Seismic Data and Fault Detection Labels for Machine Learning Analysis

This dataset contains seismic data and corresponding fault detection labels used for the research article titled "Fault Detection in Seismic Data Using Machine Learning Models." The seismic data includes preprocessed seismic traces in MATLAB format, while the fault labels are provided as binary matrices representing fault locations. The dataset was generated and analyzed using various seismic attributes, including similarity, coherency, and instantaneous phase, to enhance the accuracy of fault detection.

The data can be used for benchmarking fault detection algorithms, developing machine learning models, and validating geophysical interpretation methods.

Content Overview:

Seismic Data: Processed seismic sections in MATLAB format.

Fault Labels: Binary images indicating fault locations.

Attribute Maps: Extracted seismic attributes (e.g., Coherency, Similarity) in .mat format.

Metadata: Information about data preprocessing and attribute extraction.

Data Usage:
Researchers are encouraged to use this dataset for further studies in fault detection, seismic interpretation, and machine learning applications. Proper citation of the related article is appreciated.

Contact:
For inquiries regarding the dataset, please contact the corresponding author of the article.

本数据集配套于题为《基于机器学习模型的地震数据断层检测》的研究论文，包含地震数据与对应的断层检测标签。其中地震数据为MATLAB格式的预处理地震道，断层标签则以表征断层位置的二值矩阵形式提供。本数据集通过多种地震属性（包括相似性、相干性与瞬时相位）生成并分析，以提升断层检测的精度。

该数据集可用于基准测试断层检测算法、开发机器学习模型以及验证地球物理解释方法。

内容概览：
地震数据：MATLAB格式的处理后地震剖面。
断层标签：表征断层位置的二值图像。
属性图：格式为.mat的提取地震属性（如相干性、相似性）。
元数据：关于数据预处理与属性提取的相关信息。

数据使用须知：
欢迎研究人员使用本数据集开展断层检测、地震解释及机器学习应用相关的后续研究，敬请正确引用相关论文。

联系方式：
若对本数据集有任何疑问，请联系该论文的通讯作者。

搜集汇总

背景与挑战

背景概述

该数据集包含预处理的地震数据和对应的断层检测标签，专门用于机器学习分析，以提高断层检测的准确性。数据内容包括地震轨迹、二进制断层标签和提取的地震属性（如相干性和相似性），适用于算法基准测试、模型开发和地球物理解释验证。