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Sobolev Scalar Products in the Construction of Velocity Models: Application to Model Hess and to SEG/EAGE Salt Model

机译:Sobolev标量产品在速度模型构建中的应用:在Hess模型和SEG / EAGE盐模型中的应用

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摘要

— The minimization of the Sobolev norm during linearized inversion of given data allows control of the model parameters unresolved by the data being fitted. Even if a reasonably looking model can be obtained without minimizing the Sobolev norm, it may be too rough for some computational methods. We may construct models optimally smooth for given computational methods by minimizing the corresponding Sobolev norm during the inversion. Probably the smoothest models are required by the ray methods. The efficiency of ray tracing can be evaluated in terms of the “average Lyapunov exponent” for the model. The “average Lyapunov exponent” may be approximated by the square root of the corresponding Sobolev norm of the model, which allows models most suited for ray tracing to be constructed.
机译:—在给定数据的线性求逆过程中,Sobolev范数的最小化允许控制模型参数,而该模型参数无法通过拟合数据来求解。即使可以在不使Sobolev范数最小的情况下获得合理外观的模型,对于某些计算方法来说,它可能也过于粗糙。我们可以通过在反演过程中最小化相应的Sobolev范数来构造给定计算方法的最佳平滑模型。射线方法可能需要最平滑的模型。可以根据模型的“平均Lyapunov指数”来评估光线跟踪的效率。 “平均李雅普诺夫指数”可以通过模型的相应Sobolev范数的平方根来近似,从而可以构建最适合射线追踪的模型。

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