production optimization – a gas lift odyssey
TRANSCRIPT
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SPE Distinguished Lecturer Program
Primary funding is provided by
The SPE Foundation through member donations
and a contribution from Offshore Europe
The Society is grateful to those companies that allow their
professionals to serve as lecturers
Additional support provided by AIME
Society of Petroleum Engineers
Distinguished Lecturer Programwww.spe.org/dl
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Production Optimisation:
A Gas Lift Odyssey
Dr. Rick LemanczykSenergy
Society of Petroleum Engineers
Distinguished Lecturer Programwww.spe.org/dl
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Objectives
• Examine various levels of gas lift “optimisation”
in current practice.
• Review recent advances in gas lift technology.
• Identify key challenges for future gas lift
operations.
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Gas Lift Perspective
Gas Lift as % of Artificial Lift Production
source: www.alrdc.com
BP 46% 2002
ExxonMobil 53% 2004
Petrobras 89% Campos Basin
Shell 64% 2001
Qatar Petroleum 35% 2008; of total oil
PCSB Malaysia 40% 2002; of total oil
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Stages of Gas Lift Optimisation
Design &
Implementation
Single Well Diagnostics
& Remediation
Full Field
Optimisation - RTO
tools
equipment
models
measurement
surveillance
data
management/
algorithms
problems & evolving solutions exist at each level
1
2
3
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The Prize
• Design & Implementation– More production can be safely gas lifted
– Avoidance of costly workovers/re-entries
• Single Well Remediation– 0-25% on flowing wells
– Revival of shut-in wells
• Full Field Optimisation– 2-5% oil increase of field wide production
– Up to 40% improvement in gas injection efficiency
– Sustained production increases with Real Time Optimisation (RTO)
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Stage 1: Evolving Challenges in Gas Lift
Design & Implementation
• Gas Lift Rate Control
• Deep Water Completions
• Well Integrity
• Gas Lift Valve Reliability
Source Weatherford
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Venturi Orifice Valve
TUBING PRESSURE (psi)
SUB-CRITICAL
FLOW
PCASING
PTUBING = 90% of PCASING
PTUBING = 55% of PCASING
CRITICAL FLOW
Qgi (M
MS
CF
/D)
NORMAL ORIFICE
VENTURI ORIFICE
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Surface Controlled Gas Injection Valve
• Features - ajustability
– orifice size can change as well conditions change without intervention
– reduces risk of erosion. Can remain “full open” during unloading and then close to necessaryorifice size.
– controlling lift gas originating from a gas zone in same well as the oil reservoir (“auto” GL)
• Current Issues
– Not a new technology
– Specific applications
• e.g. subsea installations w/o GL control at WH
• SMART wells
– Expensive for existing developments
– Hydraulic vs. electric control (cable?)
• Electric cable downhole “…one $2 O-Ring causesUS million dollar workovers…”
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Advanced Gas Lift Valve Modellingactual gas rate through IPO as a function of valve
performance (inflow) and tubing performance (outflow)
ga
s flo
w r
ate
MM
scf/
d
Pt tubing pressure psi
GLV
performance
Pc casing
pressure
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High Pressure Injection Valve• Features
– meets “zero intervention” philosophy set for subsea developments
• High reliability orifice
• No unloading valves required
• Fewer leakage paths
– IPO valves to 5000 psi; Orifice valves
to 7500 psi. 10MMscf/d
– premium materials/elastomers
– flow path limits erosion
• Current Issues
– requires a minimum gas injection rate
for well stability
– requires a higher injection
pressure (compression)
– potential valve erosion
– no flexibility
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High Performance Back Check
• Increasing industry emphasis on valve & well integrity
• New valves
– valve & tubing become first barrier element
– metal to metal seal at back check
– spring activated (protected from flow)
– flow geometry optimised for seal area protection
– 10,000 psi, 20-180oC, 8.5 MMscf/d
• Qualifies as barrier element under Norsok D10 and StatoilHydro
– Eliminates need for annular safety valve
– fewer well interventions/opex
– deep well performance & integrity
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Gas Lift Valve Reliability
• Valve performance
– Valve PerformanceClearing House(joint industry project)
• Valve testing
– Equipment: Automatic Validation Tester (AVT)
– QA/QC, valvehistories
• Revised API/ISOstandards &procedures
AVT II advanced valve test bench
Source Decker Technology Inc.
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Stage 1
• Advances in equipment, software,
standards and testing make gas lift
designs more robust , repeatable and
secure.
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Stage 2: Single Well Diagnostics
& Remediation
• Maintaining optimum gas injection
– Valve behaviour
– Injection depth
• Technology
– Moving beyond Flowing Gradient Survey + nodal analysis
– Sensor improvements
– Dynamic well modelling
– Multiwell surveillance
• Challenges
– Increased data load -> overload
– Increasing lack of gas lift engineering expertise
– “…gas lift works, even if it’s broken!”
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Improving Lift Efficiency
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Fibre Optics – Distributed Temperature
Sensors/Systems (DTS)
• Simultaneous real time measurements through entire completion
• Permanent installation or slick line
• Temperature vs time vs depth
dep
th
temperature
GLV1 @ t1
GLV2 @ t2
GLV3 @ t3
GLV4 @ t4
Source Schlumberger
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CO2 Tracer Injection
• CO2 slug injected into GL supply line
• Produced fluid stream analysed at well head vs. time.
• CO2 peaks correlate with active GL valve or leaks.
• GLV verification &tubing integrity.
• Features:
– No shut-in
– No downhole tools
– Alternative to flowing gradientsurvey (FGS)
– HSE
Time: hh:min:sec
CO
2 C
oncentr
ation (
%)
Source ALRDC/AppSmiths
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Dynamic GL Simulation
Effect of decreasing Gas injection rate at a constant FTHP
Effect of decreasing Gas injection rate at a constant FTHP
gas flow through orifice valve
e.g. DynaliftTM, OLGATM, FlowLiftTM
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Improved Data Management
• On line data acquisition, storage and analysis
• Conceived for large fields (100’s of wells)
• Surveillance: display, sorting, trending
• Management by exception: alarms/flags
• Offline analysis using engineering applications
• Storage of well service histories
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Desktop Intelligence: “Smart” Diagnostics
Artificial Intelligence – a virtual “robot”
• Monitor GL well data: CHP/THP, prod/inj rates, GLV data…
• Expert Systemknowledge base:initial “expert” input:define a range ofabnormal conditions.Trainable, probabilistic,expandable.
• Data assessment:pattern recognition,intelligent systems,machine learning.
• Diagnostics: providesresults & recommendations
Source Weatherford
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Stage 2
• Advances in sensors, data acquisition &
storage, and diagnostics provide
methods (tailored or generic) for
improved well surveillance, intervention
and planning.
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Stage 3: Field Gas Lift Optimisation
• determine (and set) optimalgas rates for each well
• high frequency (daily)optimisation
• integrated asset model
• requires adequateinfrastructure ininstrumentation, metering,communications.
• implementationrelies on adapting people& work processes.
• “Digital Oil Field”:i-Field, Smart Field,e-Field, etc.
Fuel, Qgc
Formation
Gas, Qgf
Produced
Gas
= Qgf+Qgi
Other uses
= Qgf-Qgc
Lift Gas,
Qgi
Oil + Water+$ -$
-$
+$
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Sustainable Production Optimisation
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Time
Incre
ased
Valu
e O
ver
‘Do
No
thin
g’
Simple Manual Optimisation
Complex Manual Optimisation (Offline)
Complex Automated Optimisation
Optimisation gains revert to norm
as system changes: automation of
process is key to sustain the gains
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Approaches to Field GL Optimization
Well Data
Well Behaviour
Deterministic
Engineering
Models
“Data
Driven”
Models
surveillancereal time
optimisationanalysis
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Generalised Online Real Time
Optimisation (RTO) Architecture
SCADA*
Systems
Data
Management
Applications
Manager
OptimiserWell
Models
Network
Models
Internet/IntranetS
CA
DA
Inte
rface
3rd
Part
y I
nte
rfaces
Model Export/Import
Other
Applications
Offline Engineering
Applications
Corporate
DatabasesData Driven or
Deterministic
Models
*supervisory control and data acquisition
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On Line GL Optimisation Examples
Lobito Tomboco
Offshore Angola
Ekofisk
Norwegian NS
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Field Optimisation: Issues & Challenges
• Individual wells must already be
optimised.
• Cost of implementation: brown fields?
• Increased data availability vs. decrease
in engineering knowledge.
• Reliability, calibration & maintenance of
SCADA and sensors -> unmanned
offshore environment?
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Stage 3
• Advances in SCADA, optimisation algorithms and data management have allowed gas lifted systems to be optimised on a relative high frequency cycle, resulting in increased oil production and more efficient lift gas usage.
• Real time/on-line gas lift optimisation is now a field proven methodology.
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The Prize
• Design & Implementation– More production can be safely gas lifted
– Avoidance of costly workovers/re-entries
• Single Well Remediation– 0-25% on flowing wells
– Revival of shut-in wells
• Full Field Optimisation– 2-5% oil increase of field wide production
– Up to 40% improvement in gas injection efficiency
– Sustained production increases with RTO
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Conclusions
• The last decade has seen a step change in the understanding, surveillance, control and optimisation of the gas lift process:
– GLV performance
– Web based IT infrastructure
– Optimisation algorithms & surveillance routines
– SCADA and associated instrumentation
• Outstanding issues:
– Measurement (notably Qgi)
– Well testing
– Maintenance
– Training
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Gas Lift may be robust and forgiving, however it
can be improved with better applied engineering
Data Acquisition
Data Management
?
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acknowledgements & thanks
• Dr. Ken Decker – Independent Consultant & VPC Chairman
• Steve Gossel – Aramco
• Sies Hussain – ExxonMobil
• Michael Juenke – Weatherford
• Manickam Nadar – Independent Consultant
• Andrew Shere – Weatherford
• Les Taylor – Senergy
• Gatut Widianoko – Independent Consultant