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- W2000966118 abstract "Abstract In a new field development, enormous time and energy are put in to identify and quantify both static and dynamic reservoir uncertainties. This could be very challenging when information is limited and not readily available. These data uncertainties vary from project to project depending on the quantity of reliable reservoir data acquired during the exploration and appraisal stage. The first step towards managing reservoir uncertainty in field development is to identify and quantify the key reservoir parameters that affect hydrocarbon in place and recovery. These parameters or factors are so many that their combinational effects result in multiple cases of development options, which will require many simulation runs. Stochastic and statistical data analysis coupled with Experimental Design(ED) have been used in recent times to reduce time and energy expended in managing key reservoir uncertainty parameters. The case study presented in this paper gives an illustration of a successful ED application in a new gas field development. A detailed workflow was created to identify and quantify the uncertainties and risks in the dynamic model using probabilistic approach. This resulted in Probabilistic field forecasts that were further used to test surface development options in order to determine the optimal field development strategy that is robust to multiple realisations of reservoir uncertainties" @default.
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- W2000966118 date "2010-07-31" @default.
- W2000966118 modified "2023-10-05" @default.
- W2000966118 title "Managing Reservoir Uncertainty in Gas Field Development Using Experimental Design" @default.
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- W2000966118 doi "https://doi.org/10.2118/140619-ms" @default.
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