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Research On Bayesian Inversion Method Applied To Appraisal And Prediction Of Reservoir Using Seismic Data

Posted on:2009-05-08Degree:MasterType:Thesis
Country:ChinaCandidate:W T WangFull Text:PDF
GTID:2120360242497885Subject:Earth Exploration and Information Technology
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With development of the oil and gas exploration in many large oil fields, seismic reservoir prediction techniques have been widely applied and are an effective means to find the subtle hydrocarbon reservoir currently. Seismic inversion is the key technology of the reservoir prediction, but conventional inversion methods have limitations in practical application. One is difficult to quantify information about uncertainty of the estimated parameters; another is not easy to constrain inversion using simultaneously various types and precision prior information from borehole, geophysical measurements, geological information, and so on. To overcome these limitations, Bayesian Inversion Method to apply the reservoir prediction in using seismic data has been proposed in this paper.Bayesian Inversion Method belongs to the one of the uncertainty inversion methods. It is a new inversion method based on Bayesian theory and stochastic inverse methods. To complete the purpose of the research project and to overcome the problems of conventional inversion methods, what the author did are to:1. Surveying the geological structure in work area, and also summing up the parameters' range and relationship among them about lithology and physical properties.2. The theory, implementation and application of Bayesian inversion method were studied deeply. In the same condition, the results of Bayesian inversion are more accurate than those of conventional inversion compared by a numerical test.3. Basing on analysis of the theory of demigration, I combined 15°finite difference demigration and Bayesian inversion method for the inversion of 2-D wave equation Bayesian using only synthetic seismic data.4. According to the geological investigation results in field, a typical model of marine reservoir zone, which based on Ordovician reef community in Tarim Basin, was constructed. Then two numerical tests are done and the results using Bayesian Inversion Method compared with those using conventional inversion methods are analyzed.5. Combining various prior information, impedance inversion of a real seismic data is presented using Bayesian inversion method. Then the effect of wavelet to the inversion results is discussed. This study proved that Bayesian Inversion Method is very practical for reservoir prediction. Within the Bayesian framework, lithologic parameters are considered as random variables and are estimated simultaneously by conditioning to prior information which is transformed into the form of probability. Bayesian Inversion Method not only makes us get better result than conventional inversion methods, but also provides information about uncertainty of estimated model, such as mean, variance and probability density function. These results obviously are more significant than the best result that is provided by conventional methods, and the uncertainty information of result is a quantitative basis for decision of the oil and gas exploration and development.In this paper there are six chapters and its detail contents are arranged as follows:The first chapter is the introduction, which summarizes the research objectives and the research procedure.In second chapter, the theory of Simulated Annealing is introduced. The physical phenomenon of solid annealing process in thermophysics, Metropolis criterion, algorithm structure of Simulated Annealing and annealing parameters for choice are discussed.Chapter three describes the theory of Bayesian inversion method and provides the Bayesian inversion method flowchart.The fourth chapter discusses the technique of Bayesian inversion combine acoustic wave equation demigration with 15°finite difference scheme, and also gives an example of inversing the stratum velocity parameters using a small geological model.Chapter five shows the application of Bayesian inversion to synthetic migrated data and real migrated seismic data combined with the prior information in work area.The sixth chapter, last one, summarizes systematically the research work of this paper and gives suggestions for further research.
Keywords/Search Tags:Bayes, seismic inversion, reservoir prediction, simulated annealing
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