Two stochastic versions of the Arps decline curve

• Analyse of stochastic curve declines. • Introduction of uncertainty in curve decline. • Oil and gas application. Based on the Arps equation, we propose two stochastic models for decline curve useful in oil engineering context. These stochastic models allow to take into account non-monotonic curve and to integrate randomness. Theoretical properties and simulations of these models are provided. The first passage time distribution of these stochastic models to a constant level is then studied. In conclusion, we introduce the oil production cumulative rate defined as the integral of the studied stochastic process over a given time interval. Statistical inference of the parameters could based on this integrated stochastic models. All these models provide a theoretical framework that could be applied to data in future work.

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Publication Details

Journal
Communications in Nonlinear Science and Numerical Simulation
Published
2025-10-10
DOI
https://doi.org/10.1016/j.cnsns.2025.109400
Primary Topic
Risk and Portfolio Optimization
Type
article
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article

Two stochastic versions of the Arps decline curve

Christian Paroissin
Communications in Nonlinear Science and Numerical Simulation
Risk and Portfolio Optimization
article

Two stochastic versions of the Arps decline curve

Christian Paroissin
article en

Abstract

• Analyse of stochastic curve declines. • Introduction of uncertainty in curve decline. • Oil and gas application. Based on the Arps equation, we propose two stochastic models for decline curve useful in oil engineering context. These stochastic models allow to take into account non-monotonic curve and to integrate randomness. Theoretical properties and simulations of these models are provided. The first passage time distribution of these stochastic models to a constant level is then studied. In conclusion, we introduce the oil production cumulative rate defined as the integral of the studied stochastic process over a given time interval. Statistical inference of the parameters could based on this integrated stochastic models. All these models provide a theoretical framework that could be applied to data in future work.

Communications in Nonlinear Science and Numerical SimulationVol. 152
Centre National de la Recherche Scientifique (FR), Université de Pau et des Pays de l'Adour (FR)
Openalex Percentile: Top 67%
Risk and Portfolio Optimization
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