基于粒子群算法的声波测井岩心自动归位

Sonic Logging Automatic Core Location Based on PSO

为解决传统岩心手动归位不准确、主观性强等缺点,提出一种全新的岩心归位方法,利用粒子群优化算法实现声波测井岩心自动归位。根据位于同一深度的声波时差与岩心的物性数据具有相关性这一原理,声波测井岩心自动归位可归结为寻找全局位移最小、数值变化趋势对应性最好的优化问题。仿真结果表明,用粒子群算法可以快速有效地实现声波测井岩心自动归位。

In order to solve the disadvantages of inaccuracy and subjective error in tradition manual core location, a novel automatic core location method is proposed. The automatic core location of sonic logging is realized by Particle Swarm Optimization（PSO）. There are relativities between the sound wave and physical data at the same deepth. According to this theory, the core location can be considered as optimization problems that the global displacement is the smallest while the trend of numerical value is the best fitted. Simulation results show that the automatic core location can be achieved prompt effectively through the particle swarm optimization algorithm.