Study On Multi-wave Pre-stack AVA Nonlinear Inversion

The elastic parameters of formation are related with lithology and fluid properties, so they are very important for hydrocarbon detection and reservoir description. P-wave velocity, S-wave velocity and density are three main parameters which can descript the formation. In addition, Pre-inversion is an effective method to obtain the value of these three parameters.On the background of seismic wave propagation theory and adopting the simulated annealing and genetic algorithm, this thesis researched the multi-wave pre-stack nonlinear inversion. The data used for the inversion is multi-wave pre-stack NMO gathers.First, this thesis inversed the parameters of single layer-model by using the parameters of upper-layer and the AVA curve of the reflector to inverse the parameters of under-layer. Even the initial model is far from the true one, high precision parameters can still be obtained. But the inversion method has a strong dependence on the upper parameters, and its efficiency is so poor that can't apply to the inversion of multi-layer.Considering the applicability and efficiency factors, multi-layer model has been established. This model used the error function of angle gather as the objective function to achieve simultaneous inversion. The result of inversion shows it has the advantage of not relying on initial model. According to computing response of every parameter's disturbance, the sensitivity of parameters has been analyzed. Furthermore the feasibility of the objective function has been demonstrated.In order to adapting the simultaneous optimization of multi-parameter, this thesis made some improvement for algorithms and model which are as follows: (1) The improvements on SA including fast heat-bath, returning temperature strategy, memory function and changing the classical SA to very fast SA. (2) Switching float encoding to quinary encoding mechanism which is more suitable for geophysical inversion problem to improve GA. (3) The improved method adopted sample points model and layer model, the sample point model focused on layer and aimed at determining the reflection interface, layer model focused on inversing high accuracy parameters of layers. Combining the advantages of these two models can realize progressive inversion. (4) This thesis also jointed PP-wave and PSV-wave to realized inversion. Compared to the sole-wave inversion, joint inversion can improve the accuracy, especially for the S-wave velocity.The improved inversion method has high accuracy for a variety of theoretic models. It has low dependence on the initial model and strong resistance to noise. It can be applied to the real seismic data and get good inversion result. The inversion results can provide a high-quality original model for linear and generalized linear inversion; also it can give a reference for the reservoir description.