000			01921nab a2200181 4500
005			20260520002030.0
008			260224s2011 xxu
245	0	0	_aEvaluation of the objective functions to improve production history matching performance based on fluid flow behaviour in reservoirs
260			_a _b _cjul. 2011
270			_a18/11/2011 ; 18/11/2011
300			_a12 p. ; 42-53
520			_aTranscripción del resumen del autor. This work deals with the problem of model performance evaluation, which is a challenge in many science branches, including subsurface fluid flow modelling (e.g. reservoir characterisation using history matching algorithms). The issue is posed as a problem of estimating the model performance by comparing the simulation results with observed data. This is accomplished by defining different statistical indicator objective functions (OF) to calculate the model efficiency, i.e. how model simulation fits observed data. Several deviation-based statistics used in literature as OF are analysed and applied to two synthetic case studies related to fluid flow in reservoir. Inaccuracies that arise from using the deviation-based statistics are discussed in a comparative way to propose an appropriate approach to boost the model accuracy when selecting the best realisation from multiple equally realisations generated during the history matching algorithm. The evaluations reveal that the suitable approach requires the adoption of an OF, that combines lag time with deviation-based statistic (SSR), to enhance the history matching process. The proposed approach has proven robust in the sense that it is able to provide an accurate and faster history matching algorithm for reservoir characterisation.
581			_a1
773	0		_tJournal of Petroleum Science & Engineering _g78
942			_cARTICULO
100	1		_aMata-Lima, Herlander _940805
999			_c186567 _d186567