a comparison of data analysis techniques for oil production prediction: the case study of ahvaz field

this paper describes two data analysis techniques adopted in a decision support system (dss), decline curve estimation and artificial neural network (ann) approaches, which aid users in predicting oil production of a field. the system generates different predictions, according to scenario, chosen for prediction. these two approaches show that to explain production of a field, ann method shows better fit to historical data, compared with regression method used for decline curve estimation. but to predict production of the same field these two show completely different forcasts, which alarms us to be careful in using a particular method for predictions. in the case of modeling a mathematical relation for production of a field, researchers should apply different approaches and compare the result to reach to a better conclusion about the production rate. jel classification: q4