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Use of genetic algorithms for optimization in the calculation of cell-based variograms for the simulation of a reservoir

Abstract:

The importance of analyzing the continuity and regularity of the properties of a reservoir lies in developing a better pbkp_rediction of oil reserves in situ, therefore, it is necessary to know how these parameters are going to be dispersed. Incorporating all the information available from the study area, we carry out the reservoir characterization process that aims to simulate a reservoir model as close to reality as possible. For this, the analysis of the variograms is applied as a geostatistical technique, which allows to analyze the spatial behavior of the regionalized variables or properties of the reservoir. For this calculation, some parameters must be defined as input data for the modeling. In the present work, an algorithm was developed to automate the calculation of variograms for the optimization of the selection of the parameters that are needed for their adjustment in geostatistical modeling. This technique consists of the implementation of Genetic Algorithms (GA), tested through experimentation, which can be used to optimize the calculation of variogram based on cells or mesh. The Genetic Algorithms (GA) technique exploits the historical information (implicit memory) of the reservoir, to consider new areas of interest with high hydrocarbon storage potential, for which the algorithm has been built to improve the calculation and adjustment variographic.