Since the middle of the 1980s, 3D

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1 Time for change Recent advances in surface seismic methods have allowed geophysicists to contribute to the study of fluid movement in the reservoir. Time-lapse, or 4D, seismic pilot projects and small-scale surveys are proving that the method can help engineers understand their reservoirs by identifying bypassed oil or evaluating the quality of enhanced recovery methods such as waterflooding. A 4D seismic survey expands the geoscientist s understanding of fluid movement in the reservoir by filling in the gaps in what can be measured at the wells. This article, based on interviews with Roland Marschall and Mark Egan, presents a simplified introduction to 4D seismic monitoring and shows how a 4D survey in the Middle East tackled the challenges of assessing waterflood performance in a carbonate reservoir.

2 zz,, yy {{,, yy zz yy zz zz,, yy,, yy z zz {{ yy {{ yy {{,, yy zz ,,,,,, Walkaway 2D seismic VSP survey 3D seismic 4D seismic Figure 1.1 Developments in seismic technology since 1980 have changed the role of geophysics in the oil field. In the past the limited resolution possible with seismic surveys meant that geophysics was limited to assessing large structural features such as major faults and folds. Modern 3D techniques are much more sensitive and can be used to monitor very small changes in fluid distribution within a reservoir. These examples are typical of the technology available in selected years Since the middle of the 1980s, 3D seismic technology has progressed from providing accurate pictures of a reservoir s structure to defining its stratigraphic features (Figure 1.1). When these detailed seismic data are combined with well log, core and other petrophysical and production information they can be used for reservoir characterization. Just as 3D seismic has improved the industry s understanding of hydrocarbon storage, 4D (time-lapse) reservoir monitoring offers the potential for a better understanding of oil and gas recovery mechanisms. Seismic information, coupled with traditional reservoir monitoring and management, can help reservoir engineers to adapt their field development plans to fit the complexity of each reservoir. The ultimate aim is increased reserves which can be produced at lower cost. The 4D results disclosed by the industry to date clearly indicate the wide applicability of the technique to a range of environments and reservoir conditions. These 4D surveys had been conducted onshore, offshore, in clastic and carbonate reservoirs and in conjunction with a broad range of recovery mechanisms such as conventional waterfloods, steamfloods and firefloods, miscible solvent floods, and CO 2 and gas injection (see box: A fine result for Foinaven). Staging 3D seismic surveys over time to monitor a producing reservoir establishes the current position of fluids and allows geoscientists to make comparisons with past fluid distribution. The time-lapse method also identifies bypassed oil and hydraulic barriers within the reservoir and can help to predict premature water or gas breakthrough and so maximize reservoir productivity. Modern 4D seismic methods were first introduced to the oil field in the 1980s, designed to monitor enhanced oil recovery (EOR) processes such as steamflooding and in-situ combustion. The high temperatures encountered in these processes mean low P-wave velocity values. The progression of temperature and gas fronts away from injection wells was mapped using seismic amplitude difference sections seismic sections created by comparing the monitor survey image with the original survey image and plotting the differences. Cores were taken after the treatment to provide independent evidence on the extent of the flooding operations. These early studies established the basis of the 4D seismic monitoring technique that is used today. However, using 4D seismic for highresolution reservoir monitoring is a relatively new application of this technology, and the benefits of the monitoring method cannot be seen in a single short project. The nature of 4D seismic surveys means that interpreters must wait and see how useful the surveys have been. With a typical gap of six months to two years between an original survey and the first monitor survey, gathering data for a comparison of fluid movements is a long-term project. To detect fluid changes, differences in acoustic impedance, reflection amplitude or travel time of the seismic waves must be discernible above the data noise levels. The rock properties that influence seismic reflection response density and velocity must show clear variation with fluid content, pressure or temperature. The original and subsequent seismic surveys must have the same acquisition and processing to ensure that all observed differences can be interpreted as changes related to production. 6

3 A fine result for Foinaven In 1995 Geco-Prakla conducted a deep marine 4D survey of Foinaven Field in the Atlantic Ocean (Figure 1A.1), using sensors permanently embedded in the seabed (Figure 1A.2). The operation at Foinaven provided a major logistical challenge. The contract for the 4D survey was signed in April 1995 and Geco-Prakla engineers knew that the baseline survey would have to be conducted before production started early in This meant that 36 km of hydrophone cable had to be manufactured to a new design and permanently buried in the seabed by the middle of September when the weather was expected to deteriorate. With a very limited weather window in the North Atlantic, Geco-Prakla had to install the cables quickly and accurately. Overcoming strong currents, the installation was completed in just nine days from late August to early September, and the first monitor survey was conducted before the bad weather began. North Atlantic Foinaven Field Scotland Figure 1A.1 Foinaven Field, offshore UK Recording vessel Sensor cable 450 m, y,, yy, y z yy zz {{,,y 1.5 km Figure 1A.2 Once installed at Foinaven Field the receiver array was used as shown, with the recording vessel connected to the permanent array while the survey was conducted Source vessel,,, yy zz {{ 300 m 7

4 P-wave section S-wave section Figure 1.2 Detection of fluid changes in a reservoir requires geophysicists to compare the seismic response of shear (S) and compressional (P) waves. The P-wave data are sensitive to fluids but S-wave data are not. Where there are discrepancies between the two data sets they will be fluid effects. In this example one of the anomalies is a proven gas field and the other has yet to be drilled Shear sense Acquiring shear (S) wave seismic as a supplement to conventional compressional (P) wave seismic data helps geoscientists to distinguish between lithology (sand/shale) and pore fluid effects and underpins detailed reservoir characterization and monitoring. P waves are sensitive to variations in lithology, porosity and pore fluid. Interpreting P-wave anomalies without additional information can present problems in determining which of the parameters is varying. S waves, however, respond only to changes in lithology and porosity. Consequently, when both data sets are available for comparison, ambiguity can be reduced and the reliability of the interpretation is greatly improved (Figure 1.2). S-wave data also offer a number of additional advantages for reservoir characterization. For example, as shear waves are relatively unaffected by fluids they can be used to obtain structural information in areas where P waves do not produce coherent images, such as below the gas chimneys associated with some reservoirs. S waves can also help determine the density and orientation of natural fractures and help to assess the regional stress direction. When gas is present in a reservoir, S waves must be used to estimate gas saturation. High-quality data acquired using the techniques described above allow geophysicists to improve the correlation of log and core data to borehole seismic data (vertical seismic profiles, VSPs) and then to surface seismic results. Innovative software developed by Schlumberger Oilfield Services (Geco-Prakla) can compute and manipulate seismic attributes and use them to classify and map reservoir properties. This tool kit is now helping to reveal reservoir structure and properties far away from wells. The most important question in any 4D survey is: how are the fluids moving? By identifying changes in fluid distribution over time, geoscientists can gain a better understanding of reservoir compartmentalization (Figure 1.3) and specific production mechanisms. zzz zzz {{{ y z{ y y z {, An example from the Middle East Using seismic surveys to monitor the effectiveness of a water-injection program can help an operator to assess the value of that program and to ensure that the waterflood is not damaging the field. This example involves a 4D seismic survey in a major onshore carbonate reservoir in north Kuwait (Figure 1.4). The field is in slope facies carbonate rocks which can be described by a standard carbonate model. The reservoir, which can be subdivided into four distinct stratigraphic units, has a total thickness of around 90 m. Isolated fault compartment Figure 1.3 Monitoring of a field in production will help reservoir engineers to identify compartments within the field that are not being drained. In this example, the oil and gas in the small graben are isolated from the rest of the field and must be drained separately 8

5 9,, yy zz QQQQ QQQQ,, yy zz Era Cenozoic Mesozoic Jurassic Cretaceous Tertiary Palaeogene Neogene Paleocene Upper Lower Senonian Lower Lower Lower Lw Upp Upper Upp Upper Middle Middle Upp Eocene Oligocene Miocene Pliocene System Quarternary Eocene Pliocene Piacenzian Zanclean Messinian Tortonian Serravallian Langhian Burdigalian Aquitanian Chattian Rupelian Priabonian Bartonian Lutetian Ypresian Thanetian Danian Maastrichtian Campanian Santonian Coniacian Turonian Cenomanian Albian Aptian Barremian Hauterivian Valanginian Berriasian Tithonian Kimmeridgian Oxfordian Callovian Bathonian Bajocian Aalenian Toarcian Pliensbacian Sinemurian Lias Lower Dogger Middle (Malm) Upper Neocomian Lower Hettangian Series Stage Kuwait SW NE Oil reservoirs Dibdibba Formation Lower Fars Formation Ghar Formation Damman Formation Rus Formation Radhuma Formation Tayarat Formation Qurna Formation Sadi Formation Khasib Mutriba Mishrif Formation Rumaila Formation Marrat Formation Dharuma Formation Sargelu Formation Najmait Formation Gotnia Formation Burgan Formation Zubair Formation Ahmadi Formation Mauddud Formation Shuaiba Formation Ratawi Formation Minagish Formation Oolite member Hith member Wara Formation Hartha Formation Figure 1.4 Source rocks, reservoir rocks and stratigraphy of Kuwait. The sequence is dominated by thick limestone and marl units,, yy 0 50 km N IRAQ KUWAIT Ash-Shaham Ratqa Mutriba Bahrah Riqua Ahmadi Burgan Hout Khafji Dorra Rugei Minagish Dharif Magwa Abduliyah Wafra Fawaris Oil field Oil show Abdali Raudhatain Sabiriyah Medina SAUDI ARABIA PARTITIONED NEUTRAL ZONE ARABIAN GULF Umm Gudair

6 ,, yy {{{{{{ zzzzz,, yy {{{{{{ zzzzz,, yy zzzzz {{{{{{ Unconsolidated sandstone Consolidated sandstone Carbonate Gas Change detectable Light oil Moved fluid Medium oil Figure 1.5 Repeat 3D surveys can usually detect gas or light oil being replaced with water. The movement of heavier hydrocarbons in carbonates is more difficult to spot Heavy oil Change not detectable,, yy,, yy,, yy,, yy,, yy Injector Source lines Receiver lines 0.5 km Figure 1.6 Details of the monitor survey setup in this north Kuwait field The whole field was examined in the original 3D seismic survey and the decision was taken to perform a second, smaller, monitor survey across part of the field where a waterflood project was underway. The key objectives of the survey were to assess saturation changes and to evaluate the quality of the waterflood project. These results would be of great importance to reservoir engineers planning drilling patterns and horizontal wells. Many of the world s 4D seismic surveys have been conducted in clastic (low impedance) reservoirs where the changes in acoustic impedance caused by fluid changes are more obvious than in carbonate (high impedance) reservoirs (Figure 1.5). The survey would also indicate the value of 4D seismic monitoring methods in a carbonate reservoir. Method and results The monitor survey (actually two identical stationary patches) was conducted six months after the original 3D survey. It produced a quantified saturation map that showed the distribution of injected water and indicated how effective a particular fivespot pattern had been in pushing oil away from an injector well towards the producers (Figure 1.6). In this field water was injected at a single well located among four producers, but water injection was not carried out continuously throughout that six-month period between surveys, and the situation within the reservoir was complicated by gravity effects which caused water to move between individual layers within the reservoir. The acoustic impedance (AI) of a rock layer is the product of the velocity and the density. When the AI information is extracted from the seismic data it can be compared with log data from the wells. The AI value and, therefore, seismic response will change as fluid saturation within a layer changes. One of the most important checks to be made before conducting a monitor 3D survey is a comparison of anticipated noise levels (controlled by survey geometry and coverage) and the expected changes in seismic response that will result from the fluid changes. In this field, the noise level was estimated at a maximum of 2%, while the maximum change in acoustic impedance would be around 5%. The fluid-related changes would therefore be detectable, and the results from the second survey would be valid. Reservoir zones are layered and there are variations between these layers. Seismic studies also identify lateral variations (whether in porosity, permeability or structure) that have made water movement through the reservoir nonuniform. In a simple homogeneous reservoir the water would be expected to spread around the injector in a circular pattern which was broadly similar throughout the reservoir interval. Vertical and horizontal variations in the reservoir combine to complicate the distribution of injected fluid. 10

7 Injector Injector Figure 1.7 This saturation map (left) is derived from the 4D survey: the saturation contours (right) have been added manually. The area outside the 0 contour is the area of no change. The area within the 2 contour, centered on the injection well, is the zone of maximum water saturation. The nonsymmetrical distribution of injected water may indicate a structural control on water distribution. Crosshatching shows the area of minimum constant background nonrepeatable-noise-energy level Figure 1.7 shows the change in the acoustic impedance map derived from the 4D survey. The area outside the 0 contour is the zone of maximum oil saturation. The area inside the 2 contour is the zone of maximum water saturation with only residual oil. The crosshatched areas on the left of the figure are those where a proprietary s-analysis showed that the change in acoustic impedance was constant. This analysis confirmed that the nonrepeatable noise level was low and that injected water had not yet invaded these areas. These results are the product of an averaging-over-time (AOT) procedure which is part of the s-analysis. Saturation variations are extremely important for the reservoir engineer. The water injected during a waterflood project pushes oil out of the rock pores towards the producing wells (Figure 1.8). Assessing these subtle changes in fluid saturation using a 4D seismic method is not simple, but presents engineers with a picture of oil and water saturation variations across an entire field. a c b d Is it worth it? Using porosity and density information from well logs and cores, the geophysicist can calculate bulk density values in the reservoir for the range of plausible fluid saturation values. Similarly, using known compressibility values for the matrix, grains and fluids, and information about clay content in the pores, the geophysicist can employ a suitable petrophysical equation Injected water Carbonate grains Formation water Oil Figure 1.8 Water injected into a reservoir causes many subtle and complex changes in fluid saturation at the pore-size scale. As water is introduced (a) it begins to alter the distribution of pore fluids (b). If the waterflood proceeds as it should, oil will be pushed out of the pores (c) and injected water will fill the space previously occupied by formation water and oil (d). Understanding these subtle changes will help reservoir engineers to control reservoir development 11

8 Figure 1.9 Subtracting the monitor survey from the original survey accounts for the repeatable noise effects of porosity and lithology. However, the fluidrelated changes in the seismic signal may still be masked by the NRN component. Unfortunately, it is impossible to make completely error-free measurements, so this figure is an idealized representation zzzzzzz,, yy zzzzz, y {{{{{,, yy zz zzzzz, y {{{{{,, yy zz zzzzz, y {{{{{,, zz yy Original survey Original signal Repeatable noise Nonrepeatable noise Monitor survey = Monitor signal Repeatable noise Nonrepeatable noise Result Change in signal Repeatable noise? Nonrepeatable noise (such as the Biot Gassmann equation) to compute P- and S-wave velocities for the range of saturation values. Knowing the densities and velocities, the geophysicist can compute the acoustic impedance values for the various saturation scenarios. Using this numerical procedure, it is possible to model changes in saturation between virgin reservoir and flooded zone. How will these saturation variations change the velocity and density values for the reservoir rocks? And how will those changes alter the acoustic impedance? The geophysicist must determine whether or not the saturation-related changes will be detectable above the nonrepeatable noise (NRN) associated with the survey. What s that nonrepeatable noise? For monitoring purposes the same 3D geometry must be used for the original and the monitor surveys. In some cases, for example in older fields, the monitor survey may be more detailed than the original 3D survey. In this situation the monitor survey can be decimated to simulate the geometry of the initial survey and so allow meaningful comparisons. If the monitor survey could be conducted in exactly the same way as the original survey, then subtracting one from the other would eliminate the noise and the similarities between the two signals, leaving only the change in the signal. Surveys, however, cannot be identical. Small changes in physical conditions (humidity, temperature, etc) will alter the surveys. Cultural noise can also change between the original and monitor surveys: for example, in a 4D survey conducted over three years, open desert terrain might become an urban area covered with tarmac and concrete. In temperate climates seasonal variations are an issue with the presence of snow on the ground or surface water making a difference to the survey. In some projects a second survey can be recorded immediately after the original one is completed. There will be a difference, and this will be the NRN (Figure 1.9). There are two steps in the determination of NRN. Examining the original and monitor survey results from rock layers above the reservoir (where there is no change in fluid saturation) gives geophysicists a value for NRN; this information can be used to evaluate the changes in the reservoir that are due to changes in fluid saturation. To further complicate the situation, some seismic processing procedures, such as deconvolution, filter the data on the basis of what has been recorded. No two surveys can be truly identical, so no two deconvolutions will be exactly the same. If the noise level is different, the filter will change to compensate, even though the geophysicists are using the same parameters and algorithms to process the data. In this example, the geophysicists calculated a 3% change in P-wave velocity and a maximum 5% change in AI as a result of changing fluid content in the rocks. They then had to determine whether that change was larger than the NRN in the survey. Careful examination of reservoir parameters and the original survey indicated that at reservoir depths the average value for the NRN would be around 2%. This is less than the average fluid-related change in acoustic impedance: the monitor survey results should, therefore, be reliable. The NRN concept can be used to divide 3D surveys into those suitable only for structural purposes (high NRN) and those which can be used for fluid monitoring (low NRN). Assessment of NRN allows the geophysicist to derive the mean error for the difference in impedance. This powerful new technique, developed by Schlumberger Oilfield Services, helps to make 4D surveys much more accurate and reliable. 12

9 Levels of NRN can vary across the reservoir. These variations can be estimated and a map generated to show where high noise values will affect the quality of the 4D data. The reliability of the 4D method in any particular reservoir depends on the levels of NRN encountered. Access to high-quality data across the whole reservoir would be the ideal situation, but where this is not possible it would be useful to be able to discriminate good data from bad. To produce this map the geophysicist will define an area of confidence for changes to mapped areas within the reservoir. Areas showing minimum NRN values are areas of no change. Anything within the reservoir interval where this minimum NRN level has been exceeded has been affected by fluid replacement. If the NRN is low enough it may be possible to subdivide the reservoir into its component layers. Changes in the acoustic impedance are calculated at every point in the reservoir to give an indication of how saturation values are changing. Armed with these data the geophysicist can generate a map of fluid saturation. Comparing the map from the original survey with that produced on the monitor survey indicates changes in water saturation and the extent of fluid movement during the intervening six months. When the original and monitor surveys are set up differently, geophysicists can assess how much the NRN level has been reduced by the improved geometry of the monitor survey. This comparison gives a clear indication of the costs and benefits of noise reduction. The future The next stage in the program will have three main objectives. The first is to history-match the observed water distribution with the reservoir model and so predict future water movements within the reservoir. To do this, the reservoir model must be refined until it matches the observed water distribution revealed by the seismic-derived map. The second objective is to break the reservoir down into its four component layers and to assess the movement of injected water in each. Even the simple reservoir simulation models developed to date show that each level within this reservoir has different fluid flow parameters and water distributions. This detailed examination of the reservoir will only be possible where NRN levels are low. The map of water saturation distribution indicates that the reservoir is not homogeneous. The third objective in this waterflood project may be to identify permeability anisotropy or structural factors which control water distribution. After that the field managers may choose to extrapolate these results to large-scale prediction of future water distribution and oil production that might be achieved by waterflooding under these conditions. The acoustic impedance changes caused by fluid movements, and the associated changes in saturation, are greater in clastic reservoirs than in carbonate reservoirs. These subtle changes can present problems for a 4D seismic survey, but if the survey is well-designed and controlled, the technique can be successfully applied in the Middle East s carbonate reservoirs. Conclusion The difference between an original survey and subsequent surveys is the key to the 4D seismic technique. To ensure that the comparison is meaningful the survey team must be aware of a whole range of survey parameters such as levels of noise, signal repeatability, navigation and survey accuracy, resolution and detection limits. The value of the 4D seismic data and their contribution to reservoir monitoring depends on resolution and signal-to-noise ratio. These are, in turn, controlled by data acquisition and processing and by the specific geological environment for a specific reservoir. Factors which can affect the quality of a 4D survey include reservoir depth and complexity, overlying structures and near-surface conditions. Further refinements in hardware and processing will enhance the importance and value of 4D seismic methods for reservoir monitoring and development. The full potential of 4D seismic as a tool to assess past fluid movement and predict future movements is still some way off, but some of the early results have been encouraging. R Marschall (1997). 3D acquisition geometries: review and summary. Presented at SEG Summer Research Workshop, Vail Colorado, 3 8 August R Marschall (1997). 4D seismics. Proceedings of the 17th Mintrop-Seminar. Unikontakt, Kontaktstelle Universität/Wirtschaft der Ruhr-Universität Bocum, Germany R Marschall (1997). 3D acquisition of seismic data. Proceedings of the 17th Mintrop-Seminar. Unikontakt, Kontaktstelle Universität/Wirtschaft der Ruhr-Universität Bocum, Germany R Marschall (1998). North Kuwait 4D experiment. Geco- Prakla report for Kuwait Oil Company, Kuwait 13