Abu Dhabi, United Arab Emirates

Alaa Maarouf

This inventor holds 1 USPTO granted patent. Top assignee: Schlumberger Technology Corporation. Active years: 2026.

IDiyas Innovation Intelligence. (2026). Inventor Profile: Alaa Maarouf. Retrieved from https://idiyas.com/inventor/alaa-maarouf

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

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Company Filing History:


Years Active: 2026

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1 patent (USPTO):Explore Patents

Title: Alaa Maarouf and Methane-Aware Field Development.

Introduction

Alaa Maarouf is an inventor based in Abu Dhabi, United Arab Emirates. His patent work addresses the use of machine learning to identify field sites that contribute disproportionately to methane emissions and to inform hydrocarbon field development planning.

Latest Patents

Maarouf is associated with 1 patent, titled “Field Emissions System.” The described method receives information about a field site within a larger field, where a minority of sites may account for most methane emissions. A trained machine-learning model assesses whether the site belongs to that high-emitting minority class. The assessment can then guide a field development plan intended to optimize hydrocarbon production and methane emissions.

Career Highlights

Maarouf is associated with Schlumberger Technology Corporation. His patent reflects an approach that combines field data, machine learning, and emissions considerations in planning hydrocarbon development.

Collaborations

The provided information names Hussein Mustapha and Samat Ramatullayev as Maarouf’s coworkers. Their specific roles in the patent or related work are not stated.

Conclusion

Alaa Maarouf’s patent work connects machine-learning analysis with methane-aware field planning, highlighting a technical approach to balancing hydrocarbon production and emissions.

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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