special topic
first break volume 31, October 2013
Data Processing
Value creation by a long-term time-lapse seismic
processing approach on the Heidrun field
Daniel Fischer,1 Nils Sørenes,1 Emanuel Teichmann,1 Hanna Blekastad,1 Anita S. Moen,1 Ivar
H. Sollie1 and Patrick Smith2* show the value created by time-lapse seismic processing on the
Heidrun field and how Statoil has used the technique to cut the timeframe on its 4D seismic.
S
tatoil has, over the past 15 years, routinely used timelapse (4D) seismic surveys to help maximize recovery
and production efficiency of its hydrocarbon reserves.
During this time the company has built an extensive
portfolio of fields that are covered by multiple vintages of
time-lapse seismic data (Figure 1), and a high level of activity
is expected to continue for the foreseeable future.
Seismic data from the time-lapse projects is integrated
into routine reservoir management processes and tends to be
used continuously throughout the life of a field. Reservoir
engineers therefore need the information from new monitor
surveys as soon as possible after data acquisition. However,
the conventional approach to time-lapse seismic processing
involves co-processing of data from all the available surveys – a task that becomes progressively more resource-intensive
and time-consuming as the number of vintages increases.
Lengthy processing and analysis can result in important
reservoir decisions having to be made before the full
information from a new monitor survey becomes available, reducing the value of the newly acquired data. While
fast-track products using a simplified flow are sometimes
useful, they usually provide less reliable information. Statoil
is mitigating these challenges by using long-term contracts
for time-lapse seismic data processing. This article describes
this strategy and illustrates it by reference to the time-lapse
seismic campaign on the Heidrun field, offshore Norway.
Figure 1 The Statoil portfolio of multi-vintage time-lapse seismic monitoring campaigns.
Statoil ASA.
WesternGeco.
*
Corresponding author, E-mail: [email protected]
1
2
© 2013 EAGE www.firstbreak.org
93
special topic
first break volume 31, October 2013
Data Processing
Processing challenges
Time-lapse seismic data processing is demanding. The
acquired datasets contain inherent variability that can
obscure the desired time-lapse signal. Compensating this variability to the necessary degree of accuracy while preserving
genuine changes between datasets can be time-consuming,
and processing turnarounds of up to six months after completion of data acquisition are commonplace.
A particular time-lapse seismic processing flow applied to
a new monitor survey may be incompatible with the results
produced on previous vintages if hardware and/or software
versions have changed in the interim. This is one reason
why, when a new survey is acquired, it has been common
practice to reprocess all available vintages in order to accurately estimate and compensate variability in a manner that
ensures consistency between the different datasets. This adds
additional cost requiring the operator to divert resources into
activities such as evaluation of the new results and updating
interpretations. It also increases the number of processed
cubes that must be stored and kept track of.
Figure 2 shows the number of datasets generated by a
multi-year time-lapse processing campaign on a Norwegian
North Sea field. The baseline survey was acquired in 1993
and the first monitor survey in 2005. The two surveys were
co-processed, generating about eight ‘prime’ datasets (i.e.,
those created by the seismic processing contractor), and four
4D datasets (i.e., those created during interpretation). A new
monitor survey was acquired in 2007, and all three surveys
were reprocessed, generating some 38 datasets. Additional
monitor surveys were acquired in 2009 and 2011, with all
surveys being reprocessed at each acquisition. The 2011
processing created more than 70 seismic cubes, all of which
required quality control (QC) processes and evaluation. As
shown in the white bars in Figure 2, it was predicted that
continuation of this approach would result in the generation
of almost 100 cubes in 2013 and 120 in 2015. Instead, a
long term contract was awarded in 2011 under which all
of the existing datasets were co-processed, and then a new
approach was adopted for processing subsequent monitor
surveys that would result in the creation of only about 40
datasets at each new acquisition.
An alternative processing strategy
Statoil is addressing the challenges described above by
implementing long-term time-lapse seismic data-processing
contracts that incorporate the following features: Firstly,
identical processing flows are used from one vintage to the
next. The flows are designed such that the new monitor
survey can be processed independently of the previous surveys. Hardware and software changes between vintages are
addressed by regression testing (described below).
Secondly, testing to improve the data processing flow,
and any necessary reprocessing, is performed in the periods
between acquisition of monitor surveys so that the new flow
and reprocessed data are available and interpreted by the
time of the next acquisition.
Thirdly, the long-term nature of the contracts enables the
data processing contractor to maintain, in partnership with
Statoil, valuable knowledge and experience of the datasets
from one survey to the next.
These concepts are probably familiar to those involved in
the processing of time-lapse seismic data from permanently
emplaced systems (e.g., Van Gestel et al., 2008). We are now
essentially applying an equivalent strategy to bring marine
streamer time-lapse data processing turnarounds down to a
similar order of magnitude to those achieved with permanent
systems.
Use of the same acquisition contractor and identical
configurations for each survey simplifies the processing by
eliminating processing steps required to compensate differences in acquisition. While it is not obligatory to use the same
contractor for acquisition and processing, this approach can
Figure 2 The number of datasets generated by a
multi-year time-lapse processing campaign on a
field in the Norwegian North Sea. The white bars
indicate the predicted number of 3D cubes that
would have been generated in 2013 and 2015 if
the alternative processing strategy had not been
adopted.
94
www.firstbreak.org © 2013 EAGE
first break volume 31, October 2013
special topic
Data Processing
Figure 3 Inline from a time-lapse seismic difference
cube between the baseline and monitor survey
created during acquisition of the monitor survey.
Figure 4 Schematic flow chart showing how sailline by sail-line time shifts can be derived without
co-processing all available time-lapse vintages.
provide additional benefits for turnaround and onboard quality control in the following ways: Firstly, onboard processing
(OBP) of the first acquired seismic lines through the early
stages of the time-lapse seismic processing flow enables highquality time-lapse comparisons with the existing data, helping
to ensure at an early stage that the acquisition and processing
are truly identical to the previous datasets.
Secondly, a high quality 3D stack cube can be built as the
survey progresses so that time-lapse QC can be performed at
intervals during acquisition (Figure 3). Acceptance criteria for
the acquired lines can then be based on true time-lapse seismic
comparisons (Osdal and Alsos, 2010), and strategies put in
place at an early stage to address any problems encountered.
Thirdly, a significant part of the processing flow and QC
can be performed on the seismic vessel during acquisition,
with the partially processed data being shipped to the data
processing centre for completion. This can substantially
reduce data processing turnaround times. Typically, processing steps performed on the vessel are applied to sail-line
© 2013 EAGE www.firstbreak.org
organised data, although strategies exist for performing 3D
demultiple and imaging where necessary.
Data perturbations for the newly acquired survey are
corrected by referring to the previously processed datasets.
Figure 4 shows schematically how this may be done for the
derivation of sail-line by sail-line time shifts. Initially, timing
measurements from all available surveys are passed to a
routine that simultaneously estimates sail-line by sail-line time
shifts for each survey. These are applied to the datasets, which
are then combined to create a reference cube. Each sail-line
of each survey is then compared with the reference cube to
re-derive the timing corrections, which should be essentially
the same as those originally estimated. The reference cube is
then archived and used to derive sail-line by sail-line time shifts
for subsequent surveys. Analogous approaches may be used
for amplitude corrections and other perturbations. Reference
datasets may also be created for time-lapse binning. The results
will not be identical to a simultaneous time-lapse binning of
all surveys, but, in practice, the differences are usually minor.
95
special topic
first break volume 31, October 2013
Data Processing
If the hardware and software systems are not frozen
between acquisitions, regression testing is used to demonstrate the compatibility of the current configuration with
those used previously. This involves the archiving of flows
and example input and output datasets for every step in
the seismic processing sequence. A few months before the
next acquisition, the processing flows are applied to the
archived input data using the current hardware and software
versions. The new outputs are compared with the previous
ones by visual inspection of differences and by computation
of NRMS difference attributes (Kragh and Christie 2001).
If the NRMS difference exceeds a pre-defined threshold,
remedial action is taken, usually by reverting to a previous
version of the algorithm responsible for the differences. On
rare occasions this is not feasible, and reprocessing of the
older surveys from a certain point in the flow is required.
Early identification of the issue enables mitigation without
delay to the project.
Application to the Heidrun time-lapse
seismic campaign
Heidrun is an oil and gas field in the Norwegian Sea on the
southernmost part of the Nordland Ridge (Figure 5). There
are three main reservoirs: the Fangst Group and the Tilje
and Åre Formations, with the Fangst Group being subdivided into the Garn and Ile Formations. The reservoirs are
spread out at depths ranging from around 2100 to 3400 m.
Expected stock tank oil initially in place (STOIIP) is about
432 x 106 Sm3 of oil, and original gas in place (OGIP) is
about 88 x 109 Sm3. Production started in 1995 and, by
early 2012, about 139.5 x 106 Sm3 of oil and 14 x 109 Sm3
of gas had been produced. The field is produced from a single platform located approximately in the centre of the field,
connected to five subsea templates.
The baseline time-lapse seismic dataset for the Heidrun
field comprises a merge of two 3D surveys, one acquired
in 1986 covering the area south-west of the platform, and
one from 1991 covering the area to the north-east. Monitor
surveys have been acquired by WesternGeco in 2001 and
2004 (covering the south-west area) and in 2006, 2008
and 2011 (covering the entire field). Undershooting of the
platform took place in 2008 and 2011. All monitor surveys
were identically parameterized.
Table 1 shows the time-lapse processing campaigns in
the Heidrun field. In 2001 the first monitor survey was
processed in parallel with the 1986 baseline, with the moni-
Figure 5 Location and stratigraphy of the Heidrun
field.
96
www.firstbreak.org © 2013 EAGE
first break volume 31, October 2013
special topic
Data Processing
Table 1 Time-lapse processing campaigns in the Heidrun field.
tor being downgraded to match the poorer quality of the
baseline survey. In 2004 all three surveys were reprocessed
in order to take advantage of the high-quality comparisons
available between the 2001 and 2004 surveys. The baseline
survey was successfully upgraded to match the bandwidth of
the newer datasets, although, as expected, the general data
quality of the baseline was worse than that of the newer
surveys.
In 2006 a subset of the 2006 survey, covering the
same area as the earlier monitor surveys, was processed
through the 2004 processing flow and delivered six weeks
after completion of acquisition. The full survey area of all
surveys was then processed through a new flow, taking
advantage of newer technology and spending considerable time trying to address the limitations of the baseline
surveys. In 2008 the entire 2008 monitor survey was
processed through the existing flow and delivered in eight
weeks. In 2010 the processing flow was revised to include
3D SRME (Dragoset et al., 2008) and further improve the
baseline survey. This delivered substantial improvements in
data quality, but took some time to perform. In 2011 the
monitor survey was processed through the 2010 flow and
delivered in 9 1/2 weeks.
In 2011 the formal long-term contract on Heidrun
began and the obvious benefits of the previous continuity
of processing were one of the driving forces behind this
strategy. As the same contractor was acquiring and process-
ing the data, OBP was used to further improve turnaround.
Figure 6 shows the timeline of the 2011 monitor survey.
Prior to acquisition, the seismic data processing centre created the necessary OBP and onshore processing flows and
performed regression testing. The flows were transferred
to the vessel, together with all required datasets, such as
velocity files and seismic reference cubes. A 3D stack was
created from the first line acquired and differenced with
an equivalent 3D stack for the 2008 survey. No obvious
problems were seen. Each acquired line was processed,
during acquisition, through navigation-seismic merge, QC,
noise attenuation and signal processing, with a 3D QC stack
volume being created progressively throughout acquisition.
4D QC of the onboard 3D stack volume against that of
the 2008 survey highlighted a small consistent phase difference of about minus 6 degrees between the 2008 and 2011
surveys, as shown in Figure 7. This turned out to be due
to the 2011 processing flow using a version of the acquisition filter that included the hydrophone impulse response,
whereas the 2008 flow had used a filter that did not include
the hydrophone response. Early identification of this subtle
error enabled correction without delay to the project.
The Statoil line acceptance criteria included evaluation
of source and receiver repetition accuracy versus the 2008
pre-plot, and an evaluation of the likely impact of acquisition issues on the seismic data processing. For example,
strict noise specs were imposed to avoid further testing of
the processing flow, and out-of-spec lines were reshot in
their entirety to avoid complicating the processing.
Due to other activities in the area, the seismic acquisition could not be completed as planned and the vessel
moved to another project before returning later in the year
to complete the survey. The remainder of the processed
data and 3D stack cube were transferred onshore, with a
full 4D QC being available within two days of data receipt.
Subsequent processing took 9 1/2 weeks to complete. The
delay in acquisition put at risk the original project plan, but
the rapid data processing turnaround ensured that the final
4D data was still available in time for the planned reservoir
interventions.
Figure 6 Timeline of the 2011 Heidrun time-lapse
seismic monitor survey.
© 2013 EAGE www.firstbreak.org
97
special topic
first break volume 31, October 2013
Data Processing
The upper part of Figure 8 lists average NRMS difference values for three different areas of the survey, as shown
colour-coded on the map. The NRMS difference values for
the 2006–2008 comparison are essentially identical to those
of the 2008–2011 comparison, even though, as described
above, the 2006 and 2008 surveys were co-processed,
whereas the 2011 dataset was processed in isolation. The
level of 4D noise on the time-lapse difference comparisons
in the lower part of Figure 8 are very similar between the
2006–2008 and 2008–2011 comparisons, and the waterfront movement is clearly visible in both cases. We conclude
from this and other examples that the long term strategy is
delivering data of consistent quality.
Impact of the 2011 Heidrun time-lapse seismic
monitor survey
The 2011 Heidrun monitor survey data had an immedi-
ate impact on the planning of intervention operations for
oil producer well A-44_A. The Ile Formation in this well
had been plugged-off in December 2007 due to increased
water production. The first panel of Figure 9 shows the
change in acoustic impedance on inverted data from 2004
to 2006. Water has moved northwards from a down-flank
water injector up to A-44_A, explaining the increased water
production. The second panel shows additional minor water
movement from the south between 2006 and 2008. Also,
a clear waterfront is seen coming from the west due to oil
production farther north. However, the area around Well
A-44_A, and to the north east, is largely unchanged. This
suggested that reopening the well in a different zone of the
Ile Formation might enable production of the remaining oil.
The first attempt at well intervention was unsuccessful and
planning for a second attempt was underway in the autumn
of 2011, incorporating information from the new 4D moniFigure 7 Phase difference between the 2011
onboard 3D QC stack and the earlier stack from
the 2008 survey.
Figure 8 Examples of time-lapse data quality for
the 2006–2008 and 2008–2011 comparisons.
98
www.firstbreak.org © 2013 EAGE
special topic
first break volume 31, October 2013
Data Processing
Figure 9 Time-lapse seismic data examples at well A-44_A.
tor survey. The 2008–2011 amplitude difference (panel C of
Figure 9) shows that the waterfront had now passed the well,
making the planned intervention unnecessary. This saved
around NOK 15–20 million (€2–2.5 million) and also freed
up the well slot for sidetracking to other targets.
The 2011 data was inverted to acoustic impedance
immediately after receipt, and both the amplitude and
acoustic impedance datasets were used in a number of ongoing well planning projects. The rapid delivery of the 2011
monitor survey ensured that the data represented an accurate
snapshot of current reservoir conditions.
Acknowledgements
The authors would like to thank the Statoil Heidrun
PTC asset for permission to publish this article and the
WesternGeco processing team, particularly Anna Smith and
Aleksandra Handzlik, for their efforts to ensure the success
of the 2011 monitor survey. We would also like to thank the
partners ConocoPhillips Skandinavia, Eni Norge and Petoro
for allowing publication of this work.
References
Dragoset, B., Moore, I., Yu M. and Zhao, W. [2008] 3D general surface
multiple prediction: An algorithm for all surveys. 78th SEG Annual
Conclusions
The use of long-term seismic processing contracts can reliably and consistently deliver high-quality time-lapse seismic
results in short timeframes. Further time savings can be
attained by using the same contractor for acquisition and
processing where possible. Reduced turnaround can have
significant economic impact in terms of both efficiency and
optimal use of the data. These concepts are being used by
Statoil on a number of North Sea fields, and their use is
expected to increase in the future.
© 2013 EAGE www.firstbreak.org
International Meeting, Expanded Abstracts, 27, 1, 2425–2430.
Kragh, E. and Christie, P. [2001] Seismic Repeatability, Normalized RMS
and Predictability. 71st SEG Annual Meeting, Expanded Abstracts,
20, 1, 1656–1659.
Osdal, B. and Alsos, T. [2010] Norne 4D and Reservoir Management
– The Keys to Success. 72nd EAGE Conference & Exhibition,
Expanded Abstracts, L012.
Van Gestel, J.P., Kommedal, J.H., Barkved, O.I., Mundal, I., Bakke, R.
and Best, K.D. [2008] Continuous seismic surveillance of Valhall
Field. The Leading Edge, 27, 1616–1621.
99