| dc.description.abstract | This thesis serves as a comprehensive study incorporating smart pigging technology and software modeling applications for flow assurance purposes, with a special emphasis on subsea pipelines.
In the modeling chapters, OLGA and PVTSim software packages were used to build a model of a hypothetical subsea pipeline, which is based on the example of the Kirinskoye gas condensate field.
The constructed dynamic model addresses several crucial aspects of pipeline flow assurance, namely:
1) Hydrate formation zones within a pipeline: their location diagnostics and mitigation via continuous inhibitor injection;
2) Estimation of the required slugcatcher unit’s capacity for liquid collection and water disposal.
As a result of the simulations and their analysis, the following goals were achieved:
1) The hydrate formation zone within the pipeline is located and the optimal solution to mitigate the issue is proposed and justified based on the multiple hydrate formation simulations’ results. The environmental effect of the solution for the hydrate problem mitigation is also taken into account, and the minimization of its ecological imprint is justified.
2) Liquid surge volumes for the cases of stabilized operational conditions and pig run are modeled in relation to the two project-proposed flow values within the pipeline: 2,64·106 m3/day and 3,5·106 m3/day, respectively. All of the cases modeled are proven to lie within the slugcatcher’s liquid receiving capacity. The optimal value of flow for the system is proposed and justified.
3) Pig run velocities for both flow value cases considered are calculated.
It is concluded that in both pig runs an intelligent pig of any physical measurement principle considered in the thesis can be implemented without a reduction in the quality of measurements. | |
