Use of Wavelet Transform in Pressure-Data Treatment

Abstract

Summary Since the beginning of the 1980s, more downhole pressure gauges (DPGs) were installed in production and injection wells. The main purpose was well monitoring and evaluation of reservoir performance. This kind of gauge provides a large amount of data, but there are various problems that do not allow their complete use. These problems are related to quantity and quality. Most software is not able to handle the main objective for using DPGs with all the data available in a long recording period. Besides that, gauges present noise and strange data (outliers). It becomes necessary to treat the data before its use in the study of reservoir behavior. The concept of wavelet transform (WT) was developed about a century ago, but it was during the 1980s that it received practical application. Now it is used in a wide variety of applications, and, especially in data treatment, it presents two main features that make it attractive: smoothing of the signal and retention of the details. In this paper, we use the WT to overcome the main problems and enhance the reliability of the information contained in the data. We tested different wavelets with several decomposition levels against actual and synthetic data. The outliers must be removed before the wavelet analysis in order to enhance its performance. We show that there is no unique "correct" WT to apply in any flow period. For example, for some data sets the Daubechies 1 wavelet at decomposition Level 6 was used for flow periods, and Level 3 for buildup. It is important to notice that the use of high decomposition levels may cause loss of information, as is shown in some examples. The wavelet analysis was also used to recognize transients from its ability to enhance the details. This is particularly useful to identify flow rate changes when they have not been reported, for example. Finally, we propose a methodology to treat the data before its use in posterior interpretation.