New Methods Enhance the Processing of Permanent Gauge Data

摘要

Permanent Downhole Gauges (PDG) are used increasingly in 'intelligent fields' to provide valuable information at different time scales. Specific processing of the massive amount of data produced by PDG is required to automatically (1) reduce the volume of data without losing valuable information, (2) remove outliers and (3) identify build-ups and re-allocate production. In the late 1990's, publications tried to address all these points using a first generation of wavelet based filters. Items (1) and (2) were successfully addressed but required prior data interpolation. Wavelets generally failed on item (3). In this paper we present the use of a new generation of wavelets, allowing a more accurate processing of items (1) and (2) without any prior interpolation. This paper also presents a new method using tangents crossing, which successfully replaces the failing wavelets for item (3).