Visit Ikon Science at EAGE for higher hit rates and faster production from simpler wells.  At the conference we will be showcasing our two linked platforms, RokDoc (the industry-leading platform for the prediction of subsurface, reservoir and fluid properties) and iPoint (software for data management, geologically consistent aggregation and visualisation of subsurface wellbore data) combined with fast developing AI methods which together enable digital geoscience to fully impact the upstream. 

Visit back soon for our booth talk schedule. 

EAGE accepted papers

1. Kester Waters will present Facies based Bayesian pre-stack seismic inversion in the depth domain and 

2. Denis Alexeenko will present Seismic data conditioning is an essential step for facies prediction.

Both of these papers are in the Seismic Interpretation - Quantitative Interpretation and AVO I session. 

Wednesday, Jun 5, 2019
1:30 PM - 5:10 PM
Room 01

3. Ehsan Naini will present a paper co-authored with Jalil Nasseri of Summit Petroleum - A probabilistic multi-scenario seismic inversion scheme for field development and appraisal

Dynamic Reservoir Characterization and Modelling III (Joint EAGE/SPE)
Wednesday, Jun 5, 2019
8:30 AM - 12:10 PM
Room 14

4. Nam Pham of University Of Texas At Austin will present a paper co-authored with Ehsan Naeini - Missing well log prediction using deep recurrent neural networks

Deep Learning and Data Analytics – Methods and Applications I
Thursday, Jun 6, 2019
8:30 AM - 12:10 PM
Room 11

Ikon Session Chairs 

Alexander Edwards will chair Integrated Subsurface Studies - Geomechanics and GeoPressure Prediction. 

Tuesday, June 4. 1:30 PM - 5:10 PM. Room 14. 

Ehsan Naeini will co-chair High-Performance Computing A & Digitalization - Data and Information Management

Tuesday, June 4. 1:30 PM - 5:10 PM. e-posters 10. &

Poster: Signal Processing B. 

Thursday June 6. 10:30 AM - 12:10 PM. e-posters 2. 

Workshops 

Ikon Science and IBM have contributed Stabilized Super Resolution Deep Generative Networks for Seismic Data to the Machine Learning workshop. Rodrigo Ferreira, Ehsan Naeini & Emilio Vital