Abstract: The method according to the invention for analyzing longitudinal data characterizing the evolution of at least a first variable as a function of at least one second variable, comprising steps for determining (22, 24, 26) adjacent variation sub-intervals for at least one of said first and/or second variables and characterizing (28) said data on said sub-intervals wherein the step for determining said sub-intervals comprises: defining (24) a representative function of a dispersion of said variable in said sub-intervals, the value of which depends on the lower and upper bounds of said sub-intervals, and determining (26) the lower and upper bounds of said sub-intervals optimizing the value of said function.

Abstract: A method for constructing a model representative of a heterogeneous medium from data expressed in different time scales with application to hydrocarbon characterization. The method first estimates sequentially, from the data expressed in each different time scale, parameters or physical quantities of the model, described for each different time scale. Second, a scale factor allowing conversion of a model described in a time scale into a model described in another time scale is determined. This determination is carried out by minimizing the dissimilarity between a parameter estimated in a time scale and this parameter estimated in the other time scale. Finally, estimation of a single model is performed, by taking simultaneously an account of the data expressed in the various time scales, and using the scale factor found previously for the time scale conversions.

Abstract: A method for constructing a model representative of a heterogeneous medium from data expressed in different time scales with application to hydrocarbon characterization. The method first estimates sequentially, from the data expressed in each different time scale, parameters or physical quantities of the model, described for each different time scale. Second, a scale factor allowing conversion of a model described in a time scale into a model described in another time scale is determined. This determination is carried out by minimizing the dissimilarity between a parameter estimated in a time scale and this parameter estimated in the other time scale. Finally, estimation of a single model is performed, by taking simultaneously an account of the data expressed in the various time scales, and using the scale factor found previously for the time scale conversions.