Abstract: A method of constructing an image representing the distribution of a categorical physical property representative of an underground zone having applications for petroleum reservoir development. A first training image representative of a geometrical structure of the categorical property is constructed. Training images representative of the distributions of several auxiliary properties are then constructed from the first training image. A probability law of the categorical property and a probability law of each auxiliary property are determined, from each training image, for a given pixel according to the values of the neighboring pixels. A probability law of the categorical property is calculated from these laws and from the images representative of the distribution of the auxiliary physical properties in the zone, and for each pixel of the image to be constructed. Finally, the value of the categorical property is determined by carrying out a random selection for the calculated probability law.

Abstract: A method of constructing an image representing the distribution of a categorical physical property representative of an underground zone having applications for petroleum reservoir development. A first training image representative of a geometrical structure of the categorical property is constructed. Training images representative of the distributions of several auxiliary properties are then constructed from the first training image. A probability law of the categorical property and a probability law of each auxiliary property are determined, from each training image, for a given pixel according to the values of the neighboring pixels. A probability law of the categorical property is calculated from these laws and from the images representative of the distribution of the auxiliary physical properties in the zone, and for each pixel of the image to be constructed.