Part 2 of 3 webinars on the theme of trusted data
Continuing from the previous webinar on the importance of trust in knowledge work, the categories of trustworthiness, and how apparent data quality impacts perceptions of trustworthiness, this webinar carries the trust concepts through into analytics and data management.
We begin by identifying facets of trustworthiness which are mathematically related to data uncertainty and introduce paths to quantification of those values. These are things like obtaining the catalog drift values to use on uncalibrated sensors or finding r-squared in the original papers defining common computations using empirical correlations (like Archie’s Law for water saturation).
We then discuss how to conveniently represent trustworthiness as metadata and carry that information along as data makes its way through the seismic to simulation (or exploration to abandonment or whatever a company uses) workflow.
We end with a discussion of the data management aspects of trustworthiness. Does trustworthiness become stale over time as data ages? How would we persist trustworthiness scores in a database? Do we need to persist them or are they derivable into the future?
It takes place June 27, 2019 at 9:00 AM Central Time, and the projected duration is one hour including time for Q&A.
To register for the webinar, please click on this link
Part one of this series is posted on our website’s Library under the Webinars and Video tab.
If you cannot follow this live session we will be posting a recorded session a few days after the webinar takes place. You will find in the LIBRARY section of our website under the tab “WEBINARS and VIDEO”.
Meet the speaker
Jay Hollingsworth is Chief Technology Officer for Energistics®. In this role, he is responsible for the technical adequacy of the standards stewarded by the organization, including WITSML™, PRODML™, and RESQML™ among others.
Jay has a BS plus post-graduate studies in Chemical Engineering at Tulane University in New Orleans. In addition, he attended graduate school in Computer Science at University of Texas in Dallas. As his career
advanced as an Environmental and Process Engineer, he focused on technical computing – first as a consultant and then for 20 years at Mobil Oil. At Mobil he was responsible for the data model of their FINDER global master data store and the suite of engineering applications in global use. After leaving ExxonMobil, he spent time in Landmark’s data modeling group before settling at Schlumberger. He spent 10 years at Schlumberger where he was responsible for the data modeling group and was the Portfolio manager for the Seabed database technology. After Schlumberger, he was an Industry Principal at Oracle®, focusing on oil & gas solutions.Jay is active in numerous industry organizations, including APSG, ISO, SPE and SEG. He was a Technical Editor of the SPE Microcomputer Journal and is currently on the Board of the SPE Digital Energy Technical Section. He was a long-time member of the Board of Directors of PPDM™ and served as past president of APSG.