Abstract
Permanent downhole gauge data provide us with reservoir information in space and time and aid in well and reservoir management. Interpretation of permanent downhole gauge data is a fairly new problem and several outstanding issues remain in this area.
This paper addresses some of the challenges in analyzing flow rate data and pressure data from permanent downhole gauges - development of improved algorithms for reliable and accurate identification of transient break points (to separate transients into relevant subsections), and investigating the impact of continuous downhole rate data in analyzing well tests.
We tested four different algorithms, one based on the stationary Harr wavelet transform method and others based on nonwavelet approaches such as Savitzky-Golay Smoothing Filters and a novel pattern recognition approach called the Segmentation Method. These four methods were developed for accurate and reliable identification of break points using both pressure and rate data.
The new methods developed in this paper were applied to real field data and the results were compared to the spline wavelet-based approach. All the nonwavelet approaches showed significant improvement over the wavelet-based method in identifying the true break points and avoiding false break points, thus reducing manual editing of break points. Also, significant difference in the estimates of permeability and skin was observed by using continuous rate information instead of average rate data for interpreting transient pressure data.
These new algorithms find their application in the interpretation of permanent downhole gauge data using conventional well test interpretation methods, to obtain dynamic information about changes in properties of the well and reservoir. The use of continuous downhole rate data can have significant advantage in well test interpretation.
