INTRODUCTION TO TIME-LAPSE SEISMIC IN RESERVOIR MONITORING

Reservoir production inevitably causes changes to a number of reservoir parameters and flow characteristics, including fluid type, pressure, temperature, porosity, permeability and fluid level. In some reservoirs, these changes may be characterized by a distinct change in seismic response.

By measuring and comparing seismic attributes in a producing reservoir over time, it may be possible to detect differences in seismic response that reflect production-related changes to fluid contacts and rock properties. Such time-lapse monitoring is used to optimize reservoir production by:

tracking the movement of oil, gas, and water through the reservoir,

identifying flow patterns and flow barriers,

monitoring the evolution of gas caps,

detecting water encroachment, and

identifying pockets of bypassed pay.

This type of time-lapse monitoring, commonly known as 4-D Seismic, is intended to highlight the differences between successive vintages of 3-D seismic surveys that are caused by changes in reservoir properties due to production. Figure   1 (Changes caused by production as fluid contacts move over time, courtesy of Geco-Prakla.) shows how seismic can be used to detect fluid movement caused by production.

Figure 1

The upper half of the Figure shows a reservoir containing oil (in green), and the subsequent encroachment by water (in blue) as the oil is produced. The lower half of the Figure shows

synthetic seismic sections developed before and after production. The base survey was run prior to production, and shows continuous amplitudes above the 1.2-second interval. The monitor survey was run after production, and shows decreased amplitudes between shotpoints 40 and 50. The difference between the two sections is shown in the right-hand panel, and was created by subtracting the base survey from the monitor survey. The differencing technique accentuates changes within the reservoir.

Ideally, each survey should be acquired and processed so that any changes between volumes of survey data are related to reservoir production, rather than differences in acquisition geometry or processing methods. However, exact repeatability between surveys is rarely possible. The acquisition phase of any new survey should utilize state of the art technology and ensure that acquisition parameters are optimal for the problem being addressed. Any new additional acquisition program should be designed so that subsets of the new data are comparable with existing data. In processing, the treatment of each data set should be designed to minimize non-reservoir-related variations and highlight those caused by the production process.

Changes in seismic attributes are highly dependent upon the unique characteristics of each reservoir. For example, lithology, depth, temperature, pressure, saturation, and fluid phase are among the factors that affect the seismic response to changing reservoir conditions. Some reservoirs simply do not lend themselves to such time-lapse monitoring. It is therefore necessary to model the reservoir before starting a 4-D project in order to determine its feasibility. (Figure   2 -Flowchart for integrated analysis; courtesy Schlumberger Oilfield Review).

Figure 2

The results of the modeling study will help to determine whether a seismic survey will detect changes within the reservoir, and it will identify which changes the seismic response will

be sensitive to, as well as determine the characteristics of the seismic response. It is important to ascertain, in advance, the changes that will show up between different vintages of 3-D seismic, and to know what those changes will look like.

Because repeatability may be critical to the success of a time-lapse survey, the initial survey should be designed with future surveys in mind. In certain onshore cases, operators have buried semi-permanent geophone arrays and repeated the same shotpoints. Offshore, they have buried ocean-bottom cables to maintain the same acquisition geometry from one survey to the next. Operators should consult their seismic acquisition and processing companies for help in designing a repeatable survey from the outset.

This overview briefly discusses the reservoir characteristics that affect seismic response, as well as the feasibility studies and considerations that are crucial to the success of any 4-D project. It also includes a short case history.

 

 

PROCESS SUMMARYThe 4-D seismic process begins with a comprehensive reservoir study to determine how production will affect the reservoir, and to model the seismic response to those changes. If the proposed 4-D project is technologically and economically feasible, a plan should be made to detail the optimal acquisition geometry and processing requirements needed to resolve reservoir changes.

A series of repeatable 3-D surveys is acquired over time, and processed in an identical fashion. By highlighting the differences between each vintage of survey, the changes can be tracked to provide information that will help to optimize production.

The overall process is summarized by Key, Pederson, and Smith (1998):

1. develop a detailed reservoir description,2. identify physical changes in the reservoir caused by production,3. determine which changes in seismic velocity or density are associated with reservoir changes,4. create a model to predict changes in seismic response,5. acquire and process repeat 3-D seismic data, and6. interpret changes in 3-D images in terms of fluid/pressure/temperature distributions.

 

 

 

 

FACTORS CONTROLLING PROJECT FEASIBILITY Not all reservoirs are good candidates for seismic time-lapse monitoring. According to Key, Pederson, and Smith (1998), a successful 4-D program should meet the following criteria:

An observable change in seismic velocity or density must be associated with some significant aspect of the production process. Simulations and modeling must be able to link important lithological variations to seismic observations.

Simulations and modeling must be able to link the processes taking place within the reservoir to seismic observations. Seismic acquisition and processing techniques must be sensitive enough to allow measurement of the reservoir changes taking place.

Each reservoir has unique characteristics that directly impact seismic response. Figure   1 (Seismic response as a function of fluid and formation type; courtesy of Geco-Prakla) illustrates in a general way, how formation and fluid type affect the seismic capability to image fluid movement over time.

Figure 1

In this figure, conditions in which seismic response should be able to track fluid movement range from good (green) for gas, to poor (red) for heavy oil in carbonate formations.

The success of any 4-D monitoring program hinges upon a number of important variables, as described by Lumley, Behrens, and Wang (1997), and Wang and Nur (1992). These variables can be grouped into three broad categories:

Reservoir characteristics

Fluid characteristics

Seismic characteristics

Each of these categories is explained below. While the following principles are discussed in broad terms, it should be recognized that the tolerances required to detect changing conditions are continually improving with new developments in seismic technology.

RESERVOIR CHARACTERISTICSRock Compressibility -The reservoir rock should be sufficiently compressible for fluid or pressure changes to be seen seismically. A dry rock bulk modulus test should be performed on core samples to determine the compressibility of the reservoir rock. Low dry bulk modulus signifies that the rock is very compressible; the compressibility at saturated conditions depends on the fluid type in the pore space. A high dry bulk modulus means that the rock is very incompressible, so that changes in saturation have less effect on compressibility.

Porosity -Reservoir fluids must be displaced in sufficient volumes of rock to be observed seismically. Reservoir porosity needs to be high enough to permit the necessary displacement of fluids.

Depth -Shallow depths provide the best conditions for 4-D seismic monitoring of fluid flow effects. This is because seismic frequencies tend to be higher at shallow depths, allowing higher resolution images, and rocks tend to be unconsolidated and compressible, and therefore the seismic response is more sensitive to fluid content. However, deeper reservoirs are capable of being monitored successfully depending on porosity, fluid and rock properties, and the signal to non-repeatable noise characteristics of the seismic data sets being compared.

Net Pressure -Changes in fluid saturation and pressure are more likely to be seen when the difference between overburden pressure and pore pressure is low. This often occurs when gas, steam, or water injection causes pore pressure to approach overburden pressure.

Unit Thickness -For fluid-flow changes to be resolved vertically, experience has shown that the thickness of the horizon being monitored should generally be greater than half a seismic wavelength (defined as the average reservoir rock velocity divided by the dominant seismic frequency).

FLUID CHARACTERISTICSSeismic Fluid Contacts -When confirmed fluid contacts are seen on seismic, it is likely that 4-D seismic will be able to monitor future fluid flows.

Fluid Compressibility Contrast -Reservoir fluids should have contrasting compressibility values in order for seismic methods to distinguish one fluid from the other.

Salinity -Extremely saline waters are less compressible than seawater or typical oils, and are therefore easier to distinguish seismically from oil.

Temperature -High temperatures make reservoir oils more compressible than water, thereby increasing the likelihood of monitoring oils seismically.

Fluid Saturation Change -Reservoir fluid saturations must change significantly between initial and final seismic surveys in order for differences to be observed. This change in saturation does not necessarily have to be large in order to be significant, however. If gas is involved, the introduction of a very low saturation of “free” gas, (e.g. 5%) will give rise to a very significant change of seismic response.

Gas-Oil Ratio -Seismic monitoring requires sufficient contrast to distinguish oil from water. Oils with high GOR values tend to be compressible and light, allowing better delineation of oil/water contacts.

SEISMIC CHARACTERISTICSPredicted Impedance/Traveltime Change - Changes to saturation, pressure, and temperature conditions may produce corresponding changes in acoustic impedance and traveltime. Changes in rock and fluid properties between seismic surveys should generally produce a change in acoustic impedance in excess of three to four percent in order for changes caused by production to be seismically observable under ideal conditions. Changes caused by production should be anticipated and modeled to provide a basis for comparing associated seismic changes in the future. For instance, increases in temperature decrease seismic velocity, as does the presence of gas. Zones of high pore fluid pressure should have lower seismic velocities.

Seismic Image Quality -Monitoring applications require a high-quality, repeatable image that exhibits accurate amplitude and phase variations within the reservoir over time. The signal to noise ratio will have a direct bearing on the quality and usefulness of the images.

Seismic Resolution -Resolution should be fine enough to prevent fluid effects from being averaged out and becoming invisible below the background noise.

Dominant Seismic Frequency -The higher dominant frequencies of seismic energy have the best capability of resolving changes within the reservoir.

Seismic Repeatability -Seismic images should be highly repeatable outside the reservoir zone where no changes are expected, to serve as a benchmark against changes observed within the reservoir. Seismic acquisition and processing should ideally be repeatable from survey to survey, so that differences in time-lapse images can be trusted, and attributed to reservoir production, rather than acquisition or processing artifacts. However this ideal is rarely achieved, so it is important to identify the sources of non-repeatability and deal with those unrelated to changes in the reservoir in an appropriate manner during processing.

Feasibility StudyWe’ve established that a 4-D survey images changes that occur within the reservoir, unlike traditional 3-D exploration surveys that define structure and other static characteristics. The seismic resolution demanded by the 4-D program may therefore be considerably higher than that required for exploration 3-D, and might even be beyond the scope of technology currently available. Such issues will be discovered and addressed by a feasibility study (Jackson, 1998).

A thorough knowledge of the reservoir and its unique properties is required to conduct the most effective survey possible. The field operator should conduct a feasibility study to:

characterize the reservoir;

determine what changes will occur during production, and how they will manifest themselves seismically; determine the seismic resolution required to image those changes, and

determine whether current technology can meet those requirements.

The feasibility study integrates data from cores, logs, surface and borehole seismic, and fluid flow analysis to create a rock model that reflects the character of the reservoir: its structure, layers, fluid contacts, densities, velocities, etc. A flow simulator uses this rock model to predict what changes are expected to occur within the reservoir once production takes place. Once these changes have been modeled, synthetic seismograms will be generated to show how seismic responses correspond to each change. (Figure   2 - forward modeling and inversion; courtesy Schlumberger Oilfield Review).

Figure 2

The seismic responses are then compared with legacy datasets to determine how well the current seismic technology could image the expected seismic differences within the reservoir. This technical analysis is followed by an economic evaluation to determine whether the benefits of 4-D are justified by the cost.

The modeling process invariably identifies issues about the reservoir that require closer study or more data:

Which seismic attribute can be expected to best characterize a particular reservoir/fluid property? How can that data best be obtained?

How will seismic attributes vary with changes in pressure, saturation, or other rock physics parameters? How much processing is required to address a specific problem in the reservoir model?

Can legacy seismic data be used for comparison with newly acquired seismic?

How much variance is acceptable when the calculated production derived from the reservoir model differs from actual production?

These issues require good communication between geologists, geophysicists, petrophysicists, and reservoir engineers to better integrate all available knowledge of the reservoir.

 

 

 

DESIGNING THE 4-D PROGRAMThe feasibility study serves as the model for designing the 4-D program, because the study has addressed technical and economic issues concerning optimal data acquisition and processing. Ultimately, the best 4-D programs would be conceived before acquiring the initial baseline 3-D survey. At each step in the program design process, future operations should be taken into consideration to ensure that repeatability is maintained through every phase of the project.

ACQUISITION GEOMETRYThe need for acquisition repeatability can be met by using the same acquisition method for each survey, along with identical source positioning. This means that all lines should be shot in the same direction as the original lines, and that the same bin spacing and offset/azimuth distribution should be used.

From the outset, receiver arrays should be positioned so that future production facilities or operations will not interfere with later time-lapse surveys. Receiver arrays should also be placed in exactly the same location on each subsequent survey. To accommodate this requirement, some operators have had the geophone arrays buried permanently in place. (Figure   1   -Ocean-bottom cable; courtesy of Geco-Prakla.) Burial offers the benefit of placing the cable out of the way of most field operations so that the cable remains undisturbed, and also eliminates the cost of survey and receiver layout crews on future surveys.

Figure 1

Furthermore, the constant receiver positions and improved coupling may help to simplify processing. Figure   2   (Trenching device) shows how an ROV is used to dig the trench in preparation for burying the cable.

Figure 2

Figure 3   (Shallow trench) shows the trench in which the cable will be placed.

Figure 3

Within the offshore arena, Geco-Prakla (1998) has found that ocean bottom cable surveys offer the following benefits:

absence of streamer noise,

lack of receiver ghosts resulting in broader bandwidth,

true 3-D data with good azimuth distribution,

higher fold data, with reduced infill shooting, and

less sensitivity to weather.

DATA PROCESSING The different vintages of acquired seismic data should each be processed in a manner that minimizes non-repeatable noise while retaining those differences caused by the production process. In some cases, an exact repetition of the processing sequence may be possible. In most cases, and depending on the objectives set for the time-lapse, each processing route will need to be individually optimized. Inter-survey matching and calibration against controls derived from well data will provide part of the process.

DATA ARCHIVALDuring each phase of acquisition and processing, the data should be handled, prepared, and archived in a manner to ensure that it is accessible and compatible with future surveys.

 

 

 

CASE STUDYIn AAPG Studies in Geology, Number 42, Anderson, et al discuss how they used 4-D seismic to monitor reservoir production. This time-lapse survey was carried out at Eugene Island Blocks 330 and 338, where three different 3-D surveys overlap.

SETTINGA time-lapse study was conducted on the LF sand of Eugene Island Block 330 Field, located in the Gulf of Mexico off the coast of Louisiana (Figure   1   -Location map of overlapping 3-D surveys - red triangle is study area; courtesy of AAPG and Datapages, Inc.).

Figure 1

Oil and gas production comes from stacked sand reservoirs in rollover anticlines and fault blocks associated with large regional and counter-regional growth faults and smaller antithetic faults. The field has produced more than 500 MMBOE since 1972, with a significant portion of the oil and gas produced from the JD/KE/LF series of stacked sands. During the life of this field, development

efforts have produced a great deal of seismic, production, geochemical and wireline data, thereby making it a prime candidate for studying the relationship between production and seismic response.

MODELING In order to understand the differences in seismic response that could be expected over time, it was necessary to develop an accurate characterization of current reservoir conditions, then predict the changes that could be expected as the field was produced. The seismic response to those changes would provide a model from which to compare actual changes in the future.

Through understanding the relations between stratigraphy, fluid content, and changes in seismic response, the operator would be able to identify and quantify hydrocarbon drainage by identifying changes to seismic amplitudes over time. More importantly, the comparison between modeled and observed changes would also enable the operator to locate accumulations of bypassed pay.

DATA INTEGRATIONThe reservoir characterization process called upon a wealth of information gained throughout the course of the field’s development. The operator was able to compile over 550 wireline logs from the surrounding area, in addition to geochemical data, production data, stratigraphic models, and pressure studies, as well as three vintages of seismic data. The operator also deepened a well in the field to obtain fluid and core samples, and took in-situ stress and permeability measurements of a fault zone that served as a major conduit for hydrocarbon migration.

The log data showed variations in sonic, density, porosity, and water saturations over time, while production data allowed the operator to determine changes in pressure, water-cut, and gas/oil ratios. This information was combined with stratigraphic, structural, and seismic attribute analysis to produce forward models of fluid migration and its effects on acoustic impedance. An example of this type of attribute analysis is shown in Figure   2   : Crossplot showing correlation between porosity and acoustic impedance; courtesy of Schlumberger Oilfield Review.

Figure 2

MODEL DESIGNThe operator developed a hypothetical sandstone reservoir of uniform thickness to model changes in acoustic properties as reservoir pressure decreased due to production. In this hypothetical reservoir, the gas/water, oil/water, or gas/oil contacts were moved to determine how seismic amplitudes would change with acoustic impedance across the reservoir boundaries (Figure   3   -Model study of effects of fluid change on reflectivity; courtesy of AAPG and Datapages, Inc.).

Figure 3

This model helped the operator to anticipate a number of changes to the reservoir, and to determine the seismic response to those changes.

Increase in the difference between lithostatic pressure and pore pressure as hydrocarbons are drained from the reservoir: This increased pressure differential will cause a dimming, or reduction, in seismic amplitudes within oil sands and gas sands over time (Domenico, 1976). Decrease in pore pressures as hydrocarbons are produced:

This pressure decrease will allow more gas to come out of solution to form a secondary gas cap. An increase in GOR will accompany the formation of the gas cap, and will cause a brightening, or increase, in seismic amplitudes over time. Upward migration of the oil/water contact as pressure depletion continues:

The migration of the water level will be accompanied by a dim-out, or reduction, in seismic amplitudes over time. This dim-out is caused by decreasing pore pressure, combined with a drop in impedance as low-velocity oil and gas are replaced by higher-velocity water. Development of discrete pockets of bypassed pay:

As the reservoir is produced, certain discrete areas within the reservoir may not drain, but will form accumulations of bypassed pay. These high-amplitude areas show little or no alteration to the size or character of their bright spots over time, and have had no increase in differential pressure.

MODEL RESULTSThe operator modeled a 35-foot thick reservoir having a water saturation of 40 percent, and 60 percent oil saturation. (See Figure   4   (a) -Seismic model of reservoir at 40% Sw; courtesy of

AAPG and Datapages, Inc.

Figure 4

) Next, a small gas cap (100 percent gas saturation) formed in the center of the reservoir as the oil was drained off to the west and replaced by lower-pressured water, resulting in 80 percent water saturation and 20 percent oil saturation. A pocket of bypassed oil was left in the eastern section of the reservoir, having 60 percent oil saturation and 40 percent water saturation. (See Figure   4   (b) -Seismic model of reservoir after production; courtesy of AAPG and Datapages, Inc.)

The plot showing differences between seismic response over time exhibits a dim-out in the seismic amplitude where pressured oil was drained and replaced by water with an accompanying drop in pressure. (See Figure   4   (c) -Seismic difference; courtesy of AAPG and Datapages, Inc.) The difference plot shows a significant increase in amplitude caused by the gas cap (red over blue), while bypassed oil continued to display the same amplitudes in the difference plot (yellow over light blue).

4-D MONITORING RESULTS The operator of this field conducted a time-lapse study using three vintages of seismic data, shot over a seven-year period:

1992: Shell/Exxon survey

1988: Texaco/Chevron survey

1985: Pennzoil/Mobil/BP survey

The study was conducted within a triangular area corresponding to an area of common overlap between the three surveys.

INTEGRATION AND PROCESSINGBecause the operator had no control over changing acquisition geometry and technological improvements from one survey volume to the next, the first step was to normalize the data. The normalizing process consisted of referencing the three vintages of surveys to a common grid coordinate system, then using spectral matching, amplitude normalization, and phase correction techniques to minimize the differences between seismic volumes.

INTERPRETATION OF TIME-LAPSE RESULTSAutotracking was used to delineate the major amplitude reflection marking the Western LF reservoir throughout each of the three vintages of surveys, as seen in Figure   5 (1985 Vintage),

Figure 5

Figure   6

Figure 6

(1988 Vintage) and Figure   7 (1992 Vintage) (These figures courtesy of AAPG and Datapages, Inc.).

Figure 7

After extracting the amplitude variation from each survey, the operator was able to see where certain high-amplitude reflections dimmed over time as a result of decreasing fluid pressures and oil saturations. Amplitude differences from one seismic vintage to the next showed the formation of a gas cap (red in Figure   8   : Differencing map between Early and Middle vintages of data ) and water encroachment (blue in this figure).

Figure 8

Differences between the Middle and Late vintage of data (Figure   9   ; courtesy of AAPG and Datapages, Inc.) ) reveal an amplitude dim-out corresponding to depletion of the gas cap up-dip.

Figure 9

A brightening down-dip in the recently-depleted oil zone suggests that a gas cap has formed down-dip. The production history of a nearby well supports these findings.

Next, the Eastern LF reservoir was interpreted. As expected, pockets of bypassed pay were seen as high-amplitude regions that exhibited little change from one seismic vintage to the next (green in Figure   10   ) within the Eastern LF section of the reservoir.

Figure 10

The Eastern LF section also showed decreases in amplitude over time, attributed to pressure depletion and/or water encroachment. An increase in amplitude (red in the figure) was attributed to GOR increases caused by secondary gas dissolution.

 

 

 

WATER INJECTION CASE STUDYThis case study shows an example in which 4-D seismic was used onshore, and illustrates how sensitive the technique may be in higher impedance rock. This example is taken from a 4-D seismic survey in a carbonate reservoir in northern Kuwait. The operator in this study used 4-D seismic to monitor the effectiveness of a water-injection program, and to ensure that the waterflood did not adversely affect the field.

The field produces from a slope-facies carbonate. The reservoir, which can be subdivided into four distinct stratigraphic units, has a total thickness of around 90 meters. The entire field was examined during the operator’s original 3-D seismic survey, and a second, smaller, monitor survey was subsequently acquired across part of the field that was affected by waterflooding. The key objectives of the survey were to assess saturation changes and to evaluate the quality of the waterflood project. These results would prove beneficial to reservoir engineers, who needed to plan drilling patterns and horizontal wells to improve exploitation of the reservoir.

Many of the world’s 4-D seismic surveys have been conducted in clastic (low impedance) reservoirs, where changes in acoustic impedance caused by fluid changes are more obvious than in carbonate (high impedance) reservoirs. This survey would also help the operator to assess the value of 4-D seismic monitoring methods in carbonate reservoirs.

In this field, water was injected at a single well roughly centered among four producers (Figure   1   , Field map with well and seismic locations; courtesy of Kuwait Oil Company and Schlumberger Oilfield Services).

Figure 1

Water injection was not carried out continuously throughout the six-month period between surveys. The situation within the reservoir was further complicated by gravity effects, which caused water to move between individual layers within the reservoir. The monitor survey was conducted six months after the original 3-D survey, using identical acquisition parameters. It produced a quantified saturation map that showed the distribution of injected water. The results were used to show how effective a five-spot well pattern had been in pushing oil away from an injector, toward the producer wells.

A time-lapse sequence shows the change in a map of acoustic impedance (velocity times density), which was derived from 3-D surveys taken before injection and then six months after water injection Figure   2   : Progress of waterflood; courtesy of Kuwait Oil Company and Schlumberger Oilfield Services).

Figure 2

Here, the blue shading represents changes in acoustic impedance associated with increasing water saturation, with the darkest blue surrounding the injector representing maximum water saturation accompanied by only residual oil. The red zone outside the blue area is the zone of maximum oil saturation. (In this time-lapse series, the sequence of intermediate saturations have been modeled to simulate intermediate changes that would have been observed if seismic surveys had been made more frequently. They are included to graphically demonstrate the dynamic nature of the time-lapse seismic measure.)

Before conducting a monitor 3-D survey, it is important to compare anticipated noise levels between the first survey and subsequent surveys (controlled by survey geometry and coverage). The expected changes in seismic response that will result from fluid changes should also be modeled. In this particular field, the operator estimated a maximum noise level of 2%, while the maximum change in acoustic impedance would be approximately 5%. This example shows that through the acquisition of time-lapse data on land, the operator was able to detect a 5% change in seismic response (3% above noise) relating to increases in water saturation.

Saturation variations are extremely important for reservoir engineers. The water injected during waterflood projects is meant to push oil towards the producing wells. Assessing subtle changes in fluid saturation using 4-D seismic methods is not simple, and the results must be integrated with well data and simulation measures. Such a combination enables the engineers to picture oil and water saturation variations across the area of study.

IHRDC wishes to thank Kuwait Oil Company (KOC) and Schlumberger Oilfield Services for permission to show the data in this case study.