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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,
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
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 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 seismic data, a reservoir thickness expressed by a single-cycle seismic event, only limited appraisal wells, and the likelihood for subseismic reservoir variability that could control the economic viability of the project. To assist with reserve assessments and optimization of depletion strategies, deep-water outcrop analog data were integrated with seismic and well data to produce a detailed object-based model for more accurate reservoir characterization. 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 By combining dimensional and
architectural data
Deep-Water Outcrop Analogs
Outcrop analogs span a critical gap in both scale and resolution between
seismic and wellbore data. The integration of appropriate outcrop
analogs, core, well-log, and seismic data can provide the detailed
geometric properties required for interpreting the reservoir
architecture at a subseismic or flow-unit scale. The Lower Permian
Skoorsteenberg Formation in Tanqua Karoo Basin, South Africa, and the
Upper Carboniferous Ross Formation in the Clare Basin, western Ireland,
are both composed of stacked turbiditic sandstones and mudstones
deposited in a channelized basin-floor fan setting. These laterally
continuous outcrops provide an excellent opportunity to characterize
detailed bed-scale reservoir architectures and internal heterogeneities
that affect the producibility of deep-water sand bodies in both
depositional strike and dip perspectives. The selection of appropriate
outcrop analogs, however, is extremely important. The criteria for
choosing the outcrops of the Skoorsteenberg and Ross Formations as
analogs for A-50 reservoir at Diana was based on comparison of key
reservoir characteristics such as grain size, lithofacies, net-to-gross
(ratio of sandstone vs. mudstone), and sand-body architecture. Because
of the strong similarities between the selected outcrop analogs and the
A-50 reservoir, dimensional and architectural data
Based on detailed characterization, the deep-water sandstones present in
the outcrop localities can be divided into proximal, transition
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 This
difference in the lateral degree of amalgamation,
Transition
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FIGURE 8. Forward seismic model
for medial fan sheets |
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FIGURE 9. Forward seismic model
for the proximal- to medial-fan transition channels of the Ross
Formation built using GXII seismic modeling software. (A)
Outcrop photo of the broad, compensationally stacked channels
that dominate the transition |
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FIGURE 10. Forward seismic model
for proximal fan channels |
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
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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Chapin, M.A., P. Davies, J.L. Gibson, and H.S., Pettingill, 1994, Reservoir architecture of turbidite sheet sandstones in laterally extensive outcrops, Ross Formation, western Ireland, in P. Weimer, A.H. Bouma, and B.F. Perkins, eds., Submarine fans and turbidite reservoirs: Gulf Coast Section SEPM Foundation, Fifteenth Annual Research Conference, p. 53-68.
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Sullivan, M.D., J.L. Foreman, D.C. Jennette,
D. Stern, and A. Liesch, 2000a, Application of deepwater outcrop analogs
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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