This project will be set up as an extension for a period of another two years and aims in particular at applications of Machine Learning where clear advantages can be expected compared to classical executions by ML. We are largely focusing (as in the first phase) on topics that are not already covered by other research groups. The choice of topics is based on the work of the first phase.
Here we successfully occupied the field of Deep Neural Networks (DNNs-) supported image-to-image processing. We observed high quality application results for a variety of seismic datasets – even when the networks had been trained exclusively with purely synthetic data. A key insight here was the level of abstraction for the synthetic datasets, which required feature-based modeling without the need to simulate the real-world appearance of the field data.
Take Advantage of Special Opportunities Offered by the New ML Tools
Gather conditioning tools – such as ML-Demultiple and ML-Align – show clear advantages over classical methods:
- Avoidance of parameters to control the processes
- Independence from the respective domain of the gathers (time-depth, offset angle)
- Significant acceleration of process flows due to obsolete quality control
- Avoidance of typical artifacts of classical results, such as oscillating artificial structures caused by align, or false amplitude removal due to aliased events in Radon-demultiple
The potential of these tools to be highly effective alternatives to classical methods is thus obvious. It is also clear that we can only achieve the required level of robustness and quality by working closely with industry partners. In doing so, we incorporate their data sets and expertise in evaluating the results. Technically, this collaboration was prepared in the first phase by integrating the tools into the execution platform Aloma. Aloma was successfully installed on partners´ hardware and already used on a trial basis.
The tasks and goals for Phase 2 are selected in accordance to the preparatory work of Phase 1 and to the expertise profile of our group. Applications from both, seismic data processing and seismic interpretation, are considered.
The Planned Work Packages Include:
- Gather conditioning extension
- Use of GANs for seismic applications
- Interpolating seismic data in different sortings
- Study of training with synthetic data compared to training with labeled field data
- Automated Multi-Well Tie
Please contact us in case you are interested and like to receive the project proposal.