三轴感应测井资料处理方法研究
|
摘要
近十年发展起来的三轴感应测井由于能探测地层的电各向异性,提供关于地层水平和垂直电导率以及地层倾角和走向的信息,这对砂—泥岩薄交互油储层组这类“低阻产层”的识别和开发有着重要意义,倍受人们的重视。Schlumberger公司推出的完全三轴感应仪器通过在仪器体内安装经过精心设计的电导元件而显著地减少了井眼环境包括仪器偏心等对测井响应的影响,使仪器的实用性得到极大提高。
三轴感应测井响应与地层水平和垂直电导率σh和σv、井眼(或地层)斜角α以及方位角?同时有关,而且关系复杂,再加上邻层和井眼效应等,目前普遍认为很难对三轴感应测井资料进行直观解释,有意义的资料解释结果只能通过多参数的非线性反演才能达到。然而,由于三轴感应仪器在含井眼和泥浆侵入的水平层状TI倾斜地层中的测井问题是个3D问题,其正演模拟已无解析解,目前普遍采用3D有限差分法求数值解,它的计算速度慢、占用计算机内存大,还难以适应做资料反演的要求,因而一般都采取先对实测资料进行井眼效应校正,利用校正后的数据在忽略泥浆侵入的条件下来做水平层状TI倾斜地层的纵向一维反演。本文应用横电(TE)和横磁(TM)波分解法推导的在水平层状TI倾斜地层中三轴感应测井响应的解析解,可为这种资料反演提供一种高效的正演模拟手段。即便是做纵向一维反演,由于无法对资料做直观解释,要给资料反演提供一个较好的初始地层模型也有很大困难,不仅这种资料反演的难度大,也无法满足现场对资料实时解释的需要,从而制约了它的广泛使用和进一步发展。因此三轴感应测井资料处理和解释问题至今仍是一个具有挑战性的问题,不能对它进行直观解释是个关键因素。
现在普遍采用首先确定方位角? ,将实测到的9条测井曲线变换成井眼坐标系的5条响应曲线再来做资料解释。我们发现现有的确定?的方法存在可相差π的不确定性,且转换得到的5条响应曲线的精度与?的提取精度有关。本文给出了一种与?的提取精度无关的由实测资料直接获取井眼坐标系的5条响应曲线的方法。
由于井眼坐标系的每一条响应曲线都和σh、σv、α同时相关,再加上邻层和井眼效应等复杂因素,使得很难对这些资料进行直观解释。本文最有意义的结果是:我们找到这样一条组合曲线,它通过与井眼斜角α有关的权重系数把井眼坐标系磁场张量的主分量和交叉分量组合成一条新的曲线,我们称它为水平电导率视值的组合曲线,并用符号σha表示。σha能以准方框图的形式直观再现地层水平电导率的纵向分布,通过σha对井眼斜角α的扫描还可提供一种确定井眼斜角视值αa的方法。组合曲线σha的纵向分辨率可用L cosα表征,在大井眼斜角和短源距时,σha曲线的纵向分辨率极高,用它不仅可直观定准地层的纵向边界位置,包括薄交互层组这样的薄层边界位置,对厚度大于L cosα的层σha曲线在每层中央区的标志值也相当接近于该层的水平电导率真值。σha组合曲线使三轴感应测井仪器的纵向分辨能力得到了充分的直观显示,显著地提高了它的资料直观解释能力。本文给出了一种以σha组合曲线为核心的三轴感应测井资料直观解释的方法和流程,此直观解释结果还可为资料的多参数的非线性反演提供一种较好的初始地层模型,对几个典型的水平层状TI倾斜地层模型的模拟测井资料所做的纵向1D反演得到了令人满意的结果,它迭代收敛快,反演精度高,这在很大程度上得益于σha有很好的纵向分辨率,为反演提供了好的初始模型。本文给出的以组合曲线σha为核心的三轴感应测井资料的处理方法不仅显著提高了资料的直观解释能力和效果,也使其资料的实时解释成为可能,这不仅有助于仪器的推广利用,还可为仪器进一步向随钻测井和阵列测井方向发展提供资料处理和解释方法上的支撑。因为随钻测井的地质导向必然要求能对资料进行实时解释,以便能够及时做出钻井位置和方向的安排与调整,本文3.8节的结果初步显示了将它用于地质导向的可能性。另外,在相当一段时间内,要大量对三轴感应测井资料进行3D反演还是不现实的,采取与现在阵列感应类似的资料处理和解释方法是较为现实的途径,只要三轴感应仪器有几个不同探测深度的探头,对每个探头的实测资料做了井眼效应校正后,可按本文提出的方法分别对它们进行一维反演,以实现它们在纵向分辨率上的匹配,几个不同探测深度的这种反演结果的σh和σv的差别就可用来解释它们在径向上的不均匀性,即泥浆侵入情况和原状地层的电参数。
本文的工作有些还需要充实和深入。首先,本文对存在井眼和泥浆侵入时的组合曲线的研究还只做了一个地层模型的实例,其读图数据的精度也不够高,还需要用精度高的数据做更多的地层模型实例来充实和完善它。其次,本文考察用的是无噪声数据,由于交叉耦合分量在层中央,特别是各向同性厚层的中央附近,其信噪比比主分量的低,而我们所用的σha组合曲线包含了交叉耦合分量,因此它的抗噪声能力如何是个值得重视并且最后还要通过实测资料来加以检验的问题。总之本文的结果还是初步的,要做的工作还很多,我们将继续努力。
In recently 10 years, people pay much attention to a new induction logging technology called fully triaxial induction logging. It can detect and characterize resistivity anisotropy and provide the information of formation dips and azimuths that are essential in charactering and developing low-resistivity reservoirs such as thinly laminated sand-shale sequences. A newly developed fully triaxial induction tool by Schlumberger is designed to great minimize the effects of borehole environments, deep invasion and tool eccentricity by using conductive elements in tool body and great improve the practical of the instrument.
The fully triaxial induction logging responses simultaneously depend on formation horizontal conductivityσh, vertical conductivityσv, borehole (or formation) dipαand the tool azimuth? and are highly non-linear functions, in addition to the strong effects by borehole and adjacent layers that make the responses more complex, until now, people generally agree that it is hard to process the logging data with visual explanation and the reliable results can only be obtained by nonlinear multi-parameter inversion.However, the fully triaxial induction logging is a 3D problem and no analytic forward modeling while the tool traverses a dipping TI layered formation with borehole and invasion. The 3D finite-difference modeling is generally used to solve the numerical solution that is now difficult to adapt to the requirements of data inversion for slow computing speed and very large workload. Hence, people always remove the borehole effect from the actual field logs first and then inverse the borehole-effect-corrected data with one-dimensional horizontal layered TI forward modeling.In this paper, we derive an analytic solution in horizontal layered anisotropic formation with no borehole and invasion by using TE and TM wave decomposing method to simulate the response of a fully triaxial induction tool in dipping well, which provides a high efficient forward modeling for logging data inversion. However, it is difficult to provide a reasonable initial model for inversion when we can’t make the visual explanation of logging data. It increases the difficulty even for vertical 1D inversion and also can not meet the real-time interpretation in scene that restricts the extensive application and further development of fully triaxial induction tool. So, it is still a challenging problem for fully triaxial induction logging data processing and interpretation, and the key problem is the visual interpretation of the logging data.
Now, people commonly determine the azimuth? first, and then transform the nine actual field logging curves in the tool coordinate system to the five logging curves in the borehole coordinate system, and make logging data processing and interpretation with them at last. We found that there exists the uncertainty to determine the azimuth? or( ? +π)using the existing method and the precisions of obtained five response curves depend on the precision of the extracted? . In this paper, we develop a fine algorithm to directly obtain five response curves independent of the precision of the extracted ? from nine actual field logging curves in the tool coordinate system.
Because of each response curve simultaneously depending onσh,σvandαin addition to some complex factors such as borehole and invasion effects, it is hard to make the visual explanation of logging data. The most meaningful result in this paper is that we found a fine combination curve with the principle components and cross-component via different weight coefficient relevant toαin borehole coordinate system calledσha, which has high vertical resolution and can reconstruct the distribution of horizontal conductivityσhwith a quasi-block response curve. We also provide an algorithm to determine the apparent dipαavia the scanning of dipαusing the combinationσha.The vertical resolution of the combination curveαacan be characterized by L cosα, where, L means the distance between transmitter and receiver. In highly deviated well, the combination curveσhahas high vertical resolution to visually determine the location of the bed boundary including thinly laminated sand-shale sequences with short transmitter-to-receiver structure. The value ofσhaon electric midpoint each layer is also very close to the true horizontal conductivity in the layers with thickness greater then L cosα.The combination curveσha fully reflects the vertical resolving power of the triaxial induction tool with visual display, significantly improves its ability to data visual explanation. In this paper, we develop a data visual explanation method and process with the combination curveσhaas the core for trixial induction logging. This visual explanation results are also considered as the initial value for nonlinear multi-parameter inversion. Some vertical 1D inversions of typical horizontal layered TI dipping bed have been done using simulating logging data and obtained satisfactory results. The iteration of inversion is fast and high precision. This is largely due to a very good vertical resolution ofσhathat provides a good initial value.
The fully triaxial induction logging data processing and interpretation method with the core of a combination curveσhain this paper not only significantly improve the capacity and effectiveness of the logging data visual interpretation, but also makes the real-time logging data interpretation possible. That helps promote the extension and utilization of the equipment, and provide the support of data processing and interpretation methods for the further development of the triaxial induction tool to logging-while-drilling (LWD) and array induction logging. For geosteering, logging data interpretation in real-time is extremely important in order to arrange and adjust the location and direction of the borehole. The results in the section 3.8 show the preliminary possibility for geosteering of a fully triaxial induction tool. In addition, during a certain period, a large number data inversion of triaxial induction logging using 3D numerical modeling is unrealistic, however, making a similar data processing and interpretation as array induction tool is a more realistic way. As long as there are several different probes to detect the different formation depth and correcting the borehole effect of each measured data from corresponding probe, the vertical 1D inversion can be implemented first using our method mentioned in this paper in order to meet the match of the vertical resolution for different logging curve. The difference of the electric parametersσhandσvbetween the results of inversion of different detecting depth helps to explain the inhomogeneity of formation in radial, that is, borehole, invasion and raw formation.
Some work in this paper needed to improvement and further study. First of all, we only study the combination curveσhawith one formation model including borehole and invasion, and the accuracy of its data is also not high enough. There still need higher precision simulating logging data and more formation model to improve it. Secondly, the logging data studied in this article is noise-free data, as a result of combination curveσhastudied in this article including the cross–coupling component that has lower signal to noise ratio than the main component in the middle point of bed, especially the near the central of isotropic thick bed, its anti-noise ability derive our attention and also need to be tested in the final through the actual logging data. In short, the results of this paper are still preliminary and lots of work remains to be done. We will continue to work hard.
三轴感应测井响应与地层水平和垂直电导率σh和σv、井眼(或地层)斜角α以及方位角?同时有关,而且关系复杂,再加上邻层和井眼效应等,目前普遍认为很难对三轴感应测井资料进行直观解释,有意义的资料解释结果只能通过多参数的非线性反演才能达到。然而,由于三轴感应仪器在含井眼和泥浆侵入的水平层状TI倾斜地层中的测井问题是个3D问题,其正演模拟已无解析解,目前普遍采用3D有限差分法求数值解,它的计算速度慢、占用计算机内存大,还难以适应做资料反演的要求,因而一般都采取先对实测资料进行井眼效应校正,利用校正后的数据在忽略泥浆侵入的条件下来做水平层状TI倾斜地层的纵向一维反演。本文应用横电(TE)和横磁(TM)波分解法推导的在水平层状TI倾斜地层中三轴感应测井响应的解析解,可为这种资料反演提供一种高效的正演模拟手段。即便是做纵向一维反演,由于无法对资料做直观解释,要给资料反演提供一个较好的初始地层模型也有很大困难,不仅这种资料反演的难度大,也无法满足现场对资料实时解释的需要,从而制约了它的广泛使用和进一步发展。因此三轴感应测井资料处理和解释问题至今仍是一个具有挑战性的问题,不能对它进行直观解释是个关键因素。
现在普遍采用首先确定方位角? ,将实测到的9条测井曲线变换成井眼坐标系的5条响应曲线再来做资料解释。我们发现现有的确定?的方法存在可相差π的不确定性,且转换得到的5条响应曲线的精度与?的提取精度有关。本文给出了一种与?的提取精度无关的由实测资料直接获取井眼坐标系的5条响应曲线的方法。
由于井眼坐标系的每一条响应曲线都和σh、σv、α同时相关,再加上邻层和井眼效应等复杂因素,使得很难对这些资料进行直观解释。本文最有意义的结果是:我们找到这样一条组合曲线,它通过与井眼斜角α有关的权重系数把井眼坐标系磁场张量的主分量和交叉分量组合成一条新的曲线,我们称它为水平电导率视值的组合曲线,并用符号σha表示。σha能以准方框图的形式直观再现地层水平电导率的纵向分布,通过σha对井眼斜角α的扫描还可提供一种确定井眼斜角视值αa的方法。组合曲线σha的纵向分辨率可用L cosα表征,在大井眼斜角和短源距时,σha曲线的纵向分辨率极高,用它不仅可直观定准地层的纵向边界位置,包括薄交互层组这样的薄层边界位置,对厚度大于L cosα的层σha曲线在每层中央区的标志值也相当接近于该层的水平电导率真值。σha组合曲线使三轴感应测井仪器的纵向分辨能力得到了充分的直观显示,显著地提高了它的资料直观解释能力。本文给出了一种以σha组合曲线为核心的三轴感应测井资料直观解释的方法和流程,此直观解释结果还可为资料的多参数的非线性反演提供一种较好的初始地层模型,对几个典型的水平层状TI倾斜地层模型的模拟测井资料所做的纵向1D反演得到了令人满意的结果,它迭代收敛快,反演精度高,这在很大程度上得益于σha有很好的纵向分辨率,为反演提供了好的初始模型。本文给出的以组合曲线σha为核心的三轴感应测井资料的处理方法不仅显著提高了资料的直观解释能力和效果,也使其资料的实时解释成为可能,这不仅有助于仪器的推广利用,还可为仪器进一步向随钻测井和阵列测井方向发展提供资料处理和解释方法上的支撑。因为随钻测井的地质导向必然要求能对资料进行实时解释,以便能够及时做出钻井位置和方向的安排与调整,本文3.8节的结果初步显示了将它用于地质导向的可能性。另外,在相当一段时间内,要大量对三轴感应测井资料进行3D反演还是不现实的,采取与现在阵列感应类似的资料处理和解释方法是较为现实的途径,只要三轴感应仪器有几个不同探测深度的探头,对每个探头的实测资料做了井眼效应校正后,可按本文提出的方法分别对它们进行一维反演,以实现它们在纵向分辨率上的匹配,几个不同探测深度的这种反演结果的σh和σv的差别就可用来解释它们在径向上的不均匀性,即泥浆侵入情况和原状地层的电参数。
本文的工作有些还需要充实和深入。首先,本文对存在井眼和泥浆侵入时的组合曲线的研究还只做了一个地层模型的实例,其读图数据的精度也不够高,还需要用精度高的数据做更多的地层模型实例来充实和完善它。其次,本文考察用的是无噪声数据,由于交叉耦合分量在层中央,特别是各向同性厚层的中央附近,其信噪比比主分量的低,而我们所用的σha组合曲线包含了交叉耦合分量,因此它的抗噪声能力如何是个值得重视并且最后还要通过实测资料来加以检验的问题。总之本文的结果还是初步的,要做的工作还很多,我们将继续努力。
In recently 10 years, people pay much attention to a new induction logging technology called fully triaxial induction logging. It can detect and characterize resistivity anisotropy and provide the information of formation dips and azimuths that are essential in charactering and developing low-resistivity reservoirs such as thinly laminated sand-shale sequences. A newly developed fully triaxial induction tool by Schlumberger is designed to great minimize the effects of borehole environments, deep invasion and tool eccentricity by using conductive elements in tool body and great improve the practical of the instrument.
The fully triaxial induction logging responses simultaneously depend on formation horizontal conductivityσh, vertical conductivityσv, borehole (or formation) dipαand the tool azimuth? and are highly non-linear functions, in addition to the strong effects by borehole and adjacent layers that make the responses more complex, until now, people generally agree that it is hard to process the logging data with visual explanation and the reliable results can only be obtained by nonlinear multi-parameter inversion.However, the fully triaxial induction logging is a 3D problem and no analytic forward modeling while the tool traverses a dipping TI layered formation with borehole and invasion. The 3D finite-difference modeling is generally used to solve the numerical solution that is now difficult to adapt to the requirements of data inversion for slow computing speed and very large workload. Hence, people always remove the borehole effect from the actual field logs first and then inverse the borehole-effect-corrected data with one-dimensional horizontal layered TI forward modeling.In this paper, we derive an analytic solution in horizontal layered anisotropic formation with no borehole and invasion by using TE and TM wave decomposing method to simulate the response of a fully triaxial induction tool in dipping well, which provides a high efficient forward modeling for logging data inversion. However, it is difficult to provide a reasonable initial model for inversion when we can’t make the visual explanation of logging data. It increases the difficulty even for vertical 1D inversion and also can not meet the real-time interpretation in scene that restricts the extensive application and further development of fully triaxial induction tool. So, it is still a challenging problem for fully triaxial induction logging data processing and interpretation, and the key problem is the visual interpretation of the logging data.
Now, people commonly determine the azimuth? first, and then transform the nine actual field logging curves in the tool coordinate system to the five logging curves in the borehole coordinate system, and make logging data processing and interpretation with them at last. We found that there exists the uncertainty to determine the azimuth? or( ? +π)using the existing method and the precisions of obtained five response curves depend on the precision of the extracted? . In this paper, we develop a fine algorithm to directly obtain five response curves independent of the precision of the extracted ? from nine actual field logging curves in the tool coordinate system.
Because of each response curve simultaneously depending onσh,σvandαin addition to some complex factors such as borehole and invasion effects, it is hard to make the visual explanation of logging data. The most meaningful result in this paper is that we found a fine combination curve with the principle components and cross-component via different weight coefficient relevant toαin borehole coordinate system calledσha, which has high vertical resolution and can reconstruct the distribution of horizontal conductivityσhwith a quasi-block response curve. We also provide an algorithm to determine the apparent dipαavia the scanning of dipαusing the combinationσha.The vertical resolution of the combination curveαacan be characterized by L cosα, where, L means the distance between transmitter and receiver. In highly deviated well, the combination curveσhahas high vertical resolution to visually determine the location of the bed boundary including thinly laminated sand-shale sequences with short transmitter-to-receiver structure. The value ofσhaon electric midpoint each layer is also very close to the true horizontal conductivity in the layers with thickness greater then L cosα.The combination curveσha fully reflects the vertical resolving power of the triaxial induction tool with visual display, significantly improves its ability to data visual explanation. In this paper, we develop a data visual explanation method and process with the combination curveσhaas the core for trixial induction logging. This visual explanation results are also considered as the initial value for nonlinear multi-parameter inversion. Some vertical 1D inversions of typical horizontal layered TI dipping bed have been done using simulating logging data and obtained satisfactory results. The iteration of inversion is fast and high precision. This is largely due to a very good vertical resolution ofσhathat provides a good initial value.
The fully triaxial induction logging data processing and interpretation method with the core of a combination curveσhain this paper not only significantly improve the capacity and effectiveness of the logging data visual interpretation, but also makes the real-time logging data interpretation possible. That helps promote the extension and utilization of the equipment, and provide the support of data processing and interpretation methods for the further development of the triaxial induction tool to logging-while-drilling (LWD) and array induction logging. For geosteering, logging data interpretation in real-time is extremely important in order to arrange and adjust the location and direction of the borehole. The results in the section 3.8 show the preliminary possibility for geosteering of a fully triaxial induction tool. In addition, during a certain period, a large number data inversion of triaxial induction logging using 3D numerical modeling is unrealistic, however, making a similar data processing and interpretation as array induction tool is a more realistic way. As long as there are several different probes to detect the different formation depth and correcting the borehole effect of each measured data from corresponding probe, the vertical 1D inversion can be implemented first using our method mentioned in this paper in order to meet the match of the vertical resolution for different logging curve. The difference of the electric parametersσhandσvbetween the results of inversion of different detecting depth helps to explain the inhomogeneity of formation in radial, that is, borehole, invasion and raw formation.
Some work in this paper needed to improvement and further study. First of all, we only study the combination curveσhawith one formation model including borehole and invasion, and the accuracy of its data is also not high enough. There still need higher precision simulating logging data and more formation model to improve it. Secondly, the logging data studied in this article is noise-free data, as a result of combination curveσhastudied in this article including the cross–coupling component that has lower signal to noise ratio than the main component in the middle point of bed, especially the near the central of isotropic thick bed, its anti-noise ability derive our attention and also need to be tested in the final through the actual logging data. In short, the results of this paper are still preliminary and lots of work remains to be done. We will continue to work hard.
引文
[1]曾文冲.关于我国测井技术发展的几点意见[J].测井技术,2002,26(1):1-5.
[2]张丽媛,武清钊.高频等参数感应(ВИКИЗ)测井技术应用[J].测井技术, 2001,25:452-455.
[3]卢达.兼收并蓄博采美、俄之长,提升我国测井技术和装备水平.在中国石油学会测井专业委员会组织的第三次测井高级论坛上的报告[R].大庆市, 2004.
[4] CHEW W C, Liu Q H. Inversion of induction tool measurement using distorted Born iterative method CG-FFHT [J]. IEEE Trans Geosci and Remote Sensing, 1994, 32(4):878-884.
[5]张业荣,聂在平.利用阵列感应测井仪信号反演非均匀分布地层电导率[J].地球物理学报,1998 ,41(4):579-586.
[6]张业荣,聂在平,漆芬兰.地层电导率非线性反演方法——双感应测井数据反演[J].测井技术,1998,23(3):163-167.
[7]张庚骥,汪涵明,汪功礼.成层介质中交流电测井响应[J].地球物理学报, 1995, 38:840-849.
[8]邢光龙,张美玲,刘曼芬,杨善德.利用高频电磁波测井反演地层介电常数和电阻率[J].地球物理学报,2002,45(4): 435-443.
[9] WANG H N, Yang S D. Simultaneous reconstruction of geometric parameter and resistivity around borehole in horizontally stratified formation from multiarray induction logging data [J]. IEEE Trans Geosci and Remote Sensing, 2003,41(1):81-89.
[10]康俊佐,邢光龙,杨善德.用VIKIZ测井反演砂泥岩薄互层参数的方法研究[J].测井技术,2005,29(4):321-324.
[11]康俊佐,邢光龙,杨善德.电磁传播电阻率测井的二维全参数反演方法研究.地球物理学报.2006, 49(1):275-283.
[12]邢光龙,杨善德,李曙光.电磁波测井资料反演中Jacobi矩阵的快速算法及其特征分析[J].地球物理学报,2007,50(2):642-650.
[13] XING G L, Yang S D. The response functions of electromagnetic wave logs and its applications[J]. IEEE Transactions on Geoscience and Remote Sensing, 2006, 44(6):1413-1418.
[14]党瑞荣,秦瑶,谢雁,等.三分量感应测井系统研究[J].石油地球物理勘探,2008,41(4):484-488.
[15] ZHANG Z Y, Yu L M, KRIEGSHAUSER B, et al. Simultaneous determination of relative angles and anisotropic resistivity using multicomponent induction logging data[C]. 42nd SPWLA Annual Logging Symposium, Houston, June 17-20, 2001, Paper Q.
[16] KLEIN J D, MARTIN P R, ALLEN D F. The petrophysics of electrically anisotropic reservoirs [J]. The Log Analyst, 1997, 38(3):25-36
[17]夏宏泉,吴宝玉,房军方,等.随钻电阻率测井的各向异性影响及校正方法研究[J].国外测井技术,2007,22(1):12-14.
[18] RABINOVICH M, GONFALINI M, ROCQUE T, et al. Multi-component induction logging: 10 years after[C]. 48th SPWLA Annual Logging Symposium, Houston, June 3-6, 2007, Paper CC.
[19] TABAROVSKY L A, RABINOVICH M B. High-speed 2-D inversion of induction logging data[C]. 37th SPWLA Annual Logging Symposium, Houston, June 16-19, 1996, Paper P.
[20] KRIEGSHAUSER B F, FANINI O N, MOLLISON R A, et al. increased oil-in-place in low-resistivity reservoirs from multicomponent induction log data[C]. 41th SPWLA Annual Logging Symposium, Houston, June 4-7, 2000, Paper A.
[21] KRIEGSHAUSER B F, FANINI O N, FORGANG S, et al. A new multicomponent induction logging tool to resolve anisotropic formation[C]. 41st SPWLA Annual Logging Symposium, Houston, June 4-7, 2000, Paper D.
[22] TABAROVSKY L A, RABINOVICH M B. Real time 2D inversion of induction logging data [J]. Journal of Applied Geophysics, 1998, 38:251-275.
[23] KRIEGSHAUSER, FANINI O N, LIMING Y, et al. Improved shaly sand interpretation in highly deviated and horizontal wells using multicomponent induction log data [C]. 42nd SPWLA Annual Logging Symposium, Houston, June 17-20, 2001, Paper S.
[24] RABINOVICH M, TABAROVSKY L. Enhanched anisotropy from joint processing of multi-component and multi-array induction tools [C]. 42nd SPWLA Annual Logging Symposium, Houston, June 17-20, 2001, Paper HH.
[25] MOLLISON R A, FANINI O N, KRIEGSHAUSER B F, et al. Impact of multicomponent induction technology on a deepwater turbidite sand hydrocarbon saturation evaluation [C]. 42nd SPWLA Annual Logging Symposium, Houston, June 17-20, 2001, Paper T.
[26] GOMES R, DENICOL P, DA C A, et al. Using multicomponent induction log data to enhance formation evaluation in deepwater reservoirs from Campos Basin offshore Brasil[C]. 43th SPWLA Annual Logging Symposium, Houston, June 2-5, 2002, Paper N.
[27] RABINOVICH M, BESPALOV A, CORLEY B, et al. Effect of fractures on multi-component and multi-array induction logs[C]. 45th SPWLA Annual Logging Symposium, Houston, June 6-9, 2004, Paper UU.
[28] FAWZIA H, SHAFIKA M, RICK A, et al. contributions of multi-component induction logs in difficult wellbore environment in north Kuwait low resistivity pay evaluation [C]. 46th SPWLA Annual Logging Symposium, Houston, June 26-29, 2005, Paper VV.
[29] RABINOVICH M, TABAROVSKY L, CORLEY B, et al. Processing multi-component induction data for formation dip and azimuth in anisotropic formations [C]. 46th SPWLA Annual Logging Symposium, Houston, June 26-29, 2005, Paper XX.
[30] TSILI W, ALEX B, BILL C, et al. Formation dip ,azimuth, and anisotropiy in more complex depositional environments [C]. 47th SPWLA Annual Logging Symposium, Houston, June 4-7, 2006, Paper QQQ.
[31] RICHARD R, TOM B, STEVE B, et al. Field test results of an experimental fully-triaxial induction tool [C]. 44th SPWLA Annual Logging Symposium, Houston, June 22-25, 2003, Paper QQ.
[32]王昌学,周灿灿,储昭坦等.电性各向异性地层频率域电磁响应模拟.地球物理学报[J],2006,49(6):1873-1883
[33]沈金松.用有限差分法计算各向异性介质中多分量感应测井的响应[J].地球物理学进展,2004,19(1): 101-107.
[34]杨守文,汪宏年,陈桂波,等.倾斜各向异性地层中多分量电磁波测井响应三维时域有限差分(FDTD)算法[J].地球物理学报,2009,52 (3): 833-841.
[35] JUNSHENG H, ROBERT K M, CARLOS T-V. Finite-difference simulation of borehole EM measurements in 3D anisotropic media using coupled scalar-vector potentials [J]. Geophysics, 2006, 71(5):G225-G233.
[36] SOFIA D, VLADIMIR D, TAREK H. An efficient finite-difference scheme for electromagnetic logging in 3D anisotropic in homogeneous media [J]. Geophysics, 2003, 68(5): 1525-2536.
[37] TSILI W, SHENG F. 3-D electromagnetic anisotropy modeling using finite differences [J]. Geophysics, 2001, 66(5):1386-1398.
[38] GAO G Z, CARLOS T-V, SHENG F. Fast 3D modeling of borehole induction measurements in dipping and anisotropic formations using a novel approximation technique [J]. Petrophysics, 2004, 45(4):335-349.
[39] ZHDANOV S M, SHENG F. Quasi-linear approximation in 3-D electromagnetic modeling [J]. Geophysics, 1996, 61(3):646-665
[40] WANG H, BARBER T, MORRISS C, et al. Determining anisotropic formation resistivity at any relative dip using a multiarray triaxial induction tool [C]. SPE 103113 presented at the 2006 SPE Annual Technical Conference and Exhibition: San Antonio, Texas, U.S.A., September 24-27, 2006.
[41] HONG D C, Yang S D. Analytic Forward Modeling in Layered Anisotropic Dipping Formation for Multi-Component Induction Logging [J]. Submitted to IEEE Transactions on Geoscience and Remote Sensing.
[42] ZHDANOV S M, DAVID K, ERTAN P. Foundations of tensor induction well-logging [J]. Petrophysics, 2001, 42(6):588-610.
[43]洪德成,杨善德.张量感应测井视值解释方法的改进[J].地球物理学进展,2008, 23(1):178-185
[44]洪德成,杨善德.张量感应测井资料处理中若干问题的研究[J].地球物理学报,2009,52(4).
[45] MORAN J, GIANZERO S. Effects of formation anisotropy on resistivity-logging measurements [J]. Geophysics, 1979, 44(7): 1266- 1288.
[46] ZHONG L L, JING L, LIANG C S, et al. Computation of triaxial induction logging tools in layered anisotropic dipping formations [J]. IEEE Transactions on Geoscience and Remote Sensing, 2008, 46(4):1148-1163.
[47] WANG H N, TAO H G, YAO J J, et al. Fast multiparameter reconstruction of multicomponent induction well logging datum in deviated well in a horizontally stratified anisotropic formation [J]. IEEE Transactions on Geoscience and Remote Sensing, 2008, 46 (5): 1525-1534.
[48]其木苏荣Z,汪宏年.倾斜井眼中感应测井正演模拟与响应特征[J].计算物理,2003,20(2):161-168.
[49]周永祖著,聂在平,柳清伙译.非均匀介质中的场与波(M).北京:电子工业出版社,1992年.
[50] ALAN D C. numerical integration of related Hankel transforms by quadrature and continued fraction expansion [J]. Geophysics, 1983, 48(12): 1671-1686.
[51] VERMA R K, KOEFOED O. A note on the linear filter method of computing electromagnetic sounding curves [J]. Geohysical Prospecting, 1972, 21:70-76.
[52] WALTER L A. Computer program numerical integration of related Hankel transforms of orders 0 and 1 by adaptive digital filtering [J]. Geophysics, 1979, 44(7): 1287-1305.
[53] DAS U C, GHOSH D P, BREWINGA D T. Transformation of dipole resistivity sounding measurements over layered earth by linear digital filtering [J]. Geophysical Prospecting, 1974, 22:476-489.
[54] WALTER L A. A hybrid fast Hankel transform algorithm for electromagnetic modeling. Geophysics. 1989, 54(2): 263-266.
[55]胡俊,聂在平.任意平面分层介质中正演计算的快速算法[J].电波科学学报,1998,13(2):113-116.
[56] KOEFOED O, GHOSH D P, POLMAN G J. Computation of type curves for electromagnetic depth sounding with a horizontal transmitting coil by means of a digital linear filter[J]. Geophysical Prospecting, 1972, 20:406-420.
[57] MALLAN K R, CARLOS Torres-Verdin. Effects of geometrical, environmental, and petrophysical parameters on multi-component induction measurements acquired in high-angle wells [J]. Petrophysics, 2007, 48(4): 271-288.
[58] TSILI W, LIMING Y, FANINI O N, et al. Understanding multicomponent induction logs in a 3-D borehole environment[C]. 42nd SPWLA Annual Logging Symposium, Houston, June 17-20, 2001, Paper GG.
[59] TSILI W, LIMING Y, FANINI O. Multicomponent induction response in a borehole environment [J]. Geophysics, 2003, 68(5):1510-1518.
[60] MICHAEL J T, DAVID L A, DARREL T S,et al. Numerical analysis of near-borehole and anisotropic layer effects on the response of multicomponent induction logging tools[J]. Geophysics, 2004, 69(1): 140-151.
[61] ANDERSON B, BARBER T, HABASKY T M. The interpretation and inversion of fully triaxial induction data; a sensitivity study[C]. 43th SPWLA Annual Logging Symposium, Houston, June 2-5, 2002, Paper O.
[62] ARVIDAS C, MICHAEL Z, MOTOYUKI S. Induction logging with directional coil polarizations: modeling and resolution analysis[J]. Petrophysics, 2001, 42(3): 227-236.
[63] ANDERSON B I, BARBER T D, GIANZERO S C. The effect of crossbedding anisotropy on induction tool response [J]. Petrophysics, 2001, 42(2):137-149.
[64] ROBERT K M, CARLOS T-V. Effects of petrophysical, environmental, and geomentrical parameters on multi-component induction measurements acquired in high-angle wells[C]. 47th SPWLA Annual Logging Symposium, Houston, June 4-7, 2006, Paper PPP.
[65] CLAVAUD J-B, HANMING W. Bed boundaries from multi-component induction technology: fact or fiction and what to do with them [C]. 49th SPWLA Annual Logging Symposium, Houston, May25-28, 2008, Paper IIII.
[66] ANTHONY G N. Anisotropy induction logging [J]. Geophysics, 1994,59 (3):345-350.
[67] GERALD N M, DZEVAT O, RICHARD A R. Directional electromagnetic measurements insensitive to dip and anisotropy [P]. US 6969994. 2005-11-29.
[68]邢光龙.阵列电磁波测井探测特性及其资料处理与反演方法研究[D].长春:吉林大学物理学院, 2003.
[69]张美玲.高频电磁波测井资料的非均质反演方法研究[D].长春:吉林大学物理学院,2000.
[70]张美玲,邢光龙,刘曼芬,杨善德.阻尼型高斯—牛顿法及其在高频电磁波测井反演中的应用[J].计算物理,2002,19:155-158.
[71]康俊佐.阵列传播电阻率测井资料反演方法与仪器优化组合研究[D].长春:吉林大学物理学院,2005.
[72] TICHONOV N, Arenis K V. Solution of ill-problem [M]. New York, John Wiley and Sons, 1997.
[73] ANTHONY G N. Anisotropy induction logging [J]. Geophysics, 1994, 59(3): 345-350.
[74] YIN C, MAURE H M. Electromagnetic induction in a layered earth with arbitrary anisotropy [J]. Geophysics, 2001, 66(5): 1405-1416
[75] XINGYOU L L, DAVID L A, CHESTER J W. The electric fields and currentsproduced by induction logging instruments in anisotropic media[J]. Geophysics, 2002, 67(2): 478-483.
[76] TSILI W. The electromagnetic smoker ring in a transversely isotropic medium [J]. Geophysics, 2002, 67(6): 1779-1789.
[77] GIANZERO S, KENNEDY D, GAO L. et al. The response of a triaxial induction sonde in a biaxial anisotropic medium [J]. Petrophysics, 2002, 43(3): 172-184.
[78] CHESTER J W, XINYOU L, David L A. visualization of eddy currents induced in an electrically anisotropic formation [J]. Petrophysics, 2001, 42(6): 580-587
[79] TSILI W, XIAOMING T, LIMING Y, et al. Characterizing fractures with multicomponent induction measurements [J]. Petrophysics, 2005, 46(1): 42-51
[80] ERTAN P, MICHAEL S Z. Apparent resistivity correction for tensor induction well logging in a deviated well in an anisotropic medium [J]. Petrophysics, 2003, 44(3): 196-204.
[81] ARVIDAS B C, MICHAEL S Z. Fast modeling of a tensor induction tool response in a horizontal well in inhomogeneous anisotropic formations[C]. 42th SPWLA Annual Logging Symposium, Houston, June 17-20, 2001, Paper P.
[82] ZHDANOV S M, DAVID KENNEDY W, ARVIDAS B C, et al. Principles of tensor induction well logging in a deviated well in an anisotropic medium[C]. 42nd SPWLA Annual Logging Symposium, Houston, June 17-20, 2001, Paper R.
[83] LI Q M, DZEVAT O, LAWRENCE C, et al. New directional electromagnetic tool proactive geosteering and accurate formation evaluation while drilling[C]. 46th SPWLA Annual Logging Symposium, Houston, June 26-29, 2005, PaperUU.
[84] DZEVAT O, TAREK H, CENGIZ E, et al. Real-time interpretation of formation structure from directional EM measurements[C]. 47th SPWLAAnnual Logging Symposium, Houston, June 4-7, 2006, Paper SSS.
[85] TSILI W, ROLAND C, ERIC H, et al. Real-time formation imaging, dip, and azimuth while drilling from compensated deep directional resistivity[C]. 48th SPWLA Annual Logging Symposium, Houston, June 3-6, 2007, Paper NNN.
[86] LI Q M, CHENGIN L, Carlos M. et al. Automated interpretation for LWD propagation resistivity tools througth integrated model selection. Petrophysics, 2004, 45(1): 14-26.
[2]张丽媛,武清钊.高频等参数感应(ВИКИЗ)测井技术应用[J].测井技术, 2001,25:452-455.
[3]卢达.兼收并蓄博采美、俄之长,提升我国测井技术和装备水平.在中国石油学会测井专业委员会组织的第三次测井高级论坛上的报告[R].大庆市, 2004.
[4] CHEW W C, Liu Q H. Inversion of induction tool measurement using distorted Born iterative method CG-FFHT [J]. IEEE Trans Geosci and Remote Sensing, 1994, 32(4):878-884.
[5]张业荣,聂在平.利用阵列感应测井仪信号反演非均匀分布地层电导率[J].地球物理学报,1998 ,41(4):579-586.
[6]张业荣,聂在平,漆芬兰.地层电导率非线性反演方法——双感应测井数据反演[J].测井技术,1998,23(3):163-167.
[7]张庚骥,汪涵明,汪功礼.成层介质中交流电测井响应[J].地球物理学报, 1995, 38:840-849.
[8]邢光龙,张美玲,刘曼芬,杨善德.利用高频电磁波测井反演地层介电常数和电阻率[J].地球物理学报,2002,45(4): 435-443.
[9] WANG H N, Yang S D. Simultaneous reconstruction of geometric parameter and resistivity around borehole in horizontally stratified formation from multiarray induction logging data [J]. IEEE Trans Geosci and Remote Sensing, 2003,41(1):81-89.
[10]康俊佐,邢光龙,杨善德.用VIKIZ测井反演砂泥岩薄互层参数的方法研究[J].测井技术,2005,29(4):321-324.
[11]康俊佐,邢光龙,杨善德.电磁传播电阻率测井的二维全参数反演方法研究.地球物理学报.2006, 49(1):275-283.
[12]邢光龙,杨善德,李曙光.电磁波测井资料反演中Jacobi矩阵的快速算法及其特征分析[J].地球物理学报,2007,50(2):642-650.
[13] XING G L, Yang S D. The response functions of electromagnetic wave logs and its applications[J]. IEEE Transactions on Geoscience and Remote Sensing, 2006, 44(6):1413-1418.
[14]党瑞荣,秦瑶,谢雁,等.三分量感应测井系统研究[J].石油地球物理勘探,2008,41(4):484-488.
[15] ZHANG Z Y, Yu L M, KRIEGSHAUSER B, et al. Simultaneous determination of relative angles and anisotropic resistivity using multicomponent induction logging data[C]. 42nd SPWLA Annual Logging Symposium, Houston, June 17-20, 2001, Paper Q.
[16] KLEIN J D, MARTIN P R, ALLEN D F. The petrophysics of electrically anisotropic reservoirs [J]. The Log Analyst, 1997, 38(3):25-36
[17]夏宏泉,吴宝玉,房军方,等.随钻电阻率测井的各向异性影响及校正方法研究[J].国外测井技术,2007,22(1):12-14.
[18] RABINOVICH M, GONFALINI M, ROCQUE T, et al. Multi-component induction logging: 10 years after[C]. 48th SPWLA Annual Logging Symposium, Houston, June 3-6, 2007, Paper CC.
[19] TABAROVSKY L A, RABINOVICH M B. High-speed 2-D inversion of induction logging data[C]. 37th SPWLA Annual Logging Symposium, Houston, June 16-19, 1996, Paper P.
[20] KRIEGSHAUSER B F, FANINI O N, MOLLISON R A, et al. increased oil-in-place in low-resistivity reservoirs from multicomponent induction log data[C]. 41th SPWLA Annual Logging Symposium, Houston, June 4-7, 2000, Paper A.
[21] KRIEGSHAUSER B F, FANINI O N, FORGANG S, et al. A new multicomponent induction logging tool to resolve anisotropic formation[C]. 41st SPWLA Annual Logging Symposium, Houston, June 4-7, 2000, Paper D.
[22] TABAROVSKY L A, RABINOVICH M B. Real time 2D inversion of induction logging data [J]. Journal of Applied Geophysics, 1998, 38:251-275.
[23] KRIEGSHAUSER, FANINI O N, LIMING Y, et al. Improved shaly sand interpretation in highly deviated and horizontal wells using multicomponent induction log data [C]. 42nd SPWLA Annual Logging Symposium, Houston, June 17-20, 2001, Paper S.
[24] RABINOVICH M, TABAROVSKY L. Enhanched anisotropy from joint processing of multi-component and multi-array induction tools [C]. 42nd SPWLA Annual Logging Symposium, Houston, June 17-20, 2001, Paper HH.
[25] MOLLISON R A, FANINI O N, KRIEGSHAUSER B F, et al. Impact of multicomponent induction technology on a deepwater turbidite sand hydrocarbon saturation evaluation [C]. 42nd SPWLA Annual Logging Symposium, Houston, June 17-20, 2001, Paper T.
[26] GOMES R, DENICOL P, DA C A, et al. Using multicomponent induction log data to enhance formation evaluation in deepwater reservoirs from Campos Basin offshore Brasil[C]. 43th SPWLA Annual Logging Symposium, Houston, June 2-5, 2002, Paper N.
[27] RABINOVICH M, BESPALOV A, CORLEY B, et al. Effect of fractures on multi-component and multi-array induction logs[C]. 45th SPWLA Annual Logging Symposium, Houston, June 6-9, 2004, Paper UU.
[28] FAWZIA H, SHAFIKA M, RICK A, et al. contributions of multi-component induction logs in difficult wellbore environment in north Kuwait low resistivity pay evaluation [C]. 46th SPWLA Annual Logging Symposium, Houston, June 26-29, 2005, Paper VV.
[29] RABINOVICH M, TABAROVSKY L, CORLEY B, et al. Processing multi-component induction data for formation dip and azimuth in anisotropic formations [C]. 46th SPWLA Annual Logging Symposium, Houston, June 26-29, 2005, Paper XX.
[30] TSILI W, ALEX B, BILL C, et al. Formation dip ,azimuth, and anisotropiy in more complex depositional environments [C]. 47th SPWLA Annual Logging Symposium, Houston, June 4-7, 2006, Paper QQQ.
[31] RICHARD R, TOM B, STEVE B, et al. Field test results of an experimental fully-triaxial induction tool [C]. 44th SPWLA Annual Logging Symposium, Houston, June 22-25, 2003, Paper QQ.
[32]王昌学,周灿灿,储昭坦等.电性各向异性地层频率域电磁响应模拟.地球物理学报[J],2006,49(6):1873-1883
[33]沈金松.用有限差分法计算各向异性介质中多分量感应测井的响应[J].地球物理学进展,2004,19(1): 101-107.
[34]杨守文,汪宏年,陈桂波,等.倾斜各向异性地层中多分量电磁波测井响应三维时域有限差分(FDTD)算法[J].地球物理学报,2009,52 (3): 833-841.
[35] JUNSHENG H, ROBERT K M, CARLOS T-V. Finite-difference simulation of borehole EM measurements in 3D anisotropic media using coupled scalar-vector potentials [J]. Geophysics, 2006, 71(5):G225-G233.
[36] SOFIA D, VLADIMIR D, TAREK H. An efficient finite-difference scheme for electromagnetic logging in 3D anisotropic in homogeneous media [J]. Geophysics, 2003, 68(5): 1525-2536.
[37] TSILI W, SHENG F. 3-D electromagnetic anisotropy modeling using finite differences [J]. Geophysics, 2001, 66(5):1386-1398.
[38] GAO G Z, CARLOS T-V, SHENG F. Fast 3D modeling of borehole induction measurements in dipping and anisotropic formations using a novel approximation technique [J]. Petrophysics, 2004, 45(4):335-349.
[39] ZHDANOV S M, SHENG F. Quasi-linear approximation in 3-D electromagnetic modeling [J]. Geophysics, 1996, 61(3):646-665
[40] WANG H, BARBER T, MORRISS C, et al. Determining anisotropic formation resistivity at any relative dip using a multiarray triaxial induction tool [C]. SPE 103113 presented at the 2006 SPE Annual Technical Conference and Exhibition: San Antonio, Texas, U.S.A., September 24-27, 2006.
[41] HONG D C, Yang S D. Analytic Forward Modeling in Layered Anisotropic Dipping Formation for Multi-Component Induction Logging [J]. Submitted to IEEE Transactions on Geoscience and Remote Sensing.
[42] ZHDANOV S M, DAVID K, ERTAN P. Foundations of tensor induction well-logging [J]. Petrophysics, 2001, 42(6):588-610.
[43]洪德成,杨善德.张量感应测井视值解释方法的改进[J].地球物理学进展,2008, 23(1):178-185
[44]洪德成,杨善德.张量感应测井资料处理中若干问题的研究[J].地球物理学报,2009,52(4).
[45] MORAN J, GIANZERO S. Effects of formation anisotropy on resistivity-logging measurements [J]. Geophysics, 1979, 44(7): 1266- 1288.
[46] ZHONG L L, JING L, LIANG C S, et al. Computation of triaxial induction logging tools in layered anisotropic dipping formations [J]. IEEE Transactions on Geoscience and Remote Sensing, 2008, 46(4):1148-1163.
[47] WANG H N, TAO H G, YAO J J, et al. Fast multiparameter reconstruction of multicomponent induction well logging datum in deviated well in a horizontally stratified anisotropic formation [J]. IEEE Transactions on Geoscience and Remote Sensing, 2008, 46 (5): 1525-1534.
[48]其木苏荣Z,汪宏年.倾斜井眼中感应测井正演模拟与响应特征[J].计算物理,2003,20(2):161-168.
[49]周永祖著,聂在平,柳清伙译.非均匀介质中的场与波(M).北京:电子工业出版社,1992年.
[50] ALAN D C. numerical integration of related Hankel transforms by quadrature and continued fraction expansion [J]. Geophysics, 1983, 48(12): 1671-1686.
[51] VERMA R K, KOEFOED O. A note on the linear filter method of computing electromagnetic sounding curves [J]. Geohysical Prospecting, 1972, 21:70-76.
[52] WALTER L A. Computer program numerical integration of related Hankel transforms of orders 0 and 1 by adaptive digital filtering [J]. Geophysics, 1979, 44(7): 1287-1305.
[53] DAS U C, GHOSH D P, BREWINGA D T. Transformation of dipole resistivity sounding measurements over layered earth by linear digital filtering [J]. Geophysical Prospecting, 1974, 22:476-489.
[54] WALTER L A. A hybrid fast Hankel transform algorithm for electromagnetic modeling. Geophysics. 1989, 54(2): 263-266.
[55]胡俊,聂在平.任意平面分层介质中正演计算的快速算法[J].电波科学学报,1998,13(2):113-116.
[56] KOEFOED O, GHOSH D P, POLMAN G J. Computation of type curves for electromagnetic depth sounding with a horizontal transmitting coil by means of a digital linear filter[J]. Geophysical Prospecting, 1972, 20:406-420.
[57] MALLAN K R, CARLOS Torres-Verdin. Effects of geometrical, environmental, and petrophysical parameters on multi-component induction measurements acquired in high-angle wells [J]. Petrophysics, 2007, 48(4): 271-288.
[58] TSILI W, LIMING Y, FANINI O N, et al. Understanding multicomponent induction logs in a 3-D borehole environment[C]. 42nd SPWLA Annual Logging Symposium, Houston, June 17-20, 2001, Paper GG.
[59] TSILI W, LIMING Y, FANINI O. Multicomponent induction response in a borehole environment [J]. Geophysics, 2003, 68(5):1510-1518.
[60] MICHAEL J T, DAVID L A, DARREL T S,et al. Numerical analysis of near-borehole and anisotropic layer effects on the response of multicomponent induction logging tools[J]. Geophysics, 2004, 69(1): 140-151.
[61] ANDERSON B, BARBER T, HABASKY T M. The interpretation and inversion of fully triaxial induction data; a sensitivity study[C]. 43th SPWLA Annual Logging Symposium, Houston, June 2-5, 2002, Paper O.
[62] ARVIDAS C, MICHAEL Z, MOTOYUKI S. Induction logging with directional coil polarizations: modeling and resolution analysis[J]. Petrophysics, 2001, 42(3): 227-236.
[63] ANDERSON B I, BARBER T D, GIANZERO S C. The effect of crossbedding anisotropy on induction tool response [J]. Petrophysics, 2001, 42(2):137-149.
[64] ROBERT K M, CARLOS T-V. Effects of petrophysical, environmental, and geomentrical parameters on multi-component induction measurements acquired in high-angle wells[C]. 47th SPWLA Annual Logging Symposium, Houston, June 4-7, 2006, Paper PPP.
[65] CLAVAUD J-B, HANMING W. Bed boundaries from multi-component induction technology: fact or fiction and what to do with them [C]. 49th SPWLA Annual Logging Symposium, Houston, May25-28, 2008, Paper IIII.
[66] ANTHONY G N. Anisotropy induction logging [J]. Geophysics, 1994,59 (3):345-350.
[67] GERALD N M, DZEVAT O, RICHARD A R. Directional electromagnetic measurements insensitive to dip and anisotropy [P]. US 6969994. 2005-11-29.
[68]邢光龙.阵列电磁波测井探测特性及其资料处理与反演方法研究[D].长春:吉林大学物理学院, 2003.
[69]张美玲.高频电磁波测井资料的非均质反演方法研究[D].长春:吉林大学物理学院,2000.
[70]张美玲,邢光龙,刘曼芬,杨善德.阻尼型高斯—牛顿法及其在高频电磁波测井反演中的应用[J].计算物理,2002,19:155-158.
[71]康俊佐.阵列传播电阻率测井资料反演方法与仪器优化组合研究[D].长春:吉林大学物理学院,2005.
[72] TICHONOV N, Arenis K V. Solution of ill-problem [M]. New York, John Wiley and Sons, 1997.
[73] ANTHONY G N. Anisotropy induction logging [J]. Geophysics, 1994, 59(3): 345-350.
[74] YIN C, MAURE H M. Electromagnetic induction in a layered earth with arbitrary anisotropy [J]. Geophysics, 2001, 66(5): 1405-1416
[75] XINGYOU L L, DAVID L A, CHESTER J W. The electric fields and currentsproduced by induction logging instruments in anisotropic media[J]. Geophysics, 2002, 67(2): 478-483.
[76] TSILI W. The electromagnetic smoker ring in a transversely isotropic medium [J]. Geophysics, 2002, 67(6): 1779-1789.
[77] GIANZERO S, KENNEDY D, GAO L. et al. The response of a triaxial induction sonde in a biaxial anisotropic medium [J]. Petrophysics, 2002, 43(3): 172-184.
[78] CHESTER J W, XINYOU L, David L A. visualization of eddy currents induced in an electrically anisotropic formation [J]. Petrophysics, 2001, 42(6): 580-587
[79] TSILI W, XIAOMING T, LIMING Y, et al. Characterizing fractures with multicomponent induction measurements [J]. Petrophysics, 2005, 46(1): 42-51
[80] ERTAN P, MICHAEL S Z. Apparent resistivity correction for tensor induction well logging in a deviated well in an anisotropic medium [J]. Petrophysics, 2003, 44(3): 196-204.
[81] ARVIDAS B C, MICHAEL S Z. Fast modeling of a tensor induction tool response in a horizontal well in inhomogeneous anisotropic formations[C]. 42th SPWLA Annual Logging Symposium, Houston, June 17-20, 2001, Paper P.
[82] ZHDANOV S M, DAVID KENNEDY W, ARVIDAS B C, et al. Principles of tensor induction well logging in a deviated well in an anisotropic medium[C]. 42nd SPWLA Annual Logging Symposium, Houston, June 17-20, 2001, Paper R.
[83] LI Q M, DZEVAT O, LAWRENCE C, et al. New directional electromagnetic tool proactive geosteering and accurate formation evaluation while drilling[C]. 46th SPWLA Annual Logging Symposium, Houston, June 26-29, 2005, PaperUU.
[84] DZEVAT O, TAREK H, CENGIZ E, et al. Real-time interpretation of formation structure from directional EM measurements[C]. 47th SPWLAAnnual Logging Symposium, Houston, June 4-7, 2006, Paper SSS.
[85] TSILI W, ROLAND C, ERIC H, et al. Real-time formation imaging, dip, and azimuth while drilling from compensated deep directional resistivity[C]. 48th SPWLA Annual Logging Symposium, Houston, June 3-6, 2007, Paper NNN.
[86] LI Q M, CHENGIN L, Carlos M. et al. Automated interpretation for LWD propagation resistivity tools througth integrated model selection. Petrophysics, 2004, 45(1): 14-26.
© 2004-2018 中国地质图书馆版权所有 京ICP备05064691号 京公网安备11010802017129号 地址：北京市海淀区学院路29号 邮编：100083 电话：办公室：(+86 10)66554848；文献借阅、咨询服务、科技查新：66554700 |