Integrated Modeling of Complex Gas-Condensate Networks Elliott Dudley (Senior Consultant MSi Kenny) Subsea UK 2013 Aberdeen, UK Experience that Delivers
Overview Agenda Integrated Modelling Methodology Scope of integrated modelling Benefits to design and operational guidelines Application of Software to Gas-Condensate Networks Restart Procedure Case Study Removal of Pigging Case Study
Integrated Modelling Links Systems Wells Pipelines Processing - Distribution Benefits of fully integrated modelling: Simulate the real impacts of each system on the connecting systems Develop Operating Guidelines Test Operational Strategies DRY TREES Artificial Lift Insulation/annulus SUBSEA TIEBACKS Multiphase engine MEG Tracking Composition Tracking Blend Management TOPSIDES Dynamic simulation Separation/Dehydration ONSHORE Slug catchers Compression/Pumping Heat Exchangers OIL / GAS EXPORT Pigging Multiphase mass Transfer WELL BORES IPR Casing and Insulation OPERATING PROCEDURES Start-up/shutdown Commissioning Operation Line Pack Testing Chemical requirements
Integrated Modelling Moves Boundaries Realistic Boundary Conditions Isolating pipeline modelling requires more assumptions about boundary conditions Combination of pipelines with the processing units creates more realistic behaviour VS. Simulates effect of downstream pipe and compressor/pump control philosophy
Software Solutions: Core Technology Thermo-Hydraulic Pipeline Integrated with Dynamic Topsides Processing Thermo-Hydraulic Pipeline Modelling All-in-one software used In-house software Dynamic Unit Operations and Processing Models Customized user friendly displays and controls specific to client
Case Study: Restart Philosophy Development Network Layout Dehydration and stabilization units Dynamic Compressors and Pumps Dry gas trunkline and liquids trunkline Multiple Wells per drill center Dynamic blending of compositions Primary separation Hydraulically connected gas pipeline network Liquid pipelines
Pressure (Bara) Pressure (Bara) Case Study: Restart Philosophy Development Separation conditions vary during restart, the phase compositions are dynamic 180 160 140 Phase Envelopes of Gas Compositions During a Restart P85_T50_Gas P115_T70_Gas P130_T85_Gas 120 Pressure and temperature float 100 80 180 160 140 120 Phase Envelopes of Liquid Compositions During a Restart P85_T50_Liquids P115_T70_Liquids P130_T85_Liquids 60 40 20 0-150 -100-50 0 50 100 150 Temperature ( C) 100 80 60 Integrated simulator couples wells with gas and liquid pipelines 40 20 0-200 -100 0 100 200 300 400 500 Temperature ( C) Used composition tracking to capture change in fluid properties
Case Study: Restart Philosophy Development Goals and Results from Study Optimize well ramp up rates Led to new well ramp up strategy and requirements, slug capacity Optimize depressurization rates Showed optimal valve layout and sizing Demonstrate ability to utilize depressurization to restart topsides processing Predicted timing and flowrates required to start up topsides processing Onshore downtime estimate
Case Study: Restart Philosophy Development More Results from Study More operational cases to test line pack, partial production trips, and turndown timing First start up and commissioning procedures Expanding network to include MEG distribution
Case Study: Pigging Frequency Goal: Decrease Pigging Frequency High liquid content was resulting in high pigging frequencies With an integrated model, the study was able to deliver an operational strategy that removed the need to pig entirely Varying well ramp up rates can remove liquid slugs safely without flooding the slug catcher Required including wells, platforms, trunkline, and slug catcher in one simulator
Summary Integrated Modelling Allows Realistic Operational Studies Can be used to design and develop strategies for: Partial or system wide restarts and shutdowns First start up and commissioning procedures and requirements Ramp up and turndown procedures Includes restrictions of entire network Increases understanding of network interaction Uniform software platform environment keeps the simulation stability Can pin-point operational bottle-necks early on in design phase