Seismic inversion is a method that extracts acoustic impedance data from the seismic traces. Source wavelets are band-limited, and thus seismic traces do not contain low and high frequency information. Therefore, there is a serious problem when the deterministic seismic inversion is applied to real data and the result of deterministic inversion is smooth. Low frequency component is obtained fro...

The aim of seismic inversion is mapping all of the subsurface structures from seismic data. Due to the band-limited nature of the seismic data, it is difficult to find a unique solution for seismic inversion. Deterministic methods of seismic inversion are based on try and error techniques and provide a smooth map of elastic properties, while stochastic methods produce high-resolution maps of el...

In this paper, I present a modification of the Beylkin inversion operator. This modification accounts for the band-limited nature of the data and makes the role of discontinuities in the sound speed more precise. The inversion presented here partially dispenses with the small-parameter constraint of the Born approximation. This is shown by applying the proposed inversion operator to upward scat...

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...

We develop a systematic approach for the analysis of 2-D refraction experiments using traveltimes that allows progressive improvement of velocity structure through a sequence from 1-D models to pseudo-2-D models, and then 2-D models. The approach consists of three steps. First, 1-D velocity models are constructed for each segment of the pro¢le using a genetic algorithm inversion, and then pseud...

Deep-learning has achieved good performance and demonstrated great potential for solving forward inverse problems. In this work, two categories of innovative deep-learning-based modeling methods are proposed compared. The first category is deep-learning surrogate-based inversion methods, in which the Theory-guided Neural Network (TgNN) constructed as a surrogate problems with uncertain model pa...

seismic inversion is a method that extracts acoustic impedance data from the seismic traces. sourcewavelets are band-limited, and thus seismic traces do not contain low and high frequency information.therefore, there is a serious problem when the deterministic seismic inversion is applied to real dataand the result of deterministic inversion is smooth. low frequency component is obtained from w...

in this paper we get some results and applications for duals and approximate duals of g-frames in hilbert spaces. in particular, we consider the stability of duals and approximate duals under bounded operators and we study duals and approximate duals of g-frames in the direct sum of hilbert spaces. we also obtain some results for perturbations of approximate duals.

Oculo-auriculovertebral dysplasia (Goldenhar) is a congenital syndrome. Its phenotype differs from craniofacial anomalies to cardiac, vertebral or central nervous system defects. This syndrome is rare and its etiology is not apparent yet. Pericentric inversion of chromosome 9 is one of the most common structural balanced chromosomal aberrations with its incidences 15% to 25%. Herein we present ...

here in, an application of a new seismic inversion algorithm in one of iran’s oilfields is described. stochastic (geostatistical) seismic inversion, as a complementary method to deterministic inversion, is perceived as contribution combination of geostatistics and seismic inversion algorithm. this method integrates information from different data sources with different scales, as prior informat...