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Performance analysis of gas-lifted subsea wells from combined well tests

Performance analysis of gas-lifted subsea wells from combined well tests. by Wim der Kinderen Consultant Production Technologist Shell UK Exploration and Production Aberdeen w.derkinderen@expro.shell.co.uk. API/ASME Gas Lift Workshop, Houston, February 2001. Subsea gas lift.

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Performance analysis of gas-lifted subsea wells from combined well tests

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  1. Performance analysis of gas-lifted subsea wells from combined well tests by Wim der Kinderen Consultant Production Technologist Shell UK Exploration and Production Aberdeen w.derkinderen@expro.shell.co.uk API/ASME Gas Lift Workshop, Houston, February 2001

  2. Subsea gas lift why is gas lift optimisation of subsea wells so difficult? • what are the consequences of limited testing and surveillance? • how can we improve testing and surveillance in a cost-effective way?

  3. typical GL performance curve (fixed FTHP) net or gross (m3/d) 2000 1500 1000 500 0 0 50 100 150 200 injection rate (*1000m3/d)

  4. gross (m3/d) 2000 1500 1000 500 0 0 50 100 150 200 injection rate (*1000m3/d) influence of wellhead choke or flowline

  5. Problems of subsea gas lift • wells usually share flowline to platform: • FTHP cannot be considered constant • over-injecting lift gas causes oil deferment • flowline/riser system is prone to severe slugging: • limited validity of steady-state models • difficult well kick off (risk of platform trip) • subsea wells are hardly ever surveyed (expensive access) • wells are sporadically tested (oil deferment) • downhole gauges/flowmeters are lacking/ malfunctioning

  6. Well testing long flowline -> several hours stabilisation time (typ. > 8 hrs after GL rate change) • slugging -> long test times (typ. >6 hours) • difficult to test at normal operating conditions • cumbersome playing with chokes to match normal FTHP • multi-rate testing of one well takes days

  7. Limited survey and test data usually just one P/Q datapoint at one lift gas rate available • lift point, reservoir pressure, and IPR are uncertain: • too many degrees of freedom to match well and flowline models • performance analysis is very time-consuming • models are useless for lift gas allocation and well routing

  8. How to improve surveillance in a cost-effective way? use pressure drop across subsea oil chokes for production trending: install dP transmitters (FTHP and manifold pressure gauges are too inaccurate at small dP) • install distributed temperature sensors (DTS) in the wellbore • apply modified ‘piggy-back’ well test method: • less production deferment • reduced slugging problems • multi-rate test data available

  9. Test Sep subsea manifold GD-01 Gannet A 15.5 km from platform MPM Bulk Sep GD-02 R31 6” 6” GD-03 R32 Bulk Sep GD-04 4” (gas lift) Gannet G GD-06 GD-06 New well Andrew Tay reservoirs Gannet D field - central North Sea 4 well test campaigns cost 2 MM£/yr

  10. Testing two subsea wells simultaneously standard ‘piggy-back’ testing is not possible: the FTHP of well A changes when well B is added to the test flowline: therefore, the production of well A is no longer known unless its PQ curve is first established: this requires a multi-rate well test, or a calibrated well model • combined test data can be unravelled: • by assuming that the PQ and lift performance curves of a well can be linearised around an operating point

  11. 100 Well model, no GL 90 Linearised, no GL model, GL 20 Km3/d 80 Linearised model, GL 40 Km3/d 70 Linearised 60 50 40 30 20 10 0 0 100 200 300 400 500 600 700 Linearised PQ curves THP (bar) 800 900 Gross flowrate (m3/d)

  12. model, THP 50 bar 150 model, 55 bar model, 60 bar 100 Linearised, 50 bar Linearised, 55 bar Linearised, 60 bar 50 0 Linearised GL curves 350 300 250 200 Gross flowrate (m3/d) 0 10 20 30 40 50 60 70 80 90 Lift gas injection rate (Km3/d)

  13. Around an operating point for well 1: where the constant c includes the reference Qgl and THP For a second well: Adding both wells: Linearised equations The production of a well can be written as a function of the wellhead pressure (THP) and the lift gas rate (Qgl) 6 unknowns (a, b, c, d, e, f) ----> 6 independent equations to be solved

  14. Dual well test Procedure: 1. Select two wells for combined testing 2. Test most prolific well at one THP and GL rate 3. Add second well and select GL combinations 4. Use choke to change THPs if required 5. Solve inverse matrix to find a, b, c etc. (Excel macro) Matrix of measured THPs and GL rates

  15. Dual well test - input data set Example:

  16. Input data plot 80 70 60 50 THP (barg) 40 test 1, GD4 only, no GL 30 test 2, GD4 only, 40 K GL test 3, GD01 (40 K) + GD04 (40 K) 20 test 4, GD01 (40 K) + GD04 (40 K) test 5, GD01 (45 K) + GD04 (no GL) 10 test 6, GD01 (20 K) + GD04 (no GL) 0 0 200 400 600 800 1000 1200 Total gross flowrate (m3/d)

  17. 80 70 GD04: 20.25 sm3/d/bar 60 50 test 1 GD04, no GL THP (barg) 40 test 2 GD04, 40 K GL split test 3 split test 4 30 split test 5 GD01: 6.04 sm3/d/bar split test 6 20 GD04, no GL GD04, 40 K GL GD01, 20 K GL 10 GD01, 37.5 K GL GD01, 45 K GL 0 0 200 400 600 800 1000 1200 Gross flowrate (m3/d) Split after matrix inversion

  18. Assumption: BSW and GOR are not rate-dependent: BSW2 = (Qwater,combined - BSW1* Qgross,1)/Qgross,2 Similar for the GOR of well 2: GOR2 = (Qgas,combined - GOR1* Qnet,1)/Qnet,2 How to unravel BSW and GOR? Single well test of well 1 reveals BSW1 and GOR1 Requires accurate well test measurements!

  19. Conclusions • Deriving PQ curves from dual well tests is feasible • Method works for gross, net and produced gas • Method requires just one single well test (and 5 combined tests) • Adequate accuracy for most purposes, but depends on input data quality (a.o. THP, liftgas rate) • Provides valuable information for system model calibration (-> to generate actual P/Q and GL curves) • Significant cost savings (1-2 MM£ for Gannet D) • Now applied in other subsea fields of Shell Expro

  20. Enhancements • use multivariate analysis when more well tests are available • use downhole gauge data where available • use oil and/or water composition from samples to improve production allocation • extend method to multiple well testing

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