Practical Considerations for Decline Curve Analysis in Unconventional Reservoirs - Application of Recently Developed Rate-Time Relations

2012 ◽  
Author(s):  
Viannet Okouma Mangha ◽  
Dilhan Ilk ◽  
Thomas Alwin Blasingame ◽  
Dave Symmons ◽  
Nima Hosseinpour-zonoozi
Keyword(s):  
Curve Analysis ◽  
Unconventional Reservoirs ◽  
Decline Curve Analysis ◽  
Decline Curve

Mechanistic Model Validation of Decline Curve Analysis for Unconventional Reservoirs

2020 ◽  
Author(s):  
Mikhail Gorditsa ◽  
Eric Bryan ◽  
George J. Moridis ◽  
Thomas A. Blasingame
Keyword(s):  
Model Validation ◽  
Mechanistic Model ◽  
Curve Analysis ◽  
Unconventional Reservoirs ◽  
Decline Curve Analysis ◽  
Decline Curve

Is Decline Curve Analysis the Right Tool for Production Forecasting in Unconventional Reservoirs?

2021 ◽  
Author(s):  
Oscar Molina ◽  
Laura Santos ◽  
Francisco Herrero ◽  
Agustin Monaco ◽  
Darren Schultz
Keyword(s):  
Curve Analysis ◽  
Stochastic Simulations ◽  
Unconventional Reservoirs ◽  
Sufficient Evidence ◽  
Production Data ◽  
Optimization Approach ◽  
Metaheuristic Algorithm ◽  
Decline Curve Analysis ◽  
Production Forecasting ◽  
Decline Curve

Abstract This study presents a novel metaheuristic algorithm that uses a physics-based model for multi-fractured horizontal wells (MFHW) to accurately predict the estimated ultimate recovery (EUR) for unconventional reservoirs. The metaheuristic algorithm creates a sizeable number of stochastic simulations and keeps the simulation results from those random models that closely reproduce observed production data. Unlike other optimization methods, the proposed algorithm does not aim at finding the exact solution to the problem but a group of sufficiently accurate solutions that help to construct the partial solution to the optimization problem as a function of production history. Results from this work provide sufficient evidence as to why traditional decline curve analysis (DCA) is not a suitable solution for production forecasting in unconventional reservoirs. Two case studies are discussed in this work where results from both modeling strategies are compared. Evolutionary prediction of EUR over time using DCA behaves erratically, regardless of the amount of historical production data available to the regression model. Such erratic behavior can, in turn, yield an erroneous estimation of key economic performance indicators of an asset. In contrast, the proposed metaheuristic algorithm delivers precise and accurate results consistently, achieving a significant reduction of uncertainties as more production data becomes available. In conclusion, the proposed partial optimization approach enables the accurate calculation of important metrics for unconventional reservoirs, including production forecasting and expected productive life of an asset.

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