automatic near surface time anomaly correction

简明释义

1. 自动表层时间异常校正; 2. 自动静校正程序;

英英释义

例句

1.With automatic near surface time anomaly correction, we can reduce the manual effort required in data processing.

通过近地表时间异常自动校正，我们可以减少数据处理所需的人工工作量。

2.By applying automatic near surface time anomaly correction, we were able to identify hidden faults in the rock layers.

通过应用近地表时间异常自动校正，我们能够识别岩层中的隐蔽断层。

3.The research team utilized automatic near surface time anomaly correction to analyze geological formations more effectively.

研究团队利用近地表时间异常自动校正更有效地分析地质构造。

4.The software implements automatic near surface time anomaly correction to improve the accuracy of seismic data.

该软件实施了近地表时间异常自动校正以提高地震数据的准确性。

5.The latest version of our application includes automatic near surface time anomaly correction for improved performance.

我们应用的最新版本包含了近地表时间异常自动校正以提高性能。

作文

In the field of geophysics, accurate data interpretation is crucial for understanding subsurface structures and processes. One significant challenge that researchers face is the presence of anomalies in time measurements, particularly when dealing with near-surface geological formations. These anomalies can lead to misinterpretations and affect decision-making in various applications, such as resource exploration and environmental assessments. To address this issue, the concept of automatic near surface time anomaly correction emerges as a vital tool. This technique involves the use of algorithms and computational methods to automatically identify and correct time anomalies in geophysical data, particularly those related to seismic waves traveling through near-surface materials.The process begins with the collection of seismic data, which may include reflections from various geological layers. However, due to factors such as varying material properties, topography, and human activities, the recorded times may not accurately represent the true travel times of seismic waves. This is where automatic near surface time anomaly correction plays a pivotal role. By applying sophisticated algorithms, the system can analyze the data to detect discrepancies and make necessary adjustments.One of the key advantages of automatic near surface time anomaly correction is its efficiency. Traditional methods often require manual intervention and expert knowledge, which can be time-consuming and prone to human error. In contrast, automated systems can process large datasets rapidly, providing corrections in real-time or near-real-time. This capability not only saves time but also enhances the reliability of the results, allowing geophysicists to focus on analysis rather than data cleaning.Moreover, the implementation of automatic near surface time anomaly correction contributes to improved accuracy in subsurface imaging. By correcting time anomalies, the resulting seismic images become clearer and more representative of the actual geological conditions. This is especially important in industries like oil and gas exploration, where precise imaging can significantly impact drilling decisions and resource extraction strategies.Additionally, automatic near surface time anomaly correction can be integrated with other geophysical techniques, such as ground-penetrating radar (GPR) and electrical resistivity tomography (ERT). This integration allows for a more comprehensive understanding of subsurface conditions, leading to better-informed decisions in engineering projects, environmental monitoring, and archaeological investigations.The future of automatic near surface time anomaly correction looks promising, with advancements in machine learning and artificial intelligence paving the way for even more sophisticated correction methods. As these technologies continue to evolve, we can expect enhanced capabilities in identifying complex anomalies and improving the overall quality of geophysical data.In conclusion, automatic near surface time anomaly correction represents a significant advancement in geophysical data processing. By automating the correction of time anomalies, researchers can achieve greater accuracy, efficiency, and reliability in their analyses. As the demand for precise subsurface information grows, the importance of this technique will only increase, solidifying its role as a cornerstone in modern geophysical research and application.

在地球物理学领域，准确的数据解释对于理解地下结构和过程至关重要。研究人员面临的一个重大挑战是时间测量中存在的异常，特别是在处理近地表地质构造时。这些异常可能导致误读，并影响各种应用中的决策，例如资源勘探和环境评估。为了解决这个问题，自动近地表时间异常校正的概念作为一种重要工具出现。这种技术涉及使用算法和计算方法，自动识别和纠正地球物理数据中的时间异常，特别是与穿过近地表材料的地震波相关的时间。该过程始于收集地震数据，这可能包括来自不同地质层的反射。然而，由于材料属性、地形和人类活动等因素，记录的时间可能无法准确表示地震波的真实传播时间。这就是自动近地表时间异常校正发挥关键作用的地方。通过应用复杂的算法，系统可以分析数据以检测差异并进行必要的调整。自动近地表时间异常校正的一个主要优点是其效率。传统方法通常需要人工干预和专业知识，这可能耗时且容易出错。相比之下，自动化系统可以快速处理大量数据集，提供实时或接近实时的校正。这一能力不仅节省了时间，还提高了结果的可靠性，使地球物理学家能够专注于分析而不是数据清理。此外，实施自动近地表时间异常校正有助于提高地下成像的准确性。通过校正时间异常，生成的地震图像变得更加清晰，更能代表实际的地质条件。这在石油和天然气勘探等行业尤为重要，因为精确的成像对钻探决策和资源开采策略有显著影响。此外，自动近地表时间异常校正可以与其他地球物理技术集成，如地面穿透雷达（GPR）和电阻率层析成像（ERT）。这种集成使对地下条件有更全面的理解，从而在工程项目、环境监测和考古调查中做出更明智的决策。自动近地表时间异常校正的未来看起来很有前景，机器学习和人工智能的进步为更复杂的校正方法铺平了道路。随着这些技术的不断发展，我们可以期待在识别复杂异常和提高地球物理数据整体质量方面的能力增强。总之，自动近地表时间异常校正代表了地球物理数据处理的重要进展。通过自动化校正时间异常，研究人员可以在分析中实现更大的准确性、效率和可靠性。随着对精确地下信息的需求不断增长，这一技术的重要性只会增加，巩固其在现代地球物理研究和应用中的基石角色。