Calculation of Klinkenberg permeability, slip factor and turbulence factor of core plugs via nonlinear regression
Pazos, Fernando A. Bhaya, Amit Martins Compan, André Luiz
Calculation of Klinkenberg permeability, slip factor and turbulence factor of core plugs via nonlinear regression - agos. 2009 - 9 p. ; 159-167
Transcripción del resumen del autor. Published methods to determine the Klinkenberg permeability, Klinkenberg slip factor and Forchheimer turbulence factor of core plugs can exhibit considerable error. Jones presented a technique based on gas pressure decay measurements during the transient state, where, with a single run, an algorithm can calculate the parameters with precision. However, this paper shows that Jones' method is based on a linear regression to find a fixed point of a nonlinear error function, and is presented without theoretical justification or convergence conditions. This paper proposes a simple algorithm, based on nonlinear regression, to calculate the unknown parameters, and has the advantage of theoretical justification as well as weaker requirements for convergence. In addition, a strategy to calculate the unknown physical parameters when the measurements are noisy is presented.
3-4
Calculation of Klinkenberg permeability, slip factor and turbulence factor of core plugs via nonlinear regression - agos. 2009 - 9 p. ; 159-167
Transcripción del resumen del autor. Published methods to determine the Klinkenberg permeability, Klinkenberg slip factor and Forchheimer turbulence factor of core plugs can exhibit considerable error. Jones presented a technique based on gas pressure decay measurements during the transient state, where, with a single run, an algorithm can calculate the parameters with precision. However, this paper shows that Jones' method is based on a linear regression to find a fixed point of a nonlinear error function, and is presented without theoretical justification or convergence conditions. This paper proposes a simple algorithm, based on nonlinear regression, to calculate the unknown parameters, and has the advantage of theoretical justification as well as weaker requirements for convergence. In addition, a strategy to calculate the unknown physical parameters when the measurements are noisy is presented.
3-4
