of a linearized amplitude versus angle (AVA) inversion, to directly estimate petrophysical properties, and related uncertainties, from pre-stack data under the assumptions of a Gaussian prior model and weak contrast...
We implement a transdimensional Bayesian inversion that infers petrophysical reservoir properties, l...
We apply a target-oriented amplitude versus angle (AVA) inversion to estimate the petrophysical prop...
We apply three methods that use different regularization strategies to insert spatial constrains int...
We describe a two-step Bayesian algorithm for seismic-reservoir characterization, which, thanks to s...
In geophysical inverse problems, the posterior model can be analytically assessed only in case of li...
One of the main objectives of reservoir characterization is to exploit the acquired seismic and well...
We infer the elastic and petrophysical properties from pre-stack seismic data through a transdimensi...
Seismic reservoir characterization uses pre-stack reflection seismic data to describe the spatial va...
Recent advances in seismic-constrained reservoir characterization combine statistical rock-physics a...
We implement a fast, single-step, Bayesian inversion algorithm that directly infers the relevant pet...
We formulate the amplitude versus angle (AVA) inversion in terms of a Markov Chain Monte Carlo (MCMC...
Determination of a petroleum reservoir structure and rock bulk properties relies extensively on infe...
textOne of the important goals in petroleum exploration and production is to make quantitative estim...
Algorithms for inversion of seismic prestack AVO data into lithology-fluid classes in a vertical pro...
We have developed a one-step approach for Bayesian prediction and uncertainty quantification of lith...
We implement a transdimensional Bayesian inversion that infers petrophysical reservoir properties, l...
We apply a target-oriented amplitude versus angle (AVA) inversion to estimate the petrophysical prop...
We apply three methods that use different regularization strategies to insert spatial constrains int...
We describe a two-step Bayesian algorithm for seismic-reservoir characterization, which, thanks to s...
In geophysical inverse problems, the posterior model can be analytically assessed only in case of li...
One of the main objectives of reservoir characterization is to exploit the acquired seismic and well...
We infer the elastic and petrophysical properties from pre-stack seismic data through a transdimensi...
Seismic reservoir characterization uses pre-stack reflection seismic data to describe the spatial va...
Recent advances in seismic-constrained reservoir characterization combine statistical rock-physics a...
We implement a fast, single-step, Bayesian inversion algorithm that directly infers the relevant pet...
We formulate the amplitude versus angle (AVA) inversion in terms of a Markov Chain Monte Carlo (MCMC...
Determination of a petroleum reservoir structure and rock bulk properties relies extensively on infe...
textOne of the important goals in petroleum exploration and production is to make quantitative estim...
Algorithms for inversion of seismic prestack AVO data into lithology-fluid classes in a vertical pro...
We have developed a one-step approach for Bayesian prediction and uncertainty quantification of lith...
We implement a transdimensional Bayesian inversion that infers petrophysical reservoir properties, l...
We apply a target-oriented amplitude versus angle (AVA) inversion to estimate the petrophysical prop...
We apply three methods that use different regularization strategies to insert spatial constrains int...