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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| Format: | Final Year Project |
| Language: | English |
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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. |
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