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|Type:||Artigo de evento|
|Title:||Use Of Representative Models To Improve The Decision Making Process Of Chemical Flooding In A Mature Field|
|Abstract:||Decision analysis applied to petroleum field development is always strongly related to risk due to uncertainties in the process. An important part of risk evaluation can be accomplished through the evaluation of the impact of uncertainties in the performance of the petroleum fields, yielding higher possibility of success, quantification of possible losses, minimization of sub-optimal development and identification of opportunities. The objective of the present work is to use the quantification of the impact of uncertainties related to chemical flooding (injection of Alkali-surfactant-polymer) using the concept of Representative Models (RM) integrated with economic uncertainties to improve the production forecast in a Brazilian onshore field with 19 years of production history. The main advantage of this process is to provide a few adjusted models (RM) which are selected based on the integration of objective functions previously defined to the context to represent these uncertainties. These RM are selected to represent all combined models which compose the distribution curve (risk curve) of the process. The distribution curve is obtained through the concept of derivative tree technique, combining the possible scenarios using the numerical simulation to predict the reservoir behavior. The numerical simulation is used to give more reliability to the process and to give a detailed analysis for each model in order to provide integration with economic analysis which is used in the risk mitigation. The importance of this process is to provide a detailed analysis of the impact of the chemical injection in the decision making process. An automated tool and the utilization of a defined methodology to quantify the impact of uncertainties are used to speedup the process and to improve the viability of the procedure with a significant reduction of time and effort, yielding greater reliability of the production forecast with the improvement of the decision making process. Copyright 2008. Society of Petroleum Engineers.|
|Appears in Collections:||Unicamp - Artigos e Outros Documentos|
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