| Issue |
E3S Web Conf.
Volume 352, 2022
7th International Conference on Energy Science and Applied Technology (ESAT 2022)
|
|
|---|---|---|
| Article Number | 01086 | |
| Number of page(s) | 4 | |
| Section | Fossil Energy & Geological Engineering | |
| DOI | https://doi.org/10.1051/e3sconf/202235201086 | |
| Published online | 27 June 2022 | |
Deepwater Oil-Based Drilling Fluid Systembased on Grey Wolf Optimized BP neural network
1 Guangdong University of Petrochemical Technology, Maoming 525000, Guangdong, China
2 Daqing Oilfield Co., Ltd. No.5 oil mine of No.4 oil production plant, Daqing 163318, Heilongjiang, China
* Corresponding author: 395527225@139.com
In this paper, a BP neural network model with 5-9-6 structure is constructed according to various fault gases and different fault types ofWater-based drilling fluid and synthetic-based drilling fluid. While there are few studies relating to oil-based drilling fluid, which is attributed to the potential toxicity of conventional oil-based drilling fluid to the marine environment. However, oil-based drilling fluid is excellent in protecting the borehole stability. To this end, an environmentally friendly deepwater oil-based drilling fluid was developed based on the traditional oil-based drilling fluid. With the advantages such as good borehole stability and good wettability, this drilling fluid will not pollute the marine environment, is resistant to high temperature, and protects hydrocarbon reservoir, which is of great significance for rational exploration and development of deep-sea resources.
Key words: Grey Wolf Optimized / neural network / Deepwater / Oil-Based / Drilling Flui
© The Authors, published by EDP Sciences, 2022
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