Optimizing Artificial Lift Systems With ML

DURATION:

28 min

FORMAT:

Energy, Oil & Gas,Presentation

Watch SoftServe's AI Energy & Manufacturing Consultancy Lead, Taras Hnot, and Vital Energy's Director of Data and Innovation, David Benham, present Optimizing Artificial Lift Systems With AI and ML at the Machine Learning in Oil & Gas Conference.

Our speakers:

Taras Hnot, AI Energy & Manufacturing Consultancy Lead

Taras is a data science expert with strong experience in performing large-scale data mining and analytical projects. The key areas of expertise include building a document understanding platform for oil & gas companies and developing a Knowledge Graph from completely unstructured content. Taras has been involved in various projects in the manufacturing and energy industries, including developing predictive maintenance solution for a cryo-pump manufacturer, building an autonomous control system for one of the largest oil & gas companies, applying unsupervised anomaly detection algorithms to build a solution for a company with thousands of devices and billions of time-series data points. Taras is an active speaker at both scientific and business conferences in ML and AI areas with topics like: "Knowledge Graph", "Unsupervised Anomaly Detection", "AI for Well-Logs Processing".

David Benham, Director of Data and Innovation & Principal Data Scientist

David's expertise lies in unlocking the power of data to accelerate digital transformation of Vital Energy. Prior to joining Vital Energy, David spent an additional nine years in the energy sector and another three years in the manufacturing sector. His focus has primarily been initiatives that solved various business challenges in the well planning, performance, and production domains.