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首页> 外文期刊>IEEE Geoscience and Remote Sensing Letters >Fast Seismic Inversion Methods Using Ant Colony Optimization Algorithm
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Fast Seismic Inversion Methods Using Ant Colony Optimization Algorithm

机译:基于蚁群算法的快速地震反演方法

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摘要

This letter presents $hbox{ACO}_{BBR} hbox{-} V$, a new computationally efficient ant-colony-optimization-based algorithm, tailored for continuous-domain problems. The $hbox{ACO}_{BBR} hbox{-} V$ algorithm is well suited for application in seismic inversion problems, owing to its intrinsic features, such as heuristics in generating the initial solution population and its facility to deal with multiobjective optimization problems. Here, we show how the $hbox{ACO}_{BBR} hbox{-} V$ algorithm can be applied in two methodologies to obtain 3-D impedance maps from poststack seismic amplitude data. The first methodology pertains to the traditional method of forward convolution of a reflectivity model with the estimated wavelet, where $hbox{ACO}_{BBR} hbox{-} V$ is used to guess the appropriate wavelet as the reflectivity model. In the second methodology, we propose an even faster inversion algorithm based on inverse filter optimization, where $hbox{ACO}_{BBR} hbox{-} V$ optimizes the inverse filter that is deconvolved with the seismic traces and results in a reflectivity model similar to that found in well logs. This modeled inverse filter is then deconvolved with the entire 3-D seismic volume. In experiments, both the methodologies are applied to a synthetic 3-D seismic volume. The results validate their feasibility and the suitability of $hbox{ACO}_{BBR} hbox{-} V$ as an optimization algorithm. The results also show that the second methodology has the advantages of a much higher convergence speed and effectiveness as a seismic inversion tool.
机译:这封信介绍了 $ hbox {ACO} _ {BBR} hbox {-} V $ ,这是一种计算效率高的新蚁群基于优化的算法,专为连续域问题量身定制。 $ hbox {ACO} _ {BBR} hbox {-} V $ 算法非常适用于地震反演问题,由于其内在特征,例如生成初始解总体的启发式方法及其处理多目标优化问题的工具。在这里,我们展示了 $ hbox {ACO} _ {BBR} hbox {-} V $ 算法如何应用于从叠后地震振幅数据获得3-D阻抗图的两种方法。第一种方法与采用估计的小波的反射率模型正卷积的传统方法有关,其中 $ hbox {ACO} _ {BBR} hbox {-} V $ 用于猜测适当的小波作为反射率模型。在第二种方法中,我们提出了一种基于逆滤波器优化的更快的反演算法,其中 $ hbox {ACO} _ {BBR} hbox {-} V $ 优化了与地震迹线解卷积的逆滤波器,并产生了与测井曲线相似的反射率模型。然后将此建模的逆滤波器与整个3-D地震体积进行反卷积。在实验中,两种方法都适用于合成的3D地震体。结果验证了它们的可行性和适用性 $ hbox {ACO} _ {BBR} hbox {-} V $ 作为优化算法。结果还表明,第二种方法具有收敛速度快和作为地震反演工具的有效性的优点。

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