Response surface method for assessing energy production from geopressured geothermal reservoirs

Geothermal Energy

Science – Society – Technology

Table 3 Summary of the second-order linear regression for the regular design: representing the interaction between two factors

Factors	\(\beta \,\, \mathrm{value}\)	Standard error	t value	Pr (\({>}\|\)t\|)
(Intercept)	−0.027	0.009	−3.037	0.006
Thickness	0.218	0.003	83.748	0.000
Length	0.745	0.003	289.663	0.000
Permeability	0.000	0.003	0.162	0.873
Porosity	0.039	0.003	15.264	0.000
ReservoirDip	0.230	0.003	88.528	0.000
I (thickness\(^{2}\))	−0.007	0.005	−1.277	0.214
I (length\(^{2}\))	−0.050	0.005	−9.904	0.000
I (porosity\(^{2}\))	−0.001	0.005	−0.245	0.809
I (permeability\(^{2}\))	0.001	0.005	0.216	0.831
I (reservoirDip\(^{2}\))	−0.035	0.005	−6.750	0.000
Thickness: length	0.041	0.005	7.929	0.000
Thickness: porosity	0.007	0.005	1.344	0.192
Thickness: permeability	0.001	0.005	0.220	0.828
Thickness: reservoirDip	0.020	0.005	3.927	0.001
Length: porosity	0.007	0.005	1.316	0.201
Length: permeability	0.002	0.005	0.353	0.727
Length: reservoirDip	0.138	0.005	26.580	0.000
Permeability: porosity	0.001	0.005	0.178	0.861
Porosity: reservoirDip	0.004	0.005	0.734	0.471
Permeability: reservoirDip	0.000	0.005	0.065	0.949

Estimate stands for the coefficient value of the regression model. Standard error, t value and p value for each coefficient is given. Gray color shows the important terms that should be retained in the reduced model. The p value is used for selecting the important predictors for the reduced model