Stretched Exponential Production Decline (SEPD)
Overview
The Stretched Exponential Production Decline (SEPD) model was introduced by ValkΓ³ and Lee (2010) as a statistically-grounded approach to decline curve analysis for unconventional reservoirs. Unlike other empirical models, SEPD has a foundation in statistical physics, specifically the theory of "fat-tailed" distributions, making it particularly suitable for analyzing large populations of wells.
Key Concepts
- Statistical Physics Basis: Derived from stretched exponential (Kohlrausch) functions used in material science
- Bounded EUR: Always produces finite cumulative production, avoiding the b > 1 problem
- Population-Based: Originally designed for analyzing entire field populations, not individual wells
- Three Parameters: Uses Qi, Ο (characteristic time), and n (stretching exponent)
When to Use SEPD
| Reservoir Type | Suitability | Notes |
|---|---|---|
| Shale gas | β Excellent | Original target application |
| Shale oil | β Excellent | Works well for tight oil |
| Tight gas | β Good | Captures transient behavior |
| Field-scale analysis | β Excellent | Designed for population statistics |
| Conventional | β οΈ Limited | May not match BDF behavior well |
Theory
Physical Basis
The SEPD model is based on the stretched exponential function (also called Kohlrausch function), which arises naturally in systems with a distribution of relaxation times. In reservoir context, this represents heterogeneity in drainage patterns and flow geometries.
The key insight is that production from unconventional wells can be viewed as a superposition of multiple exponential decays with varying time constants:
When follows a specific "fat-tail" distribution, the result is the stretched exponential form.
Stretched Exponential Function
The stretched exponential differs from a standard exponential by the exponent n on the time term:
- Standard exponential:
- Stretched exponential:
For , the function decays more slowly at early times and faster at late times compared to a standard exponential, capturing the transition from high initial decline to slower long-term decline.
Equations
Rate Equation
where:
- = Initial (peak) production rate (LΒ³/T)
- = Characteristic time parameter (T)
- = Stretching exponent (dimensionless, typically 0.2-0.5)
- = Time (T)
Cumulative Production
The cumulative production involves the incomplete gamma function:
where:
- = Complete gamma function
- = Upper incomplete gamma function
Ultimate Recovery (EUR)
As , the incomplete gamma function approaches zero:
This closed-form EUR is a key advantage of the SEPD model.
Time to Economic Limit
Solving for time when :
Functions Covered
| Function | Description | Returns |
|---|---|---|
| StretchedExponentialDeclineRate | Rate at time t | q(t), LΒ³/T |
| StretchedExponentialDeclineCumulative | Cumulative production at time t | Np(t), LΒ³ |
| StretchedExponentialDeclineTime | Time to reach economic rate limit | t, T |
| StretchedExponentialDeclineEUR | EUR to economic rate limit | Np(tβcon), LΒ³ |
| StretchedExponentialDeclineFitParameters | Fit [Qi, Ο, n] to data | Array[3] |
| StretchedExponentialDeclineWeightedFitParameters | Weighted fit [Qi, Ο, n] | Array[3] |
See each function page for detailed parameter definitions, Excel syntax, and usage examples.
Applicability & Limitations
Applicability Ranges
| Parameter | Recommended Range | Notes |
|---|---|---|
| Exponent n | 0.2 - 0.5 | n = 1 reduces to standard exponential |
| Ο (tau) | > 0 | Scales the decline timeline |
| Production history | > 6 months | Shorter histories may work for fitting |
Physical Constraints
- (required for declining rate)
- (physically meaningful stretching)
- (positive time constant)
- (physical rate)
Limitations
- No Physical Dβ Term: Unlike PLE, SEPD does not explicitly model terminal decline rate
- Late-Time Behavior: May not accurately capture boundary-dominated flow behavior
- Statistical Nature: Best suited for population analysis rather than individual well prediction
- Gamma Function: Cumulative calculation requires special mathematical functions
Comparison with Other Models
| Aspect | SEPD | Arps Hyperbolic | PLE |
|---|---|---|---|
| Theoretical basis | Statistical physics | Empirical | Loss-ratio |
| EUR formula | β Closed-form | β οΈ Only if b < 1 | β Numerical |
| Parameters | 3 | 3 | 4 |
| BDF modeling | β Implicit | β οΈ Poor | β Explicit Dβ |
| Population analysis | β Designed for | β Individual wells | β οΈ Possible |
Relationship to PLE
When in the PLE model:
This is equivalent to SEPD with . The key difference is that PLE explicitly includes a terminal decline term for boundary-dominated flow.
References
-
ValkΓ³, P.P. and Lee, W.J. (2010). "A Better Way to Forecast Production from Unconventional Gas Wells." SPE Annual Technical Conference and Exhibition, Florence, Italy. SPE-134231-MS.
-
ValkΓ³, P.P. (2009). "Assigning Value to Stimulation in the Barnett Shale: A Simultaneous Analysis of 7000 Plus Production Histories and Well Completion Records." SPE-119369-MS.
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Ali, T.A. and Sheng, J.J. (2015). "Production Decline Models: A Comparison Study." SPE-177300-MS.
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Abramowitz, M. and Stegun, I.A. (1972). Handbook of Mathematical Functions with Formulas, Graphs and Mathematical Tables. New York: Dover Publications.