Research on methods for predicting oil well fracturing results

Based on the result evaluation of measures used to enhance oil production of fractured wells,a sample database with different types of measures and processes is established.Main factors taken into account in the database include the effective perforation thicknesses of whole wells,the formation coefficients of fractured layers,the pre-fracturing liquid production,the pre-fracturing water cut,the number of fracturing layers,and the total sand volume.Quantitative relationship is established between fracturing results and those factors mentioned above by employing the artificial neural network method.A model used to predict fracturing results is therefore established.Field application shows that the prediction results on the basis of the method are more reliable.