Background:

Specifying, designing and commissioning equipment that is suitable for both the initial, high productivity phase of production operations as well as for long term declining production pose significant challenges. Improved designs for equipment such as artificial lift pumps, compressors and separation equipment can help assure productivity, reduce cost and maintain uptime throughout the life of the well.

Most wells have been put onto SCADA systems and gather large amounts of data. New technologies in machine learning and predictive analytics can help utilize this data to provide better production forecasts and support more effective planning, as well as to help in real time optimization and failure prediction of major equipment.

While many core well operations have a high degree of instrumentation, much of the supporting facilities and equipment still require manual intervention. This manual intervention in addition to outsourcing to service companies can lead to poor visibility and elevated costs for many operations. Improved monitoring and data aggregation technologies can help bring visibility to these operations, reduce costs and improve regulatory and safety compliance.

Study Scope:

Production Technologies

• Artificial lift and flow management (Multiphase handling designs, improved control and operating window, lower energy use)
• Process automation/well surveillance (wireless well monitoring, data management)
• Workforce and equipment optimization (Machine learning, Stability optimization)
• Associated production process (Sand/ power/ compression)

Water Management Technologies

• Water recycling and treatment technologies (advanced filtration, oxidation, flocculation)
• Water transfer/ disposal

Production Chemicals

• Flow assurance (chemical or other methods to assure the ability of wells to flow)
• Chemical diagnostic and dosage control (IT solutions, advanced controllers)
• Well integrity and workovers