Simulated annealing velocity analysis: Automating the picking process

虚假关系 算法 马克西玛 计算机科学 模拟退火 分段 正常时差 过程(计算) 分段线性函数 跳跃式监视 最大值和最小值 数学优化 数学 数学分析 人工智能 偏移量(计算机科学) 艺术 机器学习 表演艺术 程序设计语言 艺术史 操作系统
作者
Danilo R. Velis
出处
期刊:Geophysics [Society of Exploration Geophysicists]
卷期号:86 (2): V119-V130 被引量:8
标识
DOI:10.1190/geo2020-0323.1
摘要

We have developed an automated method for velocity picking that allows us to estimate appropriate velocity functions for the normal moveout correction of common-depth-point (CDP) gathers, valid for either hyperbolic or nonhyperbolic trajectories. In the hyperbolic velocity analysis case, the process involves the simultaneous search (picking) of a certain number of time-velocity pairs in which the semblance, or any other coherence measure, is high. In the nonhyperbolic velocity analysis case, a third parameter, usually associated with the layering and/or the anisotropy, is added to the searching process. Our technique relies on a simple but effective search of a piecewise linear curve defined by a certain number of nodes in a 2D or 3D space that follows the semblance maxima. The search is carried out efficiently using a constrained very fast simulated annealing algorithm. The constraints consist of static and dynamic bounding restrictions, which are viewed as a means to incorporate prior information about the picking process. This allows us to avoid those maxima that correspond to multiples, spurious events, and other meaningless events. Results using synthetic and field data indicate that our technique permits automatically obtaining accurate and consistent velocity picks that lead to flattened events, in agreement with the manual picks. As an algorithm, the method is very flexible for accommodating additional constraints (e.g., preselected events) and depends on a limited number of parameters. These parameters are easily tuned according to data requirements, available prior information, and the user’s needs. The computational costs are relatively low, ranging from a fraction of a second to, at most, 1–2 s per CDP gather, using a standard PC with a single processor.

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
砍柴少年发布了新的文献求助10
刚刚
Hello应助HQQ采纳,获得10
1秒前
1秒前
深情安青应助Jidekxin采纳,获得10
1秒前
Tammy发布了新的文献求助10
2秒前
2秒前
3秒前
ltz完成签到,获得积分10
3秒前
隐形曼青应助MMHH11采纳,获得10
3秒前
3秒前
可靠访蕊完成签到,获得积分10
4秒前
科研通AI6.2应助友好傲白采纳,获得30
4秒前
大模型应助LIKO采纳,获得10
5秒前
付银薇完成签到,获得积分10
5秒前
骨科小李完成签到,获得积分10
5秒前
Monroe完成签到,获得积分10
5秒前
吴呜呜完成签到,获得积分10
5秒前
5秒前
YYM发布了新的文献求助10
6秒前
华仔应助风吹麦浪采纳,获得100
6秒前
顺利莛发布了新的文献求助10
6秒前
7秒前
7秒前
7秒前
perty02完成签到,获得积分10
7秒前
Frances发布了新的文献求助10
7秒前
南博赛文完成签到 ,获得积分10
7秒前
艾妮吗发布了新的文献求助10
8秒前
东方元语应助alicia采纳,获得20
8秒前
lewellyn完成签到,获得积分10
8秒前
8秒前
冰冰发布了新的文献求助10
9秒前
10秒前
10秒前
兴奋蘑菇发布了新的文献求助10
10秒前
bkagyin应助小黑采纳,获得10
10秒前
11秒前
11秒前
初景发布了新的文献求助30
11秒前
szh123发布了新的文献求助10
11秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
化工安全与环保 1000
Autoparametric Resonance in Mechanical Systems 1000
基于锂离子电池正极材料回收的绿色溶剂开发及工程化应用研究 800
Cosmos as Art Object: Studies in Plato's Timaeus and Other Dialogues 600
Management and the Arts 510
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7654393
求助须知:如何正确求助?哪些是违规求助? 9225799
关于积分的说明 19820628
捐赠科研通 7220730
什么是DOI,文献DOI怎么找? 3279617
关于科研通互助平台的介绍 2440138
邀请新用户注册赠送积分活动 2279009