Decision support system for gas cooling temperature optimization

Introduction. One of the key issues at the front-end development phase for gas and condensate fields refers to selection of the most economically effective processing technology for natural and associated gas. Justification of the optimal solution is a complex technical and economic task that requires significant effort from a team of experts.
Aim. The purpose of this paper is to present a digital tool based on multi-agent technologies that form a flexible and adaptive system of many elements that interact with each other to achieve a common goal.
Materials and methods. Methods of system engineering, intelligent multi-agent technologies, surrogate modeling (AI-based proxy models) are used.
Results. This paper presents results of development of the digital tool that determines the optimal temperature for low-temperature condensation processes (LTC) providing the optimal output of commercial products, with consideration of necessary technologies and transport environment/capabilities.
Conclusion. The prototype of abovementioned digital tool is useable at the stages of conceptual design for solving problems related to selection of gas treatment technology.

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