A function optimization problem is presented to demonstrate the feasibility of this method as well as demonstrating the global optimization functionality of genetic algorithm.

In this paper, the authors describe a new global optimization strategy to solve some problems such as the initial model sensitivity, frequent local traps for the conventional impedance inversion based on model in the method searching model based on genetic algorithm is added into the calculating flow of logging constraint inversion.

This paper presents a new inversion algorithm,quantum genetic algorithm,which adopts the qubit chromosomes as presentations and updates the population using quantum rotation gate,to accelerate the search speed,to improve convergent efficiency,and to get a better global optimization.