| Issue |
E3S Web Conf.
Volume 267, 2021
7th International Conference on Energy Science and Chemical Engineering (ICESCE 2021)
|
|
|---|---|---|
| Article Number | 01038 | |
| Number of page(s) | 4 | |
| Section | Energy Development and Utilization and Energy-Saving Technology Application | |
| DOI | https://doi.org/10.1051/e3sconf/202126701038 | |
| Published online | 04 June 2021 | |
Recognition of Oil and Gas Reservoir Space Based on Deep Learning
1 Shaanxi Key Laboratory of Safety and Durability of Concrete Structures, XiJing University, Xi’an, Shaanxi, 710123, China
2 Longdong Natural Gas Project Department, Petro China Changqing Oilfield, Qingyang, Gansu, 745100, China
a Corresponding author: 20190100@xijing.edu.cn
The identification of oil and gas reservoir space is of great significance to oil and gas exploration. Deep learning technology represented by convolutional neural network is currently the most widely used artificial intelligence method in the field of image recognition. Using convolutional neural networks to identify the type and content of the reservoir space can not only ensure the objectivity and accuracy of the results, but also reduce labor costs and improve work efficiency. It has achieved good results in the identification of the reservoir space of the Chang 6 oil-bearing group in the Ordos Basin, which has a certain promotion significance.
© The Authors, published by EDP Sciences, 2021
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