SPWLA 58 th
Annual Logging Symposium, June 17-21, 2017
Mona Al-Rushaid, Hamad Al-Rashidi, and Munir Ahmad, Kuwait Oil Company; Hamid Hadibeik, Mehdi Azari,
Waqar Khan, Sami Eyuboglu, Mahmoud Kalawina, Sandeep Ramakrishna, Luis Quintero, Rafael Vasquez, and
Reinaldo Angulo, Halliburton
Copyright 2017, 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 58th Annual Logging
Symposium held in Oklahoma City, USA June 17-21, 2017.
ABSTRACT
Relative permeability curves were estimated with downhole pressure-transient analysis of mini-drillstem tests (mini-DSTs) and well-log-derived saturations. The relative permeability values in this sandstone reservoir were validated through history matching of production data in the oil-producing interval. during pumping out. Permeability to oil was determined to be 1.6 Darcy; whereas, the permeability to water was 60 millidarcy (md). The final point above the oil-water contact (OWC) provides oil and water permeability value estimates of 170 and 440 md, respectively. Based on the saturation and pressure measurement ranges, an uncertainty envelope was generated for the relative permeability curves. Finally, history matching of production data was performed with a multiphase flow simulation to validate the relative permeability results.
The new approach was based on performing mini-
DSTs in the free-water, oil, and oil/water transition zones. Analyses of the mini-DST buildup tests provided absolute formation permeability, end point of relative permeability to both oil and water, and curvature of the relative permeability data.
Additionally, resistivity, dielectric, and nuclear magnetic resonance (NMR) logs were used to determine irreducible water, residual oil, and transition zone saturations. Combining all of these downhole measurements provided the relative permeability curves.
Relative permeability curves estimation at reservoir conditions is a key task for successful reservoir modeling and production data history matching. The relative permeability data estimated from core analysis might cause concern regarding representativeness, and adjustments are typically necessary for successful production forecasting.
Therefore, this new method can be a step forward in terms of overcoming such challenges and estimating relative permeabilities.
INTRODUCTION
The method was applied in a well with a 35-ft oil column. Because of high porosity (~33%) and permeability (> 1 Darcy), the transition zone was short (approximately 5 ft). Four mini-DSTs were performed successfully. First, a pressure buildup
(PBU) test was analyzed in a free-water zone. This analysis provided the absolute formation permeability of 6.8 Darcy. The second PBU test was performed in the oil zone, with the oil permeability evaluated to be 4.4 Darcy. From openhole logs, the irreducible water saturation
(S w
) was estimated to be 7%. The third mini-DST point was in the transition zone. A weighted average density approach was used to calculate the individual phase rates from the total measured rate
When multiphase fluids flow in a reservoir, the flow rate of each phase depends on the effective permeability of that phase (Alkafeef et. al, 2016).
Effective permeability is obtained from absolute permeability of a reservoir multiplied by the relative permeability. Although absolute permeability is a function of reservoir pore geometry and does not change with fluid type, relative permeability is a fluid-dependent parameter and mainly depends on fluid saturation, pore geometry, viscosity, and surface tension
(Goda and Behrenbruch, 2004).
Relative permeability is important during field development and secondary-oil recovery processes. Water flooding plans and injector and
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SPWLA 57 th
Annual Logging Symposium, June 25-29, 2016 producer well assignments are not successful without a good estimation of relative permeability.
Additionally, production forecasting is possible through a reservoir model that includes proper number of core samples analyzed in the laboratory was not sufficient to provide appropriate relative permeability and capillary pressure curves for the dynamic reservoir model (Hetherington, 1961). relative permeability (Galley, 2016). Downhole relative permeability estimation was determined to be an alternative to core sample analysis,
Conventional measurements of relative and it was executed in the Burgan middle sand. permeability include using core data analysis in the laboratory (Honarpour and Mahmood, 1988).
This type of measurement has been widely used in the industry; however, it has shortcomings
(Anderson, 1987; Cuiec, 1975; Keelan, 1971;
Kokkedee, et al. 1996; Mungan, 1972; Richardson et al., 1954). Transferring the core from downhole conditions to surface removes the confined pressure and stresses. Additionally, cleaning and processing the core for testing changes the pore structure of the core. Moreover, the fluid used in the laboratory is not identical to the downhole insitu fluid. As such, core measurements might not be always representative of in-situ reservoir relative permeability (Bennion and Thomas, 1991;
Beal and Nunes, 1984; Crotti and Rosbaco, 1998;
Fig. 1 Great Burgan field map (Sorkhabi, 2012).
DOWNHOLE RELATIVE PERMEABILITY
ESTIMATION
Chen and Wood, 2001; Heaviside et al., 1983;
Honarpour et al., 1986; Huang and Honarpour,
1996; Rose, 1980, 1951, 1987; Nguyen et al.,
2005).
Considering the previously mentioned concerns, there is a need to estimate relative permeability using undisturbed downhole measurements
(Angeles et al., 2010).
Workflow. Formation tester measurements were used to estimate relative permeability based on the workflow depicted in Figure 2. The inputs of this workflow were pressure measurements from mini-DSTs in oil, water,
FIELD BACKGROUND and transition zones; S w
logs; NMR logs; and core data, if available. The followings steps describe Figure 2:
The Greater Burgan field (Figure 1), discovered in
1938, is located in southeast Kuwait and comprises the
Magwa, Ahmadi, and Burgan fields, constituting the largest known siliciclastic oil reservoir on Earth. The
1) Determine the oil and water relative permeability from oil and water permeability calculated from pressure transient analysis (PTA) of buildup tests.
The absolute permeability value is calculated from size of the field itself, 20 km wide and 37.5 km length, provides an estimate of its large extension. The three main formations of Wara, Burgan, and Mauddud have a global total thickness of 1,500 ft with complex behaviors resulting from fluvial/tidal depositional the buildup PTA in free water level (FWL). If the well did not encounter FWL, the absolute permeability is obtained from the core. Dividing the oil and water relative permeabilities by the absolute permeability provides the relative settings. Because of these complexities, it is necessary to generate a reservoir model consisting of several rock types, ranging from clean coarse and massive sands to permeability values. Figure 3 illustrates the steps for this part.
2) Calculate the residual water and oil; this requires silty or shaly sandstones and silts. Each rock type has been characterized by its petrophysical properties and reservoir behavior (shale volume, porosity, permeability, and S w
). Dynamic data are necessary because of these variations and the distribution of sediments to help improve the model. However, the the S w
from resistivity-based logs and/or NMR logs. Residual S w
is estimated in the oil zone, and residual oil saturation is estimated from below the
OWC.
3) To determine the curvature of relative permeability, multiphase permeability of oil and
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SPWLA 58 th
Annual Logging Symposium, June 17-21, 2017 water is measured in the transition zone. Figure 4 shows how to obtain relative permeability of oil and water in the transition zone. Increasing the number of mini-DSTs in the transition zone adds confidence to the model.
4) History matching of pressure data is performed to validate the estimated relative permeability curves.
Fig. 4 Estimation of relative permeabilities from mini-
DST measurements in the transition zone.
Fig. 2 Estimation of relative permeability curves with integration of formation tester and well logs.
Assumptions in the Workflow to Estimate Downhole
Relative Permeability. The main assumption when using this workflow is that relative permeability is measured for one rock facies. Therefore, the absolute rock permeability is constant. Based on the geological data, this assumption was valid in the Burgan middle sand for which the test was performed. During fluid pumpout in the transition zone, the flowrate was maintained at a steady rate; consequently, the water-oil ratio was constant at each station. Additionally, the formation fluid viscosity, which is necessary to calculate permeability in PTA, is estimated by knowing the fluid gas-oil ratio (GOR), pressure, temperature, and density. Another unknown factor needed for PTA is the reservoir payzone height that is open to flow (h). This height is not the same as the tool probe height and should be estimated from vertical interference tests or well logs. Well logs, such as gamma ray (GR) and density, were used in the Burgan reservoir to determine the payzone open to flow.
Calculation of S w
from Well Logs. S w
was estimated using NMR, dielectric, and resistivity logs. Resistivitybased interpretation methods use the Archie model (Eq.
1) to identify oil- and water-bearing intervals and
Fig. 3 Determining the end points of relative virgin zone. permeability curves from formation-tester measurements. provide highly accurate saturation estimates in the
∅
(1)
3
The formation water resistivity (R w
) value was obtained based on analysis of water samples taken from the
Burgan formation, the saturation exponent (n) and the cementation exponent (m) values used are based on core analysis results, “a” is a constant derived empirically, R t
is formation resistivity, and Ø is

SPWLA 57 th
Annual Logging Symposium, June 25-29, 2016 porosity.
Figure 5 shows the resistivity-based saturation calculation. The hydrocarbon-bearing zone has a minimum S w
of 4%; the transition zone has a minimum
S w
of 40%, which is followed by a long interval with residual oil below OWC in clean sand. The bottom zone is interpreted as a 100% water-bearing zone.
Fig. 6 Comparison between the total porosity from neutron density and water-filled porosity from dielectric is shown in fifth track. S w
obtained by the Archie model and S xo
obtained by dielectric saturation analysis are presented in the last two tracks.
Fig. 5 Wireline logs and resistivity-based S w
. The first track is the dry minerals present in the reservoir. The second track is measured depth (MD). The third track is
GR and caliper. The forth track is an array of resistivities. The fifth track is density-neutron, Pe, and porosity. The sixth track is fluid saturation. Oil, transition, and water zones have been labeled as well.
The objectives of the NMR log were to identify the fluid properties and determine the formation total and effective porosity, irreducible volumes, and clay-bound water (Khan et al., 2015). Figure 7 shows that the amount of S w
identified by NMR appears higher than
S w
calculated based on deep resistivity and dielectric tools. Variation in depth of investigation measured by each tool and invasion causes the NMR tool to show more S w
.
To help reduce uncertainties for S w
calculation, particularly in oil and water zones, and uncertainty about the end points of relative permeabilities, dielectric and NMR logs were also run in the reservoir.
The dielectric log had a primary objective to identify the water-filled porosity and also to identify the residual hydrocarbon. Figure 6 shows a comparison between resistivity-based and dielectric-based saturations. The separation between the saturation of uninvaded zone obtained by deep resistivity and the flushed zone obtained by dielectric also indicates the invasion and depth of the OWC.
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SPWLA 58 th
Annual Logging Symposium, June 17-21, 2017
Pumpout Depth 1: Water Zone. The first pumpout point was in water. The objective of this point was to determine the absolute permeability for this sand; hence, it was taken below FWL. The measured density by the formation tester (1.08 g/cc) indicated a water sample of 160,000-ppm salinity. Figure 9 shows the pumpout point on a composite plot. The interval open to flow for this zone was 10 ft.
Fig. 7 Integrated presentation of conventional logs,
NMR, and dielectric analysis.
Fig. 9 Wireline logs for the water sample zone.
Designing Formation Tester Pumpouts. A formation tester with a simple circular probe was used to perform the mini-DST because of large mobility that was expected in the reservoir. Based on the logs, four points were selected for fluid pumpout. Figure 8 shows the pumpout points.
A total of 150 L was pumped during this drawdown test. Figure 10 shows the log-log, semi-log, and simulation match along with the results of the mini-
DST. Absolute permeability, k, was determined to be
6877 md, with a corresponding kh of 68 773 md-ft.
Fig. 10 Log-log, semi-log, simulation match, and the analysis results for mini-DST at the water zone.
Fig. 8 Pumpout stations are depicted by black dots on the fourth track.
5
Pumpout Depth 2: Oil Zone. Pretest pressure measurements indicated an oil gradient of 0.338 psi/ft, corresponding to a fluid density of 0.78 gm/cc, which correlated well with the density of 0.78 g/cc measured at this sampling depth during the pumpout. The oil gradient obtained from the pretest pressure measurements was confirmed by the oil pumpout at this

SPWLA 57 th
Annual Logging Symposium, June 25-29, 2016 depth. Figure 11 shows a pressure gradient plot with residual pressures correlated with openhole logs. Figure
12 shows the pumpout point on a composite plot. The objective of this point was to determine the end point of the relative permeability curve at irreducible S w
. This saturation was computed to be 7% based on the openhole logs.
A total of 130 L was pumped. Fluid density was measured as 0.78 g/cc by the sensor located at the outlet of the pump. Based on the well logs, the height (h) influencing the pressure was determined to be 13.2 ft.
Figure 13 shows the log-log, semi-log, and the simulation match along with the results of the mini-
DST. Absolute permeability, k, was determined to be
4441 md, with a corresponding kh of 58 617 md-ft.
Fig. 12 Wireline logs for the oil sample zone. The area that is open to flow (h) is 13.2 ft.
Fig. 13 Log-log, semi-log, simulation match, and the analysis results for mini-DST at the oil zone.
Fig. 11 Pressure gradient across the oil zone. Track 1: pressure gradient and GR. Track 2: residual pressures as a quality indicator of pressure gradient. Track 3: resistivity logs. Track 4: neutron and density logs.
Pumpout Depth 3 and 4: Transition Zone. The objective of the pumpout in the transition zone was to define the curvature of the relative permeability curve. A weighted density average approach was used to compute the individual phase rates from the total rate measured while pumping out by means of a wireline formation tester. Figure 14 shows the pumpout point on a composite log plot.
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SPWLA 58 th
Annual Logging Symposium, June 17-21, 2017
Fig. 14 Wireline logs for transition zone and location of the probe for pumpout.
A total of 139 L was pumped at this point. Fluid density was measured at 0.808 g/cc by the density sensor located at the outlet of the pump, indicating a mixture of oil and water flowing. Based on the well logs, the height (h) influencing the pressure was determined to 33.5 ft and S w
was estimated at
35.49%. Figure 15 shows the log-log, semi-log, and simulation match along with the results of the mini-DST. Permeability to oil, k o
, was determined to be 1636 md, and the permeability to water, k w
, was determined to be 66.7 md. Similarly, another pumpout was performed in the transition zone.
Based on the well logs, the height (h) influencing the pressure was determined to be 52.5 ft, and the
S w
was estimated at 65.6%. The S w
in these two zones is the mean values from saturation histograms for each tested interval. Figure 16 shows the log-log, semi-log, and simulation match along with the results of the mini-DST.
Permeability to oil was determined to be 173 md, and permeability to water was determined to be
414 md.
Fig. 15 Log-log, semi-log, simulation match, and the analysis results for mini-DST in the transition zone.
Fig. 16 Log-log, semi-log, simulation match, and the analysis results for mini-DST in the transition zone.
Relative Permeability Curves. The downhole relative permeability estimation is described in detail. After following the workflow, the relative permeability data obtained from the mini-DST analyses were upscaled to represent the entire productive interval contributing to each flow zone. This normalized relative permeability curve, shown in Figure 17, was defined with four points, one in the irreducible S w
zone, two in the transition zones, and one in the FWL. Figure 17 shows a mixed to water-wet reservoir rock.
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SPWLA 57 th
Annual Logging Symposium, June 25-29, 2016 the pressure would be a result of the probe geometry.
This skin was carried over to the oil zone.
Fig 17 Relative permeability obtained from mini-
DST analysis.
Fig. 18 Fluid saturation initialization to mimic the invasion profile computed from the simulation.
To validate the relative permeability curve, a model was set up in reservoir simulation software and an invasion profile was computed through resistivity measurements at different depths of investigation radially into the formation. A radial profile of invasion was determined from various depth of investigation. Table 1 tabulates the computed invasion profile.
Because the saturation changed from 100 % water near the wellbore to irreducible S w
moving farther away from the wellbore, as shown in Table 1, history matching the pumpout allowed for an independent validation of the relative permeability curves computed from the mini-DSTs.
S w
, % Invasion Radius, in.
100 3.5
34 5
17.6 10
14.5 20
11.7 30
9.5 60
7.7 90
By rate constraining the model, if the relative permeability curves were correct, it should be possible to predict the same pressure response as observed during the pumpout. Figure 19 shows the history match for the pumpout in the oil zone. The model was constrained to the production rate and accurately predicts the bottomhole pressure throughout the pumpout, validating the computed relative permeability curves.
Table 1: Invasion profile computed from a resistivity log at the oil zone.
The computed invasion profile was used to initialize the grid saturations (Figure 18). Figure 18 shows a crosssectional view of the grids. The model was initialized with a permeability of 4400 md, as computed from the mini-DST at the oil zone. The permeability anisotropy, k z
/k r
, was assumed to be 0.8. It was initialized to a reservoir pressure of 1,954 psi, as computed from the mini-DST. To account for the additional pressure drop associated with a probe, the production in the water zone was matched to back-calculate a skin. The underlying assumption in this approach was the presence of negligible formation damage. Any additional skin necessary to match the production with
Fig. 19 History matching of the pressure response observed during pumpout at the oil zone.
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SPWLA 58 th
Annual Logging Symposium, June 17-21, 2017
DISCUSSION
Incorrect Relative Permeability Estimation. The surface laboratory-measured relative permeability cannot duplicate the fluid flow in the reservoir because permeability values. To overcome the uncertainty in saturation, resistivity, dielectric, and NMR logs were run the rock stresses and geometry of any micro fracture in the core will change. Duplicating the reservoir fluid to flow through the core is another issue making laboratory-generated relative to estimate fluid saturation separately. Based on these measurements, an uncertainty envelope was generated for the relative permeability curves shown in Figure 20. permeability less reliable as that determined from downhole flow measurements.
Estimation of saturation, particularly in the transition zone, adds uncertainty to the corresponding relative
An incorrect relative permeability value will change all of the fractional flow from the reservoir in a multiphase flow. Knowing the correct relative permeability helps establish realistic flow rate expectations from a reservoir and hence could prevent costly workover or help with reservoir management decisions concerning the proper enhanced oil recovery method to use. Water flooding a water-wet formation will provide better results than an oil-wet formation. Wettabilityreversal chemicals could be used in conformance technology applications to prevent excessive water production. Not having a good estimate of relative permeability and wettability could make the chemical application less effective.
Method Uncertainty. Varying saturations in the same rock facies are a fundamental requirement of the method described here. It might not be possible to satisfy this condition in every well. In such situations, injection into the formation can be considered. For the case of an oil zone drilled with water-based mud, water can be injected into the reservoir to generate a situation of radially varying saturation into the wellbore. Once a sufficient amount of fluid has been injected into the formation, array-based resistivity logs can be run to compute the saturation profile radially into the wellbore. After obtaining saturations across the injected zone by means of array-based resistivity tools, the injected zone can be produced. Based on the history match of the pressure response observed with the producing rate, it is possible to derive a relative permeability curve for the particular facies across which injection has been performed.
Fig. 20 Uncertainty bounds for relative permeability based on saturation.
This study was performed to obtain the two-phase relative permeability between oil and water. For a threephase relative permeability, it is necessary to use a reservoir that has all the three phases of oil, gas, and water flowing. A gas cap in communication with the oil below it or a saturated reservoir below the bubble point pressure is necessary to obtain three-phase relative permeabilities.
CONCLUSIONS
A new workflow was developed to estimate relative permeability in downhole conditions. The advantages of using this method are based on in-situ measurements that include the actual reservoir fluids and which are performed under reservoir conditions: formation stress, pore pressure, and temperature. The estimated relative permeability represents the entire tested interval with a formation tester.
Payzone Thickness. The thickness of the sand body is important for vertical interference tests. In additional to a formation tester, running high-resolution well logs, such as an imaging tool, can help determine the zonal sand thickness.
Reservoir properties, such as permeability, anisotropy, skin damage, and reservoir pressure, are also obtained by this direct method.
This method does not disturb the core to obtain the relative permeability curve. Issues, such as maintaining
9

SPWLA 57 th
Annual Logging Symposium, June 25-29, 2016 the core integrity, accidental microfracture formation during coring, using the exact fluids present in the reservoir, and accidental wettability changes during core cleaning, are avoided using this direct downhole relative permeability determination. measurements using Design of Experiment and dataweighing inversion: Synthetic and field examples.
Journal of Petroleum Science and Engineering
19–32.
75 (1),
Another beneficial advantage of this direct measurement is the sample size. The relative permeability obtained by core analysis uses a small sample of the reservoir rock, while this in-situ technique uses the entire payzone contributing to the flow and extending into the reservoir up to the radius of investigation.
Finally, this direct relative permeability measurement can be achieved much faster than core derived values because rock and fluid conditioning are not necessary.
Beal Jr., B. A., and Nunes, C. S., 1984. Velocity and
Gravity Effects In Relative Permeability Measurements.
Stanford, California: The Department of Petroleum
Engineering of Stanford University.
Bennion, D., and Thomas, F., 1991. Recent
Improvements in Experimental and Analytical
Techniques for the Determination of Relative
Permeability Data from Unsteady State Flow
Experiments. SPE 10th Technical Conference and
Exposition.
NOMENCLATURE
Chen, A., and Wood, III, A., 2001. Rate Effects on
Water-Oil Relative Permeability. International
Symposium of the Society of Core Analysts, SCA
2001-19. DST = drill-stem test
GR = gamma ray
GOR = gas-oil ratio
MD = measured depth
NMR = nuclear magnetic resonance
PBU = pressure buildup
PTA = pressure transient analysis
OWC = oil-water contact
FWL = free water level
K k ro k rw
= permeability, md
= relative permeability to oil
= relative permeability to water
R w =
R t
A
= formation resistivity
= constant derived empirically m = cementation exponent
 saturation porosity
Crotti, M., and Rosbaco, J., 1998. Relative Permeability
Curves: The Influence of Flow Direction and
Heterogeneities. Dependence of End Point Saturations on Displacement Mechanisms. SPE/DOE Improved Oil
Recovery Symposium, SPE-39657-MS.
Cuiec, L., 1975. Restoration of the Natural State of
Core Samples. 50th Annual Fall Meeting, SPE-5634-
MS.
Galley, S., 2016. Pay Cutoff Definition Based on
Dynamic Reservoir Parameters. SPWLA 57th Annual
Logging Symposium, SPWLA-2016-Y.
REFERENCES
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Brooks-Corey Model to Study Oil-Water Relative
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88538-MS.
Alkafeef, S., Hadibeik, H., Azari, M., and El-Daou, M.,
2016. Effects of Pore Pressure and Two-Phase Flow on
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International Petroleum Exhibition & Conference, SPE-
183136-MS.
Heaviside, J., Black, C., and Berry, J., 1983.
Fundamentals of Relative Permeability: Experimental and Theoretical Considerations. 58th Annual Technical
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Anderson, W., 1987. Wettability Literature Survey-
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Sepehrnoori, K., 2010. Estimation of capillary pressure and relative permeability from formation-tester
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Honarpour, M., Koederitz, L., and Harvey, A., 1986.
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Permeability Measurements: An Overview. JPT 4 (08),
963–966, SPE-18565-PA.
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GeoExPro 9 (1), 42–46.
ABOUT THE AUTHORS
Huang, D., and Honarpour, M., 1996. Capillary End
Effects in Coreflood Calculations. International
Symposium of the Society of Core Analysts, SCA
9634.
Keelan, D., 1971. A Critical Review of Core Analysis
Techniques. 2nd Annual Technical Meeting
72-02-06.
, PETSOC
Khan, W., Balliet, R., Medina, R., Galford, J., Quintero,
L. et al., 2015. A Statistical Approach to Wireline
Formation Testing Provides a Higher Level of
Reservoir Understanding. SPWLA 56th Annual
Logging Symposium, SPWLA-2015-ZZZ.
Mona Al-Rushaid is a Senior Specialist Petrophysicist with 15+ years of experience in field development of the south and east
Kuwait directorate. Al-Rushaid leads a petrophysical project and daily operation logging activities, and leads an FE team for SEK.
Al-Rushaid is also involved in geotechnical studies for Burgan.
Recently, Al-Rushaid led and managed the reservoir characterization unit for the Wara and Burgan reservoir project for the Great Burgan well log data to improve the petrophysical model. Al-Rushaid is interested in becoming the petrophysical adviser for SEK and focuses on subservice uncertainty risk management. Al-Rushaid has several publications and is a member of SPE and SPWLA.
Kokkedee, J., Boom, W., Frens, A., and Maas, J., 1996.
Improved Special Core Analysis: Scope for a Reduced
Residual Oil Saturation. International Symposium of the Society of Core Analysts, SCA 9601.
Mungan, N., 1972. Relative Permeability
Measurements Using Reservoir Fluids.
AIME , 253, SPE-3427-PA.
Transactions of
Hamad Al-Rashidi is the head of the reservoir technology cluster in the Research and Technology group at Kuwait Oil
Company (KOC). Al-Rashidi has more than
10 years of experience in the fluid and rock characterization domain and has been actively involved in the establishment of the
KOC Capability lab in 2016 to conduct and analyze advanced PVT analysis. Al-Rashidi
Nguyen, V., Sheppard, A., Knackstedt, M., and
Pinczewski, W., 2005. The Effects of Displacement
Rate and Wettability on Imbibition Relative
Permeabilities. International Symposium of the Society of Core Analysts, SCA 2005-39. holds a B.Sc. in petroleum engineering from the College of
Engineering and Petroleum, Kuwait and is a member of SPE.
Richardson, J., Perkins, F., and Osoba, J., 1954.
Differences in Behavior of Fresh and Aged East Texas
Woodbine Cores. Petroleum Branch Fall Meeting, SPE-
408-G-MS.
Munir Ahmad joined Kuwait Oil
Company (KOC) in 2014 as a
Specialist Geologist in the Subsurface
Team of Research and Technology
Group. Before joining KOC, Ahmad worked as a Senior Geologist in Long
Run Exploration Ltd, Calgary,
Rose, W., 1951. Some Problems of Relative
Permeability Measurement. World Petroleum
Conference, WPC 4130.
Canada from 2006. Ahmad has more than 23 years of industry experience, including more than 5 years as oil and gas consultant in Calgary,
Rose, W., 1980. Some Problems in Applying the
Hassler Relative Permeability Method.
1161–1163, SPE-8034-PA.
JPT 32 (07),
Canada. Ahmad holds a B.Sc. in applied geology and M.Sc. in applied geology from the University of Punjab, Lahore, Pakistan and M.Sc. in exploration geophysics and Ph.D. from the
University of Leeds, UK. Ahmad is a professional member of the
Association of Professional Engineers and Geoscientists of
Alberta (APEGA) and an active member of CSPG, AAPG, and
SPE.
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SPWLA 57 th
Annual Logging Symposium, June 25-29, 2016
Hamid Hadibeik is a petrophysicist with the Halliburton Deepwater
Reservoir Solutions Center. Hadibeik has been involved in the global operation of deepwater wireline projects performed by Halliburton, integrating advanced well logs to provide solutions for field exploration and development. Before Halliburton,
Hadibeik was an exploration petrophysicist for Gulf of Mexico at
Maersk Oil. Hadibeik holds M.Sc. and Ph.D. degrees in petroleum engineering from the University of Texas at Austin and is a member of SPWLA and SPE.
Sami Eyuboglu became a Global
Formation Testing and Sampling
Advisor at the Halliburton Deep Water
Reservoir Solutions Center in Houston in
January 2016. Before that role, Eyuboglu worked in Saudi Arabia for 4 years with different roles in both Technology and
Wireline and Perforating Services.
Eyuboglu has been with Halliburton since April 2008. Eyuboglu specializes in both wireline pumpout formation testers and logging-while-drilling. Previously, Eyuboglu was a research professor at The Ohio State University. Eyuboglu received his
B.Sc. and M.Sc. degrees in mining engineering from Hacettepe
University, Ankara, Turkey, and his Ph.D. degree in applied physics from the University of Arkansas at Little Rock. Mehdi Azari is a senior technical advisor for Halliburton with more than
35 years of experience in the oil and gas industry. Azari is currently working in the Reservoir Solutions Center of the
Wireline and Perforating product line in Houston. Azari was previously a professor of petroleum engineering at the University of Wyoming and worked at OSCO computer center in Abadan, Iran. Azari holds a B.Sc. degree in chemical engineering from Abadan Institute of
Technology and M.Sc. and Ph.D. degrees in petroleum engineering from University of Southern California, is a registered professional engineer, has authored more than 85 publications, and holds 14 US and international patents.
Mahmoud Kalawina joined Halliburton in 2012 as a petrophysicist working in the
Formation and Reservoir Solution sub-
PSL. Based in Kuwait, Kalawina is responsible for petrophysical evaluation, handling data processing, and presenting interpretation for advanced well logs, such as NMR, dielectric, and mineralogical logs. Kalawina received his
B.Sc. degree with honors in geology from Al-Azhar University,
Egypt. Before joining Halliburton, Kalawina worked 3 years as a petrophysicist for Bapetco E & P Company and a joint venture of
Royal Shell in Egypt.
Waqar Khan is a reservoir engineer with the Halliburton Deepwater
Reservoir Solutions Center. During his time in the industry, Khan has worked extensively on both offshore and onshore reservoirs. Currently,
Khan is focused on global deepwater projects specializing in pressure testing and sampling, production management, and reservoir simulation. Khan has experience working in deepwater reservoirs in the Gulf of Mexico, Angola, the Falkland Islands, and Brazil. Khan holds an M.Sc. degree in petroleum engineering from Texas A&M University and is a member of SPWLA and SPE.
Sandeep Ramakrishna manages the
Deepwater Reservoir Solutions Center in the Formation and Reservoir
Solutions (FRS) sub-PSL at
Halliburton and is based in Houston.
This center comprises a multidisciplinary team providing reservoir characterization services to operators globally. Before joining
Halliburton, Ramakrishna worked for an independent oil and gas company in the US mid-continent area and has also worked for
Geoservices in the Middle East. Ramakrishna has more than 18 years of experience in the industry and has been actively involved in the development of techniques to analyze conventional and unconventional reservoirs. Ramakrishna holds a M.Sc. degree in petroleum engineering from the University of Tulsa, Oklahoma and a B.Sc. degree in geology from the University of Pune, India.
Ramakrishna is a member of SPWLA, SPE, and AAPG.
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SPWLA 58 th
Annual Logging Symposium, June 17-21, 2017
Rafael Vasquez manages the FRS sub-
PSL at Halliburton-Northern Gulf
(Kuwait-Qatar) and is based in Kuwait.
Vasquez has 43 years of experience in electrical wireline and perforating.
Starting as a wireline field engineer in the 70s, Vasquez has held a wide range of positions across the globe, from operations management, technical management, marketing management, to training center management. Vasquez holds a B.Sc. degree in electronics engineering and a M.Sc. degree in automated control. Vasquez is a member of SPWLA.
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