Nonlinear Inversion of Plane Wave Seismograms Using Global Optimization Methods

本研究旨在开发一种改进的反演技术， 地震速度模型，如石油勘探所需的模型 地壳研究。 当前技术的问题在于， 必须对速度模型进行初步猜测;然后， 调整直到符合观察结果。 然而最终结果 往往取决于最初的猜测。 反演方法 称为模拟退火，基于冷却模型， 结晶，试图避免必须进行初始 估计，以得出最佳的最终模型， 地震数据。 第二种技术被称为遗传算法 基于自然选择和遗传学的生物学原理。 两者都是全局优化方法。 如果成功， 技术在地震勘探中有着广泛的应用前景 和地壳调查。

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.