We present a new seismic inversion method that uses deep learning (DL) features for the subsurface velocity model estimation. The DL feature is low-dimensional representation of high-dimensional data, which automatically generated by convolutional autoencoder (CAE) and preserved in latent space. contains key information input data. Therefore, instead directly comparing waveform differences betw...

We consider a Bayesian model for doing lithology–fluid prediction from prestack (amplitude versus offset) seismic data. Related to the Bayesian model, we look at two inversion algorithms. The first algorithm simulates from the posterior distribution with no approximations, but the algorithm is quite computer demanding. The second inversion algorithm introduces an approximation in the likelihood...

A method to estimate S-wave interval velocity, using P-S seismic data is presented. The method is composed of three steps. First, the P-S data are converted to a relative change in S-velocity section. The section is then linearized. Constrained inversion is used to convert this last section to S-interval velocity. To illustrate the method, the S velocity of a field data set was derived, and a V...

The word tomography finds its origins in the two Greek words tomos, meaning section, and graphy, which translates as drawing. There are many different types of tomography used in many sciences such as medicine, biology, materials science and geology. The basic idea of tomography in all of its uses is to obtain a cross-section of an object which will then be used to infer various facts regarding...

The Helium abundance in the solar envelope is one of the most important seismic observables. We investigate the accuracy of its determination taking into account uncertainties in the data and in the inversion procedure. Our best value for the helium abundance in the photosphere is Y = 0.248. The estimated uncertainty of 0.002 is dominated by uncertainties in the inversion. This does not account...

Algorithms for inversion of seismic prestack AVO data into lithology-fluid classes in a vertical profile are evaluated. The inversion is defined in a Bayesian setting where the prior model for the lithology-fluid classes is a Markov chain, and the likelihood model relates seismic data and elastic material properties to these classes. The likelihood model is approximated such that the posterior ...

Heavy crude oil is known as oil that is highly viscous and of a higher density than that of conventional oil. Sand reservoirs containing heavy oil generally consist of unconsolidated sediments deposited at a shallow burial depth, with high porosity and permeability. In seismic exploration, acoustic impedance inversion is a commonly used tool in reservoir prediction. However, due to the unconsol...