Web: http://arxiv.org/abs/2206.07680

June 16, 2022, 1:11 a.m. | Tailin Wu, Qinchen Wang, Yinan Zhang, Rex Ying, Kaidi Cao, Rok Sosič, Ridwan Jalali, Hassan Hamam, Marko Maucec, Jure Leskovec

cs.LG updates on arXiv.org arxiv.org

Subsurface simulations use computational models to predict the flow of fluids
(e.g., oil, water, gas) through porous media. These simulations are pivotal in
industrial applications such as petroleum production, where fast and accurate
models are needed for high-stake decision making, for example, for well
placement optimization and field development planning. Classical finite
difference numerical simulators require massive computational resources to
model large-scale real-world reservoirs. Alternatively, streamline simulators
and data-driven surrogate models are computationally more efficient by relying
on approximate physics …

arxiv graph hybrid learning lg network scale simulations

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