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Smart Oilfield| Corerain x Northwest Oilfield

Introduction

The Northwestern Oilfield in China is one of the largest oil producers in western China. Its crude oil production has been growing steadily for 25 consecutive years, with a cumulative oil output of more than 200 million tons.



Challenges
数据管理孤岛
Frequent Oil Safety Accidents
Owing to the flammable and explosive characteristics of the products, strengthenning production safety management is the focus of government departments, oilfield enterprises, and industry professionals currently.
Drawbacks of Traditional Methods
Drawbacks of Traditional Methods
Oil extraction, oil transmission and refining process have high risks, while traditional video analysis system lacks real-time warning.
Solutions

Adopting an integrated Acclerators-Algorithm-Platform oilfield system, the project is divided into two phases: six deep learning algorithms such as helmet detection, uniform detection, glove detection, phone call detection, crude oil leak detection and personnel intrusion detection, AI accelerators with high performance and high cost efficiency, and AI video analysis platform are provided by Corerain at Phase I; and customized algorithms for oilfield production based on the deep understanding of production scenarios is provided by Corerain at Phase II.

Results
AI intelligent video analysis system is constructed to reduce the risk of accidents caused by human factors.
Centralized visual safety supervision of key areas such as production sites, entrances and exits, crude oil storage areas are realized based on AI image recognition technology and 400 channels of videos accessing the field for an early warning on potential accidents in the first time;
变电站视频智能分析系统能够与地市主站系统、巡检系统实现信息交换。
Visualized AI center is established to view and analyze alarm results in real time, transforming from an after-checking mode under traditional methods to an intelligent management mode of pre-warning and improving the intelligence level of oilfields.
Relevant Cases

Accelerate AI Deployment with Next-Gen Computing Platform

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