Blog
Sharing Trained Machine Learning Models will redefine our modus operandi
- Written by: Marieke van Hout
My colleague Hardeep Jaglan from dGB Earth Sciences will be presenting at the EAGE (European Association of Geoscientists and Engineers) in Madrid in the ARK CLS Limited booth #1154.
Read more: Sharing Trained Machine Learning Models will redefine our modus operandi
Cyber Security Certified - Saudi Aramco’s stamp of approval
- Written by: Arjan Burggraaf
We are proud to announce that we have officially received Saudi Aramco's Third Party Cybersecurity Compliance Certificate (CCC).
Read more: Cyber Security Certified - Saudi Aramco’s stamp of approval
Thalweg Tracker: Geobodies Extraction tool
- Written by: Hesham Refayee
A unique piece of functionality in OpendTect Pro is the Thalweg tracker.
A Thalweg tracker is a 3D amplitude tracker that grows 3D bodies along the path of least resistance. The tracker has two main applications:
- to detect and isolate 3D bodies of sedimentary features such as channels, lobes, splays, and reef buildups, and
- to create labels for supervised Machine Learning seismic facies segmentation workflows.
OpendTect vs OpendTect Pro
- Written by: Marieke van Hout
In this video Paul de Groot from dGB Earth Sciences explains the main differences between the free platform OpendTect and our commercial platform OpendTect Pro.
Spectral Decomposition - Free webinar
- Written by: Marieke van Hout
Spectral Decomposition - Free webinar on 12 May, 11 am CET
Integrated Machine Learning Rock Property Prediction Workflow
- Written by: Hesham Refayee
OpendTect allows geoscientists to integrate and transform data from 1 D model to a predicted 3D rock property cube.
Read more: Integrated Machine Learning Rock Property Prediction Workflow
OpendTect patch release 6.6.7
- Written by: Raman Singh
Hi all,
We have made a patch release for our latest stable version: OpendTect 6.6.7, which is now available for installation/update.
Fault Dip and Azimuth for Machine Learning Fault Likelihood
- Written by: Paul de Groot
In today’s post we share an elegant workflow proposed by Roar Heggland of Equinor ASA to compute Fault Dip and Fault Azimuth for Machine Learning predicted Fault Likelihood (ML-FL).
Read more: Fault Dip and Azimuth for Machine Learning Fault Likelihood
High-resolution unsupervised 3D segmentation of waveforms for quick geomorphological analysis - Free webinar
- Written by: Friso Brouwer
High-resolution unsupervised 3D segmentation of waveforms for quick geomorphological analysis - Free webinar on Thursday 14 April, 4 pm CET by Friso Brouwer and dGB Earth Sciences.