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

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.

本研究旨在开发一种改进的地震速度模型反演技术，用于石油勘探和地壳研究等领域。当前技术的一个问题是，必须对速度模型进行初步猜测；然后对其进行调整，直到与观测结果相符。然而，最终结果往往取决于最初的猜测。一种称为模拟退火的反演方法，基于一个从冷却到结晶的模型，试图避免为了得到最适合地震数据的最终模型而进行初始估计。第二种技术被称为基于自然选择和遗传学生物学原理的遗传算法。两者都是全局优化方法。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。