This paper investigates the use of spectral decomposition for extracting information on fluid properties. Traditional theory for detecting fluid response is based on the pure elastic Gassman theory, and the resultant seismic effects are frequency-independent. Using dynamic fluid substitution, we demonstrate that the frequency response of seismic reflection and its resultant attenuation and dispersion are directly linked to fluid saturation. To extract this information, we develop an accurate two-stage spectral decomposition method by matching pursuit. This allows us to calculate a range of frequency-dependent attributes, such as, absorption coefficient and amplitude gradient in the frequency domain. Application to real data shows a good link between the anomalies and hydrocarbon saturation. The results highlight that careful data processing and modeling are necessary to understand the complex effect of different fluids on the spectral response and enable robust interpretation.
Using the empirical Gardner equation describing the relationship between density and compressional wave velocity, we propose converted wave reflection coefficient extreme attributes for AVO analysis and derive relations between the extreme position and amplitude, average velocity ratio across the interface, and shear wave reflection coefficient. The extreme position is a monotonically decreasing function of average velocity ratio, and the extreme amplitude is a function of average velocity ratio and shear wave reflection coefficient. For theoretical models, the average velocity ratio and shear wave reflection coefficient are inverted from the extreme position and amplitude obtained from fitting a power function to converted wave AVO curves. Shear wave reflection coefficient sections have clearer physical meaning than conventional converted wave stacked sections and establish the theoretical foundation for geological structural interpretation and event correlation. The method of inverting average velocity ratio and shear wave reflection coefficient from the extreme position and amplitude obtained from fitting a power function is applied to real CCP gathers.
We propose a practical approach to compensate for the diodic moveout of PS converted waves using a velocity perturbation method. In this approach, the diodic moveout can be decoupled into two parts. One part is related to a base velocity and the other part is related to a velocity perturbation. The base velocity is used to correct the curved feature of the diodic moveout and the velocity perturbation is used to correct the dipping feature of the diodic moveout. We have developed GUI tools to perform the diodic velocity analysis for stacking procedure and prestack time migration, and command line tools to perform the diodic moveout correction and prestack time migration with diodic moveout compensation. We have applied these tools to a real dataset and obtained improved images.