Abstract
Debottlenecking of existing mature oil field can be one of the easiest ways to unlock production. An Integrated Asset Operating Model (IAOM) is the quickest way to perform this system optimization modeling (IAOM) in big field with large number of wells producing from different reservoirs and hydrocarbon properties. The model can carry out several production optimization scenarios. In addition, it provides an easier and quicker system analysis to help in identifying and reducing bottleneck, deliver production mandates and sustainability.
In a major field in ADNOC Onshore, a full-field IAOM model with over 500+ wells and flowlines was created for this purpose The model was used to identify a short-term optimization opportunity at Manifold #2 which resulted in a sustained gain of 8.0 MBOD. This model determine that extra production could be added from healthy, choked back wells if the system operating pressure was allowed to rise above the current 30 bar limit. These wells were identified based on IAOM network scenario runs which were used to demonstrate that the increased back pressure would not impact the weak wells connected to Manifold #2. With this solution in hand, the system pressure was increased from 30 bar to 35 bar from ∼12 wells that were choked open. This manifold was operating at this new condition for over 12 months at the time of this paper.
Another major issue encountered in the surface network of this field is slugging. Slugging can occur during significant reduction on choke sizes and continues increase in drawdown that will result in additional gas production. The additional gas will flow and further reduction on bottom hole pressure at the reservoir creating higher liquid hold up. At a certain stage, the gas will not be able to lift the liquid due to the backpressure created causing slugging flow on the system. Using IAOM, a solution was identified to reduce to find the well operating range that would not induce slugging yet say within the operating limits (integrity, reservoir guidelines, etc.) The modeling results indicates that slugging will improve at a higher flow rates based on the solution provided candidate wells have been identified on the same station.
Utilization of integrated system optimization modeling can help in understanding well-by-well behavior and properties of hydrocarbon fluids passing through the system and assist in identifying the slugging source and low station pressure. The effect of the pressure increase has been modeled for different production rate scenarios and to estimate the flow regime in the transfer line (i.e stratified, annular, slugging or bubble flow). Expected flow regime is combination of stratified and slugging. The results indicates that more severe slugging is occurring at lower flow rates. On the other hand, operating at higher rates and operating pressure can alleviate the slugging problems.
As a result, the system optimization modeling carried out on the station helped in identifying slugging issues and reduced bottleneck by improving the total production by more than 5%. This solution improved the asset sustainability and performance with minimal cost.
