One of the most remarkable basis of the gravity data inversion is the recognition of sharp boundaries between an ore body and its host rocks during the interpretation step. Therefore, in this work, it is attempted to develop an inversion approach to determine a 3D density distribution that produces a given gravity anomaly. The subsurface model consists of a 3D rectangular prisms of known sizes ...

Frame design for phaseless reconstruction is now part of the broader problem of nonlinear reconstruction and is an emerging topic in harmonic analysis. The problem of phaseless reconstruction can be simply stated as follows. Given the magnitudes of the coefficients of an output of a linear redundant system (frame), we want to reconstruct the unknown input. This problem has first occurred in X-r...

In this paper the problem of estimating an unknown input for discretetime, non-minimum phase, multivariable, linear time-varying systems (LTV) is considered. The initial condition of the plant may be unknown and stochastic process and measurement noise are included. The input signal is modelled as a random walk with drifts. Then it is estimated using a Kalman filter for a uniformly detectable a...

Acoustic travel-time tomography allows one to reconstruct temperature and wind velocity fields in the atmosphere. In a recently published paper [S. Vecherin et al., J. Acoust. Soc. Am. 119, 2579 (2006)], a time-dependent stochastic inversion (TDSI) was developed for the reconstruction of these fields from travel times of sound propagation between sources and receivers in a tomography array. TDS...

In this paper we introduce a Bayesian framework for solving a class of problems termed Multi-agent Inverse Reinforcement Learning (MIRL). Compared to the well-known Inverse Reinforcement Learning (IRL) problem, MIRL is formalized in the context of a stochastic game rather than a Markov decision process (MDP). Games bring two primary challenges: First, the concept of optimality, central to MDPs,...

Snapping shrimp noise is thought to be a major component of ambient noise at high frequencies (2 kHz 300 kHz) in warm shallow water. We have designed an experiment to investigate its temporal and spatial distribution and variability. This information has application to many underwater acoustic systems in providing background knowledge about the structure of this class of noise. The experiment r...

This research successfully extends a deterministic, physically-based inverse theory that is capable of simultaneous parameter and boundary condition estimation to uncertainty quantification in inverting steady-state groundwater flow in a two-dimensional aquifer with facies heterogeneity. Using facies and dynamic flow measurements sampled at wells as observations, a stochastic subsurface data in...

Seismic inversion is one of the important methods to realize reservoir prediction in oil and gas field exploration. The seismic stochastic based on Metropolis-Hastings algorithm makes full use well logging data improves vertical resolution results. However, conventional has slow convergence speed poor stability. In this paper, an elastic impedance method optimized established by combining quant...

an experimental study of the phase inversion behavior of liquid-liquid dispersion has been conducted in a spray extraction column for systems of toluene / water, n-hexane/water, ccl4/water, toluene /water + glycerol (25 % wt), toluene + ccl4 (25 % wt) / water and toluene / acetic acid (5 % wt)/water. the effects of physical properties, mass transfer and column geometry on phase inversion have b...

The Euler equations subject to uncertainty in the input parameters are investigated via the stochastic Galerkin approach. We present a new fully intrusive method based on a variable transformation of the continuous equations. Roe variables are employed to get quadratic dependence in the flux function and a well-defined Roe average matrix that can be determined without matrix inversion. In previ...