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Journal of Petroleum Geology, vol.26 (1), January 2003, pp 00-00 1
GEOLOGICAL INTERPRETATION
OF WELL TEST ANALYSIS:
A CASE STUDY FROM A FLUVIAL RESERVOIR
IN THE GULF OF THAILAND
S.Y. Zheng1*, P.W.M. Corbett1 and A. Emery2
One problem with the inversion of transient well test data is that it can yield a non-
unique solution. The uncertainty resulting from this type of approach can only be resolved
by considering information from another source such as geology. Geological information
will help to define the interpretation model which will ensure the correct analysis of the
well test data. The results of well test analyses are of little value to reservoir characterisation
and modelling unless they can be explained from a geological point of view. This last step
is what we refer to here as geological interpretation. Other sources of information which
can help with well test analyses come from seismic surveys and petrophysics. Modern
well test interpretation therefore consists of two major steps: analysis of the well test
data; and interpretation of the results. In detail, this should include the following:
(1) definition of an interpretation model — this requires the integration of geological,
seismic and petrophysical data with transient pressure data;
(2) analysis of the well test data based on the interpretation model defined;
(3) geological interpretation of the results, which is necessary in order to explain or
give meaning to the results.
In this paper, we present a case study from a fluvial gas reservoir in the Gulf of Thailand
which demonstrates these procedures. In the context of a defined geological environment,
a transient pressure test has been fully analysed. Newly-developed software based on the
finite element method has been used to forward model the test scenarios. This allowed the
results of seismic and petrophysical analyses to be integrated into the well test model.
This case study illustrates the integrated use of geological, petrophysical, well test and
seismic attribute data in defining a reservoir model which respects both the reservoir
geometry at some distance from the well location and also the reservoir’s heterogeneity.
We focus on a particular well in the Pattani Basin at which conventional well test analyses
have been conducted. By considering the results of these analyses, forward modelling was
carried out in which the drainage area was “cut” out of the structural map defined by
1
Department of Petroleum Engineering, Heriot-Watt University, Edinburgh, EH14 4AS.
2
Western Geophysical, London.
*Author for correspondence: shiyi.zheng@pet.hw.ac.uk
2 Geological interpretation of well test analysis
seismic interpretation; also, the formation’s internal heterogeneity was modelled according
to well logs and petrophysical analyses. Finally, analytical and simulation results were
compared with the transient pressure data.
We conclude that the integration of geological, seismic, petrophysical and well test
data greatly reduced uncertainties in well test interpretation. The consistency of the results
and the fact that they satisfied all the relevant disciplines meant that much more confidence
could be given to their interpretation.
INTRODUCTION
A general problem in conventional well test analysis is the non-uniqueness of the solution
due to the inverse nature of the problem. This can lead to uncertainties in the characterization
of a reservoir, particularly with respect to its geometry and properties such as layering.
Geological data can help to reduce this kind of uncertainty by ensuring that a correct
interpretation model is selected. The importance of combining geological data with well
test analyses to improve reservoir characterisation was not fully recognised until the early
1990s (Zheng, 1997), but after about a decade of development, tools such as computer
software for this purpose are now available to the oil industry. The role of well testing has
therefore been extended from production testing to reservoir characterisation, reservoir
management and reservoir modelling (Horne, 1995; Zheng, 1997).
The integration of geology and well testing requires an improved understanding of
these measurements particularly with respect to their scale and limit. In general, a well test
measures a reservoir volume at a length scale of about 500m. From this, the effective
properties of the reservoir such as its permeability can be derived, and can be compared to
upscaled core-derived measurements (Zheng et al., 2000). Furthermore, the reservoir
geometry (or the “geological shape”) derived by inversion of the transient pressure data
tends to be symmetric. Together, these yield a reservoir model which has a symmetric
geometry and uniform properties. This, of course, can be matched by an analytical solution
if it is available. However, this kind of model can be very different from one derived from
a geological and petrophysical approach (Zheng, 1997). In order to define the meaning of
the derived parameters from such an analysis, a geological interpretation is required.
Another aspect of the integration relates to the difference between the dynamic
performance and static description of the reservoir. For example, a change in formation
heterogeneity at a borehole scale (e.g. due to a high permeability streak of limited extent)
will change the test performance (i.e. the pressure derivative curve), although the description
at a reservoir scale will remain the same (Corbett et al., 1996).
A consistent interpretation satisfying both the analytical solution and the geology can
only be derived when the reservoir is homogeneous or nearly homogeneous. In the case of
a heterogeneous system such as a fluvial reservoir, the analytical solution alone cannot
clearly explain the model scenarios. Also, an analytical solution may be very hard (or
impossible) to achieve, in which case a numerical approach is required.
The numerical method of modelling well test data in a heterogeneous reservoir is
straightforward. A numerical model is constructed based on a geological description and
on the well test analysis. The dynamic reservoir response, expressed in the form of a
pressure derivative curve, is derived by well test simulation. Analytical solutions (e.g.
those in published literature) can easily be generated in this way. In addition, geological
and petrophysical inputs together with those from other relevant disciplines can be integrated
into the reservoir model, so that a range of responses can be generated to represent scenarios
which are close to reality. This approach can also be used to validate an existing well test
interpretation. By forward modelling the interpretation results, data from geophysics
(seismics), geology and petrophysics can be integrated into the well test model to derive
an interpretation with improved confidence (Zheng et al., 2000).
S.Y.Zheng et al. 3
Fig. 1. Location map of the study area in the Pattani Basin, Gulf of Thailand.
CASE STUDY:
GEOLOGICAL AND PETROPHYSICAL DESCRIPTION
We use well test data from an appraisal well, “well E”, located in the gas-producing
Pattani Basin, Gulf of Thailand (Fig.1). Reservoir rocks are Tertiary fluvial channel
sandstones (Lian and Bradley, 1986; Duval and Gouadain, 1994). Sandbodies in the thick
Miocene succession are discontinuous, and most of the fields are affected by normal faulting.
A major challenge in reservoir characterisation is to distinguish between reservoir
boundaries produced by channel margins and those caused by faulting. Since these complex
reservoirs are seldom penetrated by more than one well, it is important to make good use
of techniques which can enable us to visualise the reservoir morphology at some distance
from the well location. Both well testing and seismic data can provide the necessary
information (Brown, 1991; Beydoun and Guerillot, 1993) and when properly integrated
with geological data from core and wireline logs, should give enhanced confidence to
reservoir models.
The cored interval at well E, which corresponds almost exactly with the tested interval,
represents a 44ft thick sandstone body (Fig. 2). The basal 2.5ft of the sandbody consists of
4 Geological interpretation of well test analysis
Fig. 2. Well E, Paltani Basin: composite logs (left) show the GR response and density profile
through the 40ft thick perforated interval. Core description (centre) and permeability
distributions (right: plug and probe) for the sandbody tested were
together used to define four flow units.
a carbonate-cemented, conglomeratic lag deposit with mudstone clasts, which is overlain
by a 7.5ft thick, medium-grained fining-up sandstone with some cross-bedding. Another,
thinner, coarse lag is followed by a cross-bedded sequence which fines up only slightly to
medium-fine sand grade, some 20ft above the base of the sandbody. Above, another thin
lag is succeeded by a coarser (mainly coarse sand) unit which is cross-bedded; this coarsens
up, with pebbles in places and sometimes reaching very coarse sand, to the top of the
sandbody. At the top of the sequence, some ripple sets were recorded as thin calcite-
cemented intervals.
Based on these observations, the lower part of the section (to 20ft) is considered to
represent meandering fluvial channel deposits. Supporting evidence includes the coarse
lag representing the channel base, the fining-upward nature of the overlying units, and the
typical internal structures. Above 20ft, the evidence points to a less sinuous, more braided,
type of fluvial system.
Permeability was measured on conventional core plugs, spaced at 2ft intervals, and
also using a probe permeameter with readings taken every 0.1ft (Fig. 2). In general, the
probe was of more use in providing a detailed picture of permeability variations in the
S.Y.Zheng et al. 5
Fig. 3. Geological interpretation of the tested fluvial reservoir sands at well E. Braided channel
sands overlie meandering channel sands.
core. The probe data-profiles generally follow grain-size trends, i.e. the coarser sands give
higher permeabilities and vice-versa although the coarse lag at the base of the sand body is
very tight because it is carbonate-cemented. However, the probe data picked out subtle
permeability variations and allowed us to define four flow units, one more than we would
have done had we used the core description alone. Flow unit 2, the second one up from the
base, was picked based on permeabilities rather than sedimentology. The extent to which
the different flow units (especially the lower three “meandering” units) represent channel
stacking or slight shifts in channel orientation etc., is not known.
The geological interpretation (Fig. 3) comprises cross-bedded coarse sandstones in
sets 0.5-1ft thick which coarsen up slightly, suggesting small bars developed in the
coalescing channels of a braided river. This is consistent with the regional structural
interpretation: braided streams generally develop on higher gradient surfaces, suggesting
a component of tectonic tilting.
Overall then, the sandbody seems to represent a composite channel form, where initial
incision and deposition of a coarse lag was followed by a meandering channel, which was
in turn succeeded by a braided channel system, before abandonment and deposition of
overbank silts. The sequence may represent an incised valley fill.
3-D SEISMIC INTERPRETATION
Data Set
A 3D seismic dataset covering an area of 65.64 sq.m (a subset of a much larger dataset)
was made available to the project. However, this study deals only with the area around
well E together with 7.72 sq.m. of seismic coverage. This particular well was selected
6 Geological interpretation of well test analysis
Fig. 4. West-east inline seismic section through the well location. The bold black line is the well
path; the green and yellow lines are the “top” and “base” sand picks, respectively. Dotted lines
are faults. Note the high amplitudes of the reservoir horizon
adjacent to the major fault (centre right).
because the operator had indicated that the channel could easily be recognised on seismic
profiles; and it was the only well in which cored and DST (Drill Stem Test) intervals
coincided.
The 3-D survey was acquired in 1993. The acquisition configuration consisted of a
single vessel, single source and dual streamers. Inline acquisition direction was east-west,
and inline bin spacing was 41ft. Cross-line, an unusually large subsurface line spacing of
246 ft was used, with an interpolation step included in the processing to reduce this to 123
ft. Data quality is in general good with two caveats: (a) wave-front distortion, velocity
shadow effects, etc. due to faulting – this caused reflection continuity to break down in the
vicinity of the faults; and (b) the large cross-line spacing which, especially in combination
with the above distortion effects, served to reduce resolution and interpretability. Point (b)
is expanded below. Reflector continuity was reasonable, the dominant frequency at the
reservoir level being approximately 30 Hz.
Processing followed a fairly standard flow. The data were “zero-phased” in the
designation step so interpreted picks should be on the peak or trough for “thick-bedded”
geology, i.e. where the top and base of the bed can be resolved.
Analysis and Interpretation
The gas sand tested in well E is 44ft thick. Theoretically, one cannot discriminate
between the top and base of beds which are thinner than a resolvable limit, which in this
S.Y.Zheng et al. 7
Fig. 5. Time-structure map for the “top” sand pick. Highs are shown in blue, lows in red. The
well path is marked with surface location (solid symbol), reservoir intersection and TD (crosses).
Faults are shown; fault to the NW is projected (dashed line) to intersect with the fault to the
South forming a “closed” reservoir “block”.
Fig. 6. Amplitude map for the “top sand” pick. Reds and yellows are high amplitudes; greens are
low amplitudes, and blue is phase changes. The well path is marked, including surface location
(solid) and reservoir intersection (circle).
8 Geological interpretation of well test analysis
Fig. 7. Interpretation of the seismic amplitude map in terms of sandbody distribution and
faulting. The heavy stipple represents possible fluvial channels (high amplitudes); the light
stipple represents possible crevasse splays (moderate amplitudes); floodplain muds and silts
(low amplitudes) are also shown (white areas).
There is uncertainty about the fault closure near the well.
case is approximately 160 ft (although this is rather pessimistic: Hardage et al., 1994). The
tuning thickness is the critical thickness at which reflections from the top and base of a
bed constructively interfere to boost the amplitude.
Some interpreted horizons were supplied in digital form by the operator and these
initially tied the well, although they required re-picking to “snap” them to the correct part
of the phase. The “top” and “base” events were picked around the well. Faulting was
interpreted afresh. Interpretation followed the conventional approach using in-lines, cross-
lines, user-defined traverses and time slices to tie-down fault positions and fault-horizon
relationships. Although we agree with Brown (1991) about the value of time slices in
interpretation, their utility in this case was reduced because the cross-line spacing was
three times the in-line spacing, causing the display to be “squashed” cross-line; and also
because the time slices were blurred which was again thought to be due to the large cross-
line spacing, which on migration would produce smearing in 3D. Reduction in event
amplitudes adjacent to fault planes was one factor which did help in picking faults.
Fig. 4 shows an in-line seismic section (oriented east-west) through the well location;
Fig. 5 is a time-structure map (“top sand”). The well encountered the reservoir sand on a
fault terrace between two major normal faults (displacement 500ft), which trend north-
south and are down-thrown to the east. The reservoir horizon dips 10° west, and the depth
to the top reservoir at the well location is 9,802ft (measured depth, MD) or 7,091ft (true
vertical depth sub-sea, TVDSS). Fig. 5 also shows a series of minor faults with various
orientations, including some which are normal to the trend of the major faults and serve to
segment the fault terrace.
S.Y.Zheng et al. 9
Fig. 6 is a map of the amplitude of the event picked as “top sand”. There is an elongate
zone of high amplitudes around the well location, but this does not exactly correspond to
the morphology of the structural high shown in Fig. 5. Indeed it is more “banana” shaped,
and following the high amplitudes away from the fault terrace itself, both to east and west,
one gets an impression of a sinuous feature cutting across the structural grain, approximately
from the top right (NE of the area) to the bottom left (SW). If one mentally “strips out” the
effect of amplitude dimming adjacent to fault planes, this effect is enhanced. There are
other high-amplitude zones, especially to the east. This suggests, by correlation with the
core interpretation, that the elongate, high-amplitude zones represent sand-prone fluvial
channel belts; that low-amplitude “background” areas are potentially alluvial plain muds;
and that intermediate amplitudes possibly represent thin sandy/silty crevasse splay deposits.
Several authors have described the seismic mapping of fluvial channels from other parts
of the Gulf of Thailand (Lian and Bradley, 1986; Duval and Gouadain, 1994; Trevena et
al., 1995).
The map in Fig. 7, is an interpretation of the seismic amplitude map and shows that the
reservoir appears to be compartmentalised by a combination of structural features (faulting)
and stratigraphic (channel belt) elements. Uncertainties in the seismic interpretation of
this area include the degree to which the margins of high-amplitude areas represent the
edges of channel belts. Also, several of the faults mapped are subtle and low-throw, and
some interpreters may not have mapped them; furthermore, the potential effects of sub-
seismic faults has not been addressed. The input from well testing is therefore important
in helping to tie down the reservoir structure.
The seismic interpretation shows a major fault 110m east of the well location (Figs.5
and 7), the western side of the reservoir being bounded by a low-throw fault and / or the
margin of a channel belt; to north and south, it is probably bounded by minor faults. The
reservoir area defined in this way covers approximately 160 acres. Below, we bring together
the seismic and DST interpretations, together with the core description and permeability
data.
WELL TEST ANALYSIS
DST-1 (well E) Description
In well E, a drill-stem-test (“DST-1”) was conducted over the interval between 9,802.0
and 9,846.0 ft (MD). A 3.3/8" tubing-conveyed perforation (TCP) was performed under-
balanced; the perforation density was six shots per foot (SPF). The objectives of the test
were to derive information on zone deliverability and reservoir performance, to sample
fluids (gas composition, condensate gravity), and to determine the reservoir limit from
reservoir depletion.
DST-1 comprised 31 minutes of initial flow (draw-down) followed by an initial shut-in
period (first “build-up”) lasting about four times the preceding flow time. Main flow for
24 hours then took place while maintaining critical flow using a 64/64" choke. The well
was then shut-in again before a final pressure build-up which lasted 36 hours or about
one-and-a-half times the preceding flow time. Fig. 8 shows the test overview.
Well Test Analysis
In Fig. 8, the reservoir depletion was determined from a comparison of the final pressures
at the end of the first and second build-ups. Test analysis was completed following a
conventional procedure, i.e. (a) definition of the time regions and flow regimes for model
10 Geological interpretation of well test analysis
Fig. 8. DST-1 well test overview, comprising an initial drawdown, an initial pressure build-up, a
main draw-down and a final pressure build-up. Reservoir depletion can be determined by
comparing the end pressures from the initial and final build-ups.
Fig. 9. Well test history match which considers only the transient pressure data. The derived
reservoir model is a simple “tank” with uniform properties in which a well is centrally located.
The pressure history match is very good, but no other data (geological, seismic, well logs,
petrophysical) have been integrated.
S.Y.Zheng et al. 11
selection; (b) analyses of the identified flow regimes; and (c) flow regime and test history
matching using the defined reservoir model and the derived corresponding parameters.
Since the theme of this paper emphasises the integration of different types of data, the
details of the well test analysis are not discussed in detail although the results are shown in
Fig. 9. This figure shows that the test history match is very good. The reservoir model
derived is an elongate “box” which is 4,800ft long, 680ft wide, and 34 ft thick. The reservoir
permeability (k) is 550mD with a skin factor (S) of 8.1. This homogeneous reservoir model
includes no information about formation layering or property contrasts between layers; it
consists of a uniform box or “tank” with two parallel no-flow boundaries and a well located
centrally between them.
Note, however, that a good history match does not represent a unique solution for the
test. The reservoir model is based on three flow regimes which were identified from the
test analysis: radial flow in the near well-bore region; linear flow due to the parallel no-
flow boundaries; and pseudo- steady-state flow resulting from reservoir depletion. This
yields a reservoir whose 2D geometry is a 4,800ft x 680ft rectangle with a drainage area of
75 acres. The distance between the two parallel boundaries is 680ft. The volume of gas
initially in place, based on the cumulative production and the reservoir depletion, is
calculated as 1.69 billion standard cubic feet (Zheng, 1997).
WELL TEST FORWARD MODELLING AND SIMULATION
In order to resolve the uncertainty resulting from the conventional well test analysis,
well test forward modelling was conducted. Since the test results cannot explain the
reservoir’s heterogeneity as indicated by the seismic, geological, well log and petrophysical
analyses, well test modelling aimed to integrate these data in order to construct a more
realistic model which honours all the data. Then, by comparing the simulated well test
pressure response against the DST data, and matching the flow regimes identified in the
primary test analysis, a more confident test interpretation can be achieved.
Forward Modelling
In the first step, a reservoir model was constructed by “cutting” the drainage area out
of the seismic map. Reservoir boundaries were defined along the faults defined by the
seismic interpretation (Fig. 7), where the fault to the NW of the reservoir has been extended
southwards. This is because the well test showed clear reservoir depletion within the testing
time scale, and the tested reservoir must therefore be a “closed” system. As shown in the
top-structure map in Fig. 10, the reservoir comprises a triangular northern section and a
rectangular southern section. The colours suggest that these two sections are different
regions within the modelled reservoir; however, both regions were assigned the same
properties, so the reservoir is areally isotropic.
The reservoir’s vertical heterogeneity was modelled according to the well-log and
petrophysical measurements in Fig. 2. Instead of giving the reservoir uniform properties,
a two-layered reservoir model was constructed; both layers had identical porosities but
different permeabilities. The overlying 30ft thick braided-channel sandbody was given a
permeability of 400mD, while the underlying 4ft thick meandering-channel sandbody had
a permeability of 1,000mD. A production well was located according to the seismic
amplitude map in Fig.6, and the reservoir model is shown in Fig. 11.
In order to capture the pressure response in the near-well region with a high-pressure
gradient, as well as the pressure changes due to the reservoir boundaries, the finite element
method was used to construct the reservoir model and the reservoir grid. Fig. 12 shows the
model in 2-D; the reservoir drainage shape is shown on the left, the finite element grid
12 Geological interpretation of well test analysis
Fig. 10. Combining the results of seismic and well test analyses, a reservoir model has been
defined with fault-defined boundaries in which the uncertainty about fault closure has been
constructed from well test analysis. The reservoir area is composed of yellow and pink regions
(see text for details), but these areas can be unified because the reservoir is considered to have
areally isotropic properties.
Fig. 11. Revised 3-D reservoir model, which integrates seismic, well test, well log and
petrophysical data. This model has taken the realistic reservoir’s drainage area and the
formation vertical heterogeneity (layering) into account.
S.Y.Zheng et al. 13
Fig. 12. Constructed 2D
reservoir model and reservoir
grid based on seismic data and
the results of well test analysis.
(a) reservoir model; (b) finite
element grid around the well;
and (c) combined reservoir
model and grid.
Fig. 13. Transient pressure
distributions generated from
well-test flow simulations.
Radial flow (a) followed by
linear flow (b, c) due to the
parallel faults which define the
reservoir’s boundaries. There
is then a transition from linear
flow to full reservoir depletion
(d, e): pseudo- steady-state
flow states are clearly
captured.
Fig. 14. Flow regime match
corresponding to the pressure
distributions in Fig.13. The
dotted points are DST
pressures and associated
derivatives with well-bore
storage, while solid lines are
analytical solutions with zero
well-bore storage. Vertical axis,
i.e. Delta m(p), is calculated
pseudo-pressure change. Radial
flow, linear flow due to parallel
faults and “closed” reservoir
depletion are all matched on
the pressure derivatives.
14 Geological interpretation of well test analysis
Fig. 15. The final match of the full DST-1 testing history corresponding the flow regime match
shown in Fig.14.
around the well in the centre, and the two together are shown on the right.
Well Test Numerical Simulation
With the reservoir model described above, a well test was simulated using the same
time and rate schedule as in DST-1. This comprised an initial draw-down and an initial
pressure build-up, followed by a main-flow period and a final pressure build-up. The total
simulation time was about 66 hours with 1,343 time steps. Gas properties and composition
were generated using correlations, according to the gas gravity and Z factor derived from
the PVT lab. Skin factors of 7 and 7.6 were assigned to the two reservoir layers, with
associated damaged zones having radii of 1.5ft and 1.8ft, respectively. The simulation was
first tuned to match the flow regimes identified from DST-1; then the skin and well-bore
storage were considered to match the full test history.
WELL TEST INTERPRETATION
Fig. 13 shows the simulated pressure distributions from the reservoir model. Red colours
represent high-pressure values, while yellow, green and blue represent decreasing pressures.
After well-bore storage, radial flow around the well is initiated (Fig. 13a). Then linear
flow starts (Fig. 13b), followed by pseudo- steady-state flow due to reservoir depletion.
As shown in Fig.14, the flow regimes correspond to the pressure distributions in Fig. 13.
The dotted red and blue points are DST pressures and derivatives associated with well-
bore storage, while solid blue and red lines are analytical solutions with zero well-bore
storage. Radial flow, linear flow due to parallel faults and “closed” reservoir depletion are
all matched on the pressure derivatives. These together are a result of a two-layered reservoir
model with variable properties and irregular geometry. This interpretation is further
S.Y.Zheng et al. 15
confirmed by the full test history match using the defined model and the corresponding
derived parameters (Fig. 15).
These results are closer to a realistic interpretation with a better representation of the
reservoir’s geology, heterogeneity and the dynamic performance of the reservoir. They are
more acceptable than those from the preliminary interpretation.
CONCLUSIONS
1. Using data from an appraisal well in the Gulf of Thailand, we show how an integrated
approach to well test interpretation can greatly reduce inherent uncertainties. In a defined
geological background, numerical forward modelling, which integrates seismic,
petrophysical and transient pressure data yields more realistic results and improved reservoir
characterisation.
2. Test analysis and interpretation are two different steps. Analysis yields a non-unique
solution, and integration of data from relevant disciplines is required to further explain or
interpret the physical meaning of the results. Well test forward modelling and numerical
simulation are essential for this integration.
3. From our case study, we show how geological interpretation of a well test can enhance
the role of geology in reservoir modelling and also bridges the gap between dynamic
reservoir performance and a static description. A transient pressure test is only useful
when such an approach has been made.
ACKNOWLEDGEMENTS
Shell, Norsk Hydro, ExxonMobil, Unocal, Phillips, Wintershall and BP are
acknowledged for funding this work within the GEOTIPE Project, and Unocal Thailand
in particular is acknowledged for providing the data and permission to publish this paper.
Edinburgh Petroleum Services Ltd (EPS) are thanked for the provision of software to
undertake this study. Journal review was by P. Wong (Veritas) and R. Horne (Stanford
University) whose comments on a previous version are acknowledged with thanks.
REFERENCES
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