GS Flow Ltd. Advances in Multiphase/Wet Gas Meter Technologies which aid the User in the Real World

Transcription

1 GS Flow Ltd SE Asia Flow Measurement Conference 2015 Advances in Multiphase/Wet Gas Meter Technologies which aid the User in the Real World Gordon Stobie, GS Flow Ltd, formerly with ConocoPhillips Company Ver 5

2 Acknowledgement Richard Streeton Arnstein Wee Co -Authors CTO,FMC-MPM SeniorMeteringEngineer,FMC-MPM

3 Contents MPM Meter and its technologies MPFM Meter Sensitivities Field configuration PVT data, sampling An alternative to sampling PVT, EoS, data from line to standard conditions Data - getting it right and wrong (wrong first!) Conclusions

4 MPM Multiphase Meter 3-D Broadband Overall Schematic 4

5 Some MPFM Meter Sensitivities

6 MPM Meter Sensitivities. Composition Map Water Continuity WLR & Physical constraints 6

7 FieldConfiguration Field configuration -fluid data input to multiphase meters single-phase properties of the oil, gas and water these are key input parameters. By and large they are obtained from fluid samples, analysis and PVT prediction depending on the meter location it can be a costly, disruptive and hazardous activity. PVT information is used in field configuration: To predict HC single-phase fluid properties at OC. Input to convert measured flow rates from Operating to Standard Conditions. Most MPFM s convert by assuming the oil and gas stay in equilibrium from the OC to SC in a single-stage flash (SSF) conversion. 7

8 Field Configuration data issues. Base uncertainty of the PVT data Real World applications at high GVF s may have a base PVT uncertainty of ±3-5% (on gas density -more depending on OP). Uncertainty of the PVT package.. Some Fluid composition variations - due to:- Poor sampling or Reservoir changes (dropping below bubble point) or EOR techniques (GL, GI, WI etc) or Variations from zones/wells in multi-zone completions. Summary Uncertainties in Real World field configuration should be expected and an MPFM needs to be adequately robust to handle these. For example: High GVF s (wet gas) -uncertainties in the gas properties impact the oil and water measurements. In high WLR/low GVF flows -water properties will have an impact. For these, frequent updates of Field Config data may be required. 8

9 Meter Sensitivity Analysis The MPM meter claims low sensitivity to HC fluid composition BUT the degree of sensitivity varies with GVF and WLR so it may help to assess each applications meter sensitivity. A similar sensitivity will exist for other vendors MPFM s MPM have developed a sensitivity tool. The tool uses raw/field configdata to assess the impact of uncertainties in oil/gas densities and water conductivity on the overall results. In high GVF s where the target is oil -the user is interested in the gas density impact on the accuracy of the oil flow -espfrom co-mingled reservoirs, GI and GL producers. For many high GVF wells, the config gas density uncertainty impacts the oil flow rates. The MPM Recalculation Tool illustrates the impact of PVT uncertainties on oil measurements. Four cases from a well test campaign are used as an illustration. Average Average GVF (%) WLR(%) This analysis is not a do once Case 1: MLW and forget throughout the Case 2: KMD field life GVF & WLR s will change & sensitivities are likely Case 3: MLN to change Case 4: MLSE

10 Sensitivity Tool Analysis ±3% Oil density on liquid flow rates ±3% Gas density on liquid flow rates ±3% Oil density on gas flow rates ±3% Gas density on gas flow rates Case 4:MLSE-5 used Droplet Count to determine flows, largely immune to fluids 10

11 So, sampling, analysis and PVT are key inputs. Is there an Alternative? Why would we think that we need an alternative? 11

12 So, sampling, analysis and PVT are key inputs. Is there an Alternative? Why would we think that we need an alternative? Sampling may be $, difficult (and hazardous) in general operations Sampling may be $$, difficult (and more hazardous) in HP, HT fluids Sampling may be $$$ and difficult to do Sub Sea And the above may lead to inadequate sampling or lots of $$$$ Sampling SO? Are we sampling too frequently??...or not frequently enough? Spending too much Not metering optimally? So.. is there an alternative to Field Configuration sampling? 12

13 GAS PROPERTIES IN-SITU MEASUREMENTS In high GVF s there are long periods where gas is the only fluid in the meter. If we look for or create gas flow periods where the liquids fall back, leaving gas in the meter. In those periods note the Pressure, Temperature and Density & Permittivity and compare with the PVT configdata. Time 13

14 Gas In-Situ Quality Measurements When GIS measurement results are reported, we will question how good they are so we need to determine their quality. Various quality parameters are used - the most important of these are: Pressure/Temperature: the average pressure/temperature during the GIS measurement should be within specific, configurable limits compared to the operating pressure/temperature. Duration: whilst a long period is desirable -however the pressure/temperature tends to drop if the duration is too long and impacts the pressure/temperature quality rating. Pressure Temperature Duration High (1) Medium (2) Low (3) The above are based on operating conditions of 60barG & 50degC 14

15 Gas In-Situ Quality Measurements Overall Measurement Quality 0-Low, 1-Medium, 2-High Pressure Quality 2 Temperature Quality 2 Duration Quality 2 Operating Temperature Average Temperature Operating Pressure Average Pressure o C 41.7 o C 54.1 Barg 53.7 Barg Average Measured Density kg/m 3 Average PVT Density kg/m 3 Measured Density Factor Average PVT Permittivity Average Measured Permittivity Permittivity Offset using Measured Density Field Composition Map Gas properties are important in ascertaining HC liquids. 95% GVF -notional line between liquid/gas dominated flows & gas properties have a major impact on liquid measurements. GIS performed when GVF s > 95%. 70% wells are GVF > 95% -so gas properties accuracy is important in ascertaining liquid production. 15

16 Conversion to Standard conditions Well test data is typically reported at SC. For test separators, a black-oil correlation may be used with a shrinkage/or meter factor. MPM meters typically use single stage flash (SSF) which assumes that the oil and gas are in equilibrium down to SC. This is the only feasible approach for an MPFM with no knowledge of the downstream process..but may not be the most suitable method to replicate a complex process. In complex processes with multiple stages allocation may be based on the oil rates from the MPFM well tests against the oil output say Stock Tank (Custody Measurement). Between the two may be a process system of several separation stages, compressors, dehyunits, etc., and. in this case the SSF assumption is invalid as the oil and gas do not stay in equilibrium down to standard conditions. 16

17 Field Processing Field Processingusing Single Stage Flash (SSF) Multiple Well Pads & Reservoirs. Campaign well tests using MPM & MPM[oil] to determine STBbls M M Facility metering (for oil) is against exports tanks and Tank Tables. The comparison was poor. V101 has poor metering so MPMs are compared against the Stock Tank out-turn.. Well test comparison to Stock Tank conditions 17

18 How poor? Well Test Campaign Balance Factors MPM[oil] Oil Water Gas 1: August Feb Feb RECALCULATED May % apparent under-reporting of ΣMPM test fluids vs Export Oil Stock Tank. These results made us stop and think 18

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20 Multi Stage Flash Processing The calculation process for an MSF: i. Flash fluid PVT to conditions at V-101. Save resulting oil as new fluid Oil V-101 ii. Flash Oil V-101 to V-102. Save resulting oil as new fluid Oil V-102 iii. Flash Oil V-102 to oil stabilizer T-101. Save resulting oil as new fluid Oil T-101 iv. Flash Oil T-101 to Stock Tank. Save resulting oil as new fluid Oil Stock Tank v. Flash Oil Stock Tank to Standard Conditions 20

21 MSF Conversion to Standard Conditions Example: MSF recalculation data from one well pad. MSF Well pad oil rate increased from 1650 to 1890sbpd (240bbl/+14.5% increase) Due to the range of fluid types, not all wells exhibit such a large change. Over the whole field (c20wells), a delta of +1500sbpd was observed on a total of 26,000sbpd (+6% increase). In addition, gas is cooled/scrubbed/compressed for GL/GI, and liquid is recovered and fed forward. An MPFM cannot account for condensation volumes, but we estimate Using one well pad the condensed oil volume was 98sbpd for a rate of 1890sbpd (a +5% increase) for the MSF oil rate. So 5% was judged to be a reasonable estimate for volatile/condensate wells. Condensed liquids are negligible for black oil wells 21

22 Summary - Production vs Stock Tank volumes using MSF where SSF indicated a 10 to 23% under-reporting Campaign Reconcill n Date No. of well tests Ave GVF (%) Stock Tank (sbpd) MPM (sbpd) Delta (%) GIS Tests 1 08/ ,614 28, / ,182 23, / ,182 24, / ,609 25, / ,705 21, / ,406 15, / ,783 18, / ,219 17, Campaign 2 and 6 consisted too few wells to be considered. 22

23 Correlation with GIS measurements Qtyof GIS checks is approx25% -50% of total well tests.. More (successful) GIS tests = Better data 23

24 Conclusions GIS removes the need for field configuration fluid sampling of high GVF wells -enhancing safety and increasing confidence. MPM have developed GIS functionality to include quality parameters. Note: Oil/Gas samples may be needed for fiscal fluid reconciliation. Increased GIS verifications reduced the oil (test vs export) measurement delta. Operators should consider the well allocation -to out-turn and implement the correct facility PVT package Sensitivity analysis can aid understanding the importance of the fluid parameters and allow the Operator to concentrate efforts on essentials Operators should endeavour to ensure that in process metering is of a quality to test the MPFM (meter confidence eroded by inability to test against production system). 24

25 Thank You Questions?? 25