We have developed an efficient stochastic AVA inversion technique that works directly in a fine-scale stratigraphic grid, and is conditioned by well data and multiple seismic angle stacks. We use a Bayesian framework and a linearized, weak contrast approximation of the Zoeppritz equation to construct a joint log-Gaussian posterior distribution for Pand S-wave impedances. We apply a Sequential G...

various methods for parametric interpolation of nurbs curves have been proposed in the past. however, the errors caused by the approximate nature of the nurbs interpolator were rarely taken into account. this paper proposes an integrated look-ahead algorithm for parametric interpolation along nurbs curves. the algorithm interpolates the sharp corners on the curve with the pythagorean-hodograph ...

This paper presents a uniied analysis of decomposition algorithms for continuously diierentiable optimization problems deened on Cartesian products of convex feasible sets. The decomposition algorithms are analyzed using the framework of cost approximation algorithms. A convergence analysis is made for three decomposition algorithms: a sequential algorithm which encompasses the classical Gauss{...

Interactive POMDP (I-POMDP) is a stochastic optimization framework for sequential planning in multiagent settings. It represents a direct generalization of POMDPs to multiagent cases. Expectedly, I-POMDPs also suffer from a high computational complexity, thereby motivating approximation schemes. In this paper, we propose using a particle filtering algorithm for approximating the I-POMDP belief ...

In this paper, we develop a qualitative theory of influence diagrams that can be used to model and solve sequential decision making tasks when only qualitative (or imprecise) information is available. Our approach is based on an orderof-magnitude approximation of both probabilities and utilities and allows for specifying partially ordered preferences via sets of utility values. We also propose ...

Using a sequential Monte Carlo algorithm, we compute a spectral approximation of the solution of the Poisson equation in dimension 1 and 2. The Feyman-Kac computation of the pointwise solution is achieved using either an integral representation or a modified walk on spheres method. The variances decrease geometrically with the number of steps. A global solution is obtained, accurate up to the i...

Using a sequential Monte Carlo algorithm, we compute a spectral approximation of the solution of the Poisson equation in dimension 1 and 2. The Feyman-Kac computation of the pointwise solution is achieved using either an integral representation or a modified walk on spheres method. The variances decrease geometrically with the number of steps. A global solution is obtained, accurate up to the i...

Bit-interleaved coded modulation with iterative detection for MIMO systems demands an efficient APP detector that delivers soft information about the coded bits. The list-sequential detector is a reduced-complexity approximation to an exhaustive APP detector. It uses a tree search employing the stack algorithm to find dominant terms of the log-likelihood ratio (LLR). We show how incomplete tree...