Dense Array Toolkit

Overview

Dense array toolkit (DAT) is an open-source, MATLAB-based software package for dense seismic array data processing and imaging. Motivated by the increasing deployment of large-N seismic arrays and the growing demand for advanced data analysis tools, DAT provides a comprehensive framework that integrates receiver function calculation, data processing techniques (such as radon transform, and rank-reduction methods), and advanced imaging algorithms including common conversion point stacking, migration, and least-squares migration.

DAT overview

Objects

DAT is designed for efficient processing of large volumes of short-period nodal seismic data, with three key modules:

  • rapid receiver function calculation

  • advanced array-based data processing

  • improved subsurface structure imaging

Features

The software comprises three key struct variables:

  • DataStruct: Stores essential seismic data information, including fields such as Waveforms, TimeAxis, StationInfo, EventInfo, Header, RF, TravelInfo, and ProcHistory.

  • GridStruct: Defines the spatial grid configuration of the array. Station coordinates are projected onto a Cartesian coordinate system aligned with the principal and secondary axes.

  • ParamStruct: Contains parameters for data preprocessing, such as filtering, normalization, and time window selection.

Framework of DAT

Quickstart

The software is entirely written in MATLAB, and can be easily installed and used on Windows, Linux, and macOS. MATLAB R2021a or later is recommended.

The following is a quickstart guide to get you started.

  1. Download the source code:

    • Clone the DAT repository (DAT-public branch) from GitHub:

      git clone -b DAT-public git@github.com:PengfeiZuo001/DenseArrayToolkit.git DenseArrayToolkit-public
      

      Or download the source code from here.

    • Run setupPaths.m in DenseArrayToolkit-public/ directory to setup the path:

  2. Run the demo:

    • Change directory to DenseArrayToolkit-public/demo/ directory.

    • Run demo_Stacking.m to perform the stacking demo.

    • Run demo_rankReduction.m to perform the rank reduction demo.

    • Run demo_Migration_2D.m to perform the 2D LSM demo.

    • Run demo_Migration_3D.m to perform the 3D LSM demo.

  3. Explore Documentation (Coming soon):

    • To be updated.

How to cite

If you use DAT in your research, please cite it as follows:

  • Chen, Y., Gu, Y. J., Zuo, P., Zhang, Q., Wang, H., & Chen, Y. (2025). Least-squares migration imaging of receiver functions. IEEE Transactions on Geoscience and Remote Sensing. PDF

Contributing

We welcome contributions!

Feel free to contact with us if you have good ideas and suggestions.