000			02718nab a2200217 4500
005			20260520004416.0
008			260224s2013 xxu ing
041			_aInglés
245	0	0	_aSeismic History Matching of Fluid Fronts Using the Ensemble Kalman Filter
260			_a _b _cfeb. 2013
270			_a16/04/2013 ; 16/04/2013
300			_a12 p. ; 159-171
520			_aTranscripción del resumen del autor: Time-lapse seismic data provide information on the dynamics of multiphase reservoir fluid flow in places where no production data from wells are available. This information, in principle, could be used to estimate unknown reservoir properties. However, the amount, resolution, and character of the data have long posed significant challenges for quantitative use in assisted-history matching workflows. Previous studies, therefore, have generally investigated methods for updating single models with reduced parameter-uncertainty space. Recent developments in ensemble-based history-matching methods have shown the feasibility of multimodel history and matching of production data while maintaining a full uncertainty description. Here, we introduce a robust and flexible reparameterization for interpreted fluid fronts or seismic attribute isolines that extends these developments to seismic history matching. The seismic data set is reparameterized, in terms of arrival times, at observed front positions, thereby significantly reducing the number of data while retaining essential information. A simple 1D example is used to introduce the concepts of the approach. A synthetic 3D example, with spatial complexity that is typical for many waterfloods, is examined in detail. History-matching cases based on both separate and combined use of production and seismic data are examined. It is shown that consistent multimodel history matches can be obtained without the need for reduction of the parameter space or for localization of the impact of observations. The quality of forecasts based on the history-matched models is evaluated by simulating both expected production and saturation changes throughout the field for a fixed operating strategy. It is shown that bias and uncertainty in the forecasts of production both at existing wells and in the flooded area are reduced considerably when both production and seismic data are incorporated. The proposed workflow, therefore, enables better decisions on field developments that require optimal placement of infill wells.
581			_a1
773	0		_tSPE Journal _g18
942			_cARTICULO
100	1		_aTrani, Mario _952993
100	1		_aArtsm Rob _952994
100	1		_aLeeuwenburgh, Olwijn _952995
999			_c187602 _d187602