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THE EFFECTS OF NOISE ON OCCAMS INVERSION OF RESISTIVITY TOMOGRAPHY DATA

机译:噪声对电阻率层析成像数据occams反演的影响

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An Occam's inversion algorithm for crosshole resistivity data that uses a finite-element method forward solution is discussed. For the inverse algorithm? the earth is discretized into a series of parameter blocks. each containing one or more elements, The Occam's inversion finds the smoothest 2-D model for which the Chi-squared statistic equals an a priori value. Synthetic model data are used to show the effects of noise and noise estimates on the resulting 2-D resistivity images. Resolution of the images decreases with increasing noise. The reconstructions are underdetermined so that at low noise levels the images converge to an asymptotic image, not the true geoelectrical section, If the estimated standard deviation is too low, the algorithm cannot achieve an adequate data fit, the resulting image becomes rough, and irregular artifacts start to appear. When the estimated standard deviation is larger than the correct value, the resolution decreases substantially (the image is too smooth), The same effects are demonstrated for field data from a site near Livermore, California, However, when the correct noise values are known, the Occam's results are independent of the discretization used. A case history of monitoring at an enhanced oil recovery site is used to illustrate problems in comparing successive images over time from a site where the noise level changes. In this case, changes in image resolution can be misinterpreted as actual geoelectrical changes. One solution to this problem is to perform smoothest, but non-Occam's, inversion on later data sets using parameters found from the background data set. [References: 17]
机译:讨论了一种Occam的井间电阻率数据反演算法,该算法使用有限元方法正解。对于逆算法?地球被离散为一系列参数块。每个Occam的反演都包含一个或多个元素,卡方统计量等于先验值的最平滑二维模型。合成模型数据用于显示噪声和噪声估计对所得二维电阻率图像的影响。图像的分辨率随着噪声的增加而降低。重建的不确定性,因此在低噪声水平下,图像会聚为渐近图像,而不是真实的地电剖面。如果估计的标准偏差太低,算法将无法获得足够的数据拟合,结果图像将变得粗糙且不规则文物开始出现。当估算的标准偏差大于正确值时,分辨率会大大降低(图像过于平滑)。对于来自加利福尼亚州利弗莫尔附近站点的现场数据也显示出相同的效果,但是,当已知正确的噪声值时, Occam的结果与所使用的离散化无关。在提高采油量的地点进行监视的案例历史用来说明在比较噪声水平变化的地点随时间变化的连续图像时出现的问题。在这种情况下,图像分辨率的变化可能会被误解为实际的地电变化。解决此问题的一种方法是使用从后台数据集中找到的参数对以后的数据集执行最平滑但非Occam的反演。 [参考:17]

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