ABSTRACT

The purpose of this study is to explore the intelligent oil well identification and model construction, so as to make the identification of oil well more intelligent. The convolutional neural network (CNN) algorithm in the deep learning algorithm is used to construct the recognition model of oil well function diagram, the collected original data are gradually converted into standardised binary images for input and CNN feature extraction. The CNN algorithm can be used to optimise the intelligent identification of oil wells, and the expected requirements can be met when the error of the intelligent identification of oil wells is small.

中文翻译：

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基于深度学习和神经网络的智能油井识别建模

摘要

本研究旨在探索智能油井识别与模型构建，使油井识别更加智能化。利用深度学习算法中的卷积神经网络（CNN）算法构建油井功能图识别模型，将采集到的原始数据逐步转化为标准化的二值图像进行输入和CNN特征提取。CNN算法可用于优化油井智能识别，在油井智能识别误差较小的情况下可以满足预期要求。