New Life for Old Data:
Brownfield Reservoir Characterization and 3D Geological Modeling from the West
Baram Delta Province, Offshore Sarawak, Malaysia*
By
Matthew Mulcahy1, Tanwi Basu1,
A. Wahid Musbah2, Gavin Douglas1,
Howard D. Johnson2, Kamarolzaman B. Yahya2, and Mustafa
Suleiman2
Search and Discovery Article #20023 (2004)
*Adapted from presentation at the AAPG Annual
Convention, Dallas, Texas, April 18-21, 2004.
1Schlumberger
DCS, Kuala Lumpur, Malaysia ([email protected])
2Petronas
Carigali Sdn Bhd, Kuala Lumpur, Malaysia ([email protected])
Reservoir characterization studies of the multiple,
vertically-stacked Miocene reservoirs in the Bokor and Betty fields (West Baram
Delta, offshore Sarawak [Figure 1]) have created
facies based 3D geological models to appraise remaining reserves and determine
strategies for economic redevelopment. This paper describes the reservoir
modeling workflow (Figure 2) and highlights lessons
learned for similar redevelopment projects in the future.
Since the discovery of these fields in the 1970’s, extensive subsurface data,
including core, well log, dipmeter, seismic and production data have been used
to evaluate these Late Miocene coastal/deltaic reservoirs. However, previously
these data had only been evaluated in traditional, 2D form and had never been
subject to a modern 3D geological modeling analysis. To do this, and to
supplement the existing data, further in-depth studies were performed, including
(A) petrography (SEM and XRD analyses) to determine framework grain and clay
mineralogy and their distribution (pore-filling vs. pore bridging as shown in
Figure 3, (B) rock fabric/texture analysis from
high-resolution dipmeter data to assess fine-scale heterogeneities (Figure
4) and (C) facies analysis of core and well logs to generate electrofacies
models (Figure 5).
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Figures Captions
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Figure 1. Location map showing location
of Betty and Bokor fields, in the Baram Delta province, offshore
Sarawak, Malaysia. Area of more than 4 km sedimentary section is
outlined. (After Ngah, 1999). |
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Figure 2. Workflow recommended for
brownfield geomodeling, illustrating new life for old data. |
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Figure 3. Petrography through SEM and
spot elemental analysis of Betty sandstones showing angular
pores within frame-working quartz grains (left) and pore-filling
chlorites (right). XRD analysis independently performed on the
shales also resulted a clay percentage dominated by chlorite and
minor illite. |
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Figure 4. Rock Fabric Analysis via
BorTex using the dipmeter logs showing least active
microresistive curves for massive, poorly stratified sandstone
(left) in Betty-5. Highly active curves are observed in
clay-clast bearing storm-dominated-event beds (top-right) and
intensely bioturbated sandstones, both of which show high
conductive heterogeneity as calculated from the analysis (red
shading on the heterogeneity track). This analysis captured the
fine scale depositional heterogeneity as conductive and
resistive anomalies. |
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Figure 5. Electrofacies Analysis using
neural network techniques via RockCell. The diagram illustrates
the raw input log data on the far left that is explicitly tagged
from core description for neural network training. In the middle
are the facies probability and final facies estimation, which
can then be checked against original core description on the
right. |
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Figure 6. Example of genetically-based
electrofacies distribution for one reservoir unit in Bokor
Field. Seismic amplitudes and reservoir engineering data,
together with core results, combine in construction of the 3D
geological model. |
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Figure 7. Hydrocarbon pore volume
thickness map (HCPVo) derived from simulation results on 3D
geological model allow identification of infill targets and
recompletion opportunities |
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Figure 8. A cross-section panel from the
SSW (left) to ENE (right) going through the depositional strike
of L3 reservoirs in Betty field showing lateral continuity of
most of the best reservoir quality sandstone (in yellow) and
inner-neritic shales (in gray). Vertical heterogeneity is also a
function of the distribution of poor quality sands (in orange).
The tracks for each of the wellbores shows the volume clay and
the lithofacies distribution as estimated from RockCell neural
network technique in the left and the right, respectively. |
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Figure 9. A North (left) to South
(right) cross-section panel from Bokor field, illustrating the
contrast between laterally heterogeneous lower coastal plain
deposits (P) and laterally continuous shoreline/shoreface (C)
and shoreface/shelf (S) deposits. Vertical heterogeneity is
prevalent throughout, resulting in numerous stacked reservoirs.
Tracks for each wellbore show the volume of clay infilled, with
electrofacies on the left and porosity and permeability on the
right. |
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Although core data were extremely limited in
Betty and Bokor fields, they were recognized to be critical to the
reservoir modeling objectives. Consequently, a key approach was the
development of electrofacies models that integrated both the core and
wireline log data. In addition, it was necessary to review the
conceptual and analog depositional models in order to provide the
optimum framework for understanding facies and sand body distribution.
This, together with analysis of well log patterns and seismic
amplitudes, enabled  propagation of a genetically based, electrofacies
interpretation to each of the hundreds of reservoirs within every well
within the two fields (Figure 6). This was
the precursor to distributing facies and rock properties data in 3D
geocellular models for each field; this has significantly improved
reservoir understanding and enhanced redevelopment decisions. In
particular, the 3D geological models provided the basis for
history-matched full-field simulation models, which have identified new
and timely infill well targets and recompletion opportunities (Figure
7). Finally, these studies have also provided additional insight
into the depositional setting and stratigraphic architecture of these
multiple stacked (100s-1000s ft thick) wave- and tide-influenced
coastal/deltaic reservoirs. Additional details of the latter are
summarized below.
The Upper Cycle V (Upper Miocene) reservoirs
in the Betty Field reflect repeated progradation and retrogradation of
the north-westward prograding West Baram Delta. Generation of
accommodation space was strongly influenced by episodic movement of the
bounding growth fault to the south. Facies and rock property
characteristics show that the reservoirs were highly wave reworked and
redistributed alongshore to form laterally continuous shoreface sand
sheets with associated transitional to offshore inner-neritic shelfal
lithofacies. The reservoirs are highly heterogeneous vertically (Figures
7 and 8), due to
the frequent intercalation of inner-neritic shales poorer quality distal
lower shoreface and transition zone lithofacies, particularly in the
lower part of each coarsening upward parasequence.
The Upper Cycle V/Lower Cycle VI (Upper
Miocene) succession in the Bokor Field displays extreme vertical
stacking of approximately 130 separate reservoirs over a 6000-ft-thick
hydrocarbon-bearing interval. The reservoirs (Figure
9) were deposited in a more variable coastal/deltaic environment,
which includes distributary channels, mouth bars, tidal
channels/estuaries, tidal flats and coastal barrier/shoreface sand
bodies. The Bokor reservoirs were deposited in a more axial deltaic
setting, when the coastal and inshore areas were influenced by both
tidal and wave processes, similar to the modern Niger Delta. The greater
abundance of channel sand bodies results in a higher degree of lateral
heterogeneity, as is evident from seismic amplitude displays. The latter
confirm the gross paleogeographic setting of the Bokor Field and provide
independent data on channel size, shape and orientation.
These studies demonstrate how modern
techniques and technologies can integrate highly variable vintages of
subsurface data into robust reservoir models capable of improved
reservoir understanding and more confident prediction of bypassed oil
location. They also highlight the additional value that can be gained
from existing and sometimes apparently neglected or under-utilized data.
Finally, we would like to emphasize how modern technologies can be used
to delivery timely results in these and other brownfield reservoir
characterization studies. The approach described here could be applied
to many other redevelopment projects.
Ngah, Khalid, 1999, Malaysia’s gas resources:
Search and Discovery article #10002 (http://www.searchanddiscovery.net/documents/Malaysia/gas.htm#sarawak).
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