CNN-LSTM Model Optimized by Bayesian Optimization for Predicting Single-Well Production in Water Flooding Reservoir

Table 4

Performance of different models (84-3).

Model	MAE	MAPE		RMSE	Accurate	Training time/min
CNN-LSTM	17.58	6.54	0.99	37.26	0.93	6.33
LSTM	20.33	7.02	0.99	44.36	0.9	5.18
GRU	21.45	7.15	0.99	47.14	0.9	3.04
Bi-LSTM	22.23	7.69	0.99	48.12	0.88	6.44
CNN	22.65	7.73	0.99	48.87	0.88	3.16
ARIMA	31.47	15.68	0.98	37.17	0.83	2.11
Attention-LSTM	40.26	18.26	0.97	60.68	0.82	8.26
Self-attention	60.15	25.36	0.96	80.67	0.66	5.01

84-3: using the data from the previous 84 months to predict oil production of the next three months.