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Estimation of flushed zone and mudcake parameters using a new micro-resistivity pad device

机译:使用新型微电阻垫设备估算冲洗区和泥饼参数

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An accurate estimation of the flushed zone and mudcake parameters is important information for formation evaluation. The desired parameters are the resistivity of the flushed zone, Rxo, the mudcake thickness, hmc, and the mudcake resistivity, Rmc. Ideally, the sensor that detects aforementioned parameters is only sensitive to the parameters of the near-borehole environment and is not influenced by deeper undisturbed formation. Pad-mounted devices generally provide these parameters at relatively high vertical resolution. As an example, such a device consists of a metal pad with a number of embedded buttons. The pad is mounted on an arm extending from the main tool body and presses against the borehole wall. The pad injects current into the formation and the amount of current from each button is measured. The size of the guard surrounding each button controls the depth of investigation. The information gathered can then be processed simultaneously to obtain the desired parameters. However, the response of the buttons to the formation parameters is nonlinear. The traditional processing method involves the use of correction and cross-plot charts, which map these measurements into the parameters of interest. These charts (or their electronic equivalents) are generated by forward modeling the tool response for a variety of postulated parameter values. Frequently, the curves on the charts cluster together, posing a challenge in resolving the parameters. A small error in measurements can result in large variations of the parameters. It is also difficult to account for the error in the measurements and uncertainties in the underlying model in this processing scheme. An alternative approach is to perform iterative inversion where the statistics of the underlying parameter variation and measurement errors can be taken into account. A number of methods have been developed using different optimization engines. The most popular ones based on Gauss-Newton, or Levenberg-Marquadt methods, require computation of a sensitivity matrix that makes processing timeconsuming and impractical for well site interpretation. The formulation discussed in this paper involves a special transformation that reduces the non-linearity and thus speeds up the inversion. The resulting algorithm is suitable for real-time application. The synthetic and real data log examples show that the micro-resistivity instrument gives excellent estimates of the parameters of interest while maintaining sufficient vertical resolution. Therefore, the results can be incorporated with other measurements for an integrated formation evaluation.
机译:冲洗区和泥饼参数的准确估算是评价地层的重要信息。所需参数是冲洗区的电阻率Rxo,泥饼厚度hmc和泥饼电阻率Rmc。理想地,检测前述参数的传感器仅对近钻孔环境的参数敏感,而不受较深的未扰动地层的影响。安装在焊盘上的设备通常以相对较高的垂直分辨率提供这些参数。例如,这种设备由带有多个嵌入式按钮的金属垫组成。垫安装在从主体主体延伸的臂上,并压在井眼壁上。垫将电流注入地层,并测量来自每个按钮的电流量。每个按钮周围的防护装置的大小控制着调查的深度。然后可以同时处理收集到的信息以获得所需的参数。但是,按钮对地层参数的响应是非线性的。传统的处理方法涉及使用校正图和交叉图,将这些测量结果映射到感兴趣的参数中。通过对各种假定参数值的工具响应进行正向建模,可以生成这些图表(或它们的电子等效物)。通常,图表上的曲线会聚在一起,这在解析参数方面带来了挑战。测量中的小误差会导致参数的较大变化。在该处理方案中,也难以考虑测量中的误差和基础模型中的不确定性。另一种方法是执行迭代反演,其中可以考虑基础参数变化和测量误差的统计信息。已经使用不同的优化引擎开发了许多方法。基于高斯-牛顿法或Levenberg-Marquadt方法的最流行方法需要计算灵敏度矩阵,这使得处理过程既费时又不可行,无法进行井场解释。本文讨论的公式涉及一种特殊的变换,该变换减少了非线性并因此加快了反演。所得算法适用于实时应用。合成和真实数据记录示例表明,微电阻率仪器在保持足够的垂直分辨率的同时,可以很好地估算目标参数。因此,结果可以与其他测量结果结合起来进行综合地层评估。

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