Total Sa

Cyril Ronot

Pierre Biver

Philippe Ruelland

According to the invention, a training image denotes, for each cell of a first three-dimensional grid, a respective type of geological facies assigned to said cell. For each cell of a second three-dimensional grid, the morphology of which is matched to estimated geological horizons, the well data comprise a respective type of geological facies estimated for said cell. Two-dimensional patterns, each of which is defined along a respective geological horizon and includes, in a cell containing the intersection of a well with said geological horizon, the type of geological facies estimated for each cell, are defined. The instances of the identified two-dimensional patterns are counted in the training image so as to verify the ability of the training image to account for correlations between wells.

Method for validating a training image for the multipoint geostatistical modeling of the subsoil

According to the invention, in order to initialize the use of a multipoint geostatistical technique (MPS), the method takes information, which was collected in wells drilled in the area of the subsoil to be modeled, into account. Particularly, the method takes inter-well connectivity data into account, which indicate one or more groups of cells of a reservoir grid that are located along a plurality of wells and between which hydrodynamic communications have been observed. For each of said groups, compatible thumbnail images are searched for in a training image used in the MPS technique. Said thumbnail images have, in the training image, facies that enable the flows between the cells of the group. The thumbnail images are applied onto the reservoir grid in order to initialize MPS simulation while ensuring that the inter-well connectivity constraints will be respected.

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Pau, France

Cyril Ronot