The program for #DigEx 2019 is getting finalized and is promising 2 interesting days with talks about the digital subsurface. Join us and sign up here!
The first day starts off with “setting the stage”. Speakers from Dig Science, Arundo Analytics and Pandion Energy are challenged to separate the hype around digitalization and artificial intelligence from reality. We also question what the enablers are for a culture change in an organization.
In the” digital perspectives” session, we will hear from authorities and companies in the digital transformation phase on their experiences, learnings and the way forward towards their digital vision. The NPD, Konkraft, Accenture and Google Norway have agreed to share their experiences.
In “enabling data sharing and new digital workflows” we hope to learn about the opportunities and challenges that come with the digitalization of data. New workflows are enabled across the value chain as a result of digitilization and sharing data – across companies and country borders. More data leads to a deeper understanding and a better foundation for analytics and machine learning – providing us with richer insight and better decision support. There will be presentations from Equinor, Cognite, Digital Norway and Bluware. The first day will be concluded by a panel discussion.
On day 2, we look at the bigger picture where Microsoft will give us some “digital perspectives” on the world and society while Schlumberger is more focused on exploration and production. After this we zoom in on the workflows in the E&P business with a session on “Data management and visualization” with contributions from Geodata, Cegal and KADME. This is followed by case studies of “automated interpretation” by Geo Teric, Lundin and Kalkulo, Ikon Sciences, Earth Science Analytics and a demo by RagnaRock Geo.
More “subsurface” applications of machine learning and artificial intelligence are shown by Aker BP and Cegal, Schlumberger, Hoolock Consulting and the NPD. In the end also, “oil companies” get the chance to share their digital strategies with the audience and to show how far they have come with digitalization.
| #DigEx Program | DAY 1 |
|---|---|
| SETTING THE STAGE: EXPONENTIAL & DISRUPTIVE | |
| “Visions & Frustrations” | Kristin Dale & Per Avseth, Dig Science |
| Demystifying AI | Ellie Dobson, Arundo Analytics |
| Partnering with AI. The Augmented Geoscientist, Fiction or Future? | Kine Johanne Årdal, Pandion Energy |
| DIGITAL PERSPECTIVES | |
| Digitalization within the Oil and Gas “Eco System” – Overall ambitions, status and challenges | Walter Qvam, Konkraft |
| NCS 2016 | Alf Veland, NPD |
| Accenture Technology Vision | Jyoti Sharma, Accenture |
| Disrupt or be Disrupted | Jan Grønbech, Google Norge |
| ENABLING DATA SHARING & NEW DIGITAL WORKFLOWS | |
| Digital Subsurface: Disrupting the Workflows | Tina Todnem, Equinor ASA |
| The pie that gets bigger by sharing | Vidar Furuholt, Aker BP & Per Arild Andresen, Cognite |
| Helge Dag Jørgensen, Digital Norway | |
| Diederich Buch, Bluware | |
| A Use-case of a Cross-vendor Reservoir Model Enrichment Workflow made Simpler and More Reliable with Industry-developed Data Transfer Standards | David Wallis, Energistics Consortium |
| #DigEx Program | DAY 2 |
| DIGITAL PERSPECTIVES | |
| AI and the World – AI’s impact on business, leadership and society | Kimberly Lein-Mathisen, Microsoft Norway |
| A New Data Ecosystem that Empowers a Cognitive Environment for Exploration & Production | Guido van der Hoff, Schlumberger |
| DATA MANAGEMENT & VISUALIZATION | |
| Cegal | |
| Erlend Kvinnesland, Geodata | |
| Insight Engines & Machine Learning Pipelines | Jesse Lord, KADME |
| AUTOMATED INTERPRETATION | |
| The application of deep learning for more accurate fault delineation | James Lowell, GeoTeric |
| RacknaRock – Demo | Markus Halvorsen, RagnaRock Geo |
| A data-driven workflow for 3D automatic seismic interpretation | Aina Bugge, Kalkulo AS, Lundin Norway, UiO – dept. of geoscience |
| Incorporating Uncertainty in Automated Seismic Interpretation: Geobody Volumetrics | Steve Purves, Earth Science Analytics |
| Deep QI: A Machine Learning Approach to Quantitative Interpretation | Ehsan Naeini, Ikon Science |
| SUBSURFACE | |
| Using machine learning to predict pressure changes and thicknesses in a chalk reservoir | AkerBP & Cegal |
| AI Automation and cloud compute enabling faster turn-arounds in E&P life cycle | Steve Freeman, Schlumberger |
| Multiple seismic attributes and machine learning improve geological understanding | Tim Gibbons, Hoolock Consulting |
| 1700 exploration wells: Machine learning from a petabyte of organic content images to answer the key questions – Age? Environment? Oxic or anoxic? | Robert W. Williams, NPD |
| OIL COMPANY PRESENTATIONS | |
| Cuillin project | David Wade, Equinor |
| Repsol – exponential and disruptive… | Francisco Ortigosa, Director Geoscience Technology |
