Method for predicting ultra-short-term wind speed and direction at emergency well site

Abstract

Abstract In order to protect the safety of emergency rescue personnel and improve the speed of well control emergency rescue, it is necessary to know the ultra-short-term wind speed and direction time series of the well field in the next 15 minutes in advance. In this paper, the 0-1 test method is used to calculate the chaotic properties of the ultra-short-term wind speed and direction in the well field, and then the Hurst index is used to calculate the predictability of the ultra-short-term wind speed and direction in the well field. The Seagull Optimization Algorithm (SOA) is used to optimize the four hyper-parameters of the Echo State Network (ESN) and to train the network output weight matrix, so that the ultra-short-term wind speed and direction in the well field can be predicted from chaotic time series of the three kinds of terrain of the well field at different time scales. Among the three terrains, the MSE of the ultra-short-term wind speed in the well field valley and the ultra-short-term wind direction in the well field mountain are the smallest, which are 0.0215 and 1.787, respectively. The experimental results show that the SOA-ESN method has a good prediction effect on the chaotic time series of the ultra-short-term wind speed and direction, and can provide a new technical support for speeding up the well control emergency rescue.