Discover the ease and efficiency of OpendTect's Presentation Maker, accessible to everyone. Seamlessly import images directly from your projects into your custom presentation template. With just a click, it auto-generates slides and titles, transforming your data into visually compelling presentations effortlessly. Experience a smarter way to communicate your project insights with this innovative tool.
Read more: Streamline Your Presentations with OpendTect: Fast, Professional Results with the free...
Spectral decomposition and RGB(A) blending is not only useful for studying sub-seismic resolution stratigraphic features, but can be a great asset to highlight potential bright (spot) amplitude anomalies.
Read more: How to Visualize Amplitude Anomaly in 3D Using Spectral Decomposition and RGB Attribute
Vulcania Energy, on behalf of MEPC, recently harnessed OpendTect's AI-based fault interpretation to supercharge seismic analysis in an offshore West African field.
Within this reservoir lie complex carbonate turbiditic deposits, molded by gravity's touch, presenting a captivating challenge for both human experts and AI.
Read more: Can AI Outshine Human Expertise in Seismic Analysis?
I really prefer this to conventionally tracking horizons in a grid!
Here's why:
Read more: Have you explored the free 3D auto tracker in OpendTect yet?
dGB Earth Sciences is thrilled to unveil the latest addition to our Machine Learning library - a state-of-the-art pre-trained model that is designed to predict faults and fractures in 2D/3D seismic data.
Read more: Introducing our new Pre-trained Fault model (Fault Net)
In our latest video, we break down the workflow to enhance the Thinned Fault Likelihood (TFL) using a two-step approach: Filtering and Computing RMS of TFL.
OpendTect’s library of trained Machine Learning models supports a set of powerful models for quickly enhancing post-stack 3D seismic data.
For example, there are models for removing random noise; suppressing horizontal multiples; predicting fault likelihood; interpolating missing traces and for improving the interpretability of seismic data.
OpendTect’s attribute engine stands out due to its ability to compute attributes-from-attributes both on-the-fly and in batch-mode. Such capability lets users craft intricate chained attributes and filters. However, as these chains grow, they become more intricate, making it challenging to decipher their computation process.
To simplify this for users, OpendTect offers a data flow visualization for chained attributes, presented as a comprehensive graph. Powering this visualization is Graphviz, a reputable open-source graph visualization tool.
Read more: Demystify Complex Chained Attributes with Data Flow Visualization in OpendTect
Today, we compare popular post-stack noise reduction filters in OpendTect. The data set is Penobscot, a free data set that is downloadable from TerraNubis, our marketplace for free and commercial data sets. A special feature of Penobscot is that it allows users to run all commercial plugins without the need for a license key. This means that anyone can replicate the tests shown in this post.
Read more: OpendTect Noise Filters Comparison: Cast your preference
OpendTect is committed to supporting the OSDUTM data platform as developed by the Open Group OSDUTM Forum. As an active member, we contributed to testing OSDU solutions developed for 3D seismic storage and access. Our work for OSDU resulted in the support of two new 3D seismic formats in OpendTect Pro v7: OpenVDS (Bluware) and OpenZGY (SLB). At the moment we support file-based storage and I/O. In future this will be extended to cloud-based data access.
Read more: OpendTect Pro supports two OSDU formats: OpenVDS and OpenZGY