Minimize, Maximize or Target Production
Production optimization is essentially “production control” where you minimize, maximize or target production of oil, gas and perhaps water. For example, you can easily maximize or target the production of oil and/or gas while minimizing water, or run oil production and gas-oil ratio (GOR) to setpoints to maintain reservoir energy. There are a myriad of alternative production objectives. Since each well, platform and field are quite different, a flexible means of controlling production is provided.
iGLO: Intelligent Gas Lift Optimization
Shell Malaysia in conjunction with Petronas gave this capability the name “iGLO” for Intelligent Gas Lift Optimization when they applied it to the South Furious and Saint Joseph fields off the north shore of Kota Kinabalu, Sabah, Malaysia. In this project we modeled oil, gas and water production for each well on multiple platforms and put those models on-line in real time as virtual meters. This gave them insights about where oil, gas and water were coming from in real-time. The asset manager immediately discovered “Lost Oil”… Previous to this, test rates did not sum to production rates, a notable amount of oil had “gone missing”. But now, with visibility of production in real-time, the asset manager could see how, and where, co-mingled streams’ interactions decreased overall production compared to test. The asset manager literally jumped up and down, clapping her hands, as a mystery had just been solved.
In Brief
- More than merely maximizing oil production, but a setpoint on production.
- Target or minimize other calculated results such as GOR or water.
- Optimize individual wells or simultaneously the entire platform
- 5%-20% production gains over hand optimizing due to being real-time
- Ultimate recovery may be enhanced.
- Field proven by major oil and gas companies.
Products Used
- Intellect Server
- Intellect Expert
- Intellect Designer
- iImprove
- LiveOptimizer
Once virtual meter models were implemented, 3 forms of real-time optimization were performed:
Model-based Predictive Control
Top quality virtual meter models are loaded into a model-predictive optimizer that seeks well control setpoints for production assist and chokes to maximize, minimize and target multiple production objectives. This fast responding “prescriptive analytics” solution immediately drives the platform to peak production.
Platform Level Hill-Climbing Performance Optimization
Requiring no models, this technology gently manipulates multiple well control setpoints within constraints, waits, measures performance, and then adjusts again, seeking to maximize, minimize and target multiple production objectives. This autonomous auto-tuning optimizer gently increases production over time and adapts to changing well, platform and reservoir conditions automatically.
Platform Level Combinatorial Performance Optimization
Also requiring no models, this technology more strongly manipulates multiple well control setpoints within constraints, waits, measures performance, and then steps the process setpoints again, seeking to maximize, minimize and target multiple production objectives. This autonomous optimizer essentially does a multi-rate platform wide test to learn where peak production is. The resulting data is excellent for creating model based predictive controllers mentioned above.
Because the platforms were optimized as a total system, not a combination of individual wells, iGLO accommodates for well interactions, both on the surface and downhole, taking the platform as a whole to peak performance.
Results
Through the use of *real-time* optimization, oil production increased by 5% on one platform and increased about 20% on the second field we applied it to, compared to off-line hand optimization. One well increased production by 500% because it was a small, overlooked producer which we woke up and got producing.
Shell reservoir engineers estimated that ultimate recovery would be increased by 2% due to better “pull” on the reservoir, improving drainage. A small increase in ultimate recovery can lead to a substantial amount of money in the long term. Also, by producing more and faster, the time the platform would need to be operated would shorten, reducing “HSE” risk (Health, Safety and Environment) and total operating expense. An added benefit was more consistent production, useful for on-shore downstream operations of oil and gas processing.y
Interesting Finding
In conducting this project we learned that there is no “lift curve” for lift gas injection vs. production. Instead the “lift curve” is actually a multi-dimensional “lift surface” that is continually changing shape as process conditions change. If you are using a solution that assumes a 2 dimensional “lift curve” then you are not getting the benefit of using a multi-dimensional solution operating in real-time.
It should be noted that any benefits mentioned here are AFTER the asset team hand-optimized the field using a tool such as WinGlue and are gains by using proper multi-dimensional technologies operating on-line optimizing in real-time using current live operating conditions.
Benefits Enumerated
Benefits achieved include:
- 5% – 20% higher production while maintaining reservoir energy
- Optimization of all wells, including small producers
- Potential reduced water cut / production
- Improved ultimate recovery on some reservoirs
- Provides a production setpoint. Enter what production you want, let the system achieve it
- More consistent production for downstream operations
- Shorter operation time to capture a reservoir, providing reduced operating cost and HSE exposure
- Ability to see oil, gas and water production by well in real-time
- Real-time production allocations
- Sensor validation and integrity
- Arrested or delayed production declines as assets age
- Enhanced asset and process understanding through advanced analytics and visualization