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Study Of The Elastic Parameters Inversion Base On Immune Genetic Algorithm

Posted on:2009-06-18Degree:MasterType:Thesis
Country:ChinaCandidate:A T WangFull Text:PDF
GTID:2120360245987459Subject:Communication and Information System
Abstract/Summary:PDF Full Text Request
Bright spot technique and AVO technique, rising in the eighties of the 20th century, have an important role in hydrocarbon detection. Many gas pools in the Gulf of Mexico and China's Sichuan Chuandong, the Shengli Oilfield in many areas mainly depend on the discovery of the technology. In the past, the bright spot technique and AVO technique were mainly used for hydrocarbon detection qualitatively, but they were rarely used to calculate lithology parameters quantitatively.The current study is based on AVO Zoeppritz equation and its approximate formula, with the development of oil and gas exploration, the interest layer is getting thin, and even some beds'thicknesses are about 10m, and in some areas constructions are very complicated,so it is difficult to meet the assumption of Zoeppritz equation semi-infinite elastic medium interface. Therefore, based on Zoeppritz equation AVO technology in oil and gas exploration may bring greater error, especially for the oil and gas thin bed, accurate AVO analysis, the Zoeppritz equation is not suitable.In this paper, based on Brekhovski equation for horizontal multi-layered media, the simplified formula (ie, the three-layer media formula) is deduced and tested for a single thin bed, and then it is used to do the AVO analysis and inversion for the thin bed model.On the shortcomings of Genetic Algorithm,we combine it with the advantages of immune algorithm immunologic memory, self-regulation and diverse function to maintain,and immune genetic optimization algorithm(IGA)is established. IGA improves the "premature" phenomenon, has good convergence, improves the computational efficiency and be suitable for multi-parameter and multi-extremum geophysical inversion problem.To the thin bed geological model, we use the immune genetic algorithm to design a middle layer inversion process.The calculation results of a number of stratigraphic model show that this algorithm is stable and efficient. Applying the IGA to P-wave AVO inversion, the elastic parameters of middle layer including the P-wave velocity,transverse wave velocity and density are better estimated, suitable for thin elastic parameters inversion.Joint geophysical inversion by which the inversion non-uniquenesses are effectively restricted are attracting increasing attention. In this paper,we explain the superiority of multi-wave exploration which has great significance on increasing the effects of reflected wave seismic exploration project in the investigation by P-wave and S-wave exploration examples.
Keywords/Search Tags:AVO inversion, immune genetic algorithm, thin layer, joint inversion
PDF Full Text Request
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