永久压力计的出现使实时油藏监测和管理成为可能。分析永久压力计压力数据的关键是通过正确的产量历史数据分析每个压降和压恢。油田的实际产量包括单井的日产数据或者累计产量数据。这些测量的数据一般误差在±10%。另外由于产量数据和压力数据的取样频率不同，导致产量数据和压力数据的时间偏移。通过使用小波变化算法，从所测量的实时永久压力计压力数据和一般正常测量的累计产量数据回归产量历史。小波变换后的压力计压力高频信息可准确识别产量变化的时间点，从而实现单井压力和产量在每个时间窗口的同步变化。另外产量的变化和小波变换后的压力振幅成正比例关系，从而得到在累积产量约束下的每个时间窗口的产量数据。%The advent of permanent gauge makes the real time reservoir monitoring and management possible. The key of perma-nent gauge data analysis is to analyze every drawdown and build-up of pressure by correct historical production data. The actual output includes daily output data or the cumulative production data of single well. The error of these measured data is about ±10 %. Besides, the different sampling frequency of production data and pressure data lead to the time migration. By the wavelet transform algorithm, production history is regressed from measured permanent gauge data and normal measured cumulative production data. High frequency pressure information after wavelet transform can accurately identify the time point of production variation to realize the synchronous change of single well pressure and production at each time window. In addition, production variation is proportion-al to the pressure amplitude after wavelet transform, so that to obtain the production data at each time window under the constraint of the cumulative production.
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