How computer science and petroleum engineering background helps to succeed in doctoral research

Our next guest of the NU Step to the Ph.D. column is Furkhat Khamitov, a Ph.D graduate at the School of Engineering and Digital Sciences of Nazarbayev University

Furkhat Khamitov has a unique experience combining programming skills and engineering knowledge in the oil and gas industry. He graduated with two master's degrees: Al-Farabi Kazakh National University with a degree in Computer Science and the University of Lorraine in France with a degree in Petroleum engineering. At Nazarbayev University, Furkhat Khamitov conducts research on the sand removal process in oil and gas fields using machine-learning technologies.

Could?you please tell us a little about your education and professional experience?

By the beginning of my studies at Nazarbayev University, I already had five years of industrial and scientific experience in the oil and gas industry and two master's degrees in Computer Science (Al-Farabi Kazakh National University) and Petroleum engineering (University of Lorraine, France). In my work, I combined programming skills and knowledge in the oil and gas industry to create new hydrodynamic simulators and software for accounting for oil and gas raw materials.

What is your doctoral research?

In my dissertation, I modeled the removal of sand during the extraction of hydrocarbon raw materials in weakly cemented oil and gas reservoirs, using the example of the Ustyurt-Buzachi sedimentary basin. I used the CFD-DEM approach to model the flow of a multiphase liquid with rock particles on a micro-scale. The main idea was to study the global phenomenon of sand removal at the micro-level, thereby explaining the macroscopic phenomenon. The dissertation examines the impact of reservoir fluid properties on sand removal and the effect of the perforation process on the formation of a plasticity zone in a weakly cemented rock.

What is the applied meaning of your work?

The results of my research in the dissertation can help engineers identify the main factors affecting the removal of sand in the field. And the most important for them is to predict and control the process by changing the methods of pit operation and field development.

What could you tell us about the process of working on your dissertation?

The study of sand removal in the conditions of Kazakhstan deposits is a big task, which requires a preliminary examination of the geological and hydrodynamic properties of the rock, multiple laboratory studies, modeling on high—performance systems, etc. Over the past 7-to 8 years, my colleagues, Ph.D. candidates, and undergraduates have also engaged in this task. My part was to model processes based on their knowledge. Constant exchange of knowledge, new results, ideas, and their implementation in my numerical experiments are all how you can describe my work in a team.

Could you please tell us about your plans?

I continue my research on sand removal using machine learning technologies as a postdoctoral student at Nazarbayev University with an excellent team led by Professor Michael Yong Zhao and external supervisor Nguyen Hop Minh.

What would you wish for future doctoral students?

I would like to wish all current and incoming candidates to adhere to the idea that there are no hopeless situations in the study. The main criterion for success is constant personal work, active communication with managers, and interaction with the international community. New ideas always come unexpectedly.