Machine learning control for automatic overflow detection and blowout prevention

Novel tools and techniques are provided for machine learning control of automatic overflow detection and blowout prevention. A system includes one or more blowout preventers (BOPs), one or more sensors, a neural network library including one or more neural networks, and a machine learning (ML) controller coupled to the one or more BOPs. The ML controller includes a processor and a non-transitory computer readable medium including instructions executable by the processor to obtain operational data associated with the local well, generate one or more feature vectors based on the operational data, and generate one or more corresponding overflow scores. In a fully automatic mode of operation, the ML controller may issue a location command based on the overflow score, and in a semi-automatic mode of operation, the ML controller determines a recommended issue location command. 提供了用于自动溢流检测和防喷的机器学习控制的新颖工具和技术。一种系统包括一个或更多个防喷器(BOP)、一个或更多个传感器、包括一个或更多个神经网络的神经网络库以及联接到所述一个或更多个BOP的机器学习(ML)控制器。ML控制器包括处理器和非暂时性计算机可读介质，该非暂时性计算机可