New well production forecast method based on long-term and short-term memory(LSTM)neural network was proposed to solve the problems that artificial intelligence production prediction method commonly used in oilfields cannot consider the temporal correlation of data with time. Based on the introduction of principle and modeling steps of back propagation(BP)neural network,recurrent neural network(RNN),and LSTM neural network,development indicators affecting yearly oil production of new single well were selected taking the yearly production forecast of new single well of an oilfield as an example,the corresponding LSTM neural network were trained,and the yearly oil production of new single well was forecasted. The forecasted results were compared to those of support vector regression model and BP neural network. The results show that the forecast model has good fitting result with higher forecast accuracy. The forecast method based on LSTM neural network can be used as a new artificial intelligence method for the oil production forecast of new well in oilfields. It is a new method to accurately forecast the oil production of new wells in oilfield and to guide oilfield development decision making.
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HOU Chunhua. New well oil production forecast method based on long-term and short-term memory neural network[J]. Petroleum Geology and Recovery Efficiency,2019,26(3):105~110