Huawei Cloud Energy China Translated from Chinese

CNOOC

IT Operations Automation · Real-time Analytics · Risk Management

CNOOC needed to connect previously separate offshore-oilfield systems, standardize development, and add intelligent monitoring and safety capabilities to core production and supply-chain workflows.

8 core technologies
R&D work hours reduced by 30%
debugging and deployment time reduced from 1 week to 1 day
more than 1.3 million lines of code

Reported impact

Business outcome

The smart-oilfield platform improved production efficiency, standardized development, and embedded more than one hundred digital algorithm models into operational workflows, including AI safety monitoring.

  • Productivity Improvement
  • Risk Reduction

Solution

CNOOC used Huawei Cloud Stack as the base of its smart offshore oilfield program, starting with the Qinhuangdao 32-6 pilot. The first layer is a central control system that connects previously separate production and IT systems so oilfield resources and operations can be monitored on a unified cloud platform. On top of that base, CNOOC built a smart oilfield management system for production monitoring and planning, then added second-phase applications for procurement execution, warehouse logistics, cross-task reminders, regional hazard notifications, real-time worksite monitoring, and AI-based unsafe-behavior recognition. Huawei CodeArts and CNOOC's internal toolchain standardize development across large engineering teams while digital algorithm models are deployed into business systems. Data from field operations flows into the unified platform, is analyzed by management and algorithm services, and is pushed back into operational decisions for safer, more coordinated production.

Data flow

Production and operational data from offshore systems is routed into the central control system and cloud platform, where management services and digital algorithm models analyze work status, hazards, logistics, and operational events. The outputs are returned to production planning, real-time monitoring, and safety workflows.

Solution architecture

5 components · 3 layers
  1. Compute
    • Huawei Cloud Stack Provides the cloud foundation that connects oilfield systems and supports smart-oilfield workloads.
    • digital algorithm models Run intelligent monitoring, planning, and safety logic inside oilfield business systems.
  2. Serving
    • smart oilfield management system Monitors and plans production work on top of the centralized platform.
  3. Orchestration
    • central control system Unifies different systems and makes IT resources visible and manageable for oilfield operations.
    • CodeArts Standardizes development workflows and supports faster delivery of smart-oilfield applications.

Architecture clues

  • AI unsafe-behavior recognition is part of the phase-two monitoring stack.
  • Development was supported by a dedicated software toolchain research project.
  • The platform includes a central control system plus smart-oilfield management and second-phase business applications.
  • The smart-oilfield program started with the Qinhuangdao 32-6 field pilot.

Evidence from the source

"After the smart-oilfield system went live on the cloud platform, production efficiency increased by 30%. (original: 通过中央控制系统上的智能油田管理系统,能够及时合理地监测、规划油田地生产作业。在云平台上,智能油田建设上线试运行之后,生产效率提高了30%。)"
"Based on Huawei Cloud Stack, CNOOC built a central control system to connect different systems and make IT resources visible and intelligent. (original: 基于华为云Stack能力,中国海油自主打造中央控制系统,通过统一的平台将不同系统连接起来,实现IT资源的可视化与智能化、支撑海上油田的数字化建设;)"
"CNOOC and Huawei Cloud Stack pushed digital technology deep into exploration and development to build an intelligent oilfield with unmanned worksites, visualized reservoir studies, coordinated operations, and scientific decision-making. (original: 中国海油携手华为云Stack积极推进数字技术与勘探开发核心业务深度融合,推动生产方式转变和管理流程优化,打造作业现场无人化、油藏研究可视化、生产运营协同化、战略决策科学化等为特征的智能化油气田建设。)"
"CodeArts helped more than 500 developers produce more than 1.3 million lines of code, launch 100+ digital algorithm models and 8 core technologies, cut R&D work by 30%, and reduce deployment time from 1 week to 1 day. (original: 帮助中国海油500多开发人员编写了130多万行代码,上线了100+个数字算法模型和8大核心技术,研发工时节省了30%,智能油田管理系统的调试和部署时间从1周缩短为1天。)"
"Phase-two smart-oilfield applications include procurement, warehouse logistics, real-time work monitoring, and AI-based unsafe-behavior recognition. (original: 当前已经开发了智能采办(比如采购执行、仓储物流管理)、智能油田二期(比如交叉工作提醒、区域隐患告知、实时作业监控、AI违章行为识别)、应用开发云平台等主要业务系统。)"
Transparency Evidence & methodology 100/100 reference value · 81% confidence · 1 source

Review how this reference was scored and trace each normalized claim back to its documented source.

01

Scoring methodology

How scores are calculated

Customer Reference Value measures usefulness as a customer reference. Evidence Confidence measures the quality and traceability of available evidence, not independent verification.

Customer reference value100/100
  • Problem clarity20/20
    Measures whether the customer's operational problem is specific enough to compare.
  • Implementation depth25/25
    Rewards named components, data flow, integrations, and architecture detail.
  • Outcome specificity20/20
    Measures whether the reported benefit is concrete rather than a generic claim.
  • Quantified impact25/25
    3 metrics describe measurable impact.
  • Deployment scale10/10
    Rewards evidence of a live or scaled deployment and meaningful integration scope.
Evidence confidence81%
  • Source authority20/25
    The main evidence is an official vendor-published customer story.
  • Claim traceability21/25
    10 of 12 key fields link to a named source.
  • Direct evidence20/20
    5 direct source quotes retained.
  • Date provenance0/10
    The publication date has no documented provenance.
  • Source transparency10/10
    1 source reference document publisher, URL, authority, retrieval, and supported fields.
  • Implementation specificity10/10
    Rewards source-backed components, data flow, quantified impact, and a specific outcome.
02

Traceability

Sources & provenance

Field coverage shows which facts each source supports. Dates are shown only when documented by the source.

  1. Huawei Cloud

    中海油携手华为云Stack探索海上智能油田之路-华为云

    First-party
    https://www.huaweicloud.com/cases/cnooc.html
    Source type
    Vendor-published customer story
    Supports
    • Customer
    • Business problem
    • Solution
    • Products
    • Solution components
    • Data flow
    • Integrations
    • technical area
    • use case category
    • Business outcome
    • outcome category
    • Metrics
    • Architecture
    • evidence quotes
Not separately sourced Industry, Region, Company size. Treat these normalized attributes as lower-confidence until a dedicated source is added.