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Subsurface analytics: Contribution of artificial intelligence and machine learning to reservoir engineering, reservoir modeling, and reservoir management

机译:地下分析:人工智能和机器学习对油藏工程,油藏建模和油藏管理的贡献

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摘要

Traditional Numerical Reservoir Simulation has been contributing to the oil and gas industry for decades.The current state of this technology is the result of decades of research and development by a large number of engineers and scientists.Starting in the late 1960s and early 1970s,advances in computer hardware along with development and adaptation of clever algorithms resulted in a paradigm shift in reservoir studies moving them from simplified analogs and analytical solution methods to more mathematically robust computational and numerical solution models.
机译:传统的数值水库模拟几十年来对石油和天然气行业有贡献。该技术的当前状态是大量工程师和科学家的研究与开发的结果。在20世纪60年代后期和20世纪70年代初期,进展在计算机硬件以及开发和适应智能算法中导致储层中的范式转换,将它们从简化的类似物和分析解决方法移动到更加数学鲁棒的计算和数字解决方案模型。

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