Search citation statements
Paper Sections
Citation Types
Year Published
Publication Types
Relationship
Authors
Journals
In old, mature fields with declining production and timeworn facility equipment, transient flow problems like slug and surge issues tend to appear during operations, especially during platform start up (PSU) processes where flowrates, pressures, and temperatures are constantly and significantly changing, which can lead to unstable production. Such situations may cause longer production stabilization time and potentially trip the entire facility if not managed properly. To mitigate this, a methodology for an integrated transient modelling advisor (ITMA) is introduced to assist engineers in determining a suitable well start up sequence at reduced risk. With ITMA, engineers can automate the determination of a well start-up sequence and simulate results of the proposed well start up sequence. This provides critical data for users to identify potential transient flow issues in advance prior to implementation. In addition, ITMA can give better clarity to operations on unseen risks that could lead to facility trips and eventually incur production loss. The ITMA we discuss here has three components integrated to work as a complete system. First, the data retrieval step is where the most recent historical well test data are retrieved from the database, and hierarchical analysis is performed to propose the most suitable well line up (WLU) sequence. The determination of WLU is produced based on pre-set well performance priority criteria and equipment capacity constraints and the proposed WLU is passed to the ITMA simulation engine. Second, the transient modelling engine simulates PSU scenarios based on proposed WLU. The baseline scenario can be modified to account for other factors, and multiple scenarios can be configured and tested. Some input data (such as choke opening and casing head pressure incremental versus time) can be modified before the run prior to simulation initiation. Third, at the end of the simulation, engineers are able to obtain and visualize critical output results such as platform production rates, separator liquid level, flowline slug/surge severity, and compressor/pump trip potential via trend plots. This result can be used to evaluate potential transient issues between scenarios and finalize the most suitable plan for use. ITMA assists engineers in planning and making proactive decisions for effectively managing PSU challenges and adding value in various areas – Operation Efficiency: Reduces risk of facility trips/shut-downs due to surge issues and slug issues during startup/ramp up stageProactiveness: Improves team ability to forecast and plan for potential problems during PSU situations and make decisions with increased operability assuranceProduction recovery: A system that assist operation to achieve normal production conditions from shutdown state in a stable and quick manner. The use of such an ITMA system in designing and proactively evaluating start up procedures can help reduce the unstable production period and minimize risk of flow assurance issues and facility trips that could lead to production loss.
In old, mature fields with declining production and timeworn facility equipment, transient flow problems like slug and surge issues tend to appear during operations, especially during platform start up (PSU) processes where flowrates, pressures, and temperatures are constantly and significantly changing, which can lead to unstable production. Such situations may cause longer production stabilization time and potentially trip the entire facility if not managed properly. To mitigate this, a methodology for an integrated transient modelling advisor (ITMA) is introduced to assist engineers in determining a suitable well start up sequence at reduced risk. With ITMA, engineers can automate the determination of a well start-up sequence and simulate results of the proposed well start up sequence. This provides critical data for users to identify potential transient flow issues in advance prior to implementation. In addition, ITMA can give better clarity to operations on unseen risks that could lead to facility trips and eventually incur production loss. The ITMA we discuss here has three components integrated to work as a complete system. First, the data retrieval step is where the most recent historical well test data are retrieved from the database, and hierarchical analysis is performed to propose the most suitable well line up (WLU) sequence. The determination of WLU is produced based on pre-set well performance priority criteria and equipment capacity constraints and the proposed WLU is passed to the ITMA simulation engine. Second, the transient modelling engine simulates PSU scenarios based on proposed WLU. The baseline scenario can be modified to account for other factors, and multiple scenarios can be configured and tested. Some input data (such as choke opening and casing head pressure incremental versus time) can be modified before the run prior to simulation initiation. Third, at the end of the simulation, engineers are able to obtain and visualize critical output results such as platform production rates, separator liquid level, flowline slug/surge severity, and compressor/pump trip potential via trend plots. This result can be used to evaluate potential transient issues between scenarios and finalize the most suitable plan for use. ITMA assists engineers in planning and making proactive decisions for effectively managing PSU challenges and adding value in various areas – Operation Efficiency: Reduces risk of facility trips/shut-downs due to surge issues and slug issues during startup/ramp up stageProactiveness: Improves team ability to forecast and plan for potential problems during PSU situations and make decisions with increased operability assuranceProduction recovery: A system that assist operation to achieve normal production conditions from shutdown state in a stable and quick manner. The use of such an ITMA system in designing and proactively evaluating start up procedures can help reduce the unstable production period and minimize risk of flow assurance issues and facility trips that could lead to production loss.
Liquid loading is experienced in high water-cut wells operating against high sealine pressure in an offshore mature field without artificial lift. This phenomenon is usually not captured by VLP/IPR representation built into reservoir simulation or steady-state well models, which results in overestimation of future oil production. Key value drivers for the project are developing an understanding of the liquid loading based on critical fluid velocity, well completion and reservoir characteristics and study its impact on simulation forecasts. Firstly, the liquid loading condition has been correlated to different well parameters such as productivity index, GOR and water-cut. The correlation is built from routinely acquired flow test data showing wells ceasing to flow due to unstable flow regimes and fluctuating sea line pressures. Additionally, extensive well modelling using Prosper software was carried out to assess the proper fluid correlation method. Secondly, that correlation was converted into a response surface model to make the link between the unstable flow regime conditions and the impacting parameters such as well PI, GOR, well geometry. Thirdly, the unstable flow correlation was implemented in the simulation model with a script of conditional events in order to flag wells with unstable flow and shut them if no activation condition is applied such as artificial lift or THP reduction. Currently, it is estimated that about 4 wells are becoming unable to flow every year due to the mentioned loading issues. These loaded wells require vessel/barge to carry out unloading which involves significant operating cost in an offshore environment. This complex behavior is normally overcome by dynamically coupling the subsurface models to the surface production system. However, in a giant field with hundreds of wells from multiple reservoirs this can be complex and resource demanding. Application of the correlation in the simulation resulted in about 80 wells with unstable flow conditions to be closed by year 2040, whereas they would have otherwise continued to flow if regular VLP curves were used. This method served to improve the model accuracy and to increase the assurance in forecasts predictability, with regards to water-cut evolution. This study was a key driver input for deciding on the acceleration of a major debottlenecking facility related to medium pressure system at surface. Sustainability of field plateau, improved wells availability, reduced in-active wells count and associated reactivation resources are tangible benefits of the mentioned study.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.