Suha Kayum

Saudi Aramco


Suha Kayum is research and development engineer with experience in upstream solutions. Over a career spanning 10+ years, Suha has experience and know-how in developing Saudi Aramco’s in-house reservoir (GigaPOWERS), basin (TeraBasin), and seismic simulators (GeoDRIVE). Her work involved leveraging different disciplines, including simulation, high-performance computing, artificial intelligence, and predictive analytics.

At Saudi Aramco, Suha has championed several digital transformation projects in the Reservoir Simulation Division, led teams in digitalization of core analysis workflows, and employed machine learning and NLP to automate petroleum engineering-related document analysis. She has also worked closely with proponents to deliver both in-house and vendor solutions and has served as a key representative on latest advanced research for senior management, ministry officials, and CEOs of other companies.

Her most notable achievements include designing and receiving six granted patents for a novel algorithm that enables the world’s first one-billion cell basin simulation run. At the Center, Suha was the first female champion in advanced scientific computing, tasked with accelerating the evolution of software algorithms and technology to enhance the company’s reservoir simulator performance, robustness, and efficiency. Her ground-breaking work lead to reduced costs an increased recovery and several patents and publications

Suha served as SPE Saudi Arabia Section's Young Professionals Chairperson for the 2018-2019 term and the SPE Subcommittee Co-chair for the International Petroleum Technology Conference in Dhahran in 2020. She has participated in several panels and given a keynote speech. 

Suha has been awarded several awards such as the Emerging Leader Global Petroleum Show award in Calgary, the SPE Regional Young Member Outstanding service award, and the Young Outstanding Professional of the year EXPEC ARC award.  She holds an MSc and BSc with highest honors in Electrical and Computer Engineering from the Georgia Institute of Technology.

All sessions by Suha Kayum

Talk 1.1 - Advancing Reservoir Simulation with Machine Learning
02:30 PM

Traditionally, reservoir simulation has benefited from increased resolutions and incorporating more physics, hence the evolution from million cells-sized reservoir simulators, billion and now trillion cells. Instead of the traditional route this talk will discuss the future of reservoir simulation in the context of Machine Learning (ML). With examples of incorporating ML to flash calculations, ML-based well placement and intelligent adaptive mesh refinement, the talk will demonstrate where ML can have an impact on reservoir simulation while maintaining fidelity of results. The replacement of parts of the simulator, or the entire simulators, by surrogate, or proxy models that are learned from physics and run at a fraction of the computational cost could be in our near future.

Suha Kayum

Saudi Aramco