Streamlined Collaboration for Geoscientists
CanopyGeo is a Python-based analysis environment that is straightforward to extend with custom data analysis workflows and visualization tools, providing a comprehensive solution for rapid development of new analysis methods, creation of user interfaces to streamline custom workflows, and in-house deployment of final applications.
- Powerful cross-domain data analysis and visualization
- Extensible for new analysis and visualization solutions
- Flexible, customizable Python-based platform
- Allows for rapid innovation and implementation
Brendon Hall | 0m48s | Co-visualizing Cross-disciplinary Data in CanopyGeo
Cross-Domain Visualization, Exploration, and Analysis Capabilities
CanopyGeo provides novel capabilities to co-visualize data spanning multiple geoscience disciplines, significantly reducing the limitations of domain-specific solutions to accelerate the delivery of innovative analysis and research methods to the geoscience community.
View a composite set of seismic data, horizons,
and well paths in a single display
Extensible and Flexible
In CanopyGeo you can add new data types, editors, menu entries, and menus to build your own extensions for custom algorithms, cross-domain workflow automation, and multi-domain visualization tools. Developers can contribute reader-writers, data objects, editors, 3D elements for the 3D viewer, menu actions, dockable side panels, and more through specialized add-ons.
The flexible I/O and data architecture and standard readers mean you can also add new data file formats and CanopyGeo data objects, and make them accessible to Canopy Geo’s various tools. With Python scripts and the Canopy Geo object model, you can extend the platform to handle additional data file formats.
Display and edit well log data interactively
Access the full power of the scientific Python ecosystem for custom data processing, interactive analyses, and advanced plotting and visualization.
CanopyGeo includes an IPython interactive command line console for inspecting and processing data objects. You can drag a SEG-Y data object into the console, print its header, edit its data and run advanced analysis or data processing scripts on it.
With CanopyGeo’s advanced editor, you can write scripts to automate analysis pipelines and new workflows. For example, a script can access a data object loaded in the data panel, analyze its content, create new data objects based on this analysis, and open a visualization tool to display the result. With the editor, you can drag a script in to open it, find context sensitive help, use auto-completion and right-click to run the script in the IPython console.
Data can be visualized in 2D using a map view, or along a traverse (inline, crossline, or user-defined)