Study on productivity prediction method of horizontal wells in thick, steep, narrow complex reservoirs of M1-1 oilfield

In view of the development of secondary faults in M1-1 oilfield, the reservoir is thick, steep and narrow, which makes the effective length of horizontal section of horizontal wells greatly different. The traditional production allocation method and formula method of specific oil recovery index can't realize the accurate prediction of productivity of this kind of horizontal well. A new method, which combines the grey relation method with the neural network method, can solve this problem well. First of all, the main factors affecting the productivity of horizontal wells in M1-1 oilfield are selected by using the grey correlation method, which are mainly horizontal section length, permeability, crude oil viscosity, production pressure difference and effective thickness. Then the main controlling factor is regarded as the neuron of BP neural network, and the neural network model is established. After the training of M1-1 oilfield actual data grid, the prediction results are consistent with the actual data, which shows that this method is suitable for the prediction of production capacity of complex reservoirs with thick, steep and narrow secondary faults in M1-1 oilfield. By using this method, the initial production capacity of the adjustment well was predicted to be 45～75 m3/d.