Blind Curvelet based Denoising of Seismic Surveys in Coherent and Incoherent Noise Environments

The localized nature of curvelet functions, together with their frequency and dip characteristics, makes the curvelet transform an excellent choice for processing seismic data. In this work, a denoising method is proposed based on a combination of the curvelet transform and a whitening filter along with procedure for noise variance estimation. The whitening filter is added to get the best performance of the curvelet transform under coherent and incoherent correlated noise cases, and furthermore, it simplifies the noise estimation method and makes it easy to use the standard threshold methodology without digging into the curvelet domain. The proposed method is tested on pseudo-synthetic data by adding noise to real noise-less data set of the Netherlands offshore F3 block and on the field data set from east Texas, USA, containing ground roll noise. Our experimental results show that the proposed algorithm can achieve the best results under all types of noises (incoherent or uncorrelated or random, and coherent noise)

Seismic resolution enhancement in shale-oil reservoirs

We developed a case study of seismic resolution enhancement for shale-oil reservoirs in the Q Depression, China, featured by rhythmic bedding. We proposed an innovative methodology for the resolution enhancement, a full-band extension method, and implemented this method in three consecutive steps: wavelet extraction, filter construction and data filtering. First, we extracted a constant-phase wavelet from the entire seismic data set. Then, we constructed the full-band extension filter in the frequency domain using the least-squares inversion method. Finally, we applied the band extension filter to the entire seismic data set. We demonstrated that this full-band extension method, with a stretched frequency band from 7-70 Hz to 2-90 Hz, may significantly enhance the 3D seismic resolution and distinguish reflection events of the rhythmite groups in shale-oil reservoirs

Compensation of Absorption Effects in Seismic Data

The frequency content of seismic data is changing with propagation depth due to intrinsic absorption. This implies that the higher frequencies are highly attenuated, thus leading to a loss in resolution of the seismic image. In addition, absorption anomalies, for example, caused by gas sands, will further dim the seismic reconstruction. It is possible to correct for such absorption effects by employing so called inverse Q filtering (IQF). This is a filtering technique that tries to restore the loss of the higher frequencies due to propagation. Newer developments within IQF can be regarded as a migration type of algorithm, and such classes of techniques are studied in this paper. As seismic waves travel through the earth, the visco-elasticity of the earth's medium will cause energy dissipation and waveform distortion. This phenomenon is referred to as seismic absorption. In explaining the propagation of seismic wave in a given medium we explore the relationship between the pressure and displacement stresses. Therefore, by introducing an absorption function into the stress and strain relationship we derived a non-linear wave equation. We, then, employed a layered earth model to solve the non-linear wave equation

Full Waveform Inversion for Time-Distance Helioseismology

Inferring interior properties of the Sun from photospheric measurements of the seismic wavefield constitutes the helioseismic inverse problem. Deviations in seismic measurements (such as wave travel times) from their fiducial values estimated for a given model of the solar interior imply that the model is inaccurate. Contemporary inversions in local helioseismology assume that properties of the solar interior are linearly related to measured travel-time deviations. It is widely known, however, that this assumption is invalid for sunspots and active regions, and likely for supergranular flows as well. Here, we introduce nonlinear optimization, executed iteratively, as a means of inverting for the sub-surface structure of large-amplitude perturbations. Defining the penalty functional as the $L_2$ norm of wave travel-time deviations, we compute the the total misfit gradient of this functional with respect to the relevant model parameters %(only sound speed in this case) at each iteration around the corresponding model. The model is successively improved using either steepest descent, conjugate gradient, or quasi-Newton limited-memory BFGS. Performing nonlinear iterations requires privileging pixels (such as those in the near-field of the scatterer), a practice not compliant with the standard assumption of translational invariance. Measurements for these inversions, although similar in principle to those used in time-distance helioseismology, require some retooling. For the sake of simplicity in illustrating the method, we consider a 2-D inverse problem with only a sound-speed perturbation.Comment: 24 pages, 10 figures, to appear in Ap

INVERSE ATTENUATION-FILTERING

When seismic waves propagate through the Earth, they are affected by numerous inelastic effects of the medium. These effects are usually characterized by the concept of the Q-factor and lead to variations of spectra of the signal and shapes of the waveforms, which further affect the results of reflection seismic imaging. Attenuation compensation, also often called the inverse Q filtering is a signal-processing procedure broadly used to compensate both of these effects of attenuation in reflection sections or volumes. The objective of this thesis is to present and investigate a new attenuation-compensation approach that is much more general than the conventional inverse Q filtering

COMPARISON OF DIFFERENT SEISMIC FILTERING TECHNIQUES ON PRESTACK INVERSION FOR PENOBSCOT AREA-NOVA SCOTIA

The goal of this study is to compare three different type of seismic filtering according to their inversion results and their quality of data improvements. To do this bandpass filter, Inverse Q, and Radon transform are applied to the original NMO corrected pre-stack data from Nova-Scotia offshore Canada. The seismic data used was provided as pre-stack data of generally good quality. The test for quality of data improvement comes from the results of inversion based on different types of filtering performed on the pre-stack gathers. Bandpass filter, Inverse Q, and Radon transform are applied to the migrated prestack data, over the time range of 0-6000 ms. The Radon transform yields a better seismic image than the bandpass and inverse Q filters, since it removes the noise and the multiples from the data quite efficiently. The respective data volumes were inverted for acoustic impedance using simultaneous prestack inversion. The Radon filtered data provided the best inversion results, based on the continuity of layers and lack of apparent artifacts or noise. The Radon filter does not appreciably alter the frequency content of the data while removing events with moveout inconsistent with primary arrivals. It is likely that the processed data provided originally contained an excellent wavelet, and the other filters were unable to improve upon it, but did diminish the information present, particularly at the lower frequencies, decreasing the quality of the inversion results