Free webinar Thursday 25 August - 4pm CET
In this webinar we will demonstrate how you can use OpendTect functionality directly in Petrel or how you can copy data across if you don't want to tie the Petrel license.
Did you know that in addition to creating great software, the dGB team also offers services in the form of software training, project management and execution as well as consultancy services. If you have a tough nut to crack, we’d love to hear from you!
This week we want to show you an example of the 4th Lundin model 'Lundin_GeoLab_SimpleDenoise". We believe this model is applicable to almost all datasets. Unlike the AJAX model, the SimpleDenoise model preserves the amplitude - frequency content. It only removes random noise.
This is the third and last post in our series on trained Machine Learning models developed by Lundin GeoLab that are released in OpendTect’s Machine Learning library. Two weeks ago, we presented SimpleHmult, a model to attenuate horizontal multiples. In last week’s post we showed an example of the application of Desmile, a model to remove migration smiles.
Last week we proudly announced the release of four stunning, pre-trained models from Lundin GeoLab in OpendTect’s Machine Learning solution. In last week’s blog post, we showed an example of one of these models: SimpleHmult, a 3D Unet model that attenuates horizontal multiples.
As of version 6.6.8, OpendTect’s library of pre-trained models boasts 4 spectaculair seismic enhancement models developed by Lundin’s GeoLab R&D group:
Dear OpendTect Users,
We have made a patch release for our latest stable version: OpendTect 6.6.8, which is now available for installation/update.
With the addition of the Machine Learning Professional plug-in, OpendTect development is further extended by allowing Python as an additional development environment. Starting from within OpendTect, a Python shell, or integrated development environment (IDE), can be launched, and one with direct access to the OpendTect-Python link, libraries and data structures that are a pre-requisite to further research and development. An advantage of Python is its flexibility, and the ability to add new tools and libraries from the command line, so, even this environment can be easily customized with additional analytics libraries. Recently we have added extended support for PyTorch, on top of our already extensive Tensorflow/Keras and scikit-learn support.
Geothermie Groep Nederland (GGN), dGB Earth Sciences and two suppliers of high-performance drilling services have joined their expertise to harvest low-enthalpy geothermal energy with temperatures ranging from 60 – 90 0C using LUC installations. LUC’s enable economic development of geothermal energy for domestic heating and heating of greenhouses, also from lower-quality aquifers in smaller-scale projects. The method consists of an innovative combination of project management, best-practices in well engineering, production technology and advanced reservoir management.