A computer-implemented method for performing a field operation of a field in the form of a survey operation, comprising collecting data of a subterranean formation with data acquisition tools (102-1, 102-2, 102-3, 102-4) positioned at various locations along the field, or a wellbore operation, comprising fracturing or production, comprising: performing a plurality of model calibration iterations based on a plurality of measurements of the field, wherein the model comprises a basin model including a petroleum system model that simulates the events leading to generation, migration and accumulation of hydrocarbons in reservoir rocks, wherein each of the plurality of model calibration iterations comprises: obtaining, during the field operation, a current measurement of the field; generating a plurality of likelihood values corresponding to a plurality of model realizations (235-1, 235-2) of the field, wherein each of the plurality of likelihood values is generated by at least comparing the current measurement of the field to a modeling result of a corresponding model realization, the likelihood value representing the likelihood of the modeling result matching the current measurement; selecting, based on the plurality of likelihood values, at least one selected model realization from the plurality of model realizations, wherein selecting the at least one selected model realization comprises: performing statistical sampling from the plurality of likelihood values using at least a genetic algorithm; generating, by at least adjusting a first input value of the at least one selected model realization, an adjusted model realization (235-3, 235-4) of the field based on the at least one selected model realization, wherein adjusting the first input value comprises a random adjustment; adding the adjusted model realization to the plurality of model realizations; and generating a calibrated modeling result of the field based on the adjusted model realization from at least one of the plurality of model calibration iterations; and generating a control signal based on the calibrated modeling result, wherein a current portion of the field operation is performed based on the control signal. performing a plurality of model calibration iterations based on a plurality of measurements of the field, wherein the model comprises a basin model including a petroleum system model that simulates the events leading to generation, migration and accumulation of hydrocarbons in reservoir rocks, wherein each of the plurality of model calibration iterations comprises: obtaining, during the field operation, a current measurement of the field; generating a plurality of likelihood values corresponding to a plurality of model realizations (235-1, 235-2) of the field, wherein each of the plurality of likelihood values is generated by at least comparing the current measurement of the field to a modeling result of a corresponding model realization, the likelihood value representing the likelihood of the modeling result matching the current measurement; selecting, based on the plurality of likelihood values, at least one selected model realization from the plurality of model realizations, wherein selecting the at least one selected model realization comprises: performing statistical sampling from the plurality of likelihood values using at least a genetic algorithm; generating, by at least adjusting a first input value of the at least one selected model realization, an adjusted model realization (235-3, 235-4) of the field based on the at least one selected model realization, wherein adjusting the first input value comprises a random adjustment; adding the adjusted model realization to the plurality of model realizations; and generating a calibrated modeling result of the field based on the adjusted model realization from at least one of the plurality of model calibration iterations; and obtaining, during the field operation, a current measurement of the field; generating a plurality of likelihood values corresponding to a plurality of model realizations (235-1, 235-2) of the field, wherein each of the plurality of likelihood values is generated by at least comparing the current measurement of the field to a modeling result of a corresponding model realization, the likelihood value representing the likelihood of the modeling result matching the current measurement; selecting, based on the plurality of likelihood values, at least one selected model realization from the plurality of model realizations, wherein selecting the at least one selected model realization comprises: performing statistical sampling from the plurality of likelihood values using at least a genetic algorithm; generating, by at least adjusting a first input value of the at least one selected model realization, an adjusted model realization (235-3, 235-4) of the field based on the at least one selected model realization, wherein adjusting the first input value comprises a random adjustment; adding the adjusted model realization to the plurality of model realizations; and generating a calibrated modeling result of the field based on the adjusted model realization from at least one of the plurality of model calibration iterations; and generating a control signal based on the calibrated modeling result, wherein a current portion of the field operation is performed based on the control signal.