首页> 外文期刊>Geoscience and Remote Sensing Letters, IEEE >Three-Dimensional Cole-Cole Model Inversion of Induced Polarization Data Based on Regularized Conjugate Gradient Method
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Three-Dimensional Cole-Cole Model Inversion of Induced Polarization Data Based on Regularized Conjugate Gradient Method

机译:基于正则共轭梯度法的诱导极化数据三维Cole-Cole模型反演

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摘要

Modeling of induced polarization (IP) phenomena is important for developing effective methods for remote sensing of subsurface geology. However, the quantitative interpretation of IP data in a complex 3-D environment is still a challenging problem of applied geophysics. This letter develops a method of determining a 3-D distribution of the four parameters of the Cole-Cole model based on surface IP data. The method takes into account the nonlinear nature of both electromagnetic induction and IP phenomena. The solution of the 3-D IP inverse problem is based on the regularized conjugate gradient method. The method was tested on a synthetic model with variable dc conductivity, intrinsic chargeability, time constant, and relaxation parameters, and it was also applied to the actual 3-D IP survey data. We demonstrate that the four parameters of the Cole-Cole model, namely, dc electrical resistivity, chargeability, time constant, and the relaxation parameter, can be recovered from the observed IP data simultaneously.
机译:感应极化(IP)现象的建模对于开发有效的地下地质遥感方法非常重要。但是,在复杂的3D环境中对IP数据进行定量解释仍然是应用地球物理学面临的难题。这封信提出了一种基于表面IP数据确定Cole-Cole模型的四个参数的3-D分布的方法。该方法考虑了电磁感应和IP现象的非线性性质。 3-D IP反问题的解决方案基于正则共轭梯度法。该方法在具有可变直流电导率,固有充电率,时间常数和弛豫参数的合成模型上进行了测试,并且还应用于实际的3D IP测量数据。我们证明了Cole-Cole模型的四个参数,即直流电阻率,可充电性,时间常数和弛豫参数,可以同时从观察到的IP数据中恢复。

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