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Research Papers: Petroleum Engineering

Advanced Deconvolution Technique for Analyzing Multirate Well Test Data

[+] Author and Article Information
Yueming Cheng1

Department of Petroleum and Natural Gas Engineering, West Virginia University, Morgantown, WV 26506-6070yueming.cheng@mail.wvu.edu

W. John Lee

Department of Petroleum Engineering, Texas A&M University, College Station, TX 77843-3116john.lee@pe.tamu.edu

Duane A. McVay

Department of Petroleum Engineering, Texas A&M University, College Station, TX 77843-3116duane.mcvay@pe.tamu.edu

1

Corresponding author.

J. Energy Resour. Technol 133(1), 012901 (Feb 17, 2011) (8 pages) doi:10.1115/1.4003442 History: Received September 03, 2010; Revised January 05, 2011; Published February 17, 2011; Online February 17, 2011

Deconvolution allows the test analyst to estimate the constant-rate transient pressure response of a reservoir-well system, and assists us in system identification and parameter estimation. Unfortunately, deconvolution amplifies the noise contained in data. Often, we cannot identify the reservoir system from deconvolved results owing to solution instability caused by noise in measured data. We previously presented a deconvolution technique based on the fast Fourier transform that we applied to a single buildup or drawdown period. In this paper, we extend our previous work and apply the deconvolution technique based on the fast Fourier transform to arbitrarily changing rate profiles such as multirate tests. The deconvolution results, which represent a constant-rate pressure drawdown response spanning the entire duration of the test, can provide helpful insight into the correct reservoir description. We have improved our original deconvolution method in number of ways, particularly with the introduction of an iterative algorithm that produces stable deconvolution results. We demonstrate application of our deconvolution method to analysis of synthetic and field examples, including both flow and shut-in periods. Our deconvolution method can efficiently reproduce the characteristic responses of the reservoir-well system and increase our confidence in parameter estimates.

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Copyright © 2011 by American Society of Mechanical Engineers
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Figures

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Figure 1

Synthetic example for an arbitrary changing flow profile: pressure response and corresponding rate data

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Figure 2

Synthetic example for an arbitrary changing flow profile: constant-rate pressure drawdown response obtained by deconvolution has diagnosed no-flow boundary effect with a unit slope, consistent with true system response

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Figure 3

Synthetic example: unit slope does not develop in individual buildup data to help identify no-flow boundary effect

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Figure 4

Field example for a production test sequence: measured pressure response and corresponding rate history

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Figure 5

Field example for a production test sequence: constant-rate pressure drawdown response obtained by deconvolution at qg=2000 MSCF/D identifies characteristics of finite-conductivity fracture, radial flow regime, and no-flow boundary effect

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Figure 6

Field example for a production test sequence: iterative deconvolved solutions with noise suppressed in the iterative process

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Figure 7

Field example for a production test sequence: RMS misfits in iteration process, convergence achieved with 72 iterations

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Figure 8

Field example for a production test sequence: measured pressure response at qg=2000 MSCF/D reproduced by convolution of recorded rate data with constant-rate pressure drawdown response

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Figure 9

Synthetic example: deconvolved pD is distorted and shifted upward due to an inaccurate estimate of initial reservoir pressure

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Figure 10

Synthetic example: constant adjustment of initial reservoir pressure is determined based on differences between deconvolved pD and pD changes in individual shut-in periods

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Figure 11

Synthetic example: deconvolved pD after adjusting initial reservoir pressure overlaps and deconvolved pD obtained by using exact initial reservoir pressure

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Figure 12

Synthetic example: overall features of system response reconstructed with inaccurate shut-in time for pressure buildups used in deconvolution operation, with exception of several isolated spikes

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