Research Projects

RGL’s commitment to optimize worldwide oil and gas operations includes ongoing research aimed at advancing the body of knowledge related to completion tools, sand, and flow control solutions. We have recently begun working on downhole instrumentation as an integrated part of completions.

Currently, RGL partners with five research groups based out of the University of Alberta Faculty of Engineering. We also expanded our R&D collaboration by working with Concordia University, University of Nazarbayev and West Virginia University. These groups are comprised of over 40 members led by 10 esteemed professors:

Dr. Li Cheng: Data analytics on the signals from downhole instrumentation (University of Alberta)
Dr. Carlos Lange: Numerical/CFD in fluid mechanics (University of Alberta)
Dr. Jingli Luo: Corrosion (University of Alberta)
Dr. Pedram Mousavi: Wireless downhole power and data transfer (University of Alberta)
Dr. Petr Musilek: Data analytics on the signals from downhole instrumentation (University of Alberta)
Dr. David S. Nobes: Flow measurement (University of Alberta)
Dr. Alireza Nouri: Sand control testing (University of Alberta)
Dr. Peyman Pourafshary: Sand control investigation (University of Nazarbayev)
Dr. Javad Sadri: Machine Learning and Data Analytics (Concordia University)
Dr. Mohtada Sadrzadeh: Filtration and scaling in sand control devices (University of Alberta)
Dr. Sean Sanders: Flow-loop well simulation (University of Alberta)
Dr. Ali Takbiri: 3D Image modeling of sand control devices (West Virginia University)
Dr. Hongbo Zeng: Scaling/fouling (Chemical Engineering Department)

RGL’s joint research team has published over 100 papers in prestigious peer-reviewed journals and conferences worldwide, with more to come. This allows RGL to provide exceptional value to our clients.
RGL’s academy joint research focuses on diverse areas that are of key importance to RGL. To access papers from these area of study, visit our Papers and Articles listing.

Sand Control Performance and Strategies

This research focuses on comprehensive laboratory investigation on sand control. Furthermore, this research also investigates the sand control management and strategies worldwide.
Sand production in thermal wells, which are typically horizontal, will result in sand accumulation in the liner, requiring the wellbore to be frequently shut-in for wellbore clean up. The production of fines will result in higher wellbore productivity since, if they are not produced, they will plug the sand and screen liner. Although liners are designed to prevent the reservoir sand from flowing into the wellbore, they do allow the production of very fine materials (i.e., fine silts and clay) into the reservoir. 

Intelligent design of liners allows the production of fines but keeps the sand in the reservoir. Previously developed liner design criteria have resulted in lower wellbore productivity. In this research, we propose the development of criteria for the design of three different types of liners and take a comprehensive approach to enhance the liner design for heavy-oil reservoirs using physical and mathematical modelling.

Sand control devices relies commonly on two types of the sand control; surface sand control and deep or three dimensional sand control. Sand control devices with 3D pore structure, such as mesh screens, need to be analyzed, designed, and investigated differently than sand control devices with surface filtering. Investigating the filtration in 3D structure of the filters/screens is essential for understanding the performance of such sand screens.

Flow Dynamics: Experimental Investigations and Numerical Modelling

This research focuses on the near-field fluid mechanics of steam-assisted gravity drainage (SAGD) [experimental, flow visualization, and computational fluid dynamics (CFD) simulations] for sand control equipment and flow control devices (FCDs). The aim of the project is to provide a detailed understanding of the near well fluid mechanics of both the injection and production wells. This information will be used to develop a stronger design procedure as well as mitigate failure mechanisms. Research takes to twofold approach: an experimental investigation using both model fluids/conditions and real field fluids/conditions will elucidate the flow phenomenon present and then provide data on the flow field on a number of different conditions. 

Numerical models using CFDs are developed using the validation data from the experiments to provide further insight into this flow field. These will then be used as part of an optimization process to provide explicit information on design directions for RGL sand control devices and flow control technology.


This research focuses on corrosion mechanisms and control of downhole equipment. Because extremely corrosive substances in the oil-recovery process create severe service conditions, damage significantly shortens the lifetime of equipment in SAGD systems. 

We aim to improve corrosion resistance of materials for slotted liners and other RGL products by investigating corrosion mechanisms and the effect of different slot cutting processes on corrosion and plugging behaviour. We can then develop a corrosion- and plugging-resistant coating that is technically simple to apply and that extends the service life of slotted liners. More specifically, new technical criteria for materials selection – a better slot manufacturing process and the development of an effective coating – will provide RGL with a set of practical design criteria for optimizing operational performance of a SAGD system and extend equipment service life.

Scaling and Fouling

This research focuses on finding the efficiency of bitumen extraction in SAGD operations and improving sand control performance in sand and flow control devices. The potential fouling and scale formation on surfaces and plugging of screens are determined by the intermolecular and surface interactions of solid sands, clays, bitumen, water, minerals, and liner surfaces, as well as the local hydrodynamic flow conditions. 

The goal is to characterize the physicochemical surface properties of the equipment and elucidate associated interfacial interaction mechanisms in the oil-sands extraction processes that lead to fouling and device failure, while also providing comprehensive solutions for a better material and coating selection with improved performances in the in-situ extraction process of bitumen for the oil-sands industry.

Furthermore, proper material selection procedure based on the scaling properties is also investigated. Existing methods for unplugging the screens is another part of this study.

Downhole Instrumentation

We believe that completion tools, sand control devices, flow control devices, and instrumentation are integrated parts of the well services. Therefore, we need to cover all these devices and services in our academy joint studies.

We are currently working on three distinct projects regarding the downhole instrumentation:

  • Flow-loop experimental testing of the downhole sensors,
  • Data analytics application on signals from downhole sensors,
  • Wireless data and power communication with downhole sensors.

Machine Learning and Data Analytics

The application of the Machine Learning (ML), Big Data, and Data Analytics in oil and gas industry is a trending subject. We are currently investigating the possible application of these new technologies in developing sand control devices, flow control devices, downhole completion, downhole instrumentation, and manufacturing process. Furthermore, ML is being used in improving our everyday activities in RGL’s proLAB, including test design, particle size and shape clustering/analysis, test analysis and quality control.

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