小波理论在试井长时压力计数据分析中的应用研究

运用长时压力计对油井进行实时监测,数据量巨大,可达几十万甚至几百万并且其中包含大量的无用信息(如外点,噪声等),给试井解释带来许多困难。运用小波理论对长时压力计数据进行分析处理,能够很好地解决数据处理困难这一问题。其主要步骤包括:去除外点、去除噪声、划分流动阶段、压缩数据量。用该方法对现场某口生产井的测试数据进行处理,结果表明,基本去除测试数据中的无用信息,减少了数据量,同时保持了数据的真实特性,可操作性强,计算速度快,精度高,达到了试井解释的要求,并且研究结果可直接进行软件开发,具有很好的应用前景。

Applied Research on Wavelet Theory in Data Analysis of Permanent Downhole Pressure Gauge During Well Test

Some completed wells have been equipped with permanent downhole pressure gauges to monitor the well condition in real time, for the number of the data collected by PDG's is tremendous and might be up to several hundred thousands even several millions that contains many useless information (such as outliers, noise and so on), the well test analysis brings many difficulties. Using wavelet-based algorithms can solve the data processing difficulty. The main procedure is as follows: outlier removal, denosing, transient identification and data reduction. Through actual field data dispose by using the method, the results showed that the useless information have been removed, the data quantity have been reduced, meanwhile, the facticity of data was preserved. The computation speed is quick and the precision is high. It has met the well test analysis requirements, and the findings might carry on the software development directly and had the very good application prospect.