Abstract: Hydrofracturing is one of the main technical means for improving the recovery efficiency in low-permeability oil/gas fields.However,there are many factors that influence the hydrofracturing effects,including geological characteristics,physical properties of reservoirs and energy of strata.In order to obtain ideal hydrofracturing results,it is necessary to give a comprehensive consideration of the relationships between various influence factors and find out the main factors that influence the hydrofracturing effects.The authors constructed a mathematic evaluation model by using the artificial neural network method and performed net training and method check and verification of a wealth of available production data.The results prove that the constructed potential evaluation model using hydrofracturing wells has good stability and a high precision of prediction.It has certain guiding significance for choosing wells and evaluating layers for hydrofracturing and forecasting of the production capacity.