Calgary, Canada

Juliana Y Leung


Average Co-Inventor Count = 4.0

ph-index = 1


Company Filing History:


Years Active: 2025

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1 patent (USPTO):Explore Patents

Title: Innovations by Juliana Y Leung in Oil Production Forecasting

Introduction

Juliana Y Leung is an accomplished inventor based in Calgary, Canada. She has made significant contributions to the field of oil production forecasting through her innovative methods and apparatus. Her work is particularly relevant in today's energy sector, where accurate predictions can lead to more efficient resource management.

Latest Patents

Juliana holds a patent for an "Apparatus and method for oil production forecasting." This invention involves a sophisticated method for forecasting oil production from an oil well in a geological formation. The process includes receiving multiple sets of predicted geological data, determining probabilities for each set, and utilizing Monte Carlo sampling to select the most relevant data. By clustering this data with historical records, the method generates predicted oil production rates over time using a machine learning-based oil model. Ultimately, this leads to a forecasted oil production rate that helps determine preferred operating parameters for the well.

Career Highlights

Juliana is currently employed at Cenovus Energy Inc., where she applies her expertise in oil production forecasting. Her innovative approach has positioned her as a valuable asset in the energy sector. With a focus on integrating advanced technologies into traditional oil production methods, she continues to push the boundaries of what is possible in her field.

Collaborations

Juliana has worked alongside notable colleagues such as Amos Ben-Zvi and Seyide Hunyinbo. Their collaborative efforts have contributed to the advancement of technologies in oil production forecasting.

Conclusion

Juliana Y Leung's contributions to oil production forecasting exemplify the impact of innovation in the energy sector. Her patented methods not only enhance the accuracy of predictions but also improve operational efficiency in oil production.

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