Oil-Production Performance Forecast with HyperDSI

Emmanuel Fetel and Jean-Laurent Mallet and Jean-Jacques Royer. ( 2004 )
in: 24th gOcad Meeting, ASGA

Abstract

This paper focuses on forecasting the uncertainty of oil-reservoir performance. Usually, to assess uncertainty, a large number of equiprobable geo-models is generated. However due to time consuming calculations and computer limitations, only a limited number of models are investigated in detailed flow simulation. This paper proposes a new approach for predicting the reservoir performance based on the simulation results for all the available models. Firstly all the realizations are described by several attributes characterizing the reservoir flow pattern. These attributes define an N-dimensional space where the expected oil-reservoir performance parameter is interpolated from the set of simulated models. The interpolator used for this method is a adapted version of the Discrete Smooth Interpolation algorithm to the N-dimensional case.

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    BibTeX Reference

    @inproceedings{FetelRM2004,
 abstract = { This paper focuses on forecasting the uncertainty of oil-reservoir performance. Usually, to assess uncertainty, a large number of equiprobable geo-models is generated. However due to time consuming calculations and computer limitations, only a limited number of models are investigated in detailed flow simulation. This paper proposes a new approach for predicting the reservoir performance based on the simulation results for all the available models. Firstly all the realizations are described by several attributes characterizing the reservoir flow pattern. These attributes define an N-dimensional space where the expected oil-reservoir performance parameter is interpolated from the set of simulated models. The interpolator used for this method is a adapted version of the Discrete Smooth Interpolation algorithm to the N-dimensional case. },
 author = { Fetel, Emmanuel AND Mallet, Jean-Laurent AND Royer, Jean-Jacques },
 booktitle = { 24th gOcad Meeting },
 month = { "june" },
 publisher = { ASGA },
 title = { Oil-Production Performance Forecast with HyperDSI },
 year = { 2004 }
}