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Common Reflection Surface Stack Based On Global Optimization Algorithm

Posted on:2022-04-28Degree:MasterType:Thesis
Country:ChinaCandidate:M R HouFull Text:PDF
GTID:2530307109461814Subject:Geophysics
Abstract/Summary:PDF Full Text Request
The current problem of seismic exploration is how to find hidden oil and gas reservoirs in complex areas.Seismic data obtained in areas with complex geological conditions often have low coverage and low signal-to-noise ratio,and it is difficult to accurately image them with conventional processing methods.The effect of the offset result obtained is also poor.To solve this kind of problems,the Common Reflection Surface stack method is proposed to improve data quality and strengthen deep imaging.The CRS stack based on the ray theory uses an analytical formula to express the kinematic reflection response of the curved interface of the inhomogeneous medium,and realizes the full use of the seismic information of the Fresnel zone.The signal-to-noise ratio is maximized under the premise of reducing the resolution.CRS stack depends on the kinematic wave field parameters,and these parameters need to be obtained by coherent analysis,and there is a situation of multi-parameter coupling.Conventional CRS stack is generally divided into multiple steps to obtain related parameters at one time,and the calculation cost is low,but it will systematically accumulate errors,which affects the accuracy of CRS attribute parameters,thereby limiting the final effect of CRS stack.In order to overcome this limitation,a CRS stack implementation strategy for determining multiple parameters at the same time is proposed,and the corresponding calculation cost is also increasing,so it is very necessary to adopt an efficient parameter search strategy.According to the structural parallelism of the global optimization algorithm,and accordingly proposes a genetic algorithm and simulated annealing hybrid parallel algorithm(GA-SAHP),which greatly improves the efficiency of CRS attribute parameter search and optimization,and greatly improves the parameters.Accuracy and the final stacking effect.Through trial calculations of 2D and 3D models,the feasibility and correctness of the method based on the GA-SAHP algorithm to simultaneously obtain the CRS stack attribute parameters are verified.Applied to the actual processing of 2D and 3D seismic data,compared with conventional CRS stack,this method consumes less time,improves efficiency,higher parameter accuracy,and significantly improves the stack effect.
Keywords/Search Tags:common reflection surface stack, parameter coupling, genetic algorithm, simulated annealing, parameter optimization
PDF Full Text Request
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