Optimisation of a heterogeneous reservoir permeability model by means of dynamic data inversion on the basis of streamline simulation

Abstract

The main objective of oilfield characterization is to establish the oilfield’s model through the integration of all usable information. The traditional scope includes the modeling based primarily on static information, having as a final stage of the process, the validation of the model with the dynamic information available. The term validation involves a procedure that only tries to guarantee that the productive zones being modeled feature adequate oilfields properties. The new trends in oilfield characterization show that the dynamic information available should be integrated to the oilfield’s model. This process is not trivia, since it includes an optimization process framed by a continuous process of light simulation.  In this paper, a semi-analytical solution is proposed, as a product of the combination of geostatistical techniques with streamline simulation algorithms and of dynamic inversion of data for the optimization of the permeability model for heterogeneous oilfields, while verifying the effectiveness of the dynamic inversion scheme in two phases: adjustments to irruption times, followed by adjustments to the amplitude of the water cuts.  The methodology proposed was successfully applied to synthetic models and to a field case. The synthetic models were used to validate the efficiency of the procedure on classical methods of oilfield characterization. The field case corresponds to a highly heterogeneous oilfield: the A2 sands of block VII of the Casabe field. This example includes 22 productive wells and 19 injecting wells in an oilfield of fluvial origin, made up of stratigraphically complex geometries, such as cross-stratification, preferential flow channels, and lateral changes to facies and thicknesses, among others. The most important conclusion from this paper is that the regular injection patterns, of five pre-established points, are not efficient enough to optimize the secondary recovery process; therefore, suggestion is made to establish irregular models based on the trajectory of the flow lines.