Boundary-Dominated Flow in Solution Gas-Drive Reservoirs

Camacho, Ramiro Gustavo Ramírez; Raghavan, R.

doi:10.2118/19009-ms

Cited by 13 publications

(21 citation statements)

References 12 publications

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“…Camacho & Raghavan [2] emphasize that in many cases one single Arps curve is not sufficient to obtain a satisfactory fit, as the production data span the entire set of curves. Thus, in many situations it may be necessary to use a combination of curves to get a satisfactory fit.…”

Section: Combining Several Arps Curves To Obtain Multisegmented Produmentioning

confidence: 99%

The Modelling of Multisegment Production Profiles Using Hybrid Systems and Ordinary Differential Equations

Haavardsson

Huseby

2007

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fax 01-972-952-9435. AbstractWhen an oil-or gasfield project is evaluated, it is crucial to have a satisfactory model for the production. Knowledge about the properties of the reservoir should be included in such a model. When used in a total value chain analysis, however, also economic and strategic factors need to be taken into account. In order to do this, more flexible modelling tools are needed. In this paper we demonstrate how this can be done using hybrid system models. In such models the production is modelled using ordinary differential equations representing both the reservoir dynamics as well as strategic control variables. The approach also allows us to break the production model into a sequence of segments. Thus, it is possible to represent various discrete events affecting the production in different ways. The flexibility of the modelling framework makes it possible to obtain realistic approximations to real-life production profiles. As the calculations can be done very efficiently, the framework can be incorporated in a full scale uncertainty analysis based on Monte Carlo simulation.)

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Section: Combining Several Arps Curves To Obtain Multisegmented Produmentioning

confidence: 99%

The Modelling of Multisegment Production Profiles Using Hybrid Systems and Ordinary Differential Equations

Haavardsson

Huseby

2007

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“…There have been many methods of decline curve analysis (DCA) in estimating production and reserves (Arps 1945;Fetkovich 1980;Agbi and Ng 1987;Camacho and Raghavan 1989;Palacio and Blasingame 1993;Masoner 1998;Agarwal et al 1999;Marhaendrajana and Blasingame 2001;Horne 2005, 2006). Aronofsky et al (1958) suggested an empirical model to match oil production by water injection in this type of reservoir.…”

Section: Introductionmentioning

confidence: 99%

Effective-Well Method for Matching and Predicting Oil Production

Guan

2011

Transp Porous Med

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Decline curve analysis (DCA) is a traditional method for production prediction, which is still being used because it works in many cases and it is relatively simple to apply. However, DCA methods can neither match nor predict the fluctuating oil production during the early period when applied to entire reservoirs. The change in oil production may be because of variation in production conditions or the number of injection/production wells. In this study, we focused on the latter problem, change in the number of production wells. Obviously, there would be a significant oil production boost during a specific time period if more oil wells are drilled. The traditional DCA approach cannot match the increase in oil production due to the increase in the number of oil production wells. We have developed a method to match the oil production of entire reservoirs for the life span by considering the change in the number of production wells. The main idea of this approach came from the concept of effective wells. We applied this approach in several sandstone oil reservoirs with different permeabilities. The proposed effective-well model could match the oil production data in different reservoirs, even during the early period of production when the oil production rate change with time because of the variation in the number of producers. Comparison with the existing models (exponential, hyperbolic model, and harmonic models) was made and the results showed the proposed approach had the best fit to the production history in the cases studied.

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“…The main purpose of this study was to conduct a comparison between the exponential model, the Li-Horne model 3 , and the harmonic model. To do so, both experimental data from core samples and production data from reservoirs with different values of permeability were analyzed using the three models.…”

Section: Introductionmentioning

confidence: 99%

Verification of Decline Curve Analysis Models for Production Prediction

Li¹,

Horne²

2005

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TX 75083-3836, U.S.A., fax 01-972-952-9435. AbstractReserves and production in petroleum reservoirs can be estimated using empirical and analytical decline curve analysis models. There have been many such models. In this study, three representative models (exponential, harmonic, and the mechanistic Li-Horne models) were chosen to predict and match oil and gas production from both core samples and reservoirs with different permeability. The recovery and reserves were estimated using the three models and the results were compared. The comparison demonstrated that the recovery at an assumed economic limit predicted using the Li-Horne model was greater than the exponential model but was less than the harmonic model. Note that the exponential model tends to underestimate reserves and production rates while the harmonic model has a tendency to overpredict the reservoir performance. It was also found that the reserves predicted using the harmonic model were greater than one pore volume in some cases, which is physically impossible. The model predictions using the experimental data of recovery in the core samples were also compared to the true values. The results demonstrated that the Li-Horne model had the best estimation of the recoverable recovery compared to the exponential and the harmonic models in the cases studied.

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Boundary-Dominated Flow in Solution Gas-Drive Reservoirs

Cited by 13 publications

References 12 publications

The Modelling of Multisegment Production Profiles Using Hybrid Systems and Ordinary Differential Equations

The Modelling of Multisegment Production Profiles Using Hybrid Systems and Ordinary Differential Equations

Effective-Well Method for Matching and Predicting Oil Production

Verification of Decline Curve Analysis Models for Production Prediction

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