Summary
The most common data that engineers can count on, especially in mature
fields, is production rate data. Practical methods for production data analysis
(PDA) have come a long way since their introduction several decades ago and
fall into two categories: decline curve analysis (DCA) and type curve matching
(TCM). DCA is independent of any reservoir characteristics, and TCM is a
subjective procedure.
State of the art in PDA can provide reasonable reservoir characteristics,
but it has two shortcomings: First, for reservoir characterization, the process
requires bottomhole or wellhead pressure data in addition to rate data.
Bottomhole or wellhead pressure data are not usually available in most of the
mature fields. Second, a technique that would allow the integration of results
from hundreds of individual wells into a cohesive fieldwide or reservoirwide
analysis for business decision making is not part of today’s PDA tool kit.
To overcome these shortcomings, a new methodology is introduced in this
paper that has three unique specifications:
• It does not “require” pressure data,
bottomhole or wellhead (but it can make use of it, if available, to enhance
accuracy of results).
• It integrates DCA, TCM, and numerical reservoir simulation or history
matching (HM) to iteratively converge to a near unique set of reservoir
characteristics for each well.
• It uses fuzzy pattern recognition technology to achieve fieldwide decisions
from the findings of the analysis.
Introduction
Techniques for PDA have improved significantly over the past several years.
These techniques are used to provide information on reservoir permeability,
fracture length, fracture conductivity, well drainage area, original gas in
place (OGIP), estimated ultimate recovery (EUR), and skin. Although several
methods are available to characterize the reservoir, there is not a unified
method that always yields the most reliable answer.
DCA is a method to fit observed production rates of individual wells, group
of wells, or reservoirs by a mathematical function to predict the performance
of the future production by extrapolating the fitted decline function.
Arps (1945) introduced the DCA method in the 1940s. The method is a
mathematical equation with no physical basis other than the equation that shows
a declining trend. Arps’ method is still being used because of its simplicity.
In the early 1980s, Fetkvoich (1985) introduced DCA by type curves. Fetkovich
used Arps’ decline curves along with type curves for transient radial symmetric
flow of low-compressibility liquids at constant bottomhole pressures. Fetkovich
related Arps’ decline parameters to some reservoir engineering parameters for
production against constant bottomhole pressures. Several other type curves
have been developed by Carter (1985), Fraim & Wattenbarger (1987), Palacio
& Blasingame (1993) and Agarwal et al. (1999) and others for different well
and reservoir conditions.
Several commercial PDA tools have been developed for the oil and gas
industry. These commercial applications use DCA, TCM, and/or HM (using
reservoir simulation) independent from each other without integrating these
techniques. Furthermore, no other technique that is currently in use provides
facilities to integrate the results from individual well analysis into a
fieldwide (reservoirwide) analysis.
© 2007. Society of Petroleum Engineers
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History
- Original manuscript received:
6 March 2006
- Meeting paper published:
15 March 2006
- Revised manuscript received:
20 April 2007
- Manuscript approved:
25 April 2007
- Version of record:
20 November 2007
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