Petroleum Engineering

A Noniterative Blind Deconvolution Approach to Unveil Early Time Behavior of Well Testings Contaminated by Wellbore Storage Effects

[+] Author and Article Information
Arash Moaddel Haghighi

 Institute of Petroleum Engineering, University of Tehranarashmh@gmail.com

Peyman Pourafshary

 Institute of Petroleum Engineering, University of Tehranpourafshari@ut.ac.ir

J. Energy Resour. Technol 134(2), 022901 (Apr 04, 2012) (7 pages) doi:10.1115/1.4005661 History: Received September 03, 2010; Revised October 29, 2011; Published April 02, 2012; Online April 04, 2012

Deconvolution method is generally used to eliminate wellbore storage dominant period of well testing. Common Deconvolution techniques require knowledge of both pressure and rate variations within test duration. Unfortunately, accurate rate data are not always available. In this case, blind deconvolution method is used. In this work, we present a new approach to improve the ability of blind deconvolution method in well testing. We examined the behavior of rate data by comparing it with a special class of images and employed their common properties to represent gross behavior of extracted rate data. Results of examinations show ability of our developed algorithm to remove the effect of wellbore storage from pressure data. Our Algorithm can deal with different cases where wellbore storage has made two different reservoirs behave identical in pressure response. Even if there is no wellbore effect or after wellbore storage period is passed, proposed algorithm can work routinely without any problem.

Copyright © 2012 by American Society of Mechanical Engineers
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Figure 2

FFT spectrum estimate for flow rate derivative (b = 1). Vertical axis shows spectrum magnitudes in Decibels

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Figure 1

A typical w-class image and its corresponding plot of natural log of absolute value of FFT of the image for different frequencies. (Adopted from Carasso (2001).)

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Figure 9

Comparison made between our algorithm and frequency domain algorithm

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Figure 3

Flowchart of the steps to correct b(t) values

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Figure 4

Pressure response of a reservoir in presence (upper trend) and absence (lower trend) of wellbore effects. The dramatic change in slope of the line can be a clue in removing wellbore effects.

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Figure 5

Pressure derivative plot of a homogenous reservoir and output of the algorithm

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Figure 6

Pressure derivative plot of a dual porosity reservoir with wellbore effects and output of the algorithm

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Figure 7

Pressure derivative plot of a dual porosity reservoir without wellbore storage effects

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Figure 8

Pressure derivative plot of a homogenous reservoir with a single fault. The algorithm removes the wellbore effects as much as possible but does not affect late time pressure responses.



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