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DC Field | Value | Language |
---|---|---|
dc.contributor.author | Akintola, A. S. | - |
dc.contributor.author | Oriji, A. B. | - |
dc.contributor.author | Duru, K. M. | - |
dc.date.accessioned | 2024-06-24T14:19:00Z | - |
dc.date.available | 2024-06-24T14:19:00Z | - |
dc.date.issued | 2015 | - |
dc.identifier.issn | 2320-0847 | - |
dc.identifier.issn | 2320-0936 | - |
dc.identifier.other | ui_art_akintola_deconvolution_2015 | - |
dc.identifier.other | American Journal of Engineering Research 4(12),pp. 134-142 | - |
dc.identifier.uri | http://ir.library.ui.edu.ng/handle/123456789/9357 | - |
dc.description.abstract | When a well test contains a series of different flow rates, or a continuously varying flow rate, the combination of the pressure transients due to varying flow rate is called convolution. while deconvolution means removing a distorting effect upon the variable of interest. This paper is on the study of an analytical technique that can be used to explicitly deconvolve wellbore storage distorted well test data using pressure data and the flow rate. Then to determine the reservoir properties from this deconvolved well test data by using the conventional well test interpretation methods. Also, the comparison of the material balance deconvolution method results with the β-deconvolution method result were carried out and then used to determine which method was a better deconvolution tool. The results showed that the material balance deconvolution technique performed very well with minor discrepancies and gave better estimation of the reservoir parameters. | en_US |
dc.language.iso | en | en_US |
dc.subject | Buildup Test | en_US |
dc.subject | β-deconvlolution | en_US |
dc.subject | Wellbore Storage Effect | en_US |
dc.subject | Material Balance deconvolution | en_US |
dc.title | Deconvolution and interpretation of well test data ‘masked’ by wellbore storage in a build up test | en_US |
dc.type | Article | en_US |
Appears in Collections: | scholarly works |
Files in This Item:
File | Description | Size | Format | |
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(15) ui_art_akinola_deconvolution_2015.pdf | 1 MB | Adobe PDF | View/Open |
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