A new inversion method to estimate high-resolution amplitude-versus-angle attributes (AVA) attributes such as intercept and gradient from prestack data is presented. The proposed technique promotes sparse-spike reflectivities that, when convolved with the source wavelet, fit the observed data. The inversion is carried out using a hybrid two-step strategy that combines fast iterative shrinkagethresholding algorithm (FISTA) and a standard least-squares (LS) inversion. FISTA, which can be viewed as an extension of the classical gradient algorithm, provides sparse solutions by minimizing the misfit between the modeled and the observed data, and the l1-norm of the solution. FISTA is used to estimate the location in time of the main reflectors. T...
Accurate mapping of subsurface structure through seismic techniques is essential in oil and gas expl...
Recent oil and gas exploration in the Lower Magdalena Valley, Northern Colombia, has shown the prese...
This thesis will address the large computational costs of solving least-squares migration and full-w...
A new inversion method to estimate high-resolution amplitude-versus-angle attributes (AVA) attribute...
With the purpose of characterizing the Earth subsurface, one of the objectives of the inversion of p...
We present a new inversion method to estimate, from prestack seismic data, blocky P- and S-wave velo...
Using seismic data, logging information, geological interpretation data, and petrophysical data, it ...
We present an algorithm to estimate blocky images of the subsurface acoustic impedance (AI) from pos...
Least squares deconvolution is a method used to sharpen tomographic images of the earth by undoing t...
This thesis covers seismic signal analysis and inversion. It can be divided into two parts. The firs...
In this work, the inverse problem of exploration geophysics is solved through two techniques based o...
Amplitude-versus-angle (AVA) inversion for pre-stack seismic data is a key technology in oil and gas...
Resolving thin layers and achieve focused layer boundaries is one of the major challenges in seismic...
Pre-stack seismic waveform inversion is a highly challenging task. Non-linearity and non-uniqueness ...
In many geophysical inverse problems, smoothness assumptions on the underlying geology are used to m...
Accurate mapping of subsurface structure through seismic techniques is essential in oil and gas expl...
Recent oil and gas exploration in the Lower Magdalena Valley, Northern Colombia, has shown the prese...
This thesis will address the large computational costs of solving least-squares migration and full-w...
A new inversion method to estimate high-resolution amplitude-versus-angle attributes (AVA) attribute...
With the purpose of characterizing the Earth subsurface, one of the objectives of the inversion of p...
We present a new inversion method to estimate, from prestack seismic data, blocky P- and S-wave velo...
Using seismic data, logging information, geological interpretation data, and petrophysical data, it ...
We present an algorithm to estimate blocky images of the subsurface acoustic impedance (AI) from pos...
Least squares deconvolution is a method used to sharpen tomographic images of the earth by undoing t...
This thesis covers seismic signal analysis and inversion. It can be divided into two parts. The firs...
In this work, the inverse problem of exploration geophysics is solved through two techniques based o...
Amplitude-versus-angle (AVA) inversion for pre-stack seismic data is a key technology in oil and gas...
Resolving thin layers and achieve focused layer boundaries is one of the major challenges in seismic...
Pre-stack seismic waveform inversion is a highly challenging task. Non-linearity and non-uniqueness ...
In many geophysical inverse problems, smoothness assumptions on the underlying geology are used to m...
Accurate mapping of subsurface structure through seismic techniques is essential in oil and gas expl...
Recent oil and gas exploration in the Lower Magdalena Valley, Northern Colombia, has shown the prese...
This thesis will address the large computational costs of solving least-squares migration and full-w...