Method for determining an electrofacies interpretation of measurements relative to at least one portion of at least one well drilled through an underground formation, comprising the following steps: A) carrying out a plurality of measurements relative to at least said portion of said at least one well drilled through said underground formation, said plurality of said measurements resulting at least from a well log and/or an image of at least one core sample taken in said at least one well; B) applying a first plurality of classification methods to said plurality of said measurements relative to at least said portion of said at least one well and determining a first plurality of electrofacies classifications of said plurality of said measurements relative to at least said portion of said at least one well, said classification methods being unsupervised classification methods, or, if learning information is available for at least one subset of said plurality of said measurements relative to at least said portion of said at least one well, supervised classification methods trained on said learning information; C) among said first plurality of electrofacies classifications of said plurality of said measurements relative to at least said portion of said at least one well, selecting a reference electrofacies classification according to a predefined criterion, and selecting a portion of said reference electrofacies classification; characterized in that the method in addition comprises the following steps: D) applying a second plurality of classification methods to said plurality of said measurements relative to at least said portion of said at least one well and determining a second plurality of electrofacies classifications of said plurality of said measurements relative to at least said portion of said at least one well, said classification methods being supervised classification methods trained on said portion of said reference electrofacies classification; E) determining said electrofacies interpretation of said plurality of said measurements relative to at least said portion of said at least one well from said second plurality of electrofacies classifications of said plurality of said measurements relative to at least said portion of said at least one well, said determining step being performed using an ensemble learning method. A) carrying out a plurality of measurements relative to at least said portion of said at least one well drilled through said underground formation, said plurality of said measurements resulting at least from a well log and/or an image of at least one core sample taken in said at least one well; B) applying a first plurality of classification methods to said plurality of said measurements relative to at least said portion of said at least one well and determining a first plurality of electrofacies classifications of said plurality of said measurements relative to at least said portion of said at least one well, said classification methods being unsupervised classification methods, or, if learning information is available for at least one subset of said plurality of said measurements relative to at least said portion of said at least one well, supervised classification methods trained on said learning information; C) among said first plurality of electrofacies classifications of said plurality of said measurements relative to at least said portion of said at least one well, selecting a reference electrofacies classification according to a predefined criterion, and selecting a portion of said reference electrofacies classification; characterized in that the method in addition comprises the following steps: D) applying a second plurality of classification methods to said plurality of said measurements relative to at least said portion of said at least one well and determining a second plurality of electrofacies classifications of said plurality of said measurements relative to at least said portion of said at least one well, said classification methods being supervised classification methods trained on said portion of said reference electrofacies classification; E) determining said electrofacies interpretation of said plurality of said measurements relative to at least said portion of said at least one well from said second plurality of electrofacies classifications of said plurality of said measurements relative to at least said portion of said at least one well, said determining step being performed using an ensemble learning method. D) applying a second plurality of classification methods to said plurality of said measurements relative to at least said portion of said at least one well and determining a second plurality of electrofacies classifications of said plurality of said measurements relative to at least said portion of said at least one well, said classification methods being supervised classification methods trained on said portion of said reference electrofacies classification; E) determining said electrofacies interpretation of said plurality of said measurements relative to at least said portion of said at least one well from said second plurality of electrofacies classifications of said plurality of said measurements relative to at least said portion of said at least one well, said determining step being performed using an ensemble learning method.