Mapping the fluid front and pressure buildup
`using 4D data on Norne Field
`BÅRDOSDAL, ODDVARHUSBY, HANSA. ARONSEN, NANCHEN,and TRINEALSOS,Statoil, Harstad, Norway
`Norne Field, in the southern part of the Nordland II area
`in the Norwegian Sea approximately 100 km north of Aasgard
`Field, is producing from an FPSO. The main field is a horst
`block approximately 9 ǂ 3 km (Figure 1). The reservoir rocks
`are sandstones of Lower and Middle Jurassic age. The hydro-
`carbon reserves consist of a gas cap (75 m), mainly situated
`in Garn Formation, and an oil leg (110 m), mainly situated in
`Ile and Tofte formations. The sandstones are very good qual-
`ity with porosities and permeabilities of 25–32% and 200–2000
`mD, respectively. Net-to-gross is close to 1 for most reservoir
`zones. Oil production started in 1997. The first 4D seismic sur-
`vey was acquired in 2001, and 4D information has been
`actively used in subsequent reservoir management.
`This paper will focus on the importance of tight integra-
`tion of all disciplines for achieving good quality and repeat-
`able 4D seismic data that can optimize new drilling targets
`and help obtain a more reliable reservoir simulation model.
`
`Acquisition. The initial seismic survey was conducted in
`1992 using a dual source and three streamers separated by
`100 m. This was a big 3D exploration survey and was not, at
`that time, thought of as a 4D baseline survey. Three monitor
`surveys have been collected since the field began producing—
`in 2001, 2003, and 2004. All surveys were acquired with the
`WesternGeco Q-marine system. Asingle source and six steer-
`able streamers separated by 50 m were used on all monitor
`surveys. This configuration repeated the base survey as much
`as possible. However, it was decided not to steer to repeat
`the feathering of the base survey. Instead all lines were
`acquired as close as possible to zero feather, because this is
`much easier to repeat. The first Q-acquisition in 2001 was con-
`sidered the base Q-survey, and all new surveys repeat this
`geometry as accurately as possible.
`Undershooting of the Norne production platform was per-
`formed in 2001, 2003, and 2004. Figure 2a shows the feather-
`ing difference between the base survey and the Q acquisition
`in 2003 (left), and between the Q acquisitions in 2001 and 2003
`(right). Much larger feathering differences are seen with the
`base survey than between the Q-marine surveys. As seen in
`Figure 3, this clearly influences the amount of nonrepeatable
`noise in the 4D data. The repeatability between the Q-marine
`surveys is clearly better than between the base and Q-sur-
`veys. Average nrms for base versus Q is approximately 40%;
`the corresponding number for Q versus Q is 19–21%.
`Detailed monitoring of source and feathering repetition
`is performed during acquisition. Araw difference stack of the
`line is produced shortly after the line is acquired. In 2004 this
`4D difference was compared to the 2001–2003 difference and
`was very useful in deciding if a newly acquired line should
`be rejected or not. The lesson learned was clearly that, in 4D,
`some swell noise can be accepted, because this can effectively
`be removed in processing. Geometry failure (source and/or
`feathering mismatch), however, is more difficult to tolerate.
`All three undershoots of the Norne FPSO used a two-boat
`operation (one conventional shooting boat and one Q-marine
`streamer boat). Again the acquisition geometry was repeated
`as accurately as possible, but good repetition in this area was
`much more difficult to achieve than in the main area covered
`by a one-boat operation. Figure 2b shows inline deviation (dis-
`tance in inline direction) between the sources of 2003 and 2004
`
`Figure 1. Top reservoir map showing Norne horst block with four seg-
`ments. G segment contains only oil in the uppermost Garn reservoir.
`Segment C, D, and E have 75 m of gas and 110 m of oil.
`
`for the main area and the undershoot area. Figure 2c shows
`the crossline deviation (distance in crossline direction)
`between far offsets (middle cable) of 2003 and 2004 for the
`main area and the undershoot area. More deviation between
`the surveys can be seen for the undershoot area than for the
`main area. This can be explained by the much more difficult
`timing challenges involved with two-boat operations than
`with one boat. On the final processed 4D line, repeatability
`is a little worse in the undershoot area between 2003 and 2004
`than between 2001 and 2003. The same undershoot vessel (and
`same source) was used in 2001 and 2003, but a new under-
`shoot boat (with a different source) was used in 2004. This
`caused a lot more work in the signature-matching process than
`we expected.
`The undershoot vessels were not Q-boats and did not have
`the calibrated marine source (CMS). A single modeled far-
`field signature is therefore used for the signature deconvo-
`lution in the undershoot area. The amplitude and timing
`relationship between the modeled far-field signature and the
`CMS signature is not straightforward and is very difficult to
`estimate properly. The lesson learned here is that either the
`same conventional source should be used each time, or that
`the same CMS source used in the main area be used in the
`undershoot area.
`In the main area, slightly better repeatability can be seen
`for 2003–2004 than for 2001–2003 (Figure 3). For the main field
`area (yellow polygon), mean nrms of 19% was measured for
`2003–2004; the corresponding number for 2001–2003 was
`21%. This is due to better accuracy of source and receiver posi-
`tion repeatability. Figure 4 shows the radial (distance between
`points) source and far-offset cumulative differences between
`the surveys. In 2004 more than 70% of the shots were within
`5 m of the shots in 2003. The corresponding number was 50%
`for 2003 and 2001. For the far-offset repetition, approximately
`70% of the shots in 2004 were closer than 25 m to the 2003
`shots. This figure was approximately 60% for 2003 compared
`with 2001.
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`Figure 3. The nrms maps and nrms histograms measured on the 4D data
`in overburden of (a) base and 2001, (b) 2001 and 2003, and (c) 2003 and
`2004. Blue data points in the histogram are related to the yellow polygon
`on the map.
`
`Figure 2. (a) Left is feathering difference between base and 2003, and
`right is difference between 2001 and 2003. (b) Inline source deviation of
`2003 and 2004 of main area (left) and undershoot area (right). (c) Far-
`offset crossline deviation of 2003 and 2004 of main area (left) and under-
`shoot area (right).
`
`Processing. The best way to interpret the OWC at Norne is
`by using the difference data, and this requires careful 4D pro-
`cessing to enhance the production-related 4D differences. All
`Norne vintages go through the same processing sequence at
`WesternGeco.
`During processing, it is essential to test processing algo-
`rithms on all vintages so that 4D difference displays can be
`analyzed and compared.
`In general, adaptive processes should be avoided and
`deterministic processes preferred. Figure 5 shows the effect
`of tau-p decon on the 4D data. The process is applied on all
`vintages and analyzed on the 4D differences. The decon
`clearly helps remove multiples, but it also degrades the 4D
`effect of the rising OWC (blue circle). The Norne data are heav-
`ily contaminated by diffracted multiples, requiring multiple
`attenuation and several passes of Radon. The best solution
`at Norne was to apply 2D SRME (Figure 5c). Even though
`this is an adaptive process, testing showed that it preserved
`the 4D signal well and was most effective in removing the
`multiples. It should be noted that the repeated acquisition
`geometry of zero feather is clearly an advantage for optimum
`results from SRME in a 4D sense.
`4D binning is important in 4D processing. To obtain good
`repeatable 4D data, it is very important to select the pair of
`traces between two vintages that best match in terms of source
`and receiver locations. Figure 6 demonstrates this. The nrms
`maps show the effect of using all available data in process-
`
`Figure 4. Cumulative radial (a) source difference and (b) far-offset differ-
`ence between vintages.
`
`ing an overfold area compared to the situation in which non-
`repeating traces are thrown away. Pairs of traces between the
`two vintages that do not match in acquisition geometry will
`clearly degrade the 4D difference.
`
`4D interpretation strategy. The rise of the OWC at Norne can
`most effectively be interpreted using the 4D difference data.
`Figure 7a shows seismic modeling (stacks) of varying rise of
`the OWC (0–70 m). The new OWC is almost impossible to
`locate on these stacks. However, if the 4D differences are
`used, the geology can be cancelled and the new and original
`OWC are left in the data as shown in Figure 7b. Figure 7c
`shows a 2003 line through a water injector. The 2003 OWC
`cannot be interpreted on this line. On the 2001–2003 differ-
`ence (Figure 7d), however, the 2003 OWC is interpretable.
`Figure 7e shows some synthetic modeled difference data in
`the injector based on repeated saturation logging in 2000 and
`2002. The left curves in Figure 7e show the relative change
`in acoustic impedance between base and 2000 (blue) and base
`and 2002 (black) surveys. A complete flushing of the oil with
`water causes an acoustic impedance change of 7–8%. Figures
`7c–e are plotted at the same depth scale. Even though the tim-
`ing of the repeated saturation logging does not coincide with
`the timing of the 4D data, this 4D modeling very much con-
`firms that our OWC interpretation strategy is valid.
`A reservoir simulation 4D modeling approach is used on
`Norne to optimize the 4D interpretation and reservoir simu-
`lation history matching. Seismic modeling of the simulation
`model is performed and compared with the 4D data.
`Updating the simulation model is done in areas where the
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`Figure 6. The nrms map showing an overfold area with (a) all data used
`in the processing and (b) 4D binning applied and nonrepeating traces
`thrown away.
`
`Figure 5. (a) Radon stack. (b) Radon and tau-p decon. (c) Radon and 2D
`SRME. Blue circle highlights the 4D effect of a rise of the OWC.
`
`simulation model does not coincide with the 4D data and pro-
`duction data. Both seismic reflection amplitudes and acoustic
`impedance are compared. A Norne rock model and the
`Gassmann equation are used for calculating seismic para-
`meters. The SimPli method from Norsar (Drottning et al., 2004)
`is used to model seismic at different vintages. Seismic mod-
`eling is important for history matching and is also a guide to
`how the 4D difference data can be interpreted and understood.
`Seismic modeling in pilot wells and in wells with repeated
`saturation logging (as in Figure 7e) is also very important as
`an interpretation guide and to validate the 4D interpretation.
`
`Case studies. The first study is from the E segment (Figure
`1). Based on 4D data from 2003, it was decided to drill infill
`production well E-3CH. The well location was confirmed to
`be good on the 2004 data, and the well was drilled with suc-
`cess during the spring of 2005. When the 2003 4D data were
`analyzed, a clear difference was seen between the 4D data
`and the reservoir simulation model. Figure 8 shows this com-
`parison for a line through well E-3CH from the simulation
`model and the 4D data. A map showing the position of this
`well is shown in Figure 8f. Figure 8a shows water saturation
`from the simulation model in mid-2003. Figure 8b shows
`modeled seismic 4D difference of the simulation model. Figure
`8c shows the real 4D difference data (2001–2003), and here
`the OWC from 4D (blue line) clearly can be interpreted deeper
`than in the simulation model (yellow line). In the simulation
`model at that time, fault A(Figure 8f) was open and the water
`flowed easily from the water injector F-1H through fault A.
`The 4D data indicated that fault Awas partly sealing and most
`
`Figure 7. (a) Seismic modeling for varying rise of OWC from 0–70 m. (b)
`Seismic differences for varying rise of OWC and the first base trace. (c)
`2003 4D data around an injector. (d) 2001–2003 4D difference around
`same injector. The 2003 OWC can clearly be interpreted here. (e) Left
`curves show change in acoustic impedance in % from base to 2000 (blue
`curve) and base to 2002 (black curve). Seismic modeling on the right
`show differences between base and 2002 and 2000–2002.
`
`water from F-1H therefore flowed along fault A instead of
`through it (red arrow in Figure 8f). This is confirmed by tracer
`data in the area. By decreasing the fault transmissibility of
`fault A and extending it farther to the main fault (B), a new
`simulation model was created that had a much better match
`with the 4D data (Figures 8d and 8e). The green line is OWC
`on the new simulation model, and this matches the 4D OWC
`(blue line). The location of E-3CH was now also good in the
`simulation model.
`The new simulation model also improved the water cut
`and pressure match in the area. This is shown for two wells
`in Figure 9. Prior to drilling the production well, it was
`decided to drill a pilot well to check the OWC. The pilot well
`confirmed the OWC level as interpreted from the 4D data and
`predicted from the new simulation model.
`Figure 10 summarizes the results from E-3CH after six
`months of production. The figure compares the actual oil
`production and water cut with the prediction from the old
`and new simulation models. The new simulation model pre-
`dicts the real observation clearly better than the old model.
`History matching using the 4D data in this area was also
`described in an earlier paper (Lygren et al., 2005).
`The next case study is from the southern part of C seg-
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`Figure 8. (a) Water saturation (red is high saturation) of old simulation model and (b) seismic modeling (4D difference) of old simulation model. (c)
`Real 4D difference data. (d) Water saturation (red is high saturation) of new simulation model and (e) seismic modeling (4D difference) of new simula-
`tion model. (f) Top reservoir map.
`
`ment (Figure 1). A horizontal producer was drilled in the
`autumn of 2003. The first planned location was based on the
`2001 4D data and the simulation model available at that time.
`Figure 11a shows the water saturation from the old simula-
`tion model in 2003. A carbonate cemented barrier is between
`Ile and Tofte formations. Pressure changes over the barrier
`were observed in several wells in the area, and it was expected
`to be a barrier for the water beneath. The first well location
`was therefore placed in the highly porous and permeable
`Lower Ile Formation, above the carbonate cemented zone.
`Figure 11b shows the 2001–2003 fast track onboard-processed
`4D acoustic impedance difference data received seven days
`after the last shot of the 2003 acquisition. Red indicates increase
`in impedance from 2001 to 2003 and is related to water replac-
`ing oil. It is clear that the water indeed passed through the
`carbonate cemented zone and flooded the lower part of Ile
`Formation. It is also evident that the toe of the originally
`planned well path seems to be in the water zone. To avoid
`early water production, the well location was moved upward
`and away from the water front (yellow line). This new well
`location was identified 14 days after the acquisition. The well
`was drilled successfully in the oil zone, and the first year after
`start up it produced with a rate of approximately 4000 Sm3/d
`without water. An explanation to the observation of water
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`Figure 9. (a) and (b) water cut match and (c) and (d) pressure match for
`two wells in the area using old and new simulation models.
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`Figure 10. Left plot shows oil production, and right plot shows water cut
`for the well E-3CH. The new simulation model has predicted observations
`more accurately.
`
`Figure 11. (a) Water saturation of old simulation model. Red is high water saturation. (b) 4D acoustic
`impedance difference. Red is increase in impedance from 2001 to 2003, indicating water replacing oil.
`(c) Water saturation of new simulation model. Red is high water saturation.
`
`breaking through the barrier can be that the area contains more
`small-scale faulting than can be observed in the seismic data.
`The carbonate cemented zone is thin (approximately 20 cm)
`and tight, and even small-scale faulting can break this bar-
`rier and allow the water to flow through. By introducing more
`small-scale faulting into the simulation model, the observa-
`tion from the 4D data can be better matched (Figure 11c).
`The third case study is from the northwestern part of C
`segment (Figure 1). The 4D data in 2003 and 2004 indicate
`that the upper part of Tofte Formation was undrained, and
`a new producer was therefore scheduled to be drilled in this
`area in the autumn of 2005. Figure 12 shows 4D amplitude
`and 4D difference data from a line through the well. The OWC
`is interpreted to be in the lower part of Tofte Formation. As
`pointed out earlier, the OWC is very difficult to interpret on
`each vintage (Figure 12a). The OWC is much clearer and
`interpretable on the Q versus Q dif-
`ferences in Figures 12b–c. Much gas
`was injected in this area prior to the
`2001 acquisition. This gas is also seen
`in the area in 2004. The base-2004
`difference (Figure 12d) shows this
`expansion of the gas cap (yellow
`line). Prior to drilling the horizontal
`producer, a pilot well was drilled
`into Tofte Formation to check the
`OWC and to take pressure mea-
`surements. Due to high pressure in
`the lower part of the formation, the
`pilot well had to be stopped before
`the OWC was reached. However,
`this pilot well confirmed that the
`upper part of Tofte Formation is
`undrained, as predicted by the 4D
`data. The pilot well also showed
`some gas cap expansion. Much of
`the water flooded into this area is
`most likely coming from the north.
`The new simulation model has fairly
`good agreement with the 4D data as
`indicated in Figure 12c by compar-
`ing the OWC from the 4D data and
`the simulation model (blue and red
`lines). The horizontal producer
`began production in January 2006.
`By the end of February 2006, the well
`was producing approximately 5500
`Sm3/d with no water.
`The last case study is from G seg-
`ment (Figure 1) in what was initially
`an undersaturated reservoir in Garn
`Formation (thickness of 25–30 m).
`No initial gas cap is present. Well E-
`4 (Figure 13) began production in
`July 2000. When the first 4D repeat
`survey was shot in 2001, the pressure
`had depleted below the bubble point
`to approximately 200 bar. Figure 13a
`shows the change in impedance
`between the base and 2001 surveys.
`Blue is related to impedance de-
`crease. This can be explained by gas
`out of solution due to the pressure drop. This anomaly out-
`lines the whole segment, and it shows that there is no pres-
`sure barrier between the E-4 producer and the rest of the oil
`in the segment. Figure 13b shows the amount of gas in the
`new simulation model in 2001, which is in accordance with
`
`Figure 12. (a) 4D data 2001. (b) 4D difference 2001–2004. (c) 4D difference 2001–2004 with OWC
`interpretation. (d) 4D difference between base and 2004 with interpretation of gas cap expansion
`(yellow).
`
`the 2001 4D data.
`Well F-4 began water injection in the autumn of 2001, and
`this resulted in a general pressure increase in the G segment.
`APLT in E-4 in 2005 reported a pore pressure of 300 bar. Figure
`13c and Figure 13d show the change in acoustic impedance
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`from 2001 to 2003 and from 2001 to
`2004, respectively. A decrease in the
`impedance around F-4 and along the
`western main fault can be seen. This
`can most likely be explained by pres-
`sure increase due to injection, and it
`also shows that the most likely com-
`munication route from F-4 to E-4 is
`along the western main fault. Apres-
`sure barrier (C) can be interpreted
`from the 4D data. East of the pres-
`sure barrier, the opposite anomaly
`can be seen, related to gas going back
`to the oil due to pressure increase.
`This anomaly could also be ex-
`plained by water flooding, but this
`explanation can be ruled out because
`there was no water production in
`E–4 in 2003. The pressure increase in
`this area must be less than the pres-
`sure increase along the western main
`fault. The water broke through to
`the E-4 producer in November 2003,
`but the effect of the water seems to
`be overprinted by the effect of gas
`going back to the oil on the 4D data
`in Figure 13c and 13d. A seismic line
`through these anomalies is shown in
`Figure 14. The top and base of the
`reservoir are indicated in yellow.
`Notice the much better quality of the
`4D difference data between the Q
`data than between the base and 2001
`data. The location of the line is col-
`ored orange in Figure 13d. Figure
`14d shows the measurement of the
`time shift below the reservoir bet-
`ween base and 2001 (red line) and 2001 and 2004 (black line).
`A clear 2–3 ms time shift is seen from 2001 to 2004 in the area
`with the strong pressure increase anomaly. A small time shift
`can be seen in the area with the gas back to oil anomaly. This
`is in accordance with our rock modeling (Figure 15). The left
`plot in Figure 15 shows velocity versus pore pressure from
`core plug measurement. Data from injector F-4 indicate pres-
`sure around 400–450 bar near the well; pressure in 2001 was
`approximately 200 bar. This pore-pressure increase will,
`according to the left plot in Figure 15, create a velocity decrease
`of 300–400 m/s, which corresponds to a time shift change of
`2–3 ms in the 25–30 m reservoir. This time shift was also
`observed on the 4D data (Figure 14d).
`To better understand the 4D effect around well E-4 and
`the area east of barrier C, the Gassmann equations can be used
`to show the effect of gas going back to oil. According to Figure
`15, the effect of gas going back to oil should be smaller (but
`opposite) than the effect of the pressure increase from 200 bar
`to 300 bar. This is not observed on the 4D data in Figure 13c
`and 13d. Here the gas back to oil dominates pressure increase.
`An explanation is that the velocity versus pressure curve can
`be flatter for pressures less than 300–350 bar, while it can be
`steep for higher pressures. The break on the curve is most
`likely related to fracturing of the rock that takes place at
`higher pressure. The uncertainty of core plug measurements
`is well known. Based on our 4D observation and rock mod-
`eling, a better velocity versus pore-pressure curve is the black
`dotted curve in the left plot in Figure 15.
`Figure 13e shows the oil saturation from the old simula-
`tion model. Here, barrier C is not included, and the water
`
`Figure 13. (a) Change in acoustic impedance base–2001 from 4D data. Blue is decrease in impedance
`related to gas out of solution due to pressure drop. (b) Gas saturation in 2001 from new simulation
`model put on top of the map in (a). (c) Change in acoustic impedance 2001–2003. (d) Change in
`acoustic impedance 2001–2004. Blue is decrease in impedance related to pressure increase due to water
`injection. Red is increase in acoustic impedance related to gas going back to the oil phase. (e) Oil satura-
`tion in 2004 from old simulation model. (f) Oil saturation from new simulation model.
`
`Figure 14. (a) 2001 4D data. (b) Base–2001 4D difference data. (c)
`2001–2004 4D difference data. (d) Time shift in ms below reservoir for
`base–2001 (red curve) and 2001–2004 (black curve).
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`primary key to achieving this value is to acquire the 4D data
`as accurately as possible from vintage to vintage. Careful
`processing and tight integration of the subsurface disciplines
`in the Norne asset are also essential and very important for
`achieving these results.
`
`Suggested reading. “A new concept of acquiring highly repeat-
`able seismic monitoring data” by Eiken et al. (GEOPHYSICS, 2003).
`“Norne steered streamer 4D case study” by Goto et al. (EAGE
`2004 Extended Abstracts). “Repeatability issues of 3D VSP data”
`by Landrø (GEOPHYSICS, 1999). Insights and Method for 4D Reservoir
`Monitoring and Characterization by Calvert (SEG, 2005). “Towards
`an efficient workflow for modelling the seismic response from
`reservoir fluid simulator data” by Drottning et al. (SGBF/SPE
`workshop, Rio de Janeiro, 2004). “History matching using 4D
`seismic and pressure data on the Norne Field” by Lygren et al.
`(EAGE Extended Abstracts 2005). “A classification for the pres-
`sure-sensitivity properties of a sandstone rock frame” by MacBeth
`(GEOPHYSICS, 2004). “The reliability of core data as input to seis-
`mic reservoir monitoring studies” by Nes at al. (SPE 65180, 2002).
`TLE
`
`Acknowledgments: We thank the Norne asset team in Harstad, Norway,
`for cooperation and discussions. Thanks to the PL128 partners: Norsk
`Hydro, ENI Norge A/S, and Petoro. Also thanks to the 4D group and the
`seismic acquisition group in Statoil, and Ola Eiken, Lars Klefstad, Odd-
`Arve Solheim, Ola-Petter Munkvold, and Bjarte Myhren for discussions
`and help during acquisition. Thanks to WesternGeco for their work and
`particularly to Patrick Smith for assistance in processing the data. Gholam
`Reza Ahmadi programmed a seismic modeling program used in this work.
`
`Corresponding author: bosd@statoil.com
`
`Figure 15. (left) P-wave velocity versus pore pressure from laboratory
`core plug measurement. Blue points are measurements. Black dotted curve
`is updated based on the 4D observations. (right) P-wave velocity versus
`gas saturation.
`
`flows directly to the producer and floods the toe of E-4 first.
`In Figure 13f, barrier C is included in the simulation model.
`The water will now flow along the western main fault area
`and flood the heel and mid part of E-4 first. This new simu-
`lation model fits the 4D data better than the old model. PLT
`logging in E-4 was performed in 2005. Unfortunately, only
`the first half of the well was logged, and we were not able to
`check if the toe area was drained. However, this PLT logging
`showed that the first perforations in the heel area have high
`water cut, which fits the new simulation model.
`A sidetrack of the F-4 water injector updip to better direct
`the oil to the E-4 producer will probably be performed in 2007.
`
`Discussion and value of the 4D data. Based on the contri-
`bution of 4D data to drilled infill wells at Norne, the 4D value
`have been estimated at approximately US$240 million. The
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