客户成功与生产微解决方案

Back allocation efficiency and early loss detection >

成熟气田中的液体载荷>

Wellbore tubulars scaling and corrosion >

Gas lift control and optimization >

挑战

• Lack of continuous well production rate measurements leads to late detection of production deferment

• Automation of production workflows is not possible without real-time production rates

解决方案

Edge intelligence-enabled data and physics-driven workflows to:

• calculate real-time single and multiphase liquid flow rate

• 使用测量的水切割（ad hoc）计算油生产阶段

• 早期检测生产损失

挑战

Natural flow:

• Liquid loading in wells decreases gas productivity

• Requires manual intervention to shut in and unload wells

Foam-assisted lift:

• 注射了不足的化学物质

解决方案

Edge intelligence-enabled data and physics-driven workflows to:

• automate control of surface choke for well shut-in for liquid unloading

• 优化化学注射（化学和注射时间）

挑战

• Late detection of flow assurance issues results in suboptimal well treatment

• 反应治疗导致意外的干预和生产延迟

• 增加opex.

解决方案

Edge intelligence-enabled data and physics-driven workflows to:

• predict wellbore scaling and corrosion indexes

• automate inhibitor (chemical) injection through process-controlled pumps

• 优化化学消费和库存

挑战

• Transient conditions create issues in scaling-up of effective gas lift optimization solutions through simulation-based models

• Total cost of ownership for subscribing, maintaining, and calibrating physics-driven models is high

解决方案

• 100% data driven, based on measurements (gas lift injection parameters, well production flow rates of different phases) creating a model-free optimization set-up generation

• Edge enablement through Agora edge AI and IoT solutions for gas injection rate setpoint communication to the flow control valve (FCV) on the gas lift injection line per well

• Operational constraints are accounted for in the optimization scheme including available gas volume for injection, surface bottle necks for liquid handling, offtake economics, and water disposal costs

• 在不可用自动FCV的情况下，要提供完整的闭环系统