Dammam, Saudi Arabia

Amell Ali Al-Ghamdi

This inventor holds 3 USPTO granted patents. Top assignee: Saudi Arabian Oil Company. Active years: 2021-2026.

IDiyas Innovation Intelligence. (2026). Inventor Profile: Amell Ali Al-Ghamdi. Retrieved from https://idiyas.com/inventor/amell-ali-al-ghamdi

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

Calculating rank

% Patents Active = 100.0

Average Co-Inventor Count = 3.5

ph-index = 1

Forward Citations = 1(Granted Patents)


Company Filing History:


Years Active: 2021-2026

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3 patents (USPTO):Explore Patents

Title: Amell Ali Al-Ghamdi: Innovator in Reservoir Simulation and Well Performance Classification

Introduction

Amell Ali Al-Ghamdi is a prominent inventor based in Dammam, Saudi Arabia. He has made significant contributions to the field of reservoir simulation and well performance classification. With a total of 3 patents, Al-Ghamdi's work is recognized for its innovative approaches to enhancing oil extraction processes.

Latest Patents

Al-Ghamdi's latest patents include a "Reservoir simulation model history matching update using a one-step procedure." This invention presents a computer-based method for rapidly updating a history-matched reservoir simulation model selected from a plurality of models hosted on an information technology system. The software module is designed to perform updates by parametrically varying the time over the selected update period and the position for each selected well model file. It replaces outdated well model file data with well update file data at each respective time and position. Users can set the well model files to be updated and the time interval for the updates.

Another notable patent is "Well performance classification using artificial intelligence and pattern recognition." This invention involves a heterogeneous classifier based on actual reservoir and well data to qualitatively classify oil well producer performance. The classification informs decisions on whether to drill a new well into a producing reservoir or adjust fluid flows in existing wells. The classifier employs four different techniques for pattern recognition on reservoir simulation vector data, including supervised learning methods like Bayesian classification, dynamic time warping, and neural networks, as well as an unsupervised clustering method.

Career Highlights

Amell Ali Al-Ghamdi is currently employed at the Saudi Arabian Oil Company, where he applies his expertise in reservoir engineering and data analysis. His innovative contributions have significantly impacted the efficiency of oil extraction processes.

Collaborations

Al-Ghamdi has collaborated with notable colleagues, including Badr M Al-Harbi and Ali A Al-Turki, to further advance research and development in the field of petroleum engineering.

Conclusion

Amell Ali Al-Ghamdi's work exemplifies the intersection of technology and engineering in the oil industry. His patents reflect a commitment to improving reservoir management and well performance through innovative solutions.

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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