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Study Of The Elastic Parameters Inversion Base On Improved Immune Algorithm

Posted on:2011-10-01Degree:MasterType:Thesis
Country:ChinaCandidate:Z L LiuFull Text:PDF
GTID:2120330332963648Subject:Signal and Information Processing
Abstract/Summary:PDF Full Text Request
AVO technique analyzes the characteristic and regular of the amplitude of the pre-stack seismic waves varied with the offset, from which the properties and lithology of the oil and gas reservoirs can be predicted and judged. In conventional AVO inversion, usual AVO attributes are obtained and can be interpreted in terms of anomalies. More recently, there has been an increasing effort to estimate the elastic parameters of the subsurface targets by means of AVO inversion.The theory of AVO is based on the Zoeppritz equations, which are complicated for reflection and transmission coefficients. This paper makes a contrastive study of the Zoeppritz equation and its different approximate equations, especially I picked out several representative and high precision equations from AVO approximate equations of the P-P and P-SV waves, which lay foundation for future AVO inversion.AVO inversion is a complicated nonlinear optimization problem, which is better achieved using global optimization methods. Conventional immune algorithm has the drawback of easily being trapped in a local optimal solution and slow convergence velocity. This paper studies an improved immune algorithm. This algorithm uses orthogonal crossover to generate initial population and uses elitist-crossover to increase the good patterns of the population and uses mixed mutation to enhance the ability of local and global optimization. IIA enhances local and global search ability, has good convergence, improves the computational efficiency and can be suitable for multi-parameter and multi-extremum geophysical inversion problem.Jointed exploration of the PP wave and P-SV wave can offer seismic lithology interpretation more information, implement refined parameters inversion exactly and improve the capacity of reservoir prediction. We use IIA to make P-wave inversion,S-wave inversion and joint inversion for different typical models and verify the stability of inversion. The results show that more stable and accurate inversion results of joint AVO inversion compared with P-P AVO inversion and P-SV AVO inversion are obtained.The results produced from traditional least-squares algorithm are unreliable when measurement data exist abnormal values, we study a kind of robust estimation algorithm in this paper. Applying robust estimation algorithm to joint inversion, the inversion results show that the method can more accurately estimate elastic parameters. Robust estimation algorithm proposed in this paper has a good prospect in other AVO inversion.
Keywords/Search Tags:AVO inversion, improved immune algorithm, joint inversion, robust estimation
PDF Full Text Request
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