Summary
The analysis of production data to determine reservoir
characteristics,completion effectiveness, and hydrocarbons in place has become
very popular in recent years. Although production analysis (PA) for reservoir
characterization is approaching the popularity of pressure-transient analysis
(PTA), there are few consistent diagnostic methods in practice for the analysis
of production data.Many of the diagnostic methods for production-data analysis
are little more than observation-based approaches--and some are essentially
rules of thumb.
In this work, we provide guidelines for the analysis of production data, as
well as identify common pitfalls and challenges. Although PTA and
production-data analyses have the same governing theory (and solutions), we
must recognize that pressure transient data are acquired as part of a
controlled experiment, performed as a specific event [e.g., a pressure-buildup
(PBU) test]. In contrast, production data are generally considered to be
surveillance/monitoring data--with little control and considerable variance
occurring during the acquisition of the production data. We note that since
both PA and PTA have the same governing relations, it is possible "in theory"
that the same deliverables of PTA can be obtained using PA.
This paper attempts to provide a state-of-the-technology review of current
production-data-analysis techniques/tools--particularly tools to diagnose the
reservoir model and assess the reservoir condition. The reservoir model is
diagnosed mainly by examining the character exhibited by the data [that is the
evidence of transient flow (e.g., quarter-slope might indicate a
finite-conductivity fracture, or half-slope might indicate radial/pseudoradial
flow)]. In addition, one can also assess the reservoir condition by inspecting
the character of production data, which can confirm the evidence of
boundary-dominated flow such that unit slope may indicate the
boundary-dominated-flow regime and, therefore, in-place fluid volume can be
estimated.
This work also identifies the challenges and pitfalls of PA--and we try to
provide guidance toward best practices and best tools. To complement this
mission, we use relevant field examples to address specific issues, and we
illustrate the value and function of production-data analysis for a wide range
of reservoir types and properties. In this work, we propose the use of a
sequence of raw and enhanced data plots for the diagnostic analysis of
production data. We strongly believe that a comprehensive and systematic
approach for production-data diagnosis has significant importance for the
analysis and forecast of production performance.
© 2010. Society of Petroleum Engineers
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History
- Original manuscript received:
24 October 2006
- Meeting paper published:
25 September 2006
- Revised manuscript received:
10 November 2009
- Manuscript approved:
11 November 2009
- Published online:
8 June 2010
- Version of record:
22 June 2010
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