Summary
Decline-curve analysis is one of the most commonly used techniques to
estimate reserves from production data. In tight formations that have been
stimulated--especially when there are multiple layers that communicate only at
the wellbore--the uncertainty in reserves estimates from this technique is
quite large because forecasting future performance is quite difficult. This
uncertainty can affect the classification of reserves, and could limit what we
should call "proved developed reserves." In this paper, we present new
procedures to mitigate the complexity of decline-curve analysis in multilayer
tight gas wells. Using synthetic and field examples, we demonstrate how
reserves can be estimated more reliably.
For tight and multilayer gas wells, it is not uncommon that decline-curve
analysis yields an Arps decline-curve parameter b greater than unity
(Arps 1945). Single-layer hydraulically fractured tight gas wells also appear
to have b-values greater than unity. Different practices are used to
handle such complexity. For forecasts, some analysts simply use the
b-value obtained from matching production data, while others force the
b value to be unity. Still others use the hyperbolic decline and the
matched value of b, but, when the decline rate reaches a predetermined
limit, they switch to exponential decline for the remainder of the forecast.
Thus, forecasted performance differs significantly when different analysts
analyze the data. Consequently, the reserves estimate has large uncertainty,
which can, in turn, affect its classification.
In this paper, we first present an in-depth investigation of decline
behavior of tight, single-layer and multilayer gas wells by analyzing depletion
characteristics using simulated data sets. We illustrate the long-duration
transient effects present in single-layer stimulated tight gas wells and the
complex flow regimes present when wells in layered reservoirs are produced
commingled. Our work indicates that, as observed in field data, transient
effects and coexistence of different flow regimes between layers lead to
abnormal decline behavior (b > 1.0) in multilayer tight gas wells,
which leads to errors in production forecasts. Our new procedure provides a
method to minimize these errors.
Introduction
Decline-curve analysis is one of the most commonly used techniques to
predict future production performance and estimate reserves from routinely
available production data. Although Arps' decline equations were developed
empirically (Arps 1945), the parameter b in the decline equations was
proved to be related to fluid properties and production conditions (Chen and
Teufel 2002; Fetkovich et al. 1996). Conventional decline-curve analysis
inherently assumes a single-layer reservoir, the well producing at constant
bottomhole pressure (BHP), and stabilized flow conditions (Fetkovich et al.
1996). In addition, use of Arps’ equations implies that there are no changes in
completion and operating conditions. It is well documented that the decline
exponent should range between zero and 1.0 when these assumptions are satisfied
(Arps 1945; Fetkovich et al. 1996).
Tight gas reservoirs are characterized by permeabilities less than 0.1 md.
Gas wells in tight formations usually require hydraulic fracturing of multiple
layers to be viable commercially. Therefore, analysis of decline behavior in
tight gas wells presents unique technical challenges (Cox et al. 2002; Neal and
Mian 1989). It is often very difficult, if not impossible, to estimate reserves
accurately in a timely and consistent fashion with decline-curve analysis. Long
times--often years--are required to reach so called pseudosteady-state flow
(actually, boundary-dominated flow because the term "pseudosteady
state" strictly applies only to constant-rate production). The production
data available for decline-curve analysis are, therefore, typically not
stabilized. As a result, it is not uncommon for tight gas wells to exhibit
Arps' decline constants, b, that exceed 1.0 (Maley 1985). With
b-values greater than 1.0, future performance and remaining reserves
will be greatly overestimated. In conventional practice, some analysts simply
use the b value obtained from matching of production data, while others
force the b value to be 1.0. Still others use the hyperbolic decline and the
matched value of b, but, when the decline rate reaches a predetermined
limit, they switch to exponential decline for the remainder of the forecast.
However, this latter procedure has no physical basis. This type of decline
behavior is highly unlikely in nature.
Another complication in analysis of decline data in tight gas wells is that,
in most cases, production is commingled from multilayered formations that are
hydraulically fractured with multiple stages. Because of variations in
formation permeability and fracture half-length, different flow regimes may
coexist in different layers. Lower-permeability zones may be in transient flow,
while higher-permeability zones have established stabilized, boundary-dominated
flow. The profile of production contribution by individual layers changes
constantly with time. Given these complications, decline-curve analysis of
multilayer tight gas wells is especially difficult, particularly with regard to
estimating long-term production and reserves.
The objective of our work is to develop method to improve reserves estimates
from decline-curve analysis of tight and multilayer gas wells, particularly
those dominated by transient flow. In this paper, we propose a new, improved
technique to analyze transient-flow-dominated production data. The distinctions
of our method from other methods currently in use are that we determine the
b value for stabilized (boundary-dominated) flow a priori,
history match multiple periods of late production data in a backward fashion to
determine a set of decline parameters qi and
Di , and then extrapolate these parameters to
qi and Di corresponding to the end of
history for use in projecting future production.
We generated synthetic production-data sets using reservoir simulation for
two cases: a single-layer gas well and a multilayer gas well. We show that,
with existing decline-curve methods, analysis of stabilized-flow data is
sufficient to produce accurate production forecasts and reserves estimates, but
analysis of transient-flow-dominated production data can result in large
errors. Using the new proposed method, significant improvement in the accuracy
of production forecasts and reserves estimates for transient-flow-dominated gas
wells is demonstrated for both the synthetic cases and a field example.
© 2008. Society of Petroleum Engineers
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History
- Original manuscript received:
20 February 2007
- Meeting paper published:
1 April 2007
- Revised manuscript received:
10 April 2008
- Manuscript approved:
19 April 2008
- Version of record:
25 October 2008
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