Application Of Rock Physics Theory In Seismic Reservior Discrimination

The study of reservoir prediction is mainly to investigate the characteristics of reservoir structure, lithologic features and reservoir parameters, aim to reduce the risk of exploration. Reservoir parameters include porosity, permeability, fluid type, etc., but seismic data only reflects on seismic traveltime, amplitude information, and elastic parameters which can be obtained through seismic inversion. Seismic rock physics builds bridges for reservoir parameters and elastic parameters. This dissertation discusses the relationship between reservoir properties, fluid characteristics and seismic response characteristics under different geological conditions, establishing rock physics analysis models of different scale, carrying out the studies of S-wave velocity estimate method, AVO forward modeling based on rock physics, seismic singularities attributes extraction, etc., in combination with earthquake absorption characteristics and post-stack and pre-stack inversion technologies to perform the prediction of reservoir lithology and fluid detection.S-wave velocity, an important geophysical parameter, plays an important role in pre-stack seismic reservoir elastic parameter inversion and fluid detection which developed in recent years. In this dissertation, the author delves into the study of meticulous estimate method of S-wave velocity through the seismic rock physics model and pre-stack elastic wave waveform inversion, using Xu-White model as the initial model to calculate rock module. The model is a sandshale medium model, taking into account of the differences of sandshale porosity and pore space shape, overcoming the shortcomings of traditional equivalent medium models. On this basis, well log reconstruction inversion method is employed to make modification to the experience modulus parameters which are necessary for the model; pre-stack seismic waveform inversion method is used to further amend the S-wave velocity from the well log reconstruction to finally get high precision S-wave velocity. The methodology takes into account the impact of different lithological pore shape and corrects the error of the original model parameters, combining rich amplitude and travel time information of pre-stack seismic data, so that the estimated S-wave is more reasonable, laying technical foundation for further research of reservoir prediction and fluid discrimination.AVO analysis performs the analysis and inversion of the lithology through reflection amplitude variation with offset distance., We get P and S wave velocities and density through the S-wave estimate method put forward in this dissertation, building AVO forward model; and forward modeling is used to analyze AVO characteristics of oil-gas-water and special lithologic bodies under different geological conditions, so as to establish corresponding detection signs, which are useful for oil gas and lithology discrimination from the actual seismic records directly. Traveltime and amplitude calculation are critical for forward modeling. This dissertation calculates traveltime and determines the angle of incidence in the method of ray tracing with constant velocity gradient, using Zoeppritz equation to obtain the amplitude value. Ray tracing forward modeling approach is more applicable to vertical non-uniform strata, and the experimental results show that the stability and accuracy of the algorithm have been up to the requirements of forward modeling. The dissertation studies typical AVO reservoirs in this method, and analyzes AVO effects of different fluids and seismic properties discrimination model, with the forward modeling analysis of fluid substitution.Through studying certain actual work area, S-wave velocity estimation results above are separately applied to seismic singularity attribute extraction and elastic impedance inversion detection. Seismic data reflects the lithology (velocity and density) as well as seismic singularity attributes on the transition interface. This dissertation gives a description of external morphology of geological bodies as well as a clear presentation of sediment interface and deposition stages in the fans, which provides an effective guarantee for the further precise interpretation and prediction of reservoirs in geologic bodies, by using wavelet transformation characterized by its good time-frequency localization properties, which can depict the location and size of the singular points of the seismic signal through Lipschitz index, to detect the local singularity of seismic signals and using wavelet transformation coefficient modulus maxima method to extract seismic singularity attributes. Pre-stack elastic impedance inversion can be performed by making full use of stacking gathers of the angles which reflect the AVO, so it has high fidelity and much information. Then elastic impedance data derived from the above inversion can be used to obtain the lithologic parameters reflecting the characteristics of lithology and fluid, such as P-wave velocity, shear velocity, density, longitudinal and transversal wave velocity ratio and Poisson's ratio, etc. by further calculation, and finally rich AVO (or AVA) attributes will be gained to help us describe the underground reservoir more accurately.