关键词: 地震数据反演, Monte~Carfo算法, 模拟退火算法, 遗传算法, 利余静校正, 情报调研

Abstract: Monte一Carlo inversion method does not solve inverse problem by way of equations，but through the inspection of a series of searching points randomly generated in solvable model space. This method has strong antinoise ability, and needs no linearizing assump-tions. Simulated annealing (SA) technique is produced by comparing the optimum problems
with the thermal balance problens in statistical mechanics，and therefore，is an optimization technique which regards the function erquired to find its extreme value as an energy function of the whole system，and the system state at any time as a point in the model space. The technique has the advantage of avoiding local minimization，but has the drawback of much
calculation. Genetic algorithm (GA)，a global optimization technique，appeared ten years earlier than SA. GA is in fact a group of operations applied to a model population to produce a new model population that has higher values of average fitness than the antecedent mem-
bers. The three algorithms mentioned above have been widely used in the solving of geo-physical problems and are a powerful mathematical tool for nonlinear inversion problems.

Key words: Seismic data inversion, Monte-Carlo algorithm, Simulated annealing al-gorithm, Genetic algorithn, Nonlinear optimization