Milan, Italy

Ilaria De Santo

This inventor holds 1 USPTO granted patent. Top assignee: Schlumberger Technology Corporation. Active years: 2025.

IDiyas Innovation Intelligence. (2026). Inventor Profile: Ilaria De Santo. Retrieved from https://idiyas.com/inventor/ilaria-de-santo-e9rnoh7t

Data source: USPTO (United States Patent and Trademark Office) public patent records. Weekly synchronization. How IDiyas builds this profile


% Patents Active = 100.0

Average Co-Inventor Count = 5.0

ph-index = 1


Company Filing History:


Years Active: 2025

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1 patent (USPTO):Explore Patents

Title: Ilaria De Santo: Innovator in Fluid Prediction Technologies

Introduction

Ilaria De Santo is a prominent inventor based in Milan, Italy. She has made significant contributions to the field of fluid prediction technologies, particularly in the context of geosteering. Her innovative approach combines machine learning with practical applications in the oil and gas industry.

Latest Patents

Ilaria holds a patent for "Methods and systems for predicting fluid type while geosteering." This method involves measuring various fluid properties of a mud gas at the surface of a wellbore. It also includes predicting fluid properties using pre-trained machine-learning models, which are refined through comparisons with measured properties. This innovative approach enhances the accuracy of fluid property predictions, which is crucial for effective geosteering.

Career Highlights

Ilaria is currently employed at Schlumberger Technology Corporation, where she applies her expertise in fluid dynamics and machine learning. Her work has positioned her as a key player in advancing technologies that improve drilling efficiency and safety.

Collaborations

Ilaria collaborates with talented professionals in her field, including Shahnawaz Hossain Molla and Maneesh Pisharat. These collaborations foster innovation and drive the development of cutting-edge technologies in the industry.

Conclusion

Ilaria De Santo's contributions to fluid prediction technologies exemplify the impact of innovative thinking in the oil and gas sector. Her work not only enhances operational efficiency but also showcases the potential of machine learning in practical applications.

Profile summary based on public USPTO records.
Data Sources: USPTO Patent Grant XML, Patent Center, EPO & CIPO • Normalized by IDiyas Innovation Graph. Methodology & provenance architecturePlease report any incorrect information to [email protected]
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