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Fast Multiparameter Reconstruction of Multicomponent Induction Well-Logging Datum in a Deviated Well in a Horizontally Stratified Anisotropic Formation

机译:水平分层各向异性地层中斜井中多分量感应测井数据的快速多参数重构

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In this paper, we advance a fast iterative inversion algorithm of multicomponent induction well-logging (MCIL) datum to simultaneously reconstruct a total model vector in a deviated well in the horizontally stratified transversally isotropic (TI) formation (TI medium) with the case-neglecting borehole. The model vector consists of the horizontal and vertical conductivities, the interface depth of each bed, and a borehole dipping angle. Because an electromagnetic field emitted by a horizontal magnetic dipole is no longer axially symmetrical, we first decompose the horizontal magnetic dipole located at borehole axis as the sum of two harmonics only so that the computation of MCIL responses can be entirely transformed into three axially symmetrical problems. Therefore, we solve them through the numerical mode matching method and obtain the semianalytic (SA) solution of an EM field in an arbitrary bed. Then, based on the perturbation principle and spatial distribution of formation conductivity related to the model vector, we set up an efficient SA algorithm of FrÉchet derivatives of the MCIL response with respect to the model vector. Then we extract an initial model from synthetic logs for the inversion through a special blocking technique. Finally, we give an iterative process to simultaneously reconstruct all model parameters from the logs through a combination of a normalization and singular value decomposition technique. Numerical tests validate the algorithms.
机译:在本文中,我们提出了一种多分量感应测井(MCIL)数据的快速迭代反演算法,可以在水平分层横观各向同性(TI)地层(TI介质)中的斜井中同时重建总模型矢量,并具有以下情况:忽略钻孔。模型矢量包括水平和垂直电导率,每个床层的界面深度以及井孔倾角。由于水平磁偶极子发出的电磁场不再是轴向对称的,因此我们首先将位于井眼轴上的水平磁偶极子分解为两个谐波之和,以便将MCIL响应的计算完全转换为三个轴向对称问题。 。因此,我们通过数值模式匹配方法求解它们,并获得了任意床中电磁场的半解析(SA)解。然后,基于扰动原理和与模型矢量有关的地层电导率的空间分布,针对模型矢量,建立了MCIL响应的FrÉchet导数的有效SA算法。然后,我们从合成测井中提取初始模型,以通过特殊的阻塞技术进行反演。最后,我们给出一个迭代过程,以通过归一化和奇异值分解技术的组合同时从日志中重建所有模型参数。数值测试验证了算法。

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