【摘要】 地下岩层中普遍存在由地应力诱导排列的垂直裂隙或裂缝,转换横波在这样的介质中传播时,会分裂成沿着裂缝传播的快横波和垂直裂缝传播的慢横波,利用这一现象可以预测地层裂缝发育的方位和密度,该技术对于裂缝系油气藏探测起到了重要作用并显示了巨大的应用潜力.本文将模拟退火法与收缩因子粒子群算法进行融合,并应用快慢横波的Pearson相关系数公式作为目标函数,来自动求取裂缝方位角度和密度,模型试算结果显示该算法能够很好的进行裂缝属性识别,而且具有收敛速度快、精度高、抗噪性能强的特性.更多还原

【Abstract】 There exist the stress-induced vertical align cracks or micro-cracks in the underground rock stratum widely,converted shear-wave will be split into fast wave parallel to fracture strike and slow wave perpendicular to the fracture strike when it propagates in this media containing cracks. Then the authors can detect polarization direction and density of crack underground by using shear-wave splitting phenomenon. The technology plays an important role and shows great potential for crack reservoir detection. In this paper,the authors combine simulated annealing with shrinkage factor particle swarm optimization algorithm,and apply the Pearson correlation coefficient formula of fast and slow waves as objective function,to obtain the fracture azimuth angle and density. The experimental results show that the algorithm can identify the crack properties,and has the characteristics of fast convergence,high accuracy and strong anti-noise performance.更多还原