Computer Modelling Group, a computer software technology company, develops and licenses reservoir simulation software in Canada. It offers CMOST AI, an intelligent optimization and analysis tool that offers solution for its reservoir by combining statistical analysis, machine learning, and non-biased data interpretation; IMEX, a black oil simulatorthat is used to model primary and secondary oil recovery processes in conventional and unconventional oil/gas reservoirs; GEM, an equation-of-state reservoir simulator for compositional, chemical, and unconventional reservoir modelling; STARS, a thermal and processes reservoir simulator for the modelling of steam, solvents, air, and chemical recovery processes; and CoFlow, a reservoir and production system modelling software that allows reservoir and production engineers to collaborate on the same asset. It also provides Builder, a pre-processor that simplifies the creation of simulation models by providing a framework for data integration and workflow management between various data sources; Results, a post-processor that helps in enhancing understanding and insight into recovery processes and reservoir performance; and WinProp, a fluid property characterization tool, as well as Autotune artificial intelligence solutions. Moreover, Computer Modelling Group provides professional services comprising support, consulting, training, and contract research services. It also sells its products and services in approximately 60 countries. Khalid Aziz founded Computer Modelling Group in 1978. It has its headquarters in Calgary in Canada.

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Computer Modelling Group Ltd.

Pramod Jain

Daniel Edelshaim

Kristina Mysev Msc Cipd

Rahul Jain

Sandra Balic

John Mortimer

The Reservoir Simulation Team at Computer Modelling Group Ltd. specializes in developing and enhancing advanced reservoir simulation software solutions. This team works on optimizing software like CMOST AI, IMEX, GEM, STARS, and CoFlow, ensuring they accurately model various oil and gas recovery processes. They focus on integrating statistical analysis, machine learning, and data interpretation to simulate and predict reservoir behavior, thereby assisting engineers and stakeholders in making informed decisions regarding reservoir management and production strategies.

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