`
`
`Ex. PGS 1065
`
`
`EX. PGS 1065
`
`
`
`
`
`

`

`
`
`
`
`SEG Technical Prcgram Expanded Abstracts 1997
`
`Table at rElements
`
`
`Next F'aber
`
`Eilalic-n I PDF I PDF wainlts [T9 KB]
`
`David E. Lumley, Ftcnald A- Behrens. and Ehijing 1I.I'I.I'ani;| {199?} Assessing the technical n'slr at a 4|] seismic brbject.
`
`SEE Technical Pro-gram Expanded Abstracts 1991'“: pp. 394-391
`dci: 10.11QWHBEE1ED
`
`Assessing the technical risk {if a 4D seismic prcject
`
`Technical Prcgram Chairpersdnts}: David E. Lumley. Renald A. Behrens.
`Ehijing Wang
`
`This Paper Appears in
`
`CHEW Petrbleum Tecnnelegy Be.
`
`Perrnalinlr: httbjrdxdbiergflllt 1 Eli]:r1 .1 8361 El]
`
`Title Infermatien
`
`
`
`SEG- Technical Pregrarn Expanded
`Abstracts 199T
`
`SEGEAE
`
`ISBN [print]: WEE-3312
`
`Ebwrignt Year: 199?
`
`Pages:
`
`Publisher: Sblcieh.r of Exploration
`Geephysicists
`
`
`
`EX. PGS 1065
`
`Ex. PGS 1065
`
`

`

`Assessing the Technical Risk of a 4D Seismic Project
`David E. Lumley*, Ronald A. Behrens & Zhijing Wang, Chevron Petroleum Technology Co.
`
`R C 4 . 2
`
`SUMMARY
`We have developed a “4D seismic technical risk
`spreadsheet” as a quantitative tool to help decide whether
`it is technically advisable to perform a time-lapse 4D
`seismic monitoring project for a specific reservoir and
`field site (Lumley et al., 1997). The spreadsheet lists the
`reservoir and seismic parameters that are vital to the
`technical success of any 4D project, and ranks each with a
`score range of 0 to 5.
`In order for a 4D project to be
`considered likely to succeed, the reservoir and seismic
`parameters must obtain a passing score of at least 60% for
`each of the reservoir and seismic subtotals.
`Field
`example values are given for Chevron 4D seismic projects
`in Indonesia, the Gulf of Mexico, West Africa and the
`North Sea.
`
`INTRODUCTION
`Over the past few years, Chevron has embarked on many
`4D seismic projects world-wide. To facilitate this activity,
`Chevron Petroleum Technology has a team of technical
`experts dedicated to researching, developing and
`optimizing the 4D seismic technique. At the initial stages
`of any 4D project, the following question is usually asked
`of us by our business-unit engineers and geoscientists: “we
`have a field which we are thinking about for 4D seismic
`reservoir monitoring, do you think it will work?‘.
`The
`answer to that question can be a complex mix of scattered
`responses from a diverse range of technical experts in
`reservoir engineering, petrophysics and seismology. A
`collection of such responses may appear to be a somewhat
`unsatisfyingly qualitative “yes, it should be great”, or
`“could be risky”, or “no, that will never fly”. Or even
`worse: “give us $100k to do a complete feasibility study
`and well get back to you in a few months.”
`
`We decided we needed an analysis tool that answered this
`question in a quick (one day) and quantitative (numerical
`score) manner, using a simple subset of the most
`important
`reservoir and seismic variables that have a
`first-order affect on a 4D seismic project.
`The result is
`our 4D technical risk spreadsheet. The following sections
`describe how to fill in the 4D risk spreadsheet and how to
`interpret the results. We believe this framework for 4D
`seismic risk analysis is unique in the industry and will be
`very useful to anyone planning their own 4D seismic
`project.
`
`STEP 1: COMPLETING THE 4D FACT SHEET
`The first step is to fill in a 4D Fact Sheet (not shown here
`due to space limitations). It consists of sections for values
`of “Reservoir”, “Rocks”, “Oil”, “Water”, “Gas”, “4D
`
`The entries represent the raw
`Fluids”, and “Seismic”.
`information at a reservoir and field site that is needed to
`determine the probability of success for a 4D seismic
`project. The following descriptions help clarify some of
`the entry data needed for the 4D Fact Sheet.
`
`depth:
`In general, shallow depths are more favorable for 4D
`seismic imaging of fluid flow effects. This is because
`seismic frequency content tends to be high, allowing high
`resolution images, and rocks tend to be unconsolidated and
`compressible,
`and sensitive to the fluid content. The
`Indonesia values are a good example of this effect.
`
`net pressure:
`Net pressure is defined as the difference between
`Generally,
`overburden pressure and pore pressure.
`reservoir rocks are more likely to show the effects of fluid
`saturation and pressure change when the net pressure is
`low.
`This occurs when the pore approaches the
`overburden pressure, as often occurs with the injection of
`gas, steam, water or C02, for example. The North Sea
`example (water injection followed by depletion) and the
`Indonesia example (steam injection) demonstrate this
`effect. We are finding that the effects of pressure during
`reservoir production are more seismically visible than
`previously thought (Lumley, 1995; Lumley et al., 1995).
`
`bubble point:
`Bubble point is the pressure, at a fixed temperature, at
`which dissolved gas first starts bubbling out of solution.
`Reservoirs that cross the bubble point in either direction,
`either by pressure depletion or fluid injection, can be
`useful in 4D seismic applications for mapping pressure
`and
`compartmentalization,
`fault sealing properties,
`hydrocarbon saturation fronts. The Indonesia example
`shows that the reservoir started at 10 psi below bubble
`point before steam injection, and then increased to as
`much as 240 psi above bubble point after steam injection.
`The initial gas in pore space dissolved after pressure
`injection, and this effect was easily mappable in the 4D
`seismic sections (Bee et al., 1994; Lumley et al., 1995).
`
`temperature:
`Generally, reservoir oils at a high temperature are more
`compressible than water and so offer a better chance of
`being monitored seismically. In the Indonesia example,
`the oil is initially so incompressible as to be considered a
`part of the rock matrix, but after heating, became more
`even compressible than water.
`
`Downloaded 08/27/14 to 173.226.64.254. Redistribution subject to SEG license or copyright; see Terms of Use at http://library.seg.org/
`
`

`

`Assessing the Technical Risk of a 4D Seismic Project
`
`unit thickness:
`Unit thickness is the thickness of the reservoir zone(s) to
`be monitored. Generally this thickness should be greater
`than half a seismic wavelength in order for fluid-flow
`changes to be vertically resolved. A seismic wavelength
`is defined as the average reservoir rock velocity divided by
`the dominant seismic frequency value.
`
`dry bulk modulus:
`The dry bulk modulus refers to core measurements made
`at non-saturated or gas-filled conditions. Rocks with a low
`dry bulk modulus are very compressible, and hence their
`compressibility at saturated conditions will be a strong
`function of the fluid type in pore space. This situation is
`typified by the unconsolidated rocks in the Indonesia and
`Gulf of Mexico examples.
`In contrast, rocks with a large
`dry bulk modulus are very incompressible, and their
`compressibility changes very little as a function of
`saturation conditions. This would be the case for the very
`deep consolidated rocks with high carbonate content in the
`North Sea example.
`
`porosity:
`Seismic waves average over large volumes of reservoir
`rock. Therefore, for subtle fluid changes to be detected
`seismically, a large volume of rock needs to undergo fluid
`replacement. This suggests that high porosity rocks are
`more favorable for 4D seismic.
`
`GOR:
`GOR is the solution gas-to-oil ratio. Oils with large GOR
`values tend to be very compressible and light, thus
`providing a good contrast in seismic properties to brine
`water. The Gulf of Mexico, West Africa and North Sea
`examples all show this effect.
`
`salinity:
`Seawater has a salinity of about 40,000 ppm. Reservoir
`water that is extremely salty, say near 200,000 ppm, can
`be considerably less compressible than seawater or typical
`oil.
`This extra “stiffness” of saline water can help
`seismically distinguish it from oil, as shown by the Gulf of
`Mexico and North Sea values.
`
`4D fluid saturation change:
`4D fluid saturation change is the difference in initial and
`final saturation values of the fluid to be monitored. For
`the West Africa example,
`an oil/water system is to be
`monitored. The initial oil saturation is 75% and the final
`swept saturation is 25%, resulting in a 50% change in
`fluid saturation conditions. In the Indonesia example,
`steam is the fluid component to be monitored. The initial
`fluid saturation is 90% and the final fluid saturation after
`steamflooding is 10%, resulting in an almost ideal 80%
`fluid saturation change.
`
`4D fluid compressibility contrast:
`This is the change in bulk modulus from fluid1 to fluid2:
`(Kf2 - Kf1)/(Kf1), where fluid1 is the initial fluid in pore
`
`space (say, oil), and fluid2 is the replacement fluid (say,
`water). Generally, the larger the fluid compressibility
`contrast the better chance of being able to seismically
`image the two fluids separately. The Indonesia example
`shows that the compressibility contrast between steam and
`oil/water is more than 1 ,OOO%! More typical values of
`125% are shown for the West Africa example of injected
`seawater displacing live oil.
`
`dominant seismic frequency:
`The higher the dominant frequency of seismic energy, the
`better the ability to resolve changes in the reservoir unit.
`The Indonesia example shows an exceptionally ideal case
`of 125 Hz dominant (250 Hz maximum) frequency
`content, obtained by buried dynamite shots and receivers
`for a very shallow reservoir target. The Gulf of Mexico,
`West Africa and North Sea examples show more typical
`values for conventional seismic recording.
`
`average resolution:
`The average resolution in a seismic image is defined as a
`quarter of a seismic wavelength. A seismic wavelength is
`defined as the average reservoir rock velocity divided by
`the dominant seismic frequency value. Optimal seismic
`resolution requires low velocity (unconsolidated) rocks
`and very high frequency seismic energy.
`
`image quality:
`Image quality refers to general signal-to-noise (s/n)
`quality, the ability to image reservoir reflections, and
`overall image clarity. For most 4D seismic applications,
`the reservoir should be well imaged, and amplitude
`variations along the reservoir reflection should be accurate
`and meaningful. All of the examples have this quality,
`except the North Sea example in which the reservoir
`reflection in any given survey is weakly visible at or near
`the noise level.
`
`repeatability:
`Optimal 4D seismic imaging requires seismic acquisition
`and processing to be “repeatable” from survey to survey,
`so that differences between two time-lapse seismic images
`can be trusted as real changes due to reservoir production,
`not acquisition or processing artifacts.
`Enhanced
`includes using
`the same
`acquisition
`repeatability
`acquisition method for each survey (say, marine streamer
`both times), accurate source and receiver positioning
`(perhaps even using a permanent installation), shooting
`seismic lines in the same direction for each survey, and
`using the same bin spacing and offset/azimuth
`distribution.
`The Indonesia example has all of these
`qualities. The North Sea example was shot in different
`directions with some question of positioning accuracy. In
`many cases, we have fields that were originally shot as
`streamer surveys before production, but now have so many
`added platforms and facilities that all future surveys will
`have to be ocean bottom cable, hence losing some
`potential acquisition repeatability.
`
`Downloaded 08/27/14 to 173.226.64.254. Redistribution subject to SEG license or copyright; see Terms of Use at http://library.seg.org/
`
`

`

`Assessing the Technical Risk of a 4D Seismic Project
`
`Using the 4D Technical Risk Spreadsheet, we can assess
`the risk of doing a 4D project at a given field. There are
`reservoir
`three major components of this analysis:
`conditions, time-lapse seismic conditions, and combined
`total score. We will discuss how to use the spreadsheet
`results at the presentation.
`
`CONCLUSION
`We present a method for assessing the technical risk of a
`4D seismic reservoir monitoring project in any production,
`reservoir and field conditions. The 4D technical risk
`spreadsheet is quick in that it can be filled out in one day
`or so, is first-order accurate in that is uses the most critical
`subset of 4D seismic parameters, and quantitative in that
`numerical scores are assigned to each parameter based on
`our experience with numerous 4D seismic projects. It is
`very useful for designing a given 4D project, and
`comparing its risk with other 4D projects world-wide that
`have been similarly quantified and archived. If the risk
`assessment shows that a given reservoir may be a good
`candidate for a 4D project, the spreadsheet can highlight
`areas for further follow-up work in a more complete
`feasibility study.
`
`ACKNOWLEDGMENTS
`We would like to thank Chevron Petroleum Technology
`Co. for allowing us to publish this work.
`
`REFERENCES
`Bee, M. F., Jenkins, S. D., Lyle, J. H., and Murhanto, E.,
`1994, A powerful new technology for monitoring steam
`movements in Duri Field, Central Sumatra: 23rd Annual
`Conv., Proceedings, Indonesian Petrol. Assoc.
`
`Lumley, D. E., Behrens, R. A., Wang, Z., 1997a,
`Assessing the technical risk of a 4D seismic project: The
`Leading Edge, in review.
`
`Lumley, D. E., 1995, Seismic time-lapse monitoring of
`subsurface fluid flow: Ph.D. Thesis, Stanford University.
`
`Lumley, D. E., Bee, M., Jenkins, S., and Wang, Z., 1995,
`4-D seismic monitoring of an active steamflood: 65th
`Annual Intemat. Mtg., Soc. Expl. Geophys., Expanded
`Abstracts, 95, 203-206.
`
`fluid contact visibility:
`This refers to the ability to clearly see fluid contacts in
`seismic over wide areas. This can be an important factor
`for 4D seismic, since monitoring fluid movement may
`simply reduce to mapping the new fluid contacts in each
`successive seismic survey. All the examples in Table 1
`exhibit good seismic fluid contact visibility, except the
`North Sea example due to the deep consolidated rock
`properties.
`
`traveltime change:
`Traveltime change is predicted for a reservoir rock by
`changing all anticipated saturation,
`pressure and
`temperature conditions from monitor time 1 to time 2,
`including all reservoir production effects. Most reservoirs
`show almost no traveltime change during reservoir
`production.
`Instead, fluid changes show up as amplitude
`changes along stationary reflection events. An exception
`to this is the Indonesia steamflood example, and to a lesser
`extent the West Africa example in which gascaps have
`been produced (“blown down”) from various reservoirs in
`between seismic surveys. A good rule of thumb for
`seismic detection is that traveltime changes between
`surveys should be greater than four time samples.
`
`impedance change:
`Impedance change is predicted for a reservoir rock by
`changing all anticipated
`saturation,
`pressure and
`temperature conditions from monitor time 1 to time 2,
`including all reservoir production effects.
`Seismic
`reflection amplitude is proportional to half the impedance
`change. Most reservoirs with unconsolidated rocks, brine
`and high-GOR oil, and depths less than 10,000 ft. show
`amplitude changes due to fluid or pressure change during
`production. A good rule of thumb for seismic detection is
`that impedance changes between surveys should be greater
`than 4%. Unconsolidated sands and live oil in the Gulf of
`Mexico generally exceed this value. West Africa rocks
`and fluids tend to give slightly smaller amplitude changes.
`Deep, consolidated, high-carbonate content rocks in the
`North Sea can show significantly smaller impedance
`changes.
`
`REMAINING STEPS
`Once the Fact Sheet has been completed, we gather a
`concise set of reservoir and seismic variables, and assign
`them each scores on a O-5 scale to give a quantitative risk
`assessment. At the presentation, we will show explicitly
`how we assign scores to each variable (space does not
`allow this here).
`These “scores” are based on our
`experience evaluating numerous 4D seismic projects in a
`variety of production scenarios, and reservoir and field
`conditions.
`Once the critical reservoir and seismic
`variables have been scored, they can be entered into the
`4D Technical Risk Spreadsheet. An example is shown in
`Table 1.
`This spreadsheet compresses the 4D seismic
`technical risk assessment to five reservoir variables and
`four seismic variables.
`
`Downloaded 08/27/14 to 173.226.64.254. Redistribution subject to SEG license or copyright; see Terms of Use at http://library.seg.org/
`
`

`

`Assessing the Technical Risk of a 4D Seismic Project
`
`Table 3: 4D Technical Risk Spreadsheet:
`
`897
`
`Downloaded 08/27/14 to 173.226.64.254. Redistribution subject to SEG license or copyright; see Terms of Use at http://library.seg.org/
`
`

`

`This article has been cited by:
`
`1. Alireza Shahin, Paul L. Stoffa, Robert H. Tatham, Diana SavaMulticomponent seismic time‐lapse cross‐plot and its applications
`1227-1231. [Abstract] [References] [PDF] [PDF w/Links] [Supplemental Material]
`
`Downloaded 08/27/14 to 173.226.64.254. Redistribution subject to SEG license or copyright; see Terms of Use at http://library.seg.org/
`
`