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An Integrated Approach to Characterization and
Modeling
of Deep-water Reservoirs, Diana Field, Western Gulf of Mexico*
By
Morgan
D. Sullivan,1
J. Lincoln Foreman,2 David C. Jennette,3 David Stern,2
Gerrick N. Jensen,4 and Frank J. Goulding4
Search and Discovery Article #40153 (2005)
Posted May 9, 2005
*Online
version of article with same title by same authors in AAPG Memoir 80, 2004, Modeling
1ExxonMobil Upstream Research Company, Houston, Texas, U.S.A.; Current affiliation: Department of Geosciences, California State University, Chico, California U.S.A. ([email protected])
2ExxonMobil Upstream Research Company, Houston, Texas, U.S.A.
3ExxonMobil Upstream Research Company, Houston, Texas, U.S.A.; Current affiliation: Bureau of Economic Geology, The University of Texas, Austin, Texas, U.S.A. ([email protected])
4ExxonMobil Exploration Company, Houston, Texas, U.S.A.
Abstract
seismic
event and limited appraisal wells spaced thousands of feet apart. There is
excellent core coverage that enables close calibration of
seismic
and well data.
Integration and analysis of the data suggest a relatively channelized reservoir
in an updip position, becoming more sheetlike and layered downdip. This
subsurface data, however, does not have the resolution to provide the
dimensional and architectural information required to populate an object-based
three-dimensional geologic model for more accurate flow simulation and
well-performance prediction. To solve these uncertainties, deep-water outcrop
analog data from the Lower Permian Skoorsteenberg Formation in the Tanqua Karoo
Basin, South Africa, and the Upper Carboniferous Ross Formation in the Clare
Basin, western Ireland, were integrated with the
seismic
and well data from the
Diana field. Bed-scale reservoir architectures were quantified with photomosaics
and by correlation of closely spaced measured sections. Bed continuity and
connectivity data, along with vertical and lateral facies variability
information, also were collected, as these factors ultimately control the
reservoir behavior. From these measurements, a spectrum of channel dimensions
and shapes were compiled to condition the modeled objects. These dimensions were
compared to Diana specific
seismic
and well data and adjusted accordingly. The
advantage of the resulting Diana geologic model is that it incorporates geologic
interpretation, honors all available information, and models the reservoir as
discrete objects with specific dimensions, facies juxtaposition, and
connectivity. This study provides the framework for optimal placement of wells
to maximize the architectural and facies controls on reservoir performance
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Introduction
The Diana field is situated in
the western Gulf of Mexico 260 km (160 mi) south of Galveston in
approximately 1430 m (4700 ft) of water (Figure
1). ExxonMobil is the operator with 66% interest, whereas British
Petroleum (BP) holds a 33% interest. Diana is the second largest of
several discoveries recently made in the Diana Subbasin and has in
excess of 100 MMBOE of recoverable hydrocarbons from the upper Pliocene
A-50 reservoir. The turbiditic sandstones and mudstones that comprise
the A-50 reservoir at the Diana field were deposited as a lowstand fan
in an intraslope basin setting. The field is located on the east flank
of a north-south The challenge at the Diana field
was to predict the production performance of a channelized deep-water
reservoir with a relatively thin oil rim and a large gas cap (Figure
1). Associated development costs are high, requiring an optimization
program to ensure a successful project. These predictions were
challenged further by variable-quality In the Diana study, two outcrop analogs were found to be most applicable to the penetrated subsurface reservoirs based on similarities in grain size, facies associations, and interpreted sand-body architecture. These were the Lower Permian Skoorsteenberg Formation in the Tanqua Karoo Basin, South Africa, and the Upper Carboniferous Ross Formation in the Clare Basin, western Ireland. These deep-water turbidite successions have been studied widely in recent years by Collinson et al. (1991), Bouma and Wickens (1994), Chapin et al. (1994), Sullivan et al. (1998), Bouma (2000), Elliot (2000), Martinsen et al. (2000), Morris et al. (2000), and Sullivan et al. (2000a, b). The main purpose of this current outcrop study was to provide the data necessary to help assess future prospects and newly discovered fields with analogous reservoir characteristics. To better understand and apply
the observations and learnings from this outcrop analog study,
normal-incidence forward By combining dimensional and
architectural data from outcrops with
Deep-Water Outcrop Analogs
Outcrop analogs span a critical gap in both scale and resolution between
Based on detailed characterization, the deep-water sandstones present in the outcrop localities can be divided into proximal, transition from proximal to medial, and medial fan settings (Figure 2). Distal fan deposits are also present but were not a focus of this study because of their limited reservoir potential and relatively poor exposure. The presented proximal-to-distal subdivision is for an idealized slope-to-basin transition. It is recognized, however, that it is the change in the slope gradient that ultimately controls the degree of channelization (Imran et al., 1998). Therefore, appropriate outcrop analogs for subsurface data sets need to be selected based on similarities in interpreted sand-body architecture and not on interpreted similarities in location in a slope-to-basin profile.
Proximal FanThe most proximal exposures of both the Skoorsteenberg and Ross Formations are dominated by compensationally stacked, erosionally confined channels and interchannel sheets. These narrow proximal fan channels are typically less than 400 m (1300 ft) wide and 5-12 m (16-39 ft) thick, with aspect ratios (width vs. thickness) ranging from 30:1 to 80:1 (Figures 3, 4). Net-to-gross ratios for individual measured sections range from 70 to 95%, with an average of approximately 90%. Two distinct styles of channel fills are recognized. The proximal fan channels of the Skoorsteenberg Formation are typically filled from axes to margins by amalgamated, thick-bedded (>30 cm), fine- to medium-grained, massive sandstones (Figure 3). Massive sandstones commonly grade upward into thick-bedded, fine-grained, planar-stratified sandstones and rare thin-bedded (<30 cm), very fine- to fine-grained, current-ripple-stratified sandstones. The interchannel strata are comprised of nonamalgamated thin- to thick-bedded current-ripple-laminated sandstones and interbedded laminated silty mudstones. In contrast, the proximal fan channels in the Ross Formation exhibit a lateral degradation in reservoir quality. They are dominated by highly amalgamated massive to cross-bedded sandstones in an axial position that grade laterally into progressively thinner-bedded, less-amalgamated massive sandstones toward the margins (Figure 4). This difference in the lateral degree of amalgamation, from axis to marginal, for the proximal fan channels of the Skoorsteenberg and Ross Formations may suggest differences in the scale and size of the turbidity currents that deposited the sandstones. The vertically and laterally amalgamated massive sandstones, which comprise the channel fills in the Skoorsteenberg Formation, are interpreted to have been deposited by high-concentration turbidity currents that completely filled the channels and, therefore, display no variations from axis to margin (Figure 3). Overbanking of these turbidity currents is interpreted to have produced the distinct interchannel association dominated by low-concentration turbidites (planar- and current-ripple-stratified sandstones). By contrast, the distinct axis-to-margin variations in the Ross Formation suggest that the turbidity currents that deposited these sandstones were underfit relative to the channels (Figure 4). This conclusion is also supported by the general lack of low-concentration turbidite-dominated interchannel deposits in the Ross Formation.
Transition from Proximal to Medial FanDominating the transition from proximal to medial fan settings for both the Skoorsteenberg and Ross Formations are compensationally stacked, very broad (high aspect ratio) weakly confined channels. These channels are as much as 1000 m (3270 ft) wide and 8-13 m (26-42 ft) thick (Figures 5, 6). Their bases tend to be nonerosional, suggesting that they are primarily aggradational in origin. In general, these channels do not infill erosional scours; instead, they are compensationally stacked because of preexisting highs related to underlying channels. Individual channelized sand bodies can be further subdivided into distinct channel-axis and channel-margin facies associations. Highly amalgamated, massive sandstones characterize channel-axis deposits. Away from the axis, beds become distinctly less amalgamated and extremely continuous to produce laterally extensive, layered wings at the channel margins (Figure 5). Net-to-gross ratios for these weakly confined to unconfined channels range from 70 to 90%, with an average of 80%. Detailed bed-by-bed correlations show that these sandstones have bed lengths much greater than the dimensions of the outcrop, whereas mudstones have much shorter bed lengths (Figure 6). Therefore, the key to understanding reservoir continuity and internal heterogeneities that affect reservoir performance in this instance is knowing the thickness and lengths of mudstone barriers and not the distribution of sandstones. Eighty percent of these mudstones are less than 0.3 m (1 ft) thick and have bed lengths less than 200 m (655 ft). Although this is a relatively high net-to-gross reservoir type with excellent lateral continuity, the vertical continuity would be moderate to low. This is caused by the preserved interbedded mudstones, although only 5-10% of these mudstones have lengths approaching or greater than 700 m (2295 ft). It is these continuous mudstones that would likely produce significant vertical barriers to fluid flow.
Medial FanMedial fan deposits are also similar for both the Skoorsteenberg and Ross outcrops and are comprised of extremely broad, unconfined channels or sheets (Figure 7). The bases of these sand-prone sheets tend to be nonerosional, comparable to the broad channels of the proximal to medial fan transition. They also appear to be compensationally stacked or laterally offset because of depositional highs related to underlying sand bodies. Individual sheets are 3-7 m (10-23 ft) thick, with narrow, amalgamated axes and more sheetlike, layered margins. The sheet axes are locally erosionally based and are typically 100-160 m (328-525 ft) wide. They are comprised of highly amalgamated massive sandstones. Away from the axes, progressively thinner-bedded, less-amalgamated sandstones replace amalgamated massive sandstones (Figure 7). The sheet margins have estimated widths in excess of 1600 m (5245 ft) on either side of the axes. Massive sandstones represent the dominant facies type and are interpreted to have been deposited rapidly from suspension from high-concentration turbidity currents in an unconfined setting. Although the sandstone bed sets are highly continuous, they consist of individual lenticular and compensatory sandstone packages. Overall, this produces a very layered architecture, with most of the amalgamation of sheet complexes occurring where axes locally cut into underlying sand bodies. Net-to-gross values for these deposits typically range from 65 to 80%, with an average of approximately 70%.
Forward
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FIGURE 8. Forward |
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FIGURE 9. Forward |
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FIGURE 10. Forward |
The major uncertainties
associated with exploration and development of deep-water reservoirs are
predrill predictions of net-to-gross and assessment of reservoir
continuity and net-to-gross away from well penetrations. Based on recent
drilling results for deep-water petroleum reservoirs, successfully
estimating reservoir continuity and net-to-gross away from well
penetrations requires correct interpretation of reservoir type.
ExxonMobil's postdrill analyses in several deep-water basins have shown
that the information required to successfully predict these parameters
is often embedded in the seismic
response of reservoirs. The challenge
for
seismic
analysis, therefore, is the proper interpretation of these
seismic
responses.
The paucity of well control and
the abundance of high-quality 3-D seismic
data at the exploration and
development scales require interpretation of reservoir type, or
environment of deposition, to be performed using detailed
seismic
facies
analysis. Key criteria of ExxonMobil's deep-water
seismic
facies scheme
include external geometry (e.g., truncation, onlap, mounding, etc.),
amplitude strength and continuity (e.g., high-amplitude continuous vs.
high-amplitude semicontinuous), and attribute map patterns. Because of
the nonuniqueness inherent in
seismic
facies analysis, translation of
these
seismic
facies into depositional environments requires careful
selection of an appropriate analog, be it either subsurface or outcrop
based. In the case of outcrops, architectural analysis can provide the
characteristics of the fundamental units that comprise subsurface
reservoirs.
Different architectural elements
yield different seismic
signatures, such as channels vs. sheets and
axial vs. marginal lithofacies associations. Typically, these elements
are at or below
seismic
resolution. Additional challenges of applying
the outcrop analogs appropriately to a
seismic
response are related to
the signatures of individual sand bodies, which can vary with the
seismic
bandwidth and rock properties. Lastly, most single channels and
sheets stack to form complexes, and the interplay between these
different individual sand bodies can also modify their
seismic
signatures.
Normal-incidence forward seismic
models have been constructed using GXII
seismic
modeling
software for
both the Skoorsteenberg and Ross Formations to calibrate the appropriate
outcrop analogs to the Diana subsurface data. These models are shown in
Figures 8, 9,
10 and illustrate both the
seismic
facies of
individual outcrops using subsurface rock properties (density and
velocity) from the Gulf of Mexico and the resolution limits of typical
seismic
data. All forward
seismic
models were generated using
vertical-incidence ray tracing and a zero-phase Ricker wavelet. A trough
(red) represents a negative impedance boundary, and a peak (black)
represents a positive impedance boundary. Each of the outcrops discussed
in the previous section would be seismically expressed as a single cycle
at the bandwidth and rock properties of the deep-water Gulf of Mexico.
These models provide a link between the architectures observed in
outcrop and
seismic
data in the same way synthetic seismograms link
well-log and core data to
seismic
data.
The comparative seismic
response
of the medial, transition from proximal to medial, and proximal portions
of the Skoorsteenberg and Ross Formations reveals that the variations in
sand-body architecture and degree of vertical and lateral amalgamation
are manifested as changes in amplitude strength and continuity and
subtle changes in isochron. As would be expected, the layered, extremely
continuous medial fan sheets of the Ross Formation (Figure
8) produce a high-amplitude continuous
seismic
character at typical
30 Hz
seismic
frequencies. The high net-to-gross section at the top of
the outcrop can only be fully resolved on the
seismic
model generated
using a 60-Hz wavelet. At this higher frequency, this interval also is
acoustically transparent because of the high percentage of sandstone and
resulting lack of internal reflectivity.
Individual channels from the proximal to medial fan transition of the Ross Formation are not resolvable except at the highest frequency (Figure 9). At the channel-complex scale, however, the lateral change from high net-to-gross axis to lower net-to-gross margin is reflected clearly in a lateral degradation of amplitude strength. This indicates that these distinct lateral changes in sand percentage should be seismically detectable.
The vertically and laterally
amalgamated, high net-to-gross proximal fan channels of the
Skoorsteenberg Formation also display a high- to moderate-amplitude,
moderately continuous seismic
character (Figure
10). In contrast to the medial fan sheets, however,
modeling
of
these outcrops exhibits greater evidence of variation in isochron
because of the channelized nature of the outcrops.
Each of these forward seismic
models is subtly different. These differences reflect the proximal to
distal variations that are inherent in many deep-water depositional
systems. Integrating the knowledge from detailed analysis of these
deep-water outcrops and forward
seismic
modeling
can provide important
information concerning variations in reservoir architecture and
net-to-gross values that can ultimately control the development
potential of many deep-water reservoirs.
Diana Subsurface Data
Figures 11-15
FIGURE 11. (A) Inline 807 is a
depositional strike section through the reservoir (see
Figure 1 for
location). The proximal portion of the
Diana Subbasin, which includes the Diana 2 and Diana 3 well
penetrations, is represented by high-amplitude, continuous
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|
FIGURE 12. (A) Inline 651 is a
depositional strike section through the reservoir (see
Figure 1 for
location). The medial portion of the
reservoir (Diana 1 well penetration) has a distinctly different
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FIGURE 13. Plain light (left side) and ultraviolet (right side) core photos from Diana 3 well. The cored interval is comprised of sharp-based, upward-fining channels (red arrows mark interpreted channel bases) and individual channel-fill successions that can be further subdivided into channel-axis, channel off-axis, and channel-margin associations. Note: core depth is in feet (modified from Sullivan and Templet, 2002). See Figure 14 for key to bed types. |
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FIGURE 15. (A) Integration of
Diana |
Based on detailed analysis, the
3-D seismic
data at the Diana field appears to be of variable quality
and does not allow direct geometric analysis of reservoir elements (Figure
1B). To assist with assessment, deep-water outcrop analog data and
forward
seismic
modeling
were integrated with
seismic
and well data to
produce a more accurate characterization of the reservoir.
Seismic
amplitude extractions for the A-50 reservoir display distinct stripes in
the in-line direction that are interpreted to be related to the
acquisition of the survey. This complicates any quantitative attribute
analysis of the reservoir and restricts the application of
seismic
amplitude map patterns to delineate sand-body trends and dimensions.
Qualitative examination of vertical
seismic
in-lines and cross-lines,
however, provides valuable information concerning the architecture of
the reservoir elements (Figures 11,
12). The A-50 sands are low impedance where
they are hydrocarbon charged and are typically represented by a
single-cycle
seismic
event (trough-peak pair) with a trough (red =
negative impedance boundary) at the top and a peak (black = positive
impedance boundary) at the base on zero-phase data.
The proximal portion of the Diana
field, which includes the Diana 2 and Diana 3 well penetrations, is
represented by high-amplitude, continuous seismic
character above the
gas-oil contact (Figure 11). The observed
amplitude dimming toward the Diana 3 location is fluid related (change
from gas to oil) and is not associated with variations in net-to-gross (Figures
13, 14, 15A).
This suggests that, if variation in net-to-gross and reservoir
architecture exists in this portion of the reservoir, it is below
seismic
detection. Furthermore, forward
seismic
modeling
indicates that
both high net-to-gross, amalgamated proximal fan channels (Figure
10) and moderate net-to-gross, layered medial fan sheets can have a
similar high-amplitude continuous
seismic
response (Figure
8). Subtle variations in isochron are observed for the A-50 interval
and may suggest a more channelized reservoir, but it is not conclusive.
The Diana 2 and Diana 3 wells, however, penetrate a very high
net-to-gross interval dominated by amalgamated high-concentration
turbidites and shale clast conglomerates (Figures
13, 14, 15A).
This association of facies, in conjunction with the
seismic
character of
the A-50 interval, suggests a relatively channelized reservoir (Figures
11C, 15A).
The medial portion of the field
(Diana 1 well penetration) has a distinctly different seismic
character
than the updip portion of the reservoir (Diana 2/Diana 3 region) and is
represented by a high-amplitude, semicontinuous
seismic
character above
the gas/oil contact (Figure 12A). Forward
seismic
modeling
shows that lateral change from high net-to-gross to
lower net-to-gross should be reflected by a degradation of amplitude
strength (Figure 9). This suggests that the
lateral variation in
seismic
character of the A-50 sands in the vicinity
of Diana 1 is caused by seismically detectable variations in
net-to-gross and reservoir architecture. Well penetrations confirm this
interpretation, as Diana 2 was drilled in a higher-amplitude portion of
the reservoir and encountered approximately 85% net-to-gross (Figure
15A). Diana 3 also is extremely high net-to-gross (Figures
13, 14, 15A),
but it was drilled in the oil leg and, as a result, has a lower
amplitude. In contrast, Diana 1 is drilled in a lower amplitude within
the gas cap, and the net-to-gross is significantly lower (approximately
65%). Laterally away from the Diana 1 penetration, the amplitudes
brighten, and this is interpreted to reflect more axial, higher
net-to-gross portions of the reservoir (Figure
12A). The
seismic
character of this segment of the reservoir,
therefore, suggests a less-channelized reservoir than updip (Figure
12C). In fact, the
seismic
character is very similar to the forward
seismic
model for the channelized sheets, which dominate the transition
from proximal to medial fan deposits of the Ross Formation (Figures
9, 12). This supports the proximal fan
interpretation for the updip deposits around Diana 2 and 3 (Figure
11).
Excellent core coverage in the
Diana field also enables close calibration of seismic
and well data. The
cored interval is comprised of stacked, sharp-based, upward-fining
channels (Figures 13,
14). Individual channel-fill successions can
be subdivided into channel-axis, channel off-axis, and channel-margin
associations in a similar fashion as the outcrops of the Skoorsteenberg
and Ross Formations (Figures 3,
4, 5,
6, 7).
Channel-axis deposits are characterized by highly amalgamated, massive
sandstones deposited from high-concentration turbidity currents (Figures
13, 14). The channel off-axis
association is composed of stacked, semi- to nonamalgamated, massive to
planar-stratified sandstones and interlaminated mudstones (Figure
14). The channel-margin deposits contain a variety of lithofacies
and are characterized by a heterolithic mixture of interbedded
sandstones and mudstones (Figures 13,
14). Statistical foot-by-foot comparisons of
log curves vs. core-described lithofacies were used to interpret
depositional facies in uncored portions of wells. Blocked wells were
further used to condition an object-based geologic model and to control
the distribution of channel elements and vertical stacking patterns (Figure
14).
Integration of seismic
, well-log,
and core data with forward
seismic
models of deep-water outcrop analogs,
therefore, suggests a more channelized reservoir updip (Figure
11), becoming more distributive and sheetlike downdip (Figure
12). This subsurface data, however, does not have the resolution to
provide the dimensional and architectural data required to populate a
geologic model for flow simulation and well-performance prediction.
Diana Reservoir Model
To solve these uncertainties,
dimensional and architectural data (e.g., width vs. thickness
measurements) from the Skoorsteenberg and Ross deep-water outcrops (Figures
3, 4, 5,
6, 7) were
compared to the interpreted thickness data derived from the
Diana-specific seismic
, well-log, and core data and were adjusted
accordingly (Figures 13,
14, 15A). From
these measurements, a spectrum of channel dimensions and shapes was
collected. Comparison of the forward
seismic
models of the
Skoorsteenberg and Ross deep-water outcrops to the actual Diana
seismic
data was made to select the appropriate architectural data to populate
the reservoir model (Figures 11,
12, 15). In
addition to the collection of channel dimensions and shapes, bed
continuity, and lateral and vertical facies, variability data also were
gathered from both outcrop analogs and well logs/core to condition the
reservoir model, as these factors ultimately control the reservoir
behavior (Figures 6,
13, 14).
In the case of the Diana field,
this data was used to help maximize the development of the relatively
thin, yet economically important oil rim. This was accomplished by
building a detailed object-based reservoir model, which integrated both
subsurface and outcrop data. The model was built using ExxonMobil
proprietary code for modeling
deep-water reservoirs and the reservoir
modeling
system IRAP-RMS object-based
modeling
tool. This model consists
of discrete objects (facies bodies), each with specific dimensions,
facies juxtapositions, and continuity. This type of
modeling
is
appropriate in data-limited situations where a facies model is based on
a conceptual interpretation of reservoir architecture. The reason for
choosing this technique to model the Diana reservoir included (1) the
poor quality of the
seismic
data, (2) limited well penetrations, (3)
interpretation of the reservoir being comprised of channels with
distinct lateral changes in facies (axis to margin), (4) interpretation
of updip to downdip changes in channel architecture and net-to-gross,
and (5) desire to apply a concept-driven geologic model that
incorporated outcrop analog information.
The fundamental object in this reservoir model is a turbidite-dominated deep-water channel. In the Diana model, individual channels are narrow updip and become wider and less amalgamated downdip (Figures 16, 17), as observed in the outcrops of both the Skoorsteenberg and Ross formations (Figures 3, 4, 5, 6, 7). Modeled channels are divided into proximal, medial, and distal regions with their own specific set of characteristics. Channels are subdivided further into axis, off-axis, and margin associations. Lateral degradation in reservoir quality from axis to margin is interpreted from core data, as observed in the outcrops of the Skoorsteenberg and Ross Formations (Figures 3, 4, 5, 6, 7). Shales were inserted as objects in a fine-layer (0.1 m) framework. The spatial distribution of shales in a given facies type is random (e.g., there was no preferential placement of shale either areally or vertically in the 3-D model volume). The volume of shale added to a facies depended on the net-to-gross of the facies type (e.g., axis vs. margin). Shale dimensions were obtained from the Skoorsteenberg and Ross Formations (Figure 6). Shale objects in the model are square or rectangular in shape, and their dimensions depend on facies type (e.g., axis vs. margin) and location (e.g., proximal vs. distal).
The final model contains more
than 100 individual channels, each one stochastically generated from a
range of possible widths and thicknesses (Figures
16, 17, 18).
The facies objects were inserted first at the well locations and then
subsequently inserted stochastically into interwell regions according to
geologic constraints (e.g., vertical stacking patterns), until volume
targets were met. Net-to-gross maps, which were generated by calculating
the average value of the sand-shale parameter at a given X, Y
location in the model, provide an indication of how the net sand is
distributed in the model (Figure 18). The
resulting net-to-gross maps strongly resemble modern deep-water systems,
such as the Mississippi Fan (Figure 19), and
further support this integrated study. Each facies and subfacies body
was then populated with petrophysical properties using Gaussian
simulation drawn from subfacies property histograms generated from
available well data. To preserve the facies architecture and
heterogeneity expected in a channel-dominated deep-water setting, the
rock property modeling
was performed in individual channel objects.
Based on this modeling
effort and
flow simulation, significant variations in reservoir performance exist
from updip to downdip (Figure 20). The
development strategy for the Diana field is to produce oil initially
from horizontal wells high in the oil rim. Once water breaks through in
significant quantities, these wells will be recompleted in the gas cap.
The goal is to maximize oil production while minimizing water production
and movement of oil into the gas cap. Typically, reservoir models are
scaled up for flow simulation. However, in this case, the updip portion
of the reservoir was actually scaled down to preserve its more
channelized and amalgamated nature (Figure 20).
The updip portion of the reservoir has higher initial oil saturations
because of its higher porosities. It also starts producing water earlier
than the downdip portion of the reservoir because of its higher
porosities and more channelized nature. This study, therefore, predicts
significant variations in reservoir producibility that exist across the
Diana field. This information was used to place wells in optimum
locations to maximize the architectural controls on reservoir
performance and has had a significant impact on the final development
strategy for the field.
Conclusions
This study shows the importance
of incorporating outcrop analogs in the analysis of subsurface
reservoirs. Outcrop research is critical because the observed updip to
downdip variability in sand-body geometry, continuity, and net-to-gross
of deep-water reservoirs affects both the exploration and production
potential of these sandstones. Commonly, this variability, as in the
case of the A-50 reservoir at the Diana field, is at or below seismic
resolution, and well penetrations are typically limited. Properly
calibrated deep-water outcrops can provide constrained geometric and
architectural data to fill the gaps between wells or stochastic
modeling
uncertainties below the resolution of
seismic
data. Dimensional and
architectural data from outcrops and forward
seismic
modeling
can
therefore be integrated with
seismic
and wellbore data to build regional
depositional models to better understand reservoir distribution and
delineate exploration plays. Deep-water outcrop data can also be used to
help populate object-based models that can be used to more accurately
predict well performance, connected volumes, and recovery efficiencies
for newly discovered fields. Furthermore, the integration of
seismic
,
well-log, core, and outcrop data with object-based models provides the
framework for optimal placement of wells to maximize the architectural
controls on reservoir performance. The bottom-line impact of this type
of integrated analysis has been a significant reduction in the range of
uncertainty attached to reservoir assessment parameters for deep-water
sandstones, both in the Diana Subbasin and in many other areas where
exploration and development of deep-water reservoirs is currently
occurring.
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Acknowledgments
The authors would like to thank Dave Larue, Mike DeVries, Arfan Khan, DeVille Wickens, and Arnold Bouma for their assistance in collecting outcrop data from the Skoorsteenberg Formation. Ian Moore, Chris Armstrong, Kevin Keogh, and Trevor Elliot are also thanked for their assistance in collecting portions of the outcrop data from the Ross Formation. Permission to publish this paper was granted by ExxonMobil Upstream Research and by BP Exploration. The authors would also like to thank Grant Wach, William Schweller, Jim Borer, Michael Grammer, and Ray Sullivan for reviewing and improving this paper. In addition, we would like to acknowledge Ed Garza for all of his assistance in producing the illustrations presented in this paper