一种多信息组合卷积神经网络速度谱自动采摘方法

IF 1.6 3区 地球科学 Q3 GEOCHEMISTRY & GEOPHYSICS
Run Jiang, Xiaodong Sun, ZhenChun Li, DongDong Peng, Liang Zhao
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引用次数: 0

摘要

地震速度是地震勘探中的一个关键参数,其准确性对数据处理和解释结果的可靠性有重大影响。然而,人工采集速度的方法不仅效率低,而且耗时长,越来越不能满足实际生产工作的需求。本文介绍了多信息组合卷积神经网络(MCCN)速度自动拾取方法。在卷积神经网络的基础上,我们设计了 MCCN 方法的网络结构,专门针对叠加速度拾取任务的特点。鉴于速度频谱能量簇同时表现出形态和趋势特征,我们采用了回归卷积神经网络来提高速度拾取的准确性。此外,由于速度频谱包含多波干扰和其他噪音,我们采用了协调注意机制来减轻干扰信息的影响。我们的方法包括通过双组合网络同时纳入速度频谱和 CMP 信息,从而进一步提高速度拾取精度。最后,我们将我们的方法与全连接卷积神经网络和人工速度拾取方法进行了比较,证明了我们提出的方法的实用性和精确性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A multi-information combined convolutional neural network velocity spectrum automatic picking method
Seismic velocity is a critical parameter in seismic exploration, and its accuracy significantly impacts the reliability of data processing and interpretation results. However, manual velocity picking methods are not only inefficient but also time-consuming, making them increasingly inadequate for meeting the demands of practical production work. This paper introduces the Multi-Information Combination Convolutional Neural Network (MCCN) velocity auto-picking method. Building upon the foundation of convolutional neural networks, we have designed the network structure of the MCCN method specifically tailored to the characteristics of stacked velocity picking tasks. Given that velocity spectrum energy clusters exhibit both morphological and trend features, we employs a regression convolutional neural network to enhance the accuracy of velocity picking. Furthermore, as the velocity spectrum contains interference from multiple waves and other noise, we employ a coordinate attention mechanism to mitigate the influence of interfering information. Our approach involves the simultaneous incorporation of velocity spectrum and CMP information through a dual-combination network, thereby further enhancing velocity picking accuracy. Finally, we compare our method with fully connected convolutional neural networks and manual velocity picking methods, demonstrating the practicality and precision of our proposed approach.
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来源期刊
Journal of Geophysics and Engineering
Journal of Geophysics and Engineering 工程技术-地球化学与地球物理
CiteScore
2.50
自引率
21.40%
发文量
87
审稿时长
4 months
期刊介绍: Journal of Geophysics and Engineering aims to promote research and developments in geophysics and related areas of engineering. It has a predominantly applied science and engineering focus, but solicits and accepts high-quality contributions in all earth-physics disciplines, including geodynamics, natural and controlled-source seismology, oil, gas and mineral exploration, petrophysics and reservoir geophysics. The journal covers those aspects of engineering that are closely related to geophysics, or on the targets and problems that geophysics addresses. Typically, this is engineering focused on the subsurface, particularly petroleum engineering, rock mechanics, geophysical software engineering, drilling technology, remote sensing, instrumentation and sensor design.
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