A method to perform diagnostic of hydrocarbon production in a field, comprising: generating a thermal-hydraulic production system model of a wellsite and a surface facility in the field; simulating, by a computer processor, using the thermal-hydraulic production system model, and based on a plurality of root causes, a hydrocarbon production problem to generate a plurality of feature vectors (238, 372) corresponding to the plurality of root causes, wherein each of the plurality of feature vectors (238, 372) comprises a plurality of parameter values corresponding to a plurality of physical parameters associated with the hydrocarbon production; configuring, using the plurality of feature vectors (238, 372), a classifier (233, 376) of the hydrocarbon production problem, wherein the classifier (233, 376) is configured to classify the hydrocarbon production problem according to the plurality of root causes; detecting the hydrocarbon production problem in the field; obtaining surveillance data (235, 375), wherein the surveillance data (235, 375) is from the wellsite and the surface facility, and wherein the surveillance data (235, 375) comprises a plurality of measurements corresponding to the plurality of physical parameters; obtaining a plurality of probability density functions, wherein each of the plurality of probability density functions represents a probability distribution of measurement noise associated with one of the plurality of measurements; generating, by the computer processor, using the classifier (233, 376), and in response to detecting the hydrocarbon production problem, a posterior probability of at least one of the plurality of root causes by modeling each of the plurality measurements as a sum of an actual measurement and a measurement noise represented by a corresponding one of the plurality of probability density functions; identifying a root cause of the plurality of root causes based on the posterior probability of at least one of the plurality of root causes; and presenting the root cause to a user. generating a thermal-hydraulic production system model of a wellsite and a surface facility in the field; simulating, by a computer processor, using the thermal-hydraulic production system model, and based on a plurality of root causes, a hydrocarbon production problem to generate a plurality of feature vectors (238, 372) corresponding to the plurality of root causes, wherein each of the plurality of feature vectors (238, 372) comprises a plurality of parameter values corresponding to a plurality of physical parameters associated with the hydrocarbon production; configuring, using the plurality of feature vectors (238, 372), a classifier (233, 376) of the hydrocarbon production problem, wherein the classifier (233, 376) is configured to classify the hydrocarbon production problem according to the plurality of root causes; detecting the hydrocarbon production problem in the field; obtaining surveillance data (235, 375), wherein the surveillance data (235, 375) is from the wellsite and the surface facility, and wherein the surveillance data (235, 375) comprises a plurality of measurements corresponding to the plurality of physical parameters; obtaining a plurality of probability density functions, wherein each of the plurality of probability density functions represents a probability distribution of measurement noise associated with one of the plurality of measurements; generating, by the computer processor, using the classifier (233, 376), and in response to detecting the hydrocarbon production problem, a posterior probability of at least one of the plurality of root causes by modeling each of the plurality measurements as a sum of an actual measurement and a measurement noise represented by a corresponding one of the plurality of probability density functions; identifying a root cause of the plurality of root causes based on the posterior probability of at least one of the plurality of root causes; and presenting the root cause to a user.