Nonlinear Inversion of Plane Wave Seismograms Using Global Optimization Methods

使用全局优化方法非线性反演平面波地震图

• 批准号: 9105922
• 负责人: Mrinal Sen
• 金额: $ 15.72万
• 依托单位: University of Texas at Austin
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 1991
• 资助国家: 美国
• 起止时间: 1991-07-15 至 1993-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9105922&HistoricalAwards=false
• 关键词: Nonlinear; Inversion; Plane; Wave; Seismograms; Nonlinear; Inversion; Plane; Wave; Seismograms

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.

这项研究是为了开发一种改进的反转技术，以用于地震速度模型，例如石油勘探和地壳研究所需的反转技术。 当前技术的一个问题是必须对速度模型进行初始猜测。然后对此进行调整，直到适合观测值。 但是，最终结果通常取决于初始猜测。 基于冷却模型的结晶模型，一种称为模拟退火的反演方法，试图避免必须进行初始估算以提出适合地震数据的最终模型。 第二种技术被称为基于自然选择和遗传学的生物学原理的遗传算法。 两者都是全局优化方法。 如果成功，这些技术将在地震石油勘探和地壳研究中广泛应用。