Recurrent neural network model for bottomhole pressure and temperature in stepdown analysis

A method for fracturing a formation is provided. Real-time fracturing data is acquired from a well bore during fracturing operation. The real-time fracturing data is processed using a recurrent neural network trained using historical data from analogous wells. A real-time response variable prediction is determined using the processed real-time fracturing data. Fracturing parameters for the fracturing operation are adjusted in real-time based on the real-time response variable prediction. The fracturing operation is performed using the fracturing parameters that were adjusted based on the real-time response variable prediction.