Participación virtual online por ZOOM a cargo de la SPEI
Lunes 28 de marzo a las 13:00 Arg (GMT-3)
DL Jessica Iriarte
Biography:
Jessica Iriarte is a Sr. Manager of Data Science at Vroom, an e-commerce company that enables consumers to buy, sell, and finance cars online. Before Vroom, Jessica launched and grew the data science team at Well Data Labs, serving as a subject matter expert to bridge the technical gap between engineers and data scientists. She led the development of robust models for time-series sensor data, work that resulted in several patent-pending technologies. }
She holds BS and MS degrees in Petroleum Engineering and has +10 years of experience in data science, research, and completions. Jessica served as the SPE Denver Chairperson, received the 2018 Denver Business Journal Top Women in Energy Award, and the 2020 SPE Young Member Outstanding Service Award.
Abstract:
Data science uses algorithms and statistics to generate knowledge and insights from data. While Oil and Gas has, at times, been at the forefront of large-scale data analysis, it has struggled with implementing data science more broadly. Some of the challenges our industry faces include poor quality and siloed data, archaic data management processes, and the lack of collaboration between data scientists and subject matter experts (engineers/geoscientists).
The applications for machine learning and data science are boundless but knowing where to start can be daunting. How do you design, prototype, and deploy models to critical endusers? Using a lean start-up approach taken from real-world experiences, this talk provides a starting point to help organizations successfully plan, implement, and launch a data science program. Data science applications to hydraulic fracturing data will be used to showcase these effective workflows and best practices. The workflows shown in this presentation can be applied to other time-series or depth datasets that exist in the industry (drilling, logging, production data, etc.). Participants will walk away with an understanding of best practices around data science and learn how to leverage efforts to gain valuable insights from time-series data.
Auspician
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