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
Edge intelligence-enabled data and physics-driven workflows to:
calculate real-time single and multiphase liquid flow rate
calculate oil production phases using measured water cut (ad hoc)
detect production loss early
Natural flow:
Liquid loading in wells decreases gas productivity
Requires manual intervention to shut in and unload wells
Foam-assisted lift:
Insufficient chemicals injected
Edge intelligence-enabled data and physics-driven workflows to:
automate control of surface choke for well shut-in for liquid unloading
optimize chemical injection (quantity of chemical and injection schedule)
Late detection of flow assurance issues results in suboptimal well treatment
Reactive treatments lead to unplanned interventions and production deferment
Increased OPEX
Edge intelligence-enabled data and physics-driven workflows to:
predict wellbore scaling and corrosion indexes
automate inhibitor (chemical) injection through process-controlled pumps
optimize chemical consumption and inventory
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
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
In cases where automated FCVs are not available, a complete closed loop system to be provided
Production impairment mitigation |
Lift solutions efficiency |
Flow assurance |
Sustainability |
|
Gas fields |
Auto choke
control Foam injection Plunger lift Virtual rate estimator Surface equipment PHM |
Foam
injection Plunger lift |
Sand influx
prediction Water influx predictor In-situ BSW measurement |
Power
optimization Emission monitoring Schedule optimization with AI |
Oil fields |
Water injector
control Water disposal control Water flood automation Virtual rate estimation Surface equipment PHM In-situ fluid quality assurance |
Annular
gas ESP and ICV optimization SRP ML remote opteration ESP optimization ESP PHM Continuous GLO |
Pump on
demand Sand influx prediction In-situ BSW measurement |
Power
optimization Emission monitoring Schedule optimization with AI |
Unconventional/tight |
ML for frac
placement Production forecasting Virtual rate estimation Surface equipment PHM |
Auto choke control |
Pump on
demand Sand influx prediction In-situ BSW measurement |
Power
optimization Emission monitoring Schedule optimization with AI |
Conventional |
Water injector
control Water disposal control Water flood automation Virtual rate estimation Surface equipment PHM In-situ fluid quality assurance |
Annular
gas ESP and ICV optimization SRP ML remote opteration ESP optimization ESP PHM Continuous GLO |
Pump on
demand Sand influx prediction In-situ BSW measurement |
Power
optimization Emission monitoring Schedule optimization with AI |
KEY
BSW: Basic sediment and water | ESP: Electric
submersible pump | GLO: Gas lift optimication | ICV: Inflow control value | ML:
Machine learning | PHM: Prognostic health management | SRP: Sucker rod
pump