Kuparuk Gas Lift Optimizer February 2006 Kenneth Lloyd Martin
• Kuparuk Production/ Gas Lift System • Development of Model • Operation • Results
Kuparuk Kuparuk
Kuparuk Gas System Gas System Kuparuk Central Production Facility Lift Gas to Wells Gas Lift Compressors Drill Site 1400 Manifold psi NGL’s MI to injection wells at 3900 psi Separation Gas Injection Compressors (MI)
CPF3 Production Lines CPF3 Production Lines
Drill Sites and Wells Drill Sites and Wells • 6 Drill Sites with automated gas lift chokes • 9 Drill Sites with manual gas lift chokes • About 160 gas lifted wells • 1 ESP • 4 Reverse-Flow Jet Pumps with water as power fluid • 2 Naturally Flowing
Existing Method for Gas Lift Existing Method for Gas Lift Optimization Optimization • Equal-Slope (IGOR) Method based on KWPS “Rate Tables” (performance curves) • Single target IGOR for all wells at each facility (or by DS if automated) • Board operator reviews “space”, changes target IGOR on DS’s • Trial and Error on rate using SCADA executed calculation See 2003 ASME GL Kuparuk Presentation (Martin, Nations)
Rate Table Curves (PC’ ’s) s) Rate Table Curves (PC
Equal- -Slope Gas Lift Optimization Slope Gas Lift Optimization Equal (and allocation) (and allocation)
Project Scope Project Scope • Build production gathering network model • Include common lines & history match ∆ P • Incorporate well performance curves from KWPS • Implement optimization to maximize oil rate • Integrate network models with SCADA (SetCim) for on-line use • Add temporary pressure instrumentation for tuning
Project Goal Project Goal • To develop a near-real time system which will increase Kuparuk production by modeling the surface hydraulics, which will in turn allow improved optimization of the current facilities. • Provide a planning tool for maintenance, debottlenecking, and expansion.
Project Plan Project Plan • Develop single Drill Site model as test of hydraulics and for vendor/company understanding of model • Develop single Facility (CPF3) model and test for results • Develop CPF1 and CPF2 models and planning tools
Project Execution Project Execution • RFP – APA Petroleum Consultants • Petroleum Experts Software – GAP for Optimizer – OpenServer for data transfer – In-house KWPS for performance curves – Glacier Services • In-house developments on SCADA
Operator Interface Operator Interface
Temperature Impacts Temperature Impacts 20F 20F 15 MMSCF 15 MMSCF
Optimization Run Optimization Run • Constraints – Water, Oil, Formation Gas, Total Gas – Individual well minimum/maximums • Objective – Maximum Oil Rate
KIOS.MS KIOS.MS / GAP / GAP CPF3 Model Server FTP Server FTP Server CPF3 Model Server KIOS. KIOS. Office Office Setcim KIOS. Setcim KIOS. UDP UDP /GAP /GAP PS PS Engineer’ Engineer ’s COE s COE Control Room Principal Server Control Room Principal Server Machine Machine
Comparison of Upstream Pressures Comparison of Upstream Pressures
Planning Interface Planning Interface
Model Maint Maint. / Engineering Interface . / Engineering Interface Model
Mapping Equipment Mapping Equipment
Well Data Well Data
Results Results • Expectations • Benefits • Challenges
Kuparuk INM Benefit Predictions Kuparuk INM Benefit Predictions • Vendor Predictions 8% to 15% • Gas lift production increases achieved in other automated fields using integrated models 1% to 3% • Potential GKA Target: • Internal predictions: 500-4000 BOPD increase (0.25%-2.0%) • CPF3 detailed project estimate 200 BOPD (0.4%)
Initial Install Benefit Initial Install Benefit 205 BOPD Predicted Benefit 205 BOPD Predicted Benefit
First Install First Install Oil Rate 50000 80 SD-TAPS Proration-WW 48000 70 46000 60 44000 50 42000 40000 40 38000 30 GASOPT 36000 KINM 20 34000 Temperature 24 per. Mov. Avg. (Temperature) 10 32000 Linear (KINM) Linear (GASOPT) 30000 0 20-May 3-Jun 17-Jun 1-Jul 15-Jul
Going “ “to model to model” ” after 10 days off after 10 days off Going 165 BOPD 165 BOPD
Compression Utilization Compression Utilization
Other Benefits Other Benefits • Identified well with high velocity through flowline, likely erosion concerns • Identified at least 10 wells and headers with inaccurate instrumentation • Provided estimates of impacts for new well drilling • Used with Prosper for downhole choke designs • Provided estimates of impacts of 3 rd party facility use • Developed better visualization tool for operators. • Identified loss in compressor rates due to forest fire smoke
Lessons Learned Lessons Learned • Difficult mix: troubleshooting vs. confidence • 90/10 rule is no joke – 6 months from approval for CPF3 to initial install – Still debugging 8 months later!
Project Difficulties Project Difficulties • Evaluating Rate Change – Change is smaller than hourly variation in field rate. – Step changes only work when going “to model” • Unable to keep model tuned with existing instrumentation – Drifts of up to 20 psi during periods of low gas rates – Requiring large investment in additional instrumentation • Rapid optimization software version changes – Significant time required to review version for “bugs” – Revisions are not all “backward-compatible”
Existing Challenges Existing Challenges • Computing time is issue during rapid temperature changes • Sensitive to small errors in PC’s • At low total gas rates, ignores minimum LG requirements • In new version, either minimum lift rate constraint or allow SI not both • Errors are difficult to trace because code is proprietary so don’t know what’s “under the hood”
Major Expenditures Major Expenditures • Optimization Developers • Automation Developers • Project Engineering • Software • Computers • Pressure Gauges
Annual O&M Costs Annual O&M Costs • Software Licenses • Automation Maintenance 1 month/yr • Optimizer Maintenance 1 month/yr • Engineering Model Tuning 1 day/mo/CPF • Engineering Well Models * 1 hr/day/CPF • Instrumentation 4 mh/tr/3yr * Existing Cost
Successful? Successful? • Met Benefit Estimate • I/O with SCADA working well • Better Operator Visualization – Operator focus on compressor rates, in addition to “gas handling available” • Long development-Ongoing troubleshooting • Operator acceptance
Acknowledgements Acknowledgements • CPF3 Production Staff • Network Model User’s Group • COP Knowledge Sharing Network Members • APA Petroleum Engineering, Calgary and Dallas • Glacier Services, Joe Griffo/Alex Charyna • Others at CPAI and BPXA
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