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1.
We simulate direct current (DC) borehole resistivity measurements acquired in steel-cased deviated wells for the assessment
of rock formation properties. The assumed data acquisition configuration considers one current (emitter) and three voltage
(collector) electrodes that are utilized to measure the second difference of the electric potential along the well trajectory.
We assume a homogeneous, 1.27-cm-thick steel casing with resistivity equal to 10 − 5 Ω· m. Simulations are performed with two different numerical methodologies. The first one is based on transferring two-dimensional
(2D) axisymmetric optimal grids to a three-dimensional (3D) simulation software. The second one automatically produces optimal
3D grids yielded by a 3D self-adaptive goal-oriented algorithm. Both methodologies utilize high-order finite elements (FE)
that are specially well-suited for problems with high-contrast coefficients and rapid spatial variations of the electric field,
as it occurs in simulations that involve steel-cased wells. The method based on transferring 2D-optimal grids is efficient
in terms of CPU time (few seconds per logging position). Unfortunately, it may produce inaccurate 3D simulations in deviated
wells, even though the error remains below 1% for the axisymmetric (vertical) well. The method based on optimal 3D grids,
although less efficient in terms of CPU time (few hours per logging position), produces more accurate results that are validated
by a built-in a posteriori error estimator. This paper provides the first existing simulations of through-casing resistivity
measurements in deviated wells. Simulated resistivity measurements indicate that, for a 30° deviated well, measurements in
conductive layers 0.01 Ω· m) are similar to those obtained in vertical wells. However, in resistive layers (10,000 Ω· m),
we observe 100% larger readings in the 30° deviated well. This difference becomes 3,000% for the case of a 60° deviated well.
For this highly-deviated well, readings corresponding to the conductive formation layer are about 30% smaller in magnitude
than those in a vertical well. Shoulder effects significantly vary in deviated wells. 相似文献
2.
S. Shibuya 《Geotechnical and Geological Engineering》2002,20(4):333-369
A double exponential fitting model (DEFM) capable of expressing the non-linear stress-stiffness relationship of geomaterials has been proposed by Shibuya et al. (1997). The model comprises two material constants; the elastic stiffness at very small strains and the strength, together with other free parameters to determine the complete stress-stiffness relationship. In this paper, the capability of the original function used for DEFM in simulating the tangent stiffness-stress relationship of geomaterials is first discussed. Second, the methods for determining the free model parameters, as well as its conversion to obtain a stress-strain relationship are proposed. The applicability of DEFM to predicting non-linear stress-stiffness relationship is examined in detail in a total of forty-nine fitting cases of compression test data on sedimentary rock, artificial soft rock and soft clay. It is found that the DEFM is effective in expressing the non-linear stress-stiffness relationship of various kinds of geomaterials at small to intermediate strains, say less than 0.5%. The superiority of this model compared to other fitting models currently in use is also demonstrated in some of the fitting cases. 相似文献
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钢结构在长期荷载及不均匀受力的作用下会产生空间变形,其中扰度是其重要的衡量指标。通常采用全站仪采集钢结构轴线上若干特征点进行分析、计算,由于钢结构特征点难以捕捉,测量存在误差,并且有限的空间离散点难以全面反应钢结构空间变形。本文采用徕卡RTC360三维激光扫描进行钢结构扰度测量;介绍了其作业流程及数据处理方法;利用标靶将各个测站的三维点云拼接成一个整体;采用拟合的方法提取空间特征点及轴线;利用三维点云构建空间模型,并与设计模型进行碰撞分析;可全面地反映钢结构的空间变形情况。 相似文献
6.
初论双三次数值模式 总被引:4,自引:1,他引:4
讨论在数学Rn空间里,存在孔斯双三次曲面拟合的可能数值模式(以下称双三次数值模式)。双三次数值模式特点是,在诊断上对天气系统中的由各个物理定律表述的(离散点)大气物理量场,可通过数学三次样条函数做双三次曲面拟合,则模式大气(包括天气系统)的各个物理量场均达到二阶可导,即是大气运动方程中的各个物理量场都存在各自的一、二阶空间微商,从而可以对模式大气与天气系统做时间积分。与有限差分模式和谱模式存在所谓的空间截断误差和波数截断误差相比较,双三次数值模式存在所谓的空间拟合误差,恰是现行有限差分模式空间截断误差的高阶小量。而双三次数值模式具有谱模式准确计算空间微商的优点,且双三次数值模式的数学构架能够较好地适应大气运动动力框架,是可与有限差分模式和谱模式相比较的另一数值分析新算法的气象数值模式。 相似文献
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���������������Ƚ� 总被引:1,自引:2,他引:1
???Shepard???????????????????????????????Kriging????????????????п???????????????????????????????????????ε?????????????????????÷?Χ??????3????????б???????????1??????????????????????????????????????????????????2?????Kriging?????????????????????????????????????????仯???????????????????????????????????????仯С?????? 相似文献
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GPS????????????????????????????????????????????????????????????????????????ó??淽?????????????????????????????EM?????????????????????????????????????????????????????Ч????????????μ?GPS?????????? 相似文献
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