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Migration velocity analysis and prestack migration of common-transmitter GPR data

机译:共发GPR数据的迁移速度分析和叠前偏移

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The accuracy of a migration image of ground-penetrating radar (GPR) depends strongly on the accuracy of permittivity distribution determined from multioffset data. This paper proposes a migration velocity analysis method using a genetic algorithm (GA). The objective function is defined as the summation of normalized zero-delay cross correlation of all common-image point gathers. Under the assumptions that the media are blockwise and that the permittivity of each block can be expressed as a polynomial with limited terms, all coefficients of the permittivity function of each block, which maximize the objective function, are determined by migration velocity analysis method with GA. Prestack migration is performed by a reverse-time migration method based on Maxwell's equations solved by the finite-difference time-domain method with a perfectly matched layer absorbing boundary conditions. The migration velocity analysis method is applied to synthetic common-transmitter datasets to test the method. Then, the velocity analysis and prestack migration method are applied to field data. From the distribution of dielectric constant obtained from the field data, water content is derived, and the depth of a water aquifer is deduced from the water content distribution and a migration stack profile.
机译:探地雷达(GPR)的偏移图像的准确性很大程度上取决于从多偏移量数据确定的介电常数分布的准确性。本文提出了一种使用遗传算法(GA)的迁移速度分析方法。目标函数定义为所有共同图像点集的归一化零延迟互相关的总和。在假设介质是块状并且每个块的介电常数可以表示为有限项的多项式的假设下,通过GA的迁移速度分析方法确定每个块的介电函数的所有系数(使目标函数最大化) 。叠前偏移是通过基于麦克斯韦方程组的逆时偏移方法进行的,该方程由有限差分时域方法求解,吸收层边界条件完美匹配。将迁移速度分析方法应用于合成的普通变送器数据集以测试该方法。然后,将速度分析和叠前偏移方法应用于现场数据。根据从现场数据获得的介电常数分布,可以得出含水量,并根据含水量分布和迁移叠层剖面推导出含水层的深度。

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