ANALYSIS AND INTERPRETATION OF PRESSURE TRANSIENT TEST DATA BY RECENT ROBUST DECONVOLUTION METHODS

Recently, the robust deconvolution algorithms that tolerate high levels of errors in pressure and rate than the previous deconvolution algorithms have been introduced in the literature. The recently developed deconvolution method by von Schroeter et al. (2002, 2004) and its variants later develop...

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Bibliographic Details
Main Author: Mohd Mustafa, Muhammad Izzatullah
Format: Final Year Project
Language:English
Published: Universiti Teknologi Petronas 2013
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Online Access:http://utpedia.utp.edu.my/10699/1/%5BDissertation%5D%20Muhammad%20Izzatullah_May_2013.pdf
http://utpedia.utp.edu.my/10699/
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Summary:Recently, the robust deconvolution algorithms that tolerate high levels of errors in pressure and rate than the previous deconvolution algorithms have been introduced in the literature. The recently developed deconvolution method by von Schroeter et al. (2002, 2004) and its variants later developed by Levitan (2005) and Pimonov et al. (2010) appear to offer robustness to the long-standing deconvolution problem and make deconvolution a viable tool to pressure transient and production data analysis. Now, most commercial software incorporates either the method developed by von Schroeter et al. or its variants developed by Levitan (2005) and Pimonov et al. (2010). However, there are some algorithmic parameters that need to be carefully selected to produce meaningful constantrate (or deconvolved) responses from these algorithms to avoid misinterpretation of the data leading to misidentification of the unknown system. In this work, by using the recent robust deconvolution algorithm of Pimonov et al. and/or the ones implemented in Weatherford PanSystem Well Test Software, the effects of the algorithmic parameters (including error levels in pressure and rate data, and the curvature constraint value) as well as the initial pressure on the deconvolved responses are investigated. Several synthetic and field test data are used to illustrate the effects of the algorithmic parameters on the deconvolved responses as well as the importance of the deconvolution in analysis and interpretation of pressure transient data.