Obtaining representative samples ofreservoir fluids has always been one of themajor challenges in reservoir engineering,particularly in the complex carbonatereservoirs of the Middle East. Reservoirstudies, crucial to production planning andprocess design, determine and utilizereservoir fluid properties, such aspressure–volume–temperature (PVT)behavior, viscosity and gas–oil ratio, on thebasis of a reservoir at its original conditions.Knowing that a sample is free ofcontamination and is contained at itsdownhole PVT conditions when it reachesthe surface, gives confidence in theanalyses that follow.

Here, Fikri Kuchuk, Frank Halford, MuratZeybek and Ali Al Shahri explain howrepresentative sampling is achieved andillustrate how this has benefited theoperators of a major Middle East oil field.

Focus in on fluids

F luid samples provide the first look ata well’s production, and operators

need to be confident that the few litersof fluid retrieved from their wells arerepresentative of the reservoir. In theMiddle East, sampling is usedextensively to help determine thecharacteristics of complex carbonateand sandstone reservoirs. The latestwireline sampling technology helpsasset teams to make informed economicdecisions. This article looks at samplingtechniques and how the MDT* ModularFormation Dynamics Tester tool is usedto overcome some of the traditionalchallenges of downhole sampling.

Good formation-fluid samples are ofgreat importance to asset teams, and arepresentative sample may often be asuseful as results from petrophysical logs.Modern wireline formation testers arebeing used increasingly for downholefluid sampling in place of the morefamiliar drillstem test (DST) orproduction tests. These formationtesters are highly selective, allowing aseries of reservoirs to be tested during asingle trip into the well. Samples can betaken at low drawdown pressure dropfor greater control, ensuring that thephysical state and the behavior of thefluid are minimally disturbed by thesampling process itself. In addition,downhole sampling operations are easierto plan, require less lead time, reduceenvironmental and safety risks, eliminatesurface testing equipment and reducetotal cost.

Composition is criticalFormation fluid samples help toestablish the physical and chemicalproperties of formation fluids, such asthe hydrocarbon type and thepressure–volume–temperature (PVT)behavior of the reserves in place.Hydrocarbon composition can varysignificantly within an oil field and mustbe adequately described. Typicalmeasurements performed on a fluidsample from an oil reservoir include PVTrelationships, viscosity, composition,gas–oil ratio (GOR), differential

vaporization, and a multistage separationtest. Fluid samples help asset teams planthe special treatments required for issuessuch as hydrogen sulfide removal. Theyalso reveal waxing tendencies andasphaltene content, and facilitatemetallurgy and refining trials.

Paraffin waxes can cause blockages inproduction facilities and cold subseapipelines. Asphaltene precipitationproduces tar-like solids that can come outof suspension in crude oil when pressuresare reduced within the formation, inproduction tubing or at the surface.

Water samples help to guideproduction and process design. Therelevant factors include scaling, hydrateformation tendencies, compatibility withpossible injected water, corrosivity, themetallurgy of tubulars, and the design ofthe water-handling plant. Knowing all ofthese important properties helps assetmanagers to ensure efficient fielddevelopment, particularly whereinvestment in facilities and processingdepends on the amount, types and flowcharacteristics of fluids in the reservoir.

The challenges of samplingThe main objective of sampling reservoirfluids is to obtain a sample that is whollyrepresentative of the original, in-placefluid. This is essential because reservoirengineering studies, which areperformed using PVT analysis data, arealways made on the basis of thereservoir at its original conditions.

Ideally, therefore, sampling should beconducted on virgin reservoirs or innew wells in undepleted zones thatcontain fluids identical to the initialreservoir fluids.

Each sampling operation is designedso that producing conditions will notalter the phase behavior of the fluid.This ensures that the sample remainsrepresentative. The pressure drawdownassociated with flow must be controlledto prevent the fluid falling below itsbubblepoint and into the two- or three-phase region.

Another concern in obtaining arepresentative sample is the degree ofvariation in the original fluid throughout

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Figure 2.1: The MDTtool in single-probemode, showing thehydraulicallyoperated probe andtwo opposing backuppistons that push theprobe against theformation

the reservoir. A pattern for the variationmust be established from severalsamples or producing characteristicsfrom various wells completed atdifferent intervals.

The choice of sampling techniquedepends on the volume of samplerequired, the type of reservoir fluid to besampled, the degree of reservoirdepletion, and the surface andsubsurface equipment. Ideally, bothsurface and bottomhole samples shouldalways be taken.

Surface sampling Surface sampling involves therecombination of oil and gas takenfrom the separator, along with accuratemeasurement of their respective rates.This method is often chosen whenlarge volumes of oil and gas arerequired for analysis, as is the case forcondensate fluids. Surface sampling isalso selected in cases where the fluidat the bottom of the well is notrepresentative of the reservoir fluid,such as gas condensate reservoirs andoil reservoirs producing largequantities of water.

The main difficulties in surfacesampling arise because fluid in theseparator is at its bubblepoint and gas atits dewpoint. Any slight fall in pressureor increase in temperature can result inthe fluid becoming diphasic during the

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sampling operation. If this happens thesample will probably not berepresentative. There is a general needto check for contamination from carry-over, water or sludge from samplingpoints, and for the consideration and/orremoval of any chemicals injected. Theseissues underline the importance of all theequipment used in the surface-samplingoperation being in first-class condition,and operated by experienced andcompetent engineers.

Generally, a bottomhole sample ispreferred if the gas and oil surfacemeasurement capabilities are in question.However, reliable surface techniques cangive a statistically valid GOR measuredover a longer period of time.

Downhole samplingThe main challenges in downhole samplingoperations are finding the best zones forsampling, connecting to the formation,obtaining acceptably low filtratecontamination, and transporting unalteredfluid samples back to the surface.

Conventional downhole samplingtechniques, such as DSTs, require thewell to be ‘conditioned’ before samplingto remove the nonrepresentativereservoir fluid around the wellbore withthe original fluid. In this process, the wellis produced at successively lower ratesuntil further reductions have no effect onthe stabilized gas–oil ratio.

Knowing where to make theconnection to the reservoir fluid iscritical. Conventional resistivity-density-porosity log and core data help toidentify potential pay zones. Frequently,the operator knows the targetreservoirs, and other openhole logs mayhelp to identify the best zones in thewell for sampling. For example, nuclearmagnetic resonance (NMR) logs, such asthose provided by the CMR* CombinableMagnetic Resonance tool, areparticularly useful for determining thezones that will be productive.

The MDT tool (Figure 2.1) consistsof a hydraulic sonde and probe module,pump-out and flow control module andan OFA* Optical Fluid Analyzer. Thebasic MDT probe module that connectsto the formation contains a variable-rate and volume pretest chamber, aflowline fluid resistivity measurementdevice, a temperature sensor and twopressure gauges. One of these gauges isa fast, high-precision CQG* CrystalQuartz Gauge that allows sensitivemonitoring of drawdown pressuresduring the sampling process. The basictool can be combined with one or moresample chamber modules.

After connecting to the formation, thesampling process involves pumpingformation fluid through the tool to theborehole, or flowing it into chamberscarried as part of the tool. The first fluidto flow will be mud filtrate from the

Com

pone

nt fr

actio

n, w

t%

Component

C1 C3 nC4

nC5

Benz

ene

Tolu

ene

Ethy

lben

zene C9 C1

1

C13

C15

C17

C19

C21

C23

C25

C27

C29

C31

C33

C35C2 iC4

iC5 C6 C7 C8

Xyle

nes

C10

C12

C14

C16

C18

C20

C22

C24

C26

C28

C30

C32

C34

C36

0.01

0.10

1

10

100

100% oil-base mud filtrateReservoir fluid

1 wt% oil-base mud filtrate10 wt% oil-base mud filtrate40 wt% oil-base mud filtrate

Figure 2.2: Samplecompositional analysisfor a hydrocarbonsample contaminatedwith varyingconcentrations of oil-base mud filtrate

CommentsColor

channelsWater,

oilchannels

Optical density

Inflate packer

Packerpretest

Startpumpout

Pumpingfiltrate

Pumping oil

StoppumpingStart sample

Throttling

Changethrottle

Seal sample

Fluid flowGas

Gas detectorLamp

Liquid detector

Light-emitting diode

Water

Oil

Figure 2.3: OFA spectrometer and gas detector

near-borehole environment. Dependingon a number of factors, such as thefiltrate invasion depth and time spentpumping, the sample will contain amixture of mud filtrate and virginformation fluid. Since the objective is toobtain formation samples withsufficiently low levels of mud-filtratecontamination for PVT analysis,operators must decide what level offiltrate contamination is acceptable.

This depends on whether the fluidsare immiscible or miscible (see Figure 2.2). Contamination becomesmuch more critical when fluids aremiscible. In this case – either crude oiland oil-base mud filtrate or connatewater and water-base mud filtrate –contamination must be sufficiently low toallow identification of the virgin fluidproperties. Oil-base mud filtrate in acondensate is extremely problematicalbecause the small amount of liquid that drops out of the gas mixescompletely with the filtrate to make ahighly contaminated liquid.

Recent studies have shown, forexample, that the ability to predict GORand saturation pressure to within 5%,requires mud filtrate contamination to beless than 20% by weight. The level offiltrate that is tolerable depends on thePVT precision requirements of end userssuch as the reservoir engineer, and on thenature of the reservoir fluid.Volatile oilsand condensate gases require a muchlower level of contamination.

Recently, several projects have beeninitiated, in Norway, the UK and the USA,to learn more about the effects of oil-basemud contamination on the prediction ofhydrocarbon properties. One such jointindustry project is being conducted atHeriot-Watt University, Edinburgh, UK,with support from Schlumberger andseveral operators including Shell,ExxonMobil and TotalFinaElf.

From earlier project work, it has nowbeen established that meaningful PVTdata can be determined for oil-base-mud-

contaminated black oil samples. Misciblecontamination of gas condensate samples,however, still poses a challenge. Thecurrent research is exploring newmethods, including tracers in the drillingmud, to be able to back out the originalgas condensate fluid properties.Understanding the limitations of collectingopenhole samples from wells drilled withoil-base mud is essential.

Bringing samples to the surface whilemaintaining their initial reservoirproperties is a major concern. As fluidenters the tool, pressure drop must bekept low to prevent the sampling pressurefrom dropping below the formation fluidbubblepoint or dewpoint. If solids, such asasphaltenes, precipitate in the samplechamber or the fluid outgases on its wayto the surface, the sample transfer mayyield fluids that do not accuratelyrepresent those in the reservoir. Thesubsequent process of transferringsamples from downhole sample chambersto transportation containers can lead togas components escaping to theatmosphere or solids being left in thedownhole sample chamber.

If sample fluids undergo phasechanges while being brought to thesurface, it can be difficult to recombinethe separated components. For example,asphaltene precipitation produces solidsthat stick to the chamber walls. Also, ifleakage occurs from the multiphase fluid the overall composition changes.However, pumping at downholehydrostatic or low differential pressuresinto special pressurized samplechambers helps to maintain reservoirfluids in their original state.

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Accurate in-situmeasurement by optical fluid analysisThe OFA module provides the flowlinefluid measurements needed todistinguish sample contamination in awide range of complex environments(Figure 2.3). It uses a combination ofvisible and near-infrared absorptionspectrometry to record the intensity oflight transmitted through the MDT toolflowline fluid at various wavelengths.

Light from a high-temperaturetungsten–halogen lamp passes through arugged sapphire window into theflowline of the MDT tool. After passingthrough the fluid sample, the light exitsthrough another sapphire and a series ofoptical filters that split the transmittedlight into narrow-wavelength bands overa broad range in the near-infraredportion of the light spectrum. This is theheart of the spectrometer.

Photodiode detectors attached to eachfilter measure the reduction in lightintensity caused by the fluid movingthrough the flowline. The observed lighttransmission is controlled by the amountof light both scattered and absorbed inthe fluid sample. In the spectrometermeasurement, the optical density of thefluid characterizes the transmission. Theanalyzer is sensitive to changes of0.001% in light transmission.

Gas evolution during sampling mustbe avoided, which means that samplingpressures should be above bubblepointpressure. The OFA module has a gasdetector that checks for the presence ofgas in real time in the MDT tool flowstream. Engineers can establishsampling conditions, particularlypressures, for which no gas evolves inthe crude oil. This allows arepresentative sample to be collected.

Optical properties ofwellbore fluidsThe transmission of light through thefluid sample depends on the combinedeffect of two distinct processes –scattering and absorption. Both of theseprocesses affect light transmission andthe optical density measurement, andcan vary with the wavelength ofincident light.

Crude oil preferentially absorbs lightof particular wavelengths. Theabsorption spectrum exhibits a series ofpeaks with diminishing intensity atshorter wavelengths (Figure 2.4).

The largest oil peak that can be seenin the OFA spectrometer is at 1725 nm.Such vibrational peaks – located atdiscrete wavelengths, or energies – arelike the resonant frequencies exhibitedby mechanical springs or tuning forksand are comparable for most oils.

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Optic

al d

ensi

tyChannel number

Wavelength, nm

Crude A

Crude B

Water

500 1000 1500 2000

0

1 2 3 4 5 6 7 8 90

1

2

3

4

Oil-basemud filtrate

Diesel

Condensate

Figure 2.4: Laboratory oil and water optical spectra

Materials that are black, such as tar,absorb the entire spectrum of visiblelight through many different molecularvibrational and electronic excitations. Inthese cases, the absorbed light energy isconverted into heat.

Water also exhibits strong vibrationalabsorption peaks that can be observed inthe spectrometer. Therefore, just as anastronomer can tell what elements arepresent in the upper atmospheres ofshining stars by the absorption lines that

Oil cut from flowmeters

Oil f

ract

ion

from

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spe

ctro

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er

1

0.8

0.6

0.4

0.2

00 0.2 0.4 0.6 0.8 1

Low flow rate(150cm3/min)

High flow rate(700cm3/min)

Figure 2.5: VerifyingOFA module oil-cutmeasurements

occur in their continuous spectra,reservoir engineers can differentiate oiland water by virtue of their differentabsorption peaks. Consequently carefulanalysis of the relative contributions inthe near-infrared spectral channels helpsdetermine the oil and water fractions inthe MDT flowline (Figure 2.5).

If the particles are small compared tothe wavelength of the light, then theintensity of scattering increases withdecreasing wavelength. This process isknown as Rayleigh scattering. Forexample, mud solids – which originatefrom other particulate material in theflowline and clay particles ranging fromless than 400 to 4000 nm in size – areexcellent scatterers of light over theentire wavelength range of thespectrometer (Figure 2.6).

On the other hand, the presence of gasreduces the degree of scattering and lightabsorption in general. Gas presence canoften be inferred from the OFAspectrometer data when the sum of theoil and the water fractions present areless than unity.

Muddy, steady, go!In formations where the invasion is deep,a large volume of mud filtrate may haveto be removed before sufficientlyuncontaminated formation fluid ispumped into the sampling tool. Thepump-out module in the MDT tool has apowerful pump that can discharge thecontents of the flowline fluid into thewellbore against a differential pressureof several thousand pounds per squareinch. After identifying a zone with highproduction potential from which asample is to be recovered, engineers runthe pump until the optical spectrometermeasurements indicate that the mudfiltrate contamination level has stabilizedat a low value. At that time, the flowlinefluid is routed to the sample chamber.

The OFA module provides an accurateand reliable distinction between gas andliquid, oil and water, and crude oil andoil-base mud filtrate. This prevents thecollection of poor-quality samples andeliminates resampling time.

Clues in crude colorIn addition to the strong vibrationalabsorption peaks in the near-infraredspectra, many crude oils exhibit acontinuous monotonic increase in theirabsorption at shorter wavelengthscaused by the numerous overlappingexcitations from the large range ofdifferent light-absorbing aromaticmolecules. The largest of thesemolecules absorbs the longestwavelength light, but the continuousabsorption spectrum tails off towardzero at longer wavelengths because thenumber of larger molecules decreaseswith increasing size in crude oils.

This continuous tail in the opticaldensity extends across the spectrumfrom the near infrared through thevisible spectrum and into theultraviolet. For this reason, theabsorption tail in the spectrum is usedto derive an index of coloration. Strictlyspeaking, the observed color of mostsubstances is due to both wavelength-dependent scattering and electronicexcitations in the material.

In the scattering process, photons inthe light beam interact with particlesand molecules in the fluid and aredeflected from the beam, reducing theoptical transmission. The extent ofscattering depends on the size of thescattering particles relative to thewavelength of the light.

When particles are large compared tothe light wavelength, the light is simplyreflected from the particle surface. Forinstance, white paint is an excellentscatterer of light and is opaque to lighttransmission. Its scattering intensity isnot dependent on the particularwavelength or color. Sand and otherparticulate material in the flowline cancause scattering and, if present insufficient quantities, prevent light frombeing transmitted in the OFA flowline.

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Wavelength, m

Energy perphoton, eV

Objects of sizecomparable towavelengthCosmic

rays

X-rays

rays

Ultraviolet

Visiblelight

Radar bands

Infrared

UHF

VHF

HF

MF

LF

TelevisionTelevisionFM TV

Radio

Water and hydrocarbon molecules

Sands

Gravel

Boulders

Rigs

Wells

10 –13

10 –12

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ShortwaveStandardbroadcastradio

Silts

Clays

Figure 2.6: Range of wavelengths

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In practiceSaudi Aramco’s Ghawar field is amassive, complex, carbonate reservoirthat has been under flank-waterinjection. It has thin, super-permeabilitylayers (10 ft), which are generallystratiform and in some cases fractured,that are associated with highproductivity. Laterally extensive, super-permeability beds in good verticalcommunication with the rest of the oil-bearing reservoir can significantlyincrease both well productivity andsweep efficiency.

However, isolated super-permeabilitylayers can cause early waterbreakthrough, which adversely affectsoil recovery and increases operationalcosts. Furthermore, large permeabilitycontrasts can complicate the effectivedrainage of the lower porosity zones inthe lower part of the reservoir thatcontain about 35% of the original oil inplace. A typical porosity log from theArab-D reservoir is shown in Figure 2.7.

Total flow 1

6600

6650

6700

6750

6800

Depth, ft0 v/v 1Limestone vol 1

Zone 2A

Zone 2B

Zone 3A

Zone 3B

Zone 4

Zone 1

Figure 2.7: Typicalporosity log from theArab-D reservoir

Determining oil properties in situ

The Shell Oil Company found good correlation between crude oil coloration and both GOR and API gravity. These importantnew applications for optical fluid analysis continue to be actively researched.

By measuring differences in color transmission, engineers derived a hydrocarbon optical property (HOP) index. This showsan excellent correlation with GOR (Figure 2.8).

These correlations were validated by laboratory PVT analysis of samples from formations in the Gulf of Mexico. A high GORmeans that there is a large gas fraction, which in turn means oil of a lighter color.

A crude oil property (COP) index was obtained by comparing the fluid absorption response in the visible wavelengthchannels with the response in the longer, near-infrared wavelength channels. Figure 2.9 shows that this index correlates wellwith the decreasing API gravity of the stock tank oil. As the API gravity of the crude oil decreases, heavy components such asdense asphaltene fractions increase. This leads to an increase in absorption at shorter wavelengths and a subsequentdecrease in the color-based crude oil property index.

In-situ values are very important because they reflect the true nature of the reservoir fluid before it is brought to thesurface. Correlations between these measurements and subsequent laboratory PVT values help reduce the uncertainties inthe OFA-derived GOR and API measurements.

Figure 2.8: Correlation between GOR and OFA-derived hydrocarbon optical property (HOP)

1 10HOP index

GOR,

scf

/STB

10,000

1000

GOR = 812e 0.114 (HOP) API = 24e0.028 (COP)

10COP index1 100

Oil g

ravi

ty, °

API

40

35

30

25

Figure 2.9: Correlation between API gravity andOFA-derived crude oil optical property (COP)

Advanced reservoirmonitoring technology in the Ghawar field

The main objectives of obtaining MDT*Modular Dynamics Formation Testerdata in the Ghawar field are:• to establish the vertical pressure

profile • to obtain fluid samples in partly swept

zones, and establish water salinity andmovable oil fraction

• to measure the in-situ permeability foruse in reservoir simulation models.Obtaining the vertical pressure

distribution is a primary focus becausethis information clarifies thecommunication between the super-permeability, thin beds and thesurrounding high-porosity zones, as wellas the communication between high-and low-porosity zones towards thebase of the reservoir.

Quantitative measurement of watersaturation is essential in understandingwater movement in the reservoir,evaluating flood sweep efficiency, andchoosing future well locations.

The injection water in the Ghawarfield is very low salinity compared withthe connate water. The openhole,electric wireline logs drilled behind theflood front are impossible to interpretquantitatively without a knowledge ofthe Rw. Figure 2.10 shows a verticalpressure profile and the salinitiesdetermined from MDT samples.

The MDT is able to pump fluids from theformation until uncontaminated formationfluid is observed (Figure 2.11). The Rwdetermined from the sample can be usedin quantitative evaluation of wireline logsto determine true water saturation.

The graph for the lowest zone in Figure 2.11 also indicates that the truermeasured water cut from the MDTsample, which is uncontaminated bymud filtrate, shows unswept movable oilthat is not indicated by conventionalsampling methods.

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WC: 48%Sal: 100 kppm

(60 kppm)

WC: 0%Sal: 70 kppm

(60 kppm)

WC: 0%Sal: 130 kppm

(60 kppm)

WC: 92-96%Sal: 170 kppm

(60 kppm)

WC: 50% 0%

Sal: 300 kppm(200 kppm)

4050 (psi)Formation pressure

4200NPHI

0 0.51 : 400

(ft)

6950

2A

2B

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3B

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7000

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1 : 400(ft)

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WC: 100%

300 600 900 1200Elapsed pump-out time, sec

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1.0

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0.40.2

0

WC: 92–96%

600 1200Elapsed pump-out time, sec

1800

1.0

0.60.8

0.40.2

0

WC: 50% (filtrate)Actual WC: 0%

600 1200Elapsed pump-out time, sec

1800 2400

1.0

0.60.8

0.40.2

0

600 1200 1800Elapsed pump-out time, sec

2400

WC: 48%1.0

0.60.8

0.40.2

0

Figure 2.10: Vertical pressure profile also showingthe actual salinity measurements obtained by theMDT tool. Figures in parentheses indicate salinityvalues previously used for saturation computations

Figure 2.11: Water cut measured usingthe MDT in dual-packer mode. Note thatthe lowest graph clearly shows thesignificantly reduced water cutmeasurement due to prolonged pump-outeliminating filtrate in the sample

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In the Ghawar field, pressure andsaturation monitoring have been keyfactors in achieving the overall reservoirmanagement objective of maximizingrecovery at the lowest cost.

Saudi Aramco is currently surveyingkey, new wells drilled behind the floodfront using the MDT tester to obtainpressure measurements, perform intervaltests, and take fluid samples along thewellbore (see box – page 18). Theprimary objective of the surveys is toestablish whether the super-permeabilitybeds, as well as the lower porosity zones,are introducing differential pressuredepletion. The answer to this will directlyinfluence the completion and productionstrategy of the field.

Obtaining fluid samples across thereservoir zones is also a key part of thesurveys. This will establish water salinityand movable oil fraction in zones such asthose with breakthrough, where theinjection and formation waters are mixed.Determining the fraction of movable oil inthe lower porosity zones, where the

conventional openhole log results areuncertain, is crucial in optimizingrecovery. It is also a powerful method forevaluating the sweep in the matrix of thelower zones where diffused fracturedensity is higher and assists the dynamicinteraction between the two systems.

Ongoing monitoring in the Ghawar fieldhas shown that there is good verticalcommunication in the higher quality zonesat the top of the reservoir, including thesuper-permeability, thin beds. However,local and reservoir-scale barriers as well asdifferential depletion have been observedtowards the base of the reservoir.Locating and identifying the lateral extentof barriers between zones are among themain reservoir management challenges inthe Ghawar field.

These barriers have resulted in poorsweep efficiency leading to thedevelopment of zones containingbypassed oil. In areas where barriers arepresent, dual completions with ahorizontal lateral are proving veryeffective in maximizing recovery.

Low-shock sampling technique

P

P

Open valve

Closed valve

Resistivity

CQG

Strain gauge

Contaminationbubbles

Pressuretest chamber

Formationfluid

Samplechamber

Pump up/downmodule

Sample fluid

Wellbore fluidat hydrostaticpressure

OFA

Figure 2.12: Thelow-shocksampling techniquelimits pressuredrawdown duringfluid samplingoperations

The low-shock sampling technique wasdeveloped to limit pressure drawdownduring fluid sampling operations. Thiswould, in turn, avoid phase separationdue to the pressure dropping below thefluid’s bubblepoint. The shock isminimized by pumping formation fluidsinto the MDT tool against pistonchambers held at borehole pressure,as opposed to drawing formation fluidinto the chambers at atmosphericpressure (Figure 2.12).

This technique is frequently used forsampling in unconsolidated sands,where a typical problem is breakdownand mobilization of sand grains. Thisproblem can be overcome by using asingle large-diameter probe and agravel-packed filter screen with alarge zone of the reservoir packed off.

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Density porosity

Depth, m

X100

X125

X150

Neutron porosityp.u.45 -15

Boreholein.6 16GRAPI0 150

T2 log meanms0.1 1000

CMR Timur/Coatespermeability, md

Clean corepermeability, md

Inductionohm-m

Tarzones

0.1 1000TCMR

porosity, p.u.40 0

CMR-FFI, p.u.

CMR 3-ms porosity, p.u.

Core porosity, p.u.

Density porosity

T2 cutoffms0.3 3000

T2 distribution

Five-level averagingon CMR data

Figure 2.13: CMR–MDTtool combination used tosample in a North Sea well

Lessons from GhawarConventional tools for pressure andsaturation monitoring have limitations incertain situations, and should beintegrated with other dynamic andgeological data when evaluating sweepefficiency. MDT fluid identificationstations, using dual-packer, optical fluidanalyzer, and sampling, can effectivelyquantify the amount of remainingmovable oil. Remaining movable oil

saturations of 5–7%, have been measuredby the MDT in swept areas of the field,supporting the current reservoirmanagement practice of allowing waterproduction to improve sweep.

The existence of a super-permeabilitylayer can improve well productivity anddrainage (due to its large exposure) if itis communicating vertically with the restof the reservoir layers. Localizedbarriers are a very important factor invertical reservoir conformance.

Integrated answersmaximize samplingefficiencyWellsite efficiency is substantiallyincreased when MDT sampling depthsare guided by CMR results. The in-situ dynamic MDT measurementscomplement the CMR continuouspermeability log, and help confirm thepresence of producible hydrocarbons.

Modeling fluid flow 1

Figure 2.14: MDT in multiprobe mode

Rig time spent pumping and cleaningup to minimize contamination has to bekept to a minimum. Given that the probehas properly penetrated the mudcake,that the mudcake provides a good sealfrom the borehole, and knowing thedepth of invasion from a resistivityprofile, a good estimate can be made ofhow long it will take to remove thefiltrate layer in front of the probe.

To address this challenge anddevelop better sampling strategies,some companies have developed 3Dmodels to examine what happens tothe formation fluids in the region of thesampling probe. The effects of variousparameters such as viscosity,anisotropy and relative fluidpermeability were analyzed bysimulation and verified by samplingfield data. Modeling in this waysuggested a number of practicalmethods to reduce cleanup time andlower contamination levels.

In many wells, the zone of interest islocated between two closely spacedshale beds. These provide a barrierthat prevents filtrate from flowingvertically and recontaminating thesample zone, so formation geometryprovides the solution.

Another approach is to use amultiprobe tool (Figure 2.14) with oneprobe acting as a guard probe toisolate the sample-taking probe fromthe natural vertical flow of the invadingfiltrate. The third probe is used to help

in setting the tool and to provide amonitoring function.

Using the guard-probe techniquereduces cleanup time by up to a factorof three, and enables sampling informations where single-probemethods cannot be applied.

In the North Sea, for example, CMRand MDT data have been acquired forStatoil (Figure 2.13). In this case, thereservoir had low-resistivity pay zones,and the 35 p.u. well-sorted, fine to veryfine-grained sands contained iron-richglauconite and chlorite clay minerals.

The microporous glauconite reducesthe reservoir’s effective porosity. TheCMR tool has helped to identify mobileoil, and to quantify irreducible watersaturation, effective porosity and boundfluid volume. Core permeability resultsavailable at the wellsite suggested thatthe large high-porosity zone from X102to X120 m should be tested.

However, poor, free-fluid signals, theabsence of porosity and the shortrelaxation decay times seen in the CMRlog identified this, and several othersmaller zones, as unproductive tar.Without the CMR results, core studieswould have prompted multiple-sampleattempts throughout the tar zones. The cores have been cleaned with a solventthat removed all traces of the tar,changing their effective permeability.With the CMR logs, good MDT sampleswere obtained, enabling the operator topinpoint a gas zone at X102.8 m and oilat X104.2 m, just above the thick tarzone, and to verify formation water in athin sand bed at X130.7 m.

The impact of the CMR data in thiswell was twofold. First, it provided abetter reservoir description – identifyingtar and gas zones as well as irreduciblewater and free-water saturations.Second, and more importantly, it helpedguide real-time operations with respectto formation sampling – helping toidentify sampling depths and confirmingthe anomalous tar zone.

Reading rainbows in the mud A key objective of the OFA measurementis to distinguish between oil-base mudfiltrate and crude oil. Achieving thisobjective is not as straightforward asdifferentiating oil and water, whereoperators can rely on readilydistinguishable absorption peaks. Oil-base mud filtrate and crude oil have thesame base fluid – saturated alkanes.Even though synthetic, oil-base mud maycontain chemical groups not found incrude oils, such as esters, they arepredominantly alkane. Oil-base mudsexhibit near-infrared vibrationalabsorption peaks similar to those of purealkanes. Thus, as far as using near-infrared spectral analysis is concerned,synthetic oil-base mud filtrates have thesame or a similar signature. On someoccasions, crude oils are used as the basefluid, exacerbating the difficultiesassociated with differentiation.

Nevertheless, an obvious distinctionbecomes apparent when looking at thecolors of different crude oils and oil-basemud filtrates. In fact, crude-oil colorationextends into the near infrared, some waybeyond the visible range of the humaneye; the crude-oil coloration in the visibleand near-infrared exhibits huge variationand is readily measured. The color ofcrude oils and, to a large extent, filtratescan be characterized by a singleparameter – coloration – that varies overmany orders of magnitude.

The electronics in the OFA module aredesigned to measure slight variations incoloration by using detection circuitrywith a high signal-to-noise ratio. Thispermits sensitive optical absorptionmeasurements to be made over a widedynamic range. In addition, several of thespectrometer channels are devotedspecifically to measurement of color, andthe wavelength location of these channelsis optimized to enhance this analysis. As aresult, high-precision measurement of

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filtrate decreases significantly at first.Following this, the coloration usuallyexhibits asymptotic behavior over longperiods. The vertical scale on individualcolor channels can be expanded tofacilitate monitoring of the asymptoticbehavior. To obtain contamination at thefew-percent level, correspondingly smallvariations in coloration are necessary.When the coloration change with time is

coloration during sampling can be usedto monitor the transition in the MDT toolflow stream from oil-base mud filtrate tocrude oil.

During sampling in a well that hasbeen drilled with oil-base mud, theinitial flow of fluid from the formation isdominated by filtrate, so the firstcoloration recorded is largely the colorof the filtrate. Over time, the fraction of

crude oil in the flow increases as theflow cleans up. The miscible mixture ofcrude oil and oil-base mud filtratecoloration simply reflects thecorresponding fluid fractions. Thus,coloration provides a continuousmeasure of clean-up.

Frequently, the initial flow in the MDTflowline exhibits rather large changes incoloration, indicating that the fraction of

Modeling fluid flow 2

250-cm3

monophasicsample

'Floating' piston

Pressure-chargednitrogen

Nitrogen pressuretransmitted tothe samplethrough thebuffer fluid

'Floating' piston

Reservoir fluid

Buffer fluid

Nitrogen

Recovering downhole samples for accurate PVT andcompositional analysis can be a problem as the single-phasefluid cools during the journey to the surface. Even though thesample has been trapped at the downhole conditions, the fallin temperature results in a pressure drop within the sealedchamber and causes the sample to pass its bubblepoint andseparate into gas and liquid (Figure 2.15).

The precipitation of asphaltene and paraffin causes majorproblems in recombination and requires a lengthyrepressuring process.

One solution to this involves overpressuring the samplechambers with nitrogen after they are taken at reservoirconditions. Sample chambers are pressurized across twopistons with a nitrogen gas chamber. This compensates forthe temperature-induced pressure drop as the samples arereturned to surface. The pistons act on a synthetic oil bufferthat ensures the sample is not contaminated by nitrogen.The SPMC* Single-Phase Multisample Chamber (Figure 2.16)is designed for use with the MDT multisample module.

Liquid

fracti

on, %

Ambient temperatureReservoir temperature

A. Initial reservoir conditions

B. Nitrogen-charged

D. Multiphase sample

C. Single-phase sample

LiquidConventional

SPMC

Multiphase zone

Gas

75%Liquid % 50%

25%0%

Critical point100%

Temperature

Pres

sure

Figure 2.15: Phase diagram of a typical crude oil indicatingthe effects of possible sampling methods

Figure 2.16: Single-phasesample chamber SPMC

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sufficiently small, sampling is performed.With this method, sample contaminationlevels below 10% are consistentlyobtained in oil fields around the world.

Flow-stream analysisThe optical density and colorationsampling method described previously isused for most wells. However, in a welldrilled with synthetic, oil-base mud, theOFA measurements show that base-oilfiltrate and other contaminants decreaserapidly as they are pumped through theMDT tool. In the field example in Figure2.17, the MDT flow stream wasmonitored with the OFA spectrometer.The responses in channels 3 to 7 evolve,indicating crude oil as the flow cleans up.The OFA log suggests that after about30 min of pumping, little filtratecontamination is present and thecoloration channels indicate that amedium-gravity hydrocarbon sample isflowing through the tool. In this well, theoptical density readings in all channelshave stabilized after 40 min, indicatingthat additional pumping would notsignificantly reduce contaminationfurther. A formation sample was

collected at this time. After beingpumped into a sample chamber held atwellbore hydrostatic pressure, thesample fluid stayed single phase.Laboratory analysis of the recoveredsample confirmed low synthetic, oil-basemud contamination – less than 15%.

In some cases, engineers observedifferent behavior. This is related to theoptical scattering process discussedearlier. For particle sizes that are largecompared to the wavelength of light, thescattering is independent of wavelength.For example, when the MDT tool islowered into the well, the flowline fillswith mud. The OFA module records themaximum optical density on all channels.No light passes through the samplebecause of scattering by the mud solids.Once the mud in the flowline has beenflushed, the filtrate and formation fluidsobtained generally do not havesuspended solids, so the scatteringgradually diminishes to zero.

The future of samplingAlthough there have been manyadvances in sampling technology,reservoir engineers, production

Elapsed time, min

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chemists and process engineers whouse formation fluid data remainconcerned with the range and qualityof the PVT and compositional analysesthey obtain from sampling.

The main area of concern is the effectof the level of contamination on fluidanalysis. Experts believe that theyunderstand what the acceptable levelsof contamination from water-base mudand miscible, oil-base-mud filtrates are,and that they know how to obtainrepresentative samples from formationswith black and volatile hydrocarbons.

With gas condensates, however, alow level of oil-base mud filtratecontamination can alter samplebehavior from a gas condensate to avolatile oil. This problem is the subjectof continuing research.

Ongoing cooperation between thosewho design and use equipment for theacquisition of samples and sample data,and the people who request and makeuse of the data is the key to continuousimprovement in sampling technology.

Figure 2.17: Oil-base mud field example