Development of Analysis Method for Geothermal Pressure Interference Test Using Kalman Filtering
Development of Analysis Method for Geothermal Pressure Interference Test Using Kalman Filtering
批准号:
02650456
负责人:
ITOI Ryuichi
金额:
$0.77万
依托单位:
依托单位国家:
日本
项目类别:
Grant-in-Aid for General Scientific Research (C)
财政年份:
1990
资助国家:
日本
项目状态:
已结题
起止时间:
1990 至 1991
中文摘要
卡尔曼滤波已被应用于分析多井、多速率压力干扰试井的方法。研究中考虑了两种不同的油藏系统:无限孔隙油藏和具有水力边界的多孔油藏。在上述情况下,观测井中观测到的压力变化可以用线源解的叠加原理来表示。这些解析解对于要识别的参数是非线性的:透射率和储存量。为此,采用了两种不同的方法来线性化解:一种是取普通对数,另一种是用泰勒级数展开来逼近非线性函数。基于线性化方法的分析方法的特点是:1)对于对数情况,即使初始估计值与最可能值之间的偏差大于几个数量级,估计值在估计过程中也不会发散。2)对于泰勒展开式,在初始估计值与最可能值相差一个数量级的条件下,可以在估计过程的早期阶段估计出合理的参数值。因此,与上述方法相比,可以进行更快速的估计。
英文摘要
Kalman filtering has been applied to develop methods to analyze pressure interference tests of multiple-well, multiple-rate problems. Two different reservoir systems are considered in this study : an infinite porous reservoir and a porous reservoir with a presence of a hydraulic boundary. Pressure change observed in an observation well under the situations above can be expressed by applying the principle of superposition to the line source solution. These analytical solutions are nonlinear with respect to parameters to be identified : transmissivity and storativity. Therefore, two different methods are adopted to linealize the solutions : one is taking the ordinary logarithm, and another is to approximate the nonlinear function with Taylor's series expansion. Then, Kalman filtering is formed using these linealized equations, and two parameters are estimated at every moment when observation pressure value is obtained.Characteristics of the analysis method depending on the way of linealization are :1)For the logarithmic case, estimated values never diverge during the estimation procedure even if the discrepancy between the initial estimates and the most probable values is greater by several orders of magnitude. Therefore, this method is particularly effective when no prior information on the parameters is available.2)For Taylor's expansion case, reasonable values of parameters can be estimated at early stage of the estimation procedure under conditions that the initial estimates are given within a difference of one order of magnitude compared with the most probable values. Thus, more quick estimation is possible compared with the method above.
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