AI for Well Log Processing and Machine Predicted Lithology


1 h



SoftServe’s team of experts discuss how cloud technologies, Machine Learning (ML) and features engineering can automate well log data processing and lithology prediction, including the possible extension of well-to-well log correlation capabilities, all tied into one workflow.

In this virtual event you will learn how to address modern upstream business and technical challenges, as well as how to bridge the gap between exploration data, science, IT, business stakeholders, and end-users.


Our speakers:

Andrii Struk

Andrii Struk, SME, Energy, Oil and Gas, Softserve

Andriy Struk is Business Analyst and Subject Matter Expert for SoftServe’s Energy Vertical. Andriy is an experienced engineer and manager who took part in a variety of Oil and Gas projects around the world. He leads Oil and Gas industry expertise at SoftServe and provides clients with domain and technical expertise, to solve business challenges in: exploration, production, and manufacturing processes optimization, assets management and monitoring, performance optimization, and digital transformation.

Taras Hnot

Taras Hnot, Data Scientist, SoftServe

Taras is a data science expert with a strong experience in performing large-scale data mining, statistical modeling and patterns extraction. He has been involved into various projects in the manufacturing industry, 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 of both scientific and business conferences in ML and AI areas with topics like: "Knowledge Graph", "Anomaly Detection", "Personalization and Recommendation in Retail".

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