Artificial Neural Network- (ANN-) Based Proxy Model for Fast Performances’ Forecast and Inverse Schedule Design of Steam-Flooding Reservoirs

Table 5

Summary of the parameters for normal distributions of all input parameters in the inverse project design ANN model.

Category	Parameter	Unit	Expectation	Standard deviation
Five-spot permeability	Permeability of injector	D	3.46	0.1
	Permeability of producer 1	D	4.37	0.1
	Permeability of producer 2	D	4.41	0.1
	Permeability of producer 3	D	4.38	0.1
	Permeability of producer 4	D	4.42	0.1
Data of cumulative oil production	Change rate of 909 m^3	Fraction	0	0.01
	Change rate of 2101 m^3	Fraction	0	0.01
	Change rate of 3261 m^3	Fraction	0	0.01
	Change rate of 4315 m^3	Fraction	0	0.01
	Change rate of 5274 m^3	Fraction	0	0.01
	Change rate of 6163 m^3	Fraction	0	0.01
	Change rate of 7004 m^3	Fraction	0	0.01
	Change rate of 7811 m^3	Fraction	0	0.01
	Change rate of 8593 m^3	Fraction	0	0.01
	Change rate of 9357 m^3	Fraction	0	0.01