Abstract: Automatic calibration for modeling a field includes performing model calibration iterations based on measurements of the field. Each model iteration includes obtaining, during the field operation, a current measurement of the field, generating likelihood values corresponding to model realizations of the field, where each likelihood value is generated by at least comparing the current measurement of the field to a modeling result of a corresponding model realization, selecting, based on the likelihood values, at least one selected model realization from the model realizations, generating, by at least adjusting a first input value of the at least one selected model realization, an adjusted model realization of the field based on the at least one selected model realization, and adding the adjusted model realization to the model realizations. Automatic calibration for modeling a field further includes generating a calibrated modeling result of the field based on the adjusted model realization.

Abstract: Automatic calibration for modeling a field includes performing START model calibration iterations based on measurements of the field. Each model iteration includes obtaining, during the field operation, a current measurement of the field, generating likelihood values corresponding to model realizations of the field, where each likelihood value is generated by at least comparing the current measurement of the field to a modeling result of a corresponding model realization, selecting, based on the likelihood values, at least one selected model realization from the model realizations, generating, by at least adjusting a first input value of the at least one selected model realization, an adjusted model realization of the field based on the at least one selected model realization, and adding the adjusted model realization to the model realizations. Automatic calibration for modeling a field further includes generating a calibrated modeling result of the field based on the adjusted model realization.