Nonlinear Inversion of Plane Wave Seismograms Using Global Optimization Methods

这项研究旨在开发一种改进的地震速度模型反演技术，如石油勘探和地壳研究所需的地震速度模型。当前技术的一个问题是，必须对速度模型进行初始猜测；然后对其进行调整，直到它符合观测结果。然而，最终结果往往取决于最初的猜测。一种名为模拟退火法的反演方法，基于冷却到结晶的模型，试图避免为了得到符合地震数据的最佳最终模型而不得不进行初始估计。第二种技术被称为遗传算法，它基于自然选择和遗传学的生物学原理。这两种方法都是全局优化方法。如果成功，该技术将在地震石油勘探和地壳调查中得到广泛应用。

This research is to develop an improved inversion technique for seismic velocity models such as those required in oil exploration and crustal studies. A problem with current techniques is that an initial guess must be made as to the velocity model; this is then adjusted until it fits the observations. However, the final result is often dependent on the initial guess. An inversion method termed simulated annealing, based on a model of cooling to crystallization, attempts to avoid having to make an initial estimate in order to come up with the best final model that fits the seismic data. A second technique is termed a genetic algorithm based on biological principles of natural selection and genetics. Both are global optimization methods. If successful, the techniques will have wide application in seismic oil exploration and crustal investigations.