Developing a Robust Surrogate Model of Chemical Flooding Based on the Artificial Neural Network for Enhanced Oil Recovery Implications

Table 1

Statistical analysis of the implemented chemical flooding data samples [9].

Parameter	Unit	Type	Min.	Max.	Average	Standard deviation
Surfactant slug size	PV	Input	0.097	0.259	0.177	0.072
Surfactant concentration	Vol. fraction	Input	0.005	0.03	0.017	0.011
Polymer concentration in surfactant slug	wt.%	Input	0.1	0.25	0.177	0.067
Polymer drive size	PV	Input	0.324	0.648	0.482	0.144
Polymer concentration in polymer drive	wt.%	Input	0.1	0.2	0.148	0.044
ratio	—	Input	0.01	0.25	0.129	0.107
Salinity of polymer drive	Meq/mL	Input	0.3	0.4	0.349	0.045
Recovery factor (RF)	%	Output	14.82	56.99	39.67	9.24
Net present value (NPV)	$ MM	Output	1.781	7.229	4.45	1.53