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Abstract This paper describes the utilization of Real-Time geochemical analysis to support geosteering of a smart multi-lateral well,

located in one of the highest flow potential areas in Kuwait. The Burgan reservoir consists of vertically stacked channel sands

along with a fault network connected to the aquifer and contains highly viscous reservoir fluid. This drastically enhances the

water mobility, and results in severe premature water breakthrough. Hence, leaves zones of by-passed oil. For optimum

reservoir characterization, it was essential to integrate all reservoir-related data from macro to micro scale. X-ray

Fluorescence elemental data collected from offset cores were used to predict key rock attributes and calibrated with standard

petrophysical logs.The scope was constructing predictive models for the following properties: 1) lithological variations which

cannot be captured by other LWD tools 2) detailed mineralogy to determine the diagenetic overprint 3) depositional

environment of different Burgan sand facies. XRF elemental analysis while drilling was used to improve borehole

positioning, and identify faults in correlation with Image logs. Nature of the fractures/faults, contributing to porosity and

communicating with the aquifer, was inferred from XRF-obtained elemental markers. The integrated approach has resulted in

successful geosteering and placing the well with maximum reservoir contact. Moreover, XRF elemental markers have been

utilized for isolation of faulted and lower reservoir quality zones, splitting up of horizontal sections and optimization nozzle

sizes of the ICDs and hence an optimized Smart completion design. X-ray fluorescence analysis on cuttings in Real-Time

provides lithological information otherwise not available while drilling. It gives proxies contributing to the identification of

faults and reservoir intervals in an otherwise homogeneous sequence. It helps designing the completion string, isolating

sections of low quality or potentially producing water.

1. Introduction

The Minagish Field in Kuwait was discovered in 1959 and is located in the southwestern part of Kuwait. It contains several

reservoir intervals in its stratigraphic column varying from early Jurassic to late Cretaceous. The Field is situated 12 km north

west from West Umm Gudair Field. The field has been penetrated by more than 180 wells, not only for the middle and lower

Minagish reservoirs of lower Cretaceous age, but also for other shallow reservoirs such as Mishrif-Rumaila carbonates and

Wara-Burgan sandstone. The Minagish Field structure of Wara and Burgan Formation is a closed elongated asymmetrical

anticline oriented in North-South direction. The top of the Burgan structure is located at about 5500 feet TVDSS. (Figure 1)

IPTC 16617

Drilling of Multilateral Wells Aided with Geochemical Analysis, Kuwait Taher EL Gezeery, Abdul Aziz Ismail, Khalaf Al Anezi, Monirah Al Jeaan, Jeevan kumar Silambuchelvan, G.S Padhy Kuwait Oil Company; Atul Wasnik, Ahmed Al Shoeibi GEOLOG International

2 IPTC 16617

Figure 1: Minagish Field is located in south west corner of Kuwait. The Burgan is of Albian age (Lower Cretaceous), and structure is asymmetrical elongated north-south anticline.

1.2 The Burgan Reservoir

The Burgan reservoir is informally divided into Upper and Lower Burgan. Lower Burgan sands are more extensive and

blocky in nature with little variations in their properties. The lower Burgan reservoir section lying above OWC and is of

significance from hydrocarbon bearing point of view. Upper Burgan sands are mainly in the form of channel sands ranging in

thickness from few feet to nearly 45 feet and have got extensive lateral facies variation. The lower part of the Burgan

Reservoir has active bottom water drive whereas the upper part of reservoir has edge water drive system. The reservoir

contains high permeability sands in order of few Darcy associated with active faults and highly viscous reservoir fluid with

viscosity of about 40cp at reservoir condition. This heterogeneous nature of the reservoir accelerates water movement inside

reservoir and results in premature water breakthrough in existing vertical as well as horizontal wells, in spite of maintaining

highest stand-off from OWC. (Figure 2) & (Figure 3)

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Figure 2: Porosity vs. Permeability plot showing the difference in reservoir properties of channel sands in the upper Burgan compared with other sands (within, above and below). Figure 3: north-south correlation line flattened on top Mauddud limestone marker shows the Burgan sand sequences below and Wara shlaes/ or sands overlie the top Mauddud.

1.3 The Work Scope

The Burgan reservoir being present in the crestal part of Minagish Field, limits the surface locations for drilling many vertical

wells to effectively deplete the reservoir. Due to the nature of the reservoir and oil quality, horizontal wells/or multilateral

wells is a viable option. Nonetheless, understanding the geometry and structural setting of the reservoir are extremely

important for generating the development scenarios. The upper part of Burgan reservoir consists of complex laminated thin

channel sand, and inter-channel silts and shale, which are associated with faults networks, poses several drilling and

geosteering challenges (Figure 4) & (Figure 5). Also, geosteering in the upper Burgan sand with lateral facies changes

associated with faulting along with deformation or drag is a big challenge. This necessitates a details planning and thorough

execution of the plan in order to place the wells optimally and maximize the reservoir contact. The multilateral well was

drilled integrating LWD, XRF data and petrophysical interpretations in real-time to geosteer the horizontal well successfully

in the zone of interest with maximum possible reservoir contact. However, in the current paper only the XRF part is

highlighted of MN-AMultilateral. After successful implementation of the workflow in the lower Lateral (LAT-0) placed in

lower Burgan, same workflow was utilized to geosteer the upper lateral (LAT-1) in upper Burgan.

Figu

Figu

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Figure 4: Seismic Coherency map along a horizontal section of a Burgan producer is used to locate areas of faulting. The coherent areas in beige color in the cross section show no faulting. All other colors (in-coherent areas) show faulted areas starting from dark blue, yellow, orange and red colors (less faulting to more faulting). Figure 5: The production log shows that in-coherent areas on seismic having very high potential for water coning. This zone is interpreted as a fault zone connected with the aquifer. The water coning is mainly due to very high mobility ratio (~40) and Oil wet reservoir characteristics.

2. Pre-Job Modeling

Pre job modeling is an important aspect of geosteering as this not only enables us to understand the reservoir challenges but

also helps to develop possible solutions to mitigate them. In the current work scope the pre job modeling consisted of a

geochemical model based on XRF analysis of core chips from offset wells. This is a crucial step in the elemental analysis

case because it enables to generate a geochemical model where all the main markers are recognized and concentration

patterns are registered.

2.1 Geochemical Pre-job Model:

Pilot Study: Prior to building the geochemical model based on offset well, a pilot geochemical study was done on 3 Wara-

Burgan wells. The high resolution geochemical analysis based on major, trace, REE and ratios of elements defined 10

chemostratigraphic packages and 15 chemostratigraphic units for the Wara-Burgan reservoir of Minagish Field (Figure 6).

The possible diagnostic geochemical elements are provided in Table 1.

352 feet sampled

390 feet sampled

403 feet sampled

MN-A

MN-B

MN-

Pilot study wells

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Figure.6 High resolution correlation panel showing main Chemostratigraphic packages defined in the studied wells.

Table 1: Geochemical elemental Analysis of Wara-Burgan pilot wells

The pilot geochemical study of the upper Burgan reservoir shows an increase in heavy mineral contents (key-ratio U/Mg),

particularly in the middle part of the main clean sand channel, then an increase in dolomite content, followed by Fe maximum

elevated values in lower part. This followed by increasing U/Th and K/Th ratios respectively at the lowest part indicating

dirty sand and shaly sections (Figure 7). The majority of calcium came from calcite or dolomite after Diagenesis. Whereas,

the main source of Fe is Glauconite, which is either detrital or early diagenetic. K is derived mainly from feldspars with little

amount from detrital glauconite. Main Ti source is Anatase which is authigenic precipitated from acidic Ti-rich fluids. Zr is

derived from Zircon mineral deposited in a higher flow regime. U/Mg: key-ratio - U sourced from heavy mineral vs. Mg

from dolomite.

Figure 7: Proposed geochemical model for Upper Burgan (MN-A) vertical well with very good correlation with (Well-B) horizontal well.

2.2 Petrographic Analysis (Upper Burgan reservoir):

The petrographic analysis of Burgan sand shows the presence of heavy minerals like Anatase and Zircon. Anatase is an

authigenic mineral common in sediments with titanium rich fluids. Titanium is closly related to iron and the origin of it can

be ores or iron rich minerals like amphibole, pyroxene or Glauconite (green), which are not stable in acidic fluids. A possible

source for the iron and titan sulpher in the pore fluid could be the dissolution of the Glauconite by the organic acids which

have been generated along with the hydrocarbon generation. Authigenic hematite, Fe2O3 crystals in black at the centre are

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formed due to same diagenetic processes. A result of the feldspars dissolution is secondary porosity and higher concentration

of SIO2 in the pore fluid. Bottom center right side shows the consequence of the precipitation of Quatz cement in pores.

Figure 8 shows Fine grained Quartz Sandstone with 23% porosity. Authigenic Anatase (TiO2) and relicts of Glauconite are still visible in the center following early diagenesis. Figure 9 shows lower quality sandstone with 21%.porosity.The image in the center shows a dolomite cement which has been affected by diagenetic leaching. The dolomite cement itself corrodes the touching detrital Quartz grains. The dissolved SiO2 from Quartz, feldspars and clays in the fluid is able to generate quartz cement. The Glauconite grains have been almost leached and transformed into Fe- chlorite

Figure 10 shows dolomite nodules associated with a coastal sabkha environment at upper part of Burgan, while Dolomite cements associated with shallow marine conditions at lower part of Burgan. 2.3 Offset Well Study

Information obtained from the geochemical pilot study based on 3 Wara-Burgan wells were utilized to validate the pre job

model based on offset well core samples. A total of 34 core samples from an offset well (Well X) were analyzed through

ED-XRF (energy Dispersive X ray fluorescence) covering both upper and lower Burgan reservoir units to build the

geochemical model. The core description of well X shows maximum clean sand channel is about 13 feet in the upper

Burgan whereas the lower Burgan has massive clean sand extending up to OWC (Figure 11).

FigureFigure

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Figure 11: Well X Core Description (Upper and Lower Burgan Sand Sequences). To the right, the first track shows the GR log response in front of core facies of upper and lower Burgan sand sequences. The depositional environment evolution in the Burgan sand sequence showed a transgressive trend above the Lower Burgan fluvial sand with clear geochemical evidence.

The elemental pattern obtained from the XRF analysis of 34 samples covering the upper and lower Burgan reservoirs is

presented in Figure 12 and Figure 13. Based on this analysis, key elemental markers are being defined to be used as a guide

while geosteering the lower and upper laterals (LAT-0& LAT-1).

Figure 12: Well X elemental pattern obtaine from XRF analysis for the upper Burgan sand reservoir.

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Figure 13: Well X elemental pattern obtaine from XRF analysis for upper and lower Burgan sand reservoirs.

3. Multi-lateral Well Location Optimization

The well locations for smart multilateral wells are optimized by integrating data from multiple disciplines starting from the

macro (seismic) to micro (petrography) scale. Further the data from seismic, geology, petrophysics, reservoir engineering,

and well surveillance were incorporated into the pre-drill characterization program. The lower lateral, LAT-0 (mother bore)

of smart multilateral wells is placed in the lower Burgan, consisting of a braided river system with stacked sand bodies. The

sediment ranges from fine, medium to coarse grain sizes with the porosity ranging from 20%-30% and having permeability

values in the order of few Darcy. The bottom part of massive thick sand bodies is directly connected to the bottom aquifer.

The upper lateral, LAT-1, of smart multilateral well is targeted in the upper Burgan reservoir consisting of silt to medium

sands. The porosity is relatively low (between 15 - 18 %) and the permeability values are in the order of hundred mD as the

reservoir still retaining the fluvial sand character. There are shaly sediments between lower Burgan and upper Burgan, which

can act as permeability barrier or baffle for vertical migration of fluids (Figure 3 & Figure 11). This complex channel

geometry makes these reservoirs most challenging for implementation of smart multilateral wells. The well trajectories were

optimized to encounter best reservoir sections by minimizing the exposure of fault networks as interpreted from high

resolution seismic (Figure 14).

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Figure 14: Coherency attribbute seismic section and map view showing MN-A muliti-lateral well location. The blue, green, yellow and red colors on seismic section refer to the faulted areas with variable degree of intensity.

4. Real time Geosteering Aided with Geochemical Analysis

Advanced multilateral well drilling and completion require the application of innovative technologies while drilling to place

the well in sweet spots by managing all the geological uncertainties. The smart multilateral wells were drilled by integrating

advanced high resolution Chemostratigraphy (XRF), advanced gas analysis along with real time geo-steering formation

characterization and seismic data interpretation. The pre-job Chemostratigraphic analysis of offset well data and modeling

has provided the reference indications for geochemical steering to characterize various facies in heterogeneous formations of

Burgan reservoir.

The high resolution 3-D seismic data interpretation has enabled to refine the geological model in terms of faults and reservoir

boundaries. (Figure 14) The real time geo-steering is performed by utilizing advanced and innovative technologies including

the high resolution XRF geochemical analysis to identify geochemical proxies and allow geochemical steering. The

optimum utilization of geochemical models was major asset while steering the multi-lateral well in complex structure of

Burgan. In the present scope of work near real-time XRF geochemical analysis complimented with log based petrophysical

evaluation was utilized to better geosteer the well bore in the zone of interest and maximizing the reservoir contact. Here we

present the details of an integrated interpretation based on real time data set for LAT-0 and LAT-1 sections of well MN-

A multi-lateral.

1. Multilateral Junction Considerations: The most relevant aspect in designing the smart multilateral well is the selection of appropriate multilateral junction4 by

considering the well completion requirements, intelligent completion requirements, downhole equipment specification,

formation exposed across the junction area, formation fluids and the well production conditions. After a complete screening

of various multilateral junctions, the level-4 junction is selected for smart multilateral wells. During the well trajectory

optimization the multilateral junction depth was selected across excellent compact shale at the base of Wara layers to ensure

junction stability during drilling, well completion and also to have junction integrity during long term production. The high

resolution XRF analysis shows a high argillaceous siliclastic zone based on chemical behavior of elements. (Figure 15)

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Figure 15 The junction depth was selected across excellent compact shale at the base of Wara layers based on the high resolution XRF elemental data analysis

2. XRF Aided Chemosteering in Lower Burgan sand (LAT-0):

The geochemical model built utilizing offset well data provided a good understanding of the geochemical imprints of the

reservoir units and thus guided us to chemosteer the well in integration with other information. In the absence of resistivity

data, XRF analysis data infact identified a fault @ 7340 ft which was not observed by near Bit Gamma (Figure 16).

Figure 16: Fault @ 7340ft detected by XRF, based on elemental model

Elementary changes, supplemented with lithological changes, confirms the Faults encountered in 7490ft, 7950ft, 8450ft &

8700ft (in the first & last fault-Sand to Sand- the main indication is Cl, while in the F2 & F3 the other elements are also

indicating the Fault). Cl could be used as a good marker before encountering the Fault. The findings of XRF analysis are

further confirmed while drilling from interpretation of azimuthal Density Images. Chemosteering thus helped to change the

well path based on elemental analysis and maximize the reservoir contact. (Figure 17)

61/8hole(LAT1)

8hole(LAT0)

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Figure 17: Chemosteering in Near Real-time, Lower Burgan sand (LAT-0)

Identification of Faults/Fractures: Azimuthal litho-density Image was interpreted while drilling not only to understand the

formation dip but most importantly to identify cluster of fractures/faults and are complemented with XRF analysis.

The Figure 18 below shows 4 fault zones identified through the LAT-0 section of Well A and the same were quite

evident from XRF Analysis as shown in Table 2. Though the real time density images were not of high confidence still were

able to provide information about formation dip and guiding the Geosteering process in upper and lower Burgan reservoirs.

Figure 18: Litho-density Image showing zones of faults (as a cluster of fractures)

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Table 2: XRF analysis complementing the findings from litho-density Image Interpretation

During geosteering the LAT-0 of well A in the lower Burgan reservoir unit, increment of K, Al, Ti, Zr is observed

(Figure 19) indicating dirty sands. The target is to keep these elements at minimum to make sure we are in good sand,

there by having a higher value of Si. XRF Geochemical Analysis showed a clean Sand/Sandstone over the drilled interval

with Si values between 18-35% and minimum concentration of Al, Fe, K, Ti, S, Zr, CO and AS elements.

Figure 19: XRF elemental alanysis in near-real-time mode for the Lower Burgan target

Transition zone

Upper Burgan

Lower Burgan

MNAL0Wellpath

Clean sand Interbedded siltstone, very fine sand and shale

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3. XRF Aided Chemosteeringin upper Burgan sand (LAT-1):

During landing the well at the top of Upper Burgan sand, XRF geochemical analysis based on elemental signature showed a

sharp increment of silica (Si) and heavy minerals (Titanium,Ti & Zirconium,Zr). Al (Aluminum), Fe (Iron), and K

(Potassium) had a downward trend. There are also other elements like Cl, Mo, Cr, Ag, Co and Sn going to zero values at the

top of Burgan sand. These proxies are considered as excellent markers and had very good correlation with the offset well

MN-X. The Silica (Si) values decreased after displacing the oil base mud (OBM) with FAZEPRO calcium carbonate mud

due to the contamination and high percentage of calcium. The correlation became difficult with MN-X and other elements

have been selected for correlation. There are 10 proxies with elemental signature in clean sand lobes of upper Burgan. While

geosteering in the sweet zone an increase in heavy mineral contents (Ti and Zr), particularly in the middle part of the main

clean sand channel, then an increase in Mg content has been noticed while cutting down structure, followed by Fe and Al

maximum elevated values while cutting further down at the lowest part of Burgan indicating dirty sand and shaly sections.

(Figure 20) The evidence of faulting in the upper lateral (LAT-1) showed elementary changes, supplemented with

lithological changes very similar to the faults encountered in the Lower Burgan lateral section (LAT-0). See (Figure 17). The

pilot XRF model and offset well MN-X are used with high confidence to steer the well based on clear geochemical finger

print and markers associated with Burgan sub-layers. This has resulted in a successful chemosteering in the clean sand lobe

with less than 10 feet thickness and maximized the reservoir contact even with structural complexity associated with faults

and significant dip changes.

Figure 20: XRF elemental alanysis in near-real-time mode for the Upper Burgan target

MNX(offsetwell)

MNA(LAT1)Multilateral

14 IPTC 16617

5. Collaborative Workflow: A Key to the Success In summary, the current work scope was a success, solely due to merger of independent data sets from different analysis

through a collaborative approach, extracting the right information at the right time. The first data to be gathered are seismic

data, providing the vital reference framework, such as: identifying the most likely faulted sections and the type of dislocation

they can cause. The seismic image below (Figure 21) shows the horizontal well section, superimposed with abundance of

main elemental marker obtained through XRF analysis. The markers chosen are amongst those which provided the better

contrast during the pre-well study: Al, Zr, Ti, K. Clear changes in the abundance of these elements are associated with the

main features of the well section, i.e. the landing point approximately @ 7300 ft, the faulted sections @ 7940 ft and 8450 ft

in particular. Al also provided an early indication of the approaching fault as it started showing an increase at the start of the

disturbed section at 7836 ft.

Figure 21: Superimposed Seismic section with Key Elemental markers.

Similarly, elemental markers are also matched with the MWD azimuthal tool response (Figure 22). Al started to increase with

the first minor fault, and peaked at 7940ft. It remained high till 8100 ft where it started to lower values. Ti had similar

behavior with the difference that it only appeared in earnest when the main fault was encountered at 7940 ft. The indication

from Aluminum is particularly important because it came as an early sign of the fault. The azimuthal information arrived

later and confirmed that a fault had dislocated the well trajectory which was corrected as a consequence.

Figure 22: Elemental markers superimposed with main events: landing and main faults

However the utilization of chemical elements measured in real-time with high density points is not the only utilization of this

technology. In fact, the same data can be utilized during the production phase to isolate the faulted interval. In our case Al

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concentration, which had a significant increase across the faulted sections was used as a proxy along with permeability

measurements to mark and isolate these zones of potential trouble (Figure 23) which would be very detrimental for water

production.

Figure 23: Isolated zones along the well path L0, Well A.

6. Conlcusions The paper demonstrated key merits of an integrated approach for geo-steering of smart multilateral well and its successful

outcome in a highly challenging Burgan reservoir. It is a belief that this workflow will benefit the industry while developing

reservoirs of similar nature.

Whenever a new dataset is entered in the Formation Evaluation process, it is crucial to make sure that it becomes part of the

work flow loop, otherwise the advantages and new information it can provide may be underutilized or ignored. This is a vital

part of the integrated approach.

It is imperative that a collaborative workflow from planning till completion involving seismic, geochemical analysis along

with petrophysical evaluation is necessary to achieve the objective. This was clearly evident in our case where:

i) Seismic data has enabled to prepare the background platform,

ii) Geochemical analysis of offset data was utilized to make a pre-job geochemical model providing the reference indications

for the key marker elements,

iii) In real time geosteering utilizing all the available data sets to place the well in the zone of interest and maximize the

drainage area.

The quick reaction to changes based on available data sets has granted a longer reservoir section to be exposed in the

horizontal drain holes, subsequently led to modification of the production plans, isolating troublesome or less productive

sections. In summary, this work scope was successfully utilized to drill the first Smart Multi-lateral Well in Kuwait as well

as in Middle East Region.

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7. Future guide lines

1. Pre drill: Reinterpret seismic using a more aggressive approach involving more small faults.

2. Re-calibrate 3D surfaces model when major seismic structures are encountered.

3. Use experience gained in current job to plan and execute the next job with a focus on consequences of hard turns in

a narrow zone.

4. Chemosteering should be an integral part of geosteering while dealing with such kind of complex reservoirs.

Acknowledgement The Authors would like to thank Kuwait Oil Company and the Ministry of Oil for permission to publish this paper. They are

grateful to Hassan Bunain (Manager, Field development, West Kuwait) and Khalaf Al Anezi (Team Leader of Minagish,

west Kuwait) for their encouragement and support.

References

1. Khalaf Al-Enezi, Om P. Das, Muhammad Aslam, Khaled Ziyab and Taher El-Gezeeri; Kuwait Oil Company: Successful Case Histories of Smart Multilateral Well with Inflow Control Device and Inflow Control Valve for Life-cycle Proactive Reservoir Management in High Mobility Reservoir, Minagish Field West Kuwait SPE 161632

2. OM. Das, Khalaf Al-Enezi, , Muhammad Aslam, Taher El-Gezeeri and Khaled Ziyab and; Kuwait Oil Company: Novel Design and Implementation of Kuwait's First Smart Multilateral Well with Inflow Control Device and Inflow Control Valve for Life-cycle Reservoir Management in High Mobility Reservoir, West Kuwait SPE 159261

3. Taher El Gezeery, Abdul Aziz Khaled Ismael and Khalaf Al Anezi, Kuwait Oil Company Horizontal Wells Optimize Production in a Super K Sandstone Reservoir, Minagish Field, West Kuwait paper SPE 684529, presented at GEO 2010, the 9th Middle East Geosciences Conference and Exhibition held in Bahrain at Bahrain International Exhibition Centre, 7 to 10 March 2010.

4. K. Al-Enezi, O.P. Das, M. Aslam, R. Bahuguna, and A. Latif, Kuwait Oil Company: Water Coning Model for Horizontal Wells in High Mobility Reservoir, West Kuwait paper SPE 130302, presented at the CPS/SPE International Oil & Gas Conference and Exhibition held in Beijing, China, 810 June 2010.

5. Taher El Gezeery, Abdul Aziz Khaled Ismael, Khalaf Al Anezi; Kuwait Oil Company and Christian Scheibe Chemostratigraphic Differentiation Between Fluvial and Shore-Face Sands as a Real-Time Geosteering Tool Within the Albian Upper Burgan Formation, Minagish Field, West Kuwait" paper SPE 684527, GEO 2010, the 9th Middle East Geosciences Conference and Exhibition held in Bahrain at Bahrain International Exhibition Centre, 7 to 10 March 2010.

6. Taher El Gezeery, Fawaz Al Saqran; Kuwait Oil Company and Ekpo Ita Archibong, and Somaya Al-Radhi, Schlumberger Utilizing Real Time Logging While Drilling Resistivity Imaging to Identify Fracture Corridors in a highly fractured Carbonate Reservoir, Kuwait SPE 118152, Abu Dhabi International Petroleum Exhibition and Conference held in Abu Dhabi, UAE, 36 November 2008.