基于粒子群算法的测井岩心深度自动归位研究

Well logging core automatic location based on particle swarm optimization

为解决传统岩心深度手动归位不准确、主观性强等缺点,提出了一种利用粒子群算法实现岩石物理实验数据深度自动归位的方法。基于同一深度的测井参数与岩心的物理试验数据具有相关性这一事实,以测井曲线深度为基准,寻找岩心深度全局位移最小、数值变化趋势对应性最好的优化算法。实验表明:用粒子群算法可以快速有效地实现以测井曲线深度为标准的岩心深度自动归位。

There are shortcomings of inaccuracy and subjective error in traditional manual core location.In order to overcome those disadvantages a new method of realizing automatic core location based on particle swarm optimization is proposed in this paper.There are relativities between the well logging curve and physical data at the same deepth.According this theory the core location can be summed up the optimization questions that the global displacement is the smallest while the trend of numerical value is the best fitted.The simulation results show that the automatic core location can be achieved through the particle swarm optimization algorithm.