I often say that INTViewer is a bit of Swiss knife. It serves multiple purposes, and each company finds a different use. This makes it hard to decide which feature to highlight. In the past few years, as the industry moved to the cloud, we created a companion for INTViewer: INTGeoServer, which makes it easy to visualize data beyond the bounds of your network. This year, with the new release of INTViewer approaching, I will highlight the opposite feature of INTViewer: its ability to work offline, disconnected from the world.
In our previous blog, Simplifying the Learning Curve of the Seismic Unix Library, we described how INTViewer can leverage the SU library. This library is typically meant for Linux, but it can also be used on Windows. This walkthrough describes how to install the SU Library on Windows 10 to use the Seismic Workbench plugin.
Two decades after its creation, the Java runtime has finally become modular. A modular approach not only makes dependency management easier, but it also makes applications more efficient as unused modules don’t need to be loaded. The NetBeans Platform predates Java 9 and has been using its own module system for years. Since INTViewer is a desktop application built on top of the NetBeans Platform, I find that it is far superior to the Java 9 module system for my use cases.
INTViewer provides a graphical user interface for the SU library, reducing the learning curve. The Seismic Workbench is a free plugin that has the documentation for the SU library built in, making it easy to find a particular command and all the parameters that this command requires. INTViewer builds the full command line for you based upon all individual commands selected.
Storing and accessing large, sometimes sensitive geoscience data is one challenge many top E&P companies face. Local data storage is one option. But what about data that is not stored locally? How do you access it quickly, and can you still use INTViewer?
A major feature of INTViewer 5.2 is the Python integration. Our development team worked very hard to ensure that our customers can get started easily and be productive once they are hooked. One consistent user feedback was that the Python terminal lacked autocompletion. It could become tedious to have to type the full name of each class, each method or each variable. We took this feedback to heart and implemented autocompletion in INTViewer 5.2.
Presenting data to clients regularly poses many challenges, especially considering that today’s datasets are more likely to exceed a petabyte or more. Slideshows that may take hours to create are often instantly obsolete and frequently don’t fully answer your clients’ questions. With one simple plugin, INTViewer transforms the art of showing data to your clients by combining the simplicity of a slideshow and the power of live data.
I have been using NetBeans daily for about 8 years, so I’d say I am pretty familiar … with the features I use all the time. Over the years, friends and colleagues have shown me that there are faster ways to get the job done. I have gathered in this post three shortcuts that I learned from others and that you can also use when you develop an INTViewer plugin.
In our blog post on Microsoft Azure, we describe various ways customers can move their data to the cloud. In the configuration where INTViewer is hosted on a remote server and needs to be accessed from a local workstation, a Teradici client is one solution. These configurations are increasingly popular with our customers. For performance […]
Horizon picking is a feature that INTViewer has included from the start. However, after discussing with several long-time users, I have found that the evolutions brought by each release can be missed. The release of INTViewer 5.2 is a good opportunity to tour basic picking options. First, a bit of terminology. The term “horizon” in […]
In our post, “Closer Look at Coordinate Conversions,” we allude to the capabilities of INTViewer with coordinate system conversions. One benefit of on-the-fly conversions is the ability to see your seismic data in context. In the example below, a time slice is reprojected to the coordinate system used by Google Maps. Showing satellite […]
If you are already a user of INTViewer, the first thing you will certainly notice when you open INTViewer 5.2 for the first time is the new window system. The way windows are laid out on screen has changed, introducing tabs to browse through these windows.
INTViewer makes coordinate conversions virtually transparent to users. Users pick two Coordinate Reference Systems (CRS), one for their data and one for the visualization map, and the visualization updates automatically. How does INTViewer do it? The short answer is “it depends”. The long answer is that the strategy used varies based upon the CRSs selected, […]
INTViewer provides many features off-the-shelf, but its extensibility is unique. Developers can customize numerous aspects of INTViewer by extending the INTViewer platform. And one way to extend this platform is to write Java plugins.
Sometimes, you don’t need to add new features to make a software great — just revisiting a design can add value. For INTViewer, the CRS selection dialog is one of the areas we improved just by tweaking the design.
The cloud is not just a set of computing resources hosting web based-applications. Microsoft Azure can also be used to host what we know today as desktop PCs. Constant availability and unlimited storage are just two of the numerous advantages of hosting your PC on the cloud.
Microsoft Windows has a standard dialog to choose and save files, but this is not an optimal way to navigate your file system from within your application. INTViewer addresses this issue.
The Normalization widget is one of the new tools in INTViewer 5.2. It shows graphically how your current selection relates to the minimum and maximum amplitudes of the entire dataset. There are several normalization options in INTViewer: RMS, Maximum, Limits, etc.