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3rd SPWLA-INDIA Symposium, Mumbai, India Nov 25-26, 2011
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Prospect Evaluation in Marginal Reservoirs by Integration of
Formation Tester Interval Pressure Transient Tests and Well
Performance Analysis: A Case Study from Onshore India
Rao, K.S1; Murthy, K.S
1; Tellapaneni, P.K
2; Ojha, A.
2; Jackson, R. R.
2; Nahar, S
2
1 Oil and Natural Gas Corporation Ltd. 2 Schlumberger
Copyright 2011, held jointly by the Society of Petrophysicists and Well Log Analysts (SPWLA) and the submitting authors.
This paper was prepared for presentation at the SPWLA 3rd Annual Logging Symposium held in Mumbai, India November 25-26, 2011.
ABSTRACT
Field development decision making increasingly needs input from cost-effective technologies and methods to
reliably evaluate reservoir prospects and assess well productivity in undeveloped or marginal reservoirs.
Conventional production or drillstem tests (DSTs) have traditionally been used by operators to decide the
commercial viability of any new prospect. However, in marginal reservoirs, conventional testing carries the risk of
inconclusive or unreliable operations. Using wireline-conveyed formation testers to conduct interval pressure
transient tests (IPTTs) provides dynamic reservoir information and is increasingly employed for mitigating risks
associated with conventional well testing operations.
We describe, by the aid of a case study, the utility of IPTT and analysis of pressure transient data for the assessment
of well productivity and flow potential. Absolute open-flow potential (AOFP) is determined by analyzing pressure
buildup data using a single-point inflow performance relationship (IPR) method. The results are consistent with
analysis of flow-after-flow (FAF) tests performed during these operations. With this formation dynamics
information, a conventional test is simulated to access the risks associated with a conventional test in terms of
effective wellbore and formation cleanup. Various sensitivities were performed on the fluid type and stimulation
scenarios. For some well test scenarios, although the well would flow to surface, production cleanup would be
incomplete even after relatively long flow periods, rendering planned well tests suboptimal and potentially
producing inconclusive or low-confidence results.
Integrating this evaluation methodology in any exploratory workflow can help improve prospect evaluation and
optimize testing operations, leading to potential cost savings for the operator and a better decision-making process
for field development.
3rd SPWLA-INDIA Symposium, Mumbai, India Nov 25-26, 2011
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INTRODUCTION
The Krishna Godavari basin (Fig. 1) in India has been under hydrocarbon exploration since late 1950s, but it was
only after 1978 when an increase in exploration activity led to several oil and gas discoveries.
Fig.1: Geographical location of the Krishna Godavari basin
The Krishna-Godavari basin is a proven petroliferous basin with commercial hydrocarbon accumulations in the
oldest deposits of Permian-Triassic Mandapeta sandstone on land to the youngest Pleistocene channel levee
complexes in deep water offshore. The basin is endowed with four petroleum systems, which can be classified
broadly into two categories, Pre-Trappean and Post-Trappean, in view of their distinct tectonic and sedimentary
characteristics. The basin is an established hydrocarbon province with a resource base of 1130 MMT, of which, 575
MMT has been assessed for the onshore region.
Owing to the continuously increasing gap between the demand for and supply of hydrocarbons in India and the huge
potential of the basin, exploration activities are at an all-time high in the region. Under the aggressive exploration
drive by the operator, Well A, an exploration Class „B‟ well, was drilled vertically with an objective to explore
sands with in Eocene (Pasarlapudi Formation) and Paleocene (Palakollu Formation) sequences. Petrophysical
evaluation showed development of a number of sand packs within this well, but the zone of interest was limited to a
4-m interval between XX08 m and XX12m. Formation evaluation was then conducted to identify the resource
potential of this sand.
WORKFLOW
Initial Evaluation. Initial formation evaluation was done by a triple-combo run in Well A, including gamma-ray,
laterolog resistivity, and density-porosity measurements (Fig. 2). Initial log analysis showed a 4-m sand
development (XX08 m–XX12 m), out of which a 1-m interval (XX09 m–XX10 m) displaying good porosity was
selected for further evaluation.
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Fig. 2: Basic petrophysical logs delineating the zone of interest
Wireline Formation Tester Pressure and Fluid Identification
Based on the openhole log evaluation, it was decided to acquire pressure and fluid information in the selected zone
of interest by means of a wireline formation tester (WFT). Pressures in the zone of interest were found to be higher
than the expected hydrostatic gradient, with mobilities ranging from 0.36 to 17.6 mD/cP. Fluid identification using a
resistivity cell showed a sharp increase in the flowline resistivity response over the course of pumping along with a
pronounced scattering effect, which suggested the possibility of hydrocarbons. A downhole sample was collected
after pumping 22 liters of formation fluid (Fig. 3). Surface draining of the sample showed it to be predominantly
gas. A resistivity cell works on the principle of potential difference measured across electrodes and the measurement
is dominated by the continuous phase. Therefore, in certain hydrocarbon-water scenarios, the measurement might
not discriminate between a continuous phase of hydrocarbons with water as the dispersed phase and pure
hydrocarbon. Also, the electrodes can be wetted by a preferential phase and therefore may respond to the wetting
phase and may not respond to the fluids we might be interested in. Therefore, sampling with a resistivity cell alone
may provide “surprises” when samples are drained on surface. The presence of a downhole optical fluid analyzer
would have proved advantageous here because the contamination could be monitored and a better sample could
have been collected.
Fig. 3: Pressure and Resistivity versus Time plot
Although the presence of hydrocarbon was confirmed by analysis of the acquired data, the main questions to be
answered were
1. Is the 1-m zone worth investing money on initial casing and the completions required for testing?
2. Would this zone be productive enough to be declared as a commercial discovery?
To this end, it was decided to do an interval pressure transient test (IPTT) to determine well deliverability.
3rd SPWLA-INDIA Symposium, Mumbai, India Nov 25-26, 2011
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Interval Pressure Transient Testing
Conventionally, drillstem tests (DSTs) are used to prove the commercial viability of a reserve. The important well
test objectives may be grouped into the following four categories:
Initial reservoir pressure
Skin (quality of completion)
Permeability and zone deliverability
Fluid properties and distribution
But prior to investing millions of dollars in a costly well test operation, it is important to analyze the extent to which
the well test objectives can be realized versus the cost involved. As a result, it was decided to use IPTT as a „go–no
go‟ for the DST (Samuelson et al., 2009)
An IPTT is the interpretation of the pressure transients generated by the production of the reservoir fluids from a
particular zone straddled between a pair of packers. Typically an IPTT is conducted using wireline-conveyed
formation testers that include straddle packers, downhole pumps, and optical fluid analyzers in the string. When at
the zone of interest, the straddle packers are inflated using downhole pumps. Upon inflation, a 1-m interval is
isolated from the wellbore. Using downhole pumps, the formation fluids are produced from the interval and cleanup
is monitored by the downhole fluid analyzer. Once representative formation fluids start to flow, the pumps are
stopped and a pressure buildup is recorded until a radial flow regime is observed. Using various analytical models,
the pressure transients during the drawdown and buildup are analyzed to estimate reservoir parameters such as
permeability and skin. These estimates can be used to calculate the productivity potential of the zone (Fig. 4).
Fig.4: IPTT interpretation workflow
IPTT Analysis in Well A. As mentioned previously, a 1-m zone was selected for an IPTT (XX09 m–XX10 m) based
on mobility and porosity characteristics. The main objective of performing IPTT analysis was to estimate the
absolute openhole flow potential (AOFP) to gauge deliverability and thus the commercial viability of the well.
The toolstring for the operation consisted of a set of straddle packers, an optical fluid analyzer, pumpout module,
and sample chambers for the downhole collection of fluid samples (Fig. 5).
The 1-m zone was isolated using the straddle packers. After packer inflation, a small-volume pretest was performed
using the pumpout module followed by an extended cleanup and main flow period at a constant downhole flow rate.
Downhole optical fluid analyzer response showed a gas breakthrough after 1 hour of pumping.
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Fig. 5: IPTT toolstring
Continued pumping showed an increasing gas fraction with time (Fig. 6). After flowing for 1.5 hours and pumping
120 litres, flow was stopped to record a main buildup, which stabilized to a pressure of ~7058 psia. The buildup was
followed by a flow-after-flow test during which the fluid was pumped at various rates equivalent to the downhole
rates of 6.1, 9.6, and 13.7 B/D. This was succeeded by a final buildup that stabilized at a pressure of 7058.8 psia
(Fig. 7).
Fig. 6: Optical fluid analyzer response with time
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Fig. 7: Pressure versus time plot of IPTT station
IPTT Interpretation Results
The buildup periods for the station were analyzed using a limited-entry vertical well model in an infinite-acting
homogenous reservoir (Fig. 8).
Fig. 8: Pressure Time plot of IPTT station
Only the buildup periods were analyzed, because the flow period was noise affected. Both the main and final
buildup pressure derivatives are consistent (Fig. 9) and are expected to show comparable results. Hence, only the
final buildup was used for analysis.
Fig. 9: Comparison of main and final buildup derivatives
Based on the log-log flow regime analysis plot of the-pressure and-pressure derivative shown in Fig. 10, an infinite-
acting radial flow regime (IARF) was identified.
0.1 1 10 100 10001E+5
1E+6
1E+7
FinalBuildUp (ref)
MainBuildUp
Log-Log plot: dm(p) and dm(p)' normalized [psi2/cp] vs dt
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Fig. 10: Log-log plot showing limited entry effects and IARF
After identification of IARF, an analytical model (black line) was used to describe the observed pressure derivative
trend (red dots). A standard vertical well model was chosen with an infinite homogeneous reservoir and constant
wellbore storage. As can be seen in Fig. 11, the modelled pressure history (observed data in blue; fitted model in
red) shows a good match to the actual pressure, thus validating the pressure derivative fit.
Fig. 11: Pressure derivative and history match
Absolute Open Flow Potential computation. Using the modeled results from the transient interpretation described
previously, AOFP was estimated by two methods, which are described as follows.
i) Single-point AOFP estimation: For using the single-point AOFP estimation, the following parameters are
required:
Average formation pressure
Net hydrocarbon pay thickness and net pay thickness based on permeability and porosity
Fluid properties
External radius
3rd SPWLA-INDIA Symposium, Mumbai, India Nov 25-26, 2011
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AOFP is estimated based upon the reservoir parameter (flow capacity) and skin obtained from transient analysis of a
single buildup period. Hence the technique is called „single-point‟ AOFP estimation, also referred as „Darcy IPR‟.
The expression used for estimating AOFP is the pseudo pressure approximation to the pseudo steady-state flow of
gas (Lee and Wattenbargar, 1996), which is as follows (in oilfield units):
MMSCF/D (1)
Reducing Equation 1 in quadratic form and solving for the positive root gives the AOFP (Karthik et al., 2008; Lee,
1982).
In this case, AOFP was calculated with and without rate-dependent skin and zero formation damage skin. As we
were dealing with a gas bearing formation, the AOFP values determined using the rate dependent skin was
considered more realistic.
ii) C & n method: The C & n method for gas case is described in the following equation:
(2)
Three flowing pressures and corresponding flow rates in the flow after flow periods (Fig. 12) were used to estimate
AOFP. Plotting the pressures and flow rates on a log-log plot, values of C and n are estimated as shown in Fig. 12.
Fig. 12: Estimating C and n using log-log plot
The AOFP values determined independently from both computation methods as mentioned above were comparable
and the flow potential was deemed acceptable to declare the well a commercial discovery. But did the well have
enough fluid influx for an effective cleanup? To address this, further investigation was conducted using numerical
simulators to assess the cleanup profiles.
3rd SPWLA-INDIA Symposium, Mumbai, India Nov 25-26, 2011
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NUMERICAL SIMULATION (Andre et al, 2005) OF PRODUCTION SCENARIOS
To predict the well behaviour during DSTs, numerical simulations were conducted for different production
scenarios. Table 4 outlines the grid generation and wellbore model creation (Fig. 13) parameters:
Modeled interval 20-m interval (XX00 m–
XX20 m)
Grid 51 × 51 × 40
Production packer setting
depth
XY90 m
Tubing shoe depth XX00 m
Perforated interval XX09.3 m–XX10.3 m
Pay thickness 1.0 m
Depth of invasion 10 ft
Table 4: Simulation grid and wellbore model parameters
Fig. 13: Simulation grid and wellbore model generation
Formation and fluid parameters input into the model are outlined in Table 5. These parameters were used to derive
relative permeability and formation volume factor curves.
Reservoir pressure 7060 psia
Reservoir temperature 234 degF
Fluid type Gas
Gas gravity 0.65
Gas viscosity 0.031cp
Rock type Sandstone
Effective porosity 20%
Connate water saturation 30%
Table 5: Formation parameters
Once the relevant parameters were input into the model, well performance was simulated by initially flowing the
well at a fixed choke size. It was observed that the tubing cushion fluid started offloading without any gas influx
even after 10 hours of flow with a corresponding drop in pressure. The choke size was then doubled which resulted
in gas breakthrough. However, even after a considerable period of time, the wellbore volume could not be
completely offloaded and no stabilization was observed in the gas rate (Fig. 14). Pressure transient analysis cannot
be performed in such a scenario leading to inconclusive results. In comparison, the IPTT analysis is not influenced
by well offloading effects since flow rate is measured downhole along with the pressures.
3rd SPWLA-INDIA Symposium, Mumbai, India Nov 25-26, 2011
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Fig. 14: Simulation of wellbore cleanup
To understand the performance of the well under damaged/stimulated conditions, various sensitivities were
simulated under positive and negative skin influences. It was observed (Fig. 15) that well performance decreased
drastically with damage (positive skin) while no significant improvement in the cleanup response could be observed
after stimulation (negative skin).
Fig. 15: Well performance simulated under various damaged/stimulated scenarios
To understand the significance of the accurate knowledge of the fluid PVT properties, sensitivities were attempted to
compare wellbore cleanup profiles for dry gas, light oil, and wet gas (condensate/gas ratio (CGR): 0.2 STB/Mscf).
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A significant reduction in well performance was observed with the increase of heavier fractions in the formation
fluid (Figs. 16 and 17).
Fig. 16: Well performance comparison between dry gas and light oil
Fig. 17: Well performance comparison between dry gas and wet gas
Using the workflow described in the paper, it was ascertained that attempting a full-scale DST in the well would not
yield conclusive results owing to the ineffective cleanup, even after long flow periods. Based on the results, the
operator decided not to go ahead with a DST, thus saving the substantial investments required for the initial
completion and casing.
CONCLUSION
Increasing hydrocarbon demand has pushed the exploration drive to new frontiers involving the tapping of resources
in low-quality reservoirs, which were previously deemed uneconomical. An early assessment of the reservoir fluids
and potential production is imperative to minimize the economic risks in such expeditions. The completion decisions
have historically been based on the results of well testing, but low-permeability well tests may not be economical
and may not provide conclusive results.
In an exploratory scenario, the presented workflow can be integrated to the prospect evaluation strategy, which can
lead to an intelligent optimization of the well testing plans (Whittle et al., 2003). This will lead to potential cost
savings and a better field development plan.
3rd SPWLA-INDIA Symposium, Mumbai, India Nov 25-26, 2011
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ACKNOWLEDGMENTS
The authors wish to thank Oil and Natural Gas Corporation Ltd. and Schlumberger for permission to publish this
paper.
NOMENCLATURE
C = wellbore fluid compressibility, bbl/psi
hw = perforated zone thickness, ft
zw = distance from midpoint of perforation to the bottom of zone, ft
Pi = initial reservoir pressure, psia
k = permeability, mD
kz/kr = permeability anisotropy
q = AOFP, Mscf/D
kh = flow capacity, mD.ft
Pres = reservoir pressure, psia
= gas viscosity, cP
T = reservoir temperature, R
Z = gas compressibility factor
re = drainage area radius, ft (1177.5ft ~ 358 m for 100-acre drainage area)
S = skin factor
D = rate dependent skin, (Mscf/D) -1
= average reservoir pressure, psia
pwf = well flowing pressure, psia
REFERENCES
Samuelsen, H.E., Gisolf A., et al, „Extending the Limit: Interval Pressure Transient Testing in Low-Permeability
Reservoirs in the North Sea‟; SPE 124842, SPE Annual Technical Conference and Exhibition, New Orleans,
Louisiana, USA, 4-7 Oct, 2009
Lee, J.; Wattenbargar, R.A., „Gas Reservoir Engineering‟, Richardson: SPE Textbook Series, Volume 5; 1996
Karthik, K.N.; Joshi, S., et al., , A new method for gas well deliverability potential estimation using miniDST and
single well modeling – Theory & examples, SPE 113650, Indian Oil and Gas Technical Conference, Mumbai, India,
46 March,2008
Lee. J, , Well Testing, Dallas: SPE Textbook Series, 1982
Andre, C.de; Canas,J.A.,„ Rigorous Approach for Viscous-Oil Productivity Forecast Before Well Completion‟-
SPE-94837, SPE Latin American and Caribbean Petroleum Engineering Conference, Rio de Janerio, Brazil,20-23
June,2005
Whittle, T.M.; Lee, J., et al, „Will Wireline Formation Testers Replace Well Tests?‟ SPE 84086 , SPE Annual
Technical Conference and Exhibition, Denver, Colorado, USA, 5-8 October, 2003