Azimuthal electromagnetic (EM) logging while drilling (LWD) has been extensively used in high-angle and horizontal (HA/HZ) wells. However, due to the effects of formation anisotropy, accurate geosteering decision and formation evaluations have become increasingly difficult. To quantitatively analyze the effect of anisotropy on tool responses and data processing, this paper investigates the sensitivity of EM LWD measurements to electric anisotropy and inversion accuracy via forward modeling and inversion. First, a sensitivity factor is defined to quantitatively analyze the sensitivity of the magnetic field components and synthetic signals to electric anisotropy. Then, azimuthal EM LWD responses in anisotropic layered formations are simulated, and the sensitivities to formation parameters for compensated and uncompensated tool configurations are comparatively analyzed. Finally, we discuss the effects of the inversion model on bed boundary inversion in anisotropic formations. Numerical simulation and inversion results show that azimuthal EM LWD can be significantly affected by electric anisotropy. Fortunately, by using a symmetrical compensation configuration, the sensitivity of the geosignals to electric anisotropy can be suppressed, and the boundary detection capability can be further enhanced. Anisotropy normally gives rise to separated resistivity curves and abnormal “horns”; moreover, complicated nonlinear distortion can also arise in geosignals as the tool approaches a bed boundary. If anisotropy effects are ignored in the inversion process, the estimated bed boundary and formation resistivity are usually unreliable, which may mislead geosteering decisions.

中文翻译：

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各向异性介质随钻测井方位电磁测井性能

随钻方位角电磁（EM）测井（LWD）已广泛用于高角度和水平（HA / HZ）井中。但是，由于地层各向异性的影响，准确的地质导向决策和地层评估变得越来越困难。为了定量分析各向异性对工具响应和数据处理的影响，本文通过正向建模和反演研究了EM LWD测量对电各向异性和反演精度的敏感性。首先，定义一个灵敏度因子以定量分析磁场分量和合成信号对电各向异性的灵敏度。然后，模拟各向异性层状地层中的EM LWD方位响应，并比较分析了补偿和未补偿工具配置对地层参数的敏感性。最后，我们讨论了反演模型对各向异性地层中床边界反演的影响。数值模拟和反演结果表明，电磁各向异性对电磁各向异性具有明显的影响。幸运的是，通过使用对称补偿配置，可以抑制地质信号对电各向异性的敏感性，并且可以进一步增强边界检测能力。各向异性通常会导致电阻率曲线分离和出现异常的“角”。此外，当工具接近床边界时，复杂的非线性失真也会在地理信号中产生。如果在反演过程中忽略了各向异性效应，