The unknown is the position-dependent storage coefficient s[.] which appears in a linear, partial differential equation of parabolic type with respect to hydraulic potential p[..,.] and multiplies the time derivative of p[.,.]. The spatial derivatives of p.,.] appear in the form div ( a grad p ), where the position-dependent conductivity a[.] is known. The identification of s[.] from knowledge of the measured hydraulic potential z[.,.] relies on the minimisation of the output error functional. The minimisation algorithm is derived from the variational formulation of the inverse problem [J. L. Lions, 1968; G. Chavent, 1971]. A discrete gradient algorithm and the corresponding computer code are described. A stopping ctiterion based on data noise ``energy'' is defined. Numerical and graphical results obtained from (computationally) exact and noisy data are presented. The methods and results apply to the modeling of aquifers and of petroleum reservoirs.
Crosta, G. (1985). On the identification of a spatially varying coefficient appearing in a parabolic partial differential equation. In F. Kappel, K. Kunisch, W. Schappacher (a cura di), Distributed parameter systems (pp. 92-108). Berlin : Springer Verlag [10.1007/BFb0005646].
On the identification of a spatially varying coefficient appearing in a parabolic partial differential equation
Crosta, GFF
1985
Abstract
The unknown is the position-dependent storage coefficient s[.] which appears in a linear, partial differential equation of parabolic type with respect to hydraulic potential p[..,.] and multiplies the time derivative of p[.,.]. The spatial derivatives of p.,.] appear in the form div ( a grad p ), where the position-dependent conductivity a[.] is known. The identification of s[.] from knowledge of the measured hydraulic potential z[.,.] relies on the minimisation of the output error functional. The minimisation algorithm is derived from the variational formulation of the inverse problem [J. L. Lions, 1968; G. Chavent, 1971]. A discrete gradient algorithm and the corresponding computer code are described. A stopping ctiterion based on data noise ``energy'' is defined. Numerical and graphical results obtained from (computationally) exact and noisy data are presented. The methods and results apply to the modeling of aquifers and of petroleum reservoirs.File | Dimensione | Formato | |
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