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Methodical approaches of ranking the remaining oil reserves of Vietnam offshore fields to optimize the development strategy

UDK: 553.98.048
DOI: 10.24887/0028-2448-2018-11-84-86
Key words: hydrodynamic modelling, oil reserves recovery, ranking, development plan efficiency
Authors: M.A. Fedoseev (Research and Engineering Institute, Vietsovpetro JV, the Socialist Republic Vietnam, Vung Tau), S.S. Karimov (Research and Engineering Institute, Vietsovpetro JV, the Socialist Republic Vietnam, Vung Tau)
Results comparison of oil reserves recovery analysis for various reservoirs and fields at diverse development stages and with different properties is the sophisticated problem for reservoir engineering specialists. Exemplified by the experience in developing Vietsovpetro offshore oil reservoirs, the method of remaining reserves block ranking, based on multifactor analysis of hydrodynamic modelling values, is proposed. The interest of such topic lies in deficiency of the consistent structured approach to analyze remaining reserves starting from definition of the study objects, description of their characteristics and comparison between each other in similar scale for the further decision-making on well interventions reasonability and their priorities. The work proposes one of the decisions on quick selection of the prospective block from the standpoint of comparing the remaining oil reserves of various reservoirs considering the contributing factors. The algorithm revealed by trial and error, allows improving the efficiency of dataset processing, which describe the current development status for separate field areas in order to define the optimization objects of hydrocarbon reserves recovery. The basis of dataset and one of the key tools is the result of geo-hydrodynamic modelling. Geo-hydrodynamic modelling allows defining the geological-field blocks and characterizes them. We performed the detailed analysis of the oil reserves recovery status for various fields and under diverse development stages and strategies. The obtained results allow to further select and rationale the well interventions, including well pattern infilling and flooding system optimization. Implementation of such technology allows the engineer to manage a bigger dataset, evaluate development status of defined field areas and to propose the optimization activities for the development strategy.
Results comparison of oil reserves recovery analysis for various reservoirs and fields at diverse development stages and with different properties is the sophisticated problem for reservoir engineering specialists. Exemplified by the experience in developing Vietsovpetro offshore oil reservoirs, the method of remaining reserves block ranking, based on multifactor analysis of hydrodynamic modelling values, is proposed. The interest of such topic lies in deficiency of the consistent structured approach to analyze remaining reserves starting from definition of the study objects, description of their characteristics and comparison between each other in similar scale for the further decision-making on well interventions reasonability and their priorities. The work proposes one of the decisions on quick selection of the prospective block from the standpoint of comparing the remaining oil reserves of various reservoirs considering the contributing factors. The algorithm revealed by trial and error, allows improving the efficiency of dataset processing, which describe the current development status for separate field areas in order to define the optimization objects of hydrocarbon reserves recovery. The basis of dataset and one of the key tools is the result of geo-hydrodynamic modelling. Geo-hydrodynamic modelling allows defining the geological-field blocks and characterizes them. We performed the detailed analysis of the oil reserves recovery status for various fields and under diverse development stages and strategies. The obtained results allow to further select and rationale the well interventions, including well pattern infilling and flooding system optimization. Implementation of such technology allows the engineer to manage a bigger dataset, evaluate development status of defined field areas and to propose the optimization activities for the development strategy.


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