In this video, we take a look at a paper that presents a framework for using reinforcement learning for field development optimization that outperforms the conventional method by 88% based on attained NVP values. I go through a quick introduction to Reinforcement Learning, how Reinforcement Learning is applied for drilling optimization, and discuss advantages in terms of its generalization ability.
Resources:
Yusuf Nasir, Jincong He, Chaoshun Hu, Shusei Tanaka, Kainan Wang, XianHuan Wen, 2021, "Deep Reinforcement Learning for Constrained Field Development Optimization in Subsurface Two-phase Flow" [ Ссылка ]
TIMESTAMPS
00:00 Introduction to Reinforcement Learning
03:55 Reinforcement Learning for drilling optimization
04:57 Environment for optimization
07:00 Reinforcement learning agent
03:50 Results
09:50 Generalization
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WHO AM I:
I am Chief Technical Officer at a software company that develops AI/ML solutions for the Oil and Gas sector. I am passionate about AI and its application in Oil and Gas. For many years, I have been developing and launching solutions based on AI for various aspects of geoscience and petroleum engineering.
I make videos about Deep Learning and Machine Learning applications within Oil and Gas.
