Abstract
Slugging is an ongoing flow assurance risk in some of the ADNOC Onshore production systems, leading to difficulty in operations, inefficiencies, integrity and HSE concerns. For example stagnant water increases the risk of pipeline corrosion, especially with increased levels of H2S and CO2, potentially leading to leaks, pressure rating downgrading and reduction in the overall system capacity. With more reservoirs being under different schemes of secondary and tertiary recovery (WI, WAG, EOR – CO2, etc.), slugging in wells and transfer lines is expected to continue to be a challenge for the efficient and safe production operations across the entire ADNOC Onshore.
This paper summarizes an integrated approach to understand the underlying causes of slugging in an onshore production system, reviews the current slug mitigation philosophy and proposes a stepwise approach to improve performance of the system, leading to production acceleration, improved profitability, efficiency and HSE performance.
The system under investigation is experiencing slugging in the Transfer Line (TL) leading to liquid surges in the first stage separator (SEP) located at the Central Facilities. The slugging in the Transfer Line is attributable to a combination of wells and terrain induced slugging, and not so much to the hydrodynamic effects of the multiphase flow.
In the current slug management philosophy, the pressure (RP) recorded at the TL receiver location is used in an algebraic formula to calculate a level set-point (LSP) that, in relation to the actual oil level in the separator (SEP), is used to act on the Surge Control Valve (SCV) located at the separator inlet. When the LSP is below the actual oil level in the separator, the SCV is tripped to 30% opening. The RP signal acts as a tell-tale sign of the incoming slug.
In an initial phase, the system performance is evaluated using real time data available in the Control Room and offices. The initial data driven approach is complemented by complex dynamic multiphase modeling efforts. The models are used for further insights into the system behavior under different operational conditions, with a focus on identifying a more stable operating envelope, where the effects of slugging are mitigated while the production levels are maintained or increased. The focus on this paper is on the interface between the Transfer Line (TL) and inlet separator (SEP), including the Slug Control Valve (SCV).
Results indicate a more stable flow regime is achieved at higher fluid velocities in the TL, where the RM pressure is increased to 35 barg from the current 29 barg. (N.B. The 35 barg is the maximum TL operating pressure, as identified in a separate study, and limited by the current HIPPS setpoints. The corresponding increase in production capacity is up to 10,000 bopd, thus accelerating the cumulative oil by up to 3.5 MMBBl / year, and accelerating revenue by up to USD 180 MM / year). However, in the current control scheme, operation at 35 bar is limited by the SCV characteristic and control scheme.
To mitigate the problem, a staggered approach is proposed. A reduction in SCV tripping frequency is expected to be achieved in the short term, by modifying the algebraic equation that govern the SCV actions. A slight increase in the B factor by 2.5% is expected to reduce the SCV tripping frequency by up to 10%. Reduction in SCV tripping frequency will further reduce the mechanical stress on the valve and associated piping, thus reducing the risk of structural damage of the system. Also, it will allow for starting to increase the fluid velocities and move towards a more stable flow regime and reduced water holdup in the pipeline (reduced corrosion risk).
Additional increase in fluid velocities appears to be limited by the SCV characteristic. In the current control scheme the pressure drop across the valve becomes sizeable at higher flowrates, leading to frequent tripping. As a longer term measure, increasing the SCV capacity is expected to facilitate operation of the system at higher fluid velocities, thus reducing the slugging, mechanical stress and corrosion risk in the TL.
As slugging will continue to be a challenge to safe and efficient operations across ADNOC Onshore, it is important to develop in house the ability to understand the underlying causes for such flow instabilities, identify mitigation and optimization workflows. This paper demonstrates that a combination of data driven analytics and integrated physics based modeling, carried out in an integrated approach by a mixed team of subsurface and surface engineers, can help understanding the system behavior under slugging conditions and identify opportunities to improve production system efficiency and profitability, while operating within a safer envelope.