Feature-based Warping Toolkit

The Feature-based Warping Toolkit is a Python-based framework designed for time shift analysis of post-stack time-lapse seismic data in a feature based approach. This toolkit enables preprocessing SEG-Y files, performing feature-based warping, saving results in SEG-Y format, and creating interactive 3D visualizations.

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Features

• Data Preprocessing:

  • Support for SEG-Y data handling.

• Feature-Based Warping:

  • A warping algorithm using peaks and troughs for feature alignment.
  • Optimized with multiprocessing and Numba for efficient computation.

• Post-Processing and Visualization:

  • Save processed outputs (time strain and shifts) in SEG-Y format.
  • Interactive 3D visualization of seismic attributes using Mayavi.

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Installation

Prerequisites

Ensure you have Python 3.5+ installed.

Steps

1. Clone the repository: git clone https://github.com/ImperialCollegeLondon/feature-based-warping.git

2. Install dependencies pip install -r requirements.txt

Quick Start

1. Running the Workflow To preprocess, warp, save, and visualize results:

python test.py

Configuration

All configurable parameters are defined in the config.py file. Below are some key parameters:

File paths:

BASE_PATH: Path to the baseline SEG-Y file.
MONITOR_PATHS: List of paths to the monitor SEG-Y files.
OUTPUT_STRAIN_PATH: Path to save the time strain SEG-Y output.
OUTPUT_SHIFT_PATH: Path to save the shifts SEG-Y output.

Processing Parameters:

STRAIN_LIMIT: Maximum allowable time strain.
UPSAMPLE_FACTOR: Factor for upsampling signals.
WINDOW_SIZE: Size of the moving average filter for smoothing.

Dependencies

The toolkit requires the following libraries:

numpy
matplotlib
segysak
numba
mayavi
tqdm
scipy

Contributing

We welcome contributions!

License

This project is licensed under the MIT License.