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Fluid Identification in Light HydrocarbonsWith Use of NMR and Downhole Fluid

AnalyzersA Case StudyMarie Van Steene, SPE, and Mario Ardila, SPE, Schlumberger; Richard Nelson, SPE, and

Amr Fekry, SPE, BP Egypt; and Adel Farghaly, SPE, RWE Dea

SummaryIn hydrocarbon reservoirs, uid types can often vary from dry gasto volatile oil in the same column. Because of varying andunknown invasion patterns and inexact clay-volume estimations,uid-types differentiation on the basis of conventional logs is notalways conclusive. A case study is presented by use of advancednuclear-magnetic-resonance (NMR) techniques in conjunctionwith advanced downhole-uid-analysis (DFA) measurements andfocused sampling from wireline formation testers (WFTs) to accu-rately assess the hydrocarbon-type variations.

The saturation-proling data from an NMR diffusion-basedtool provides uid-typing information in a continuous depth log.This approach can be limited by invasion. On the other hand, for-mation testers allow taking in-situ measurements of the virgin u-ids beyond the invaded zone, but at discrete depths only. Thus,the two measurements ideally complement each other.

In this case study, NMR saturation proling was acquired over a series of channelized reservoirs. There is a transition from awater zone to an oil zone, and then to a rich-gas reservoir, indi-cated by both the DFA and the NMR measurements. Above therich gas, is a dry-gas interval that is conclusively in a separatecompartment. Diffusion-based NMR identies the uid type in aseries of thin reservoirs above this main section, in which no sam-ples were taken. NMR and DFA both detect compositional gra-dients, invisible to conventional logs.

The work presented in this paper demonstrates how the inte-

gration of measurements from various tools can lead to a better understanding of uid types and distribution.

IntroductionHydrocarbon systems are usually dened in terms of their molar composition and their pressure/volume/temperature (PVT) behav-ior [e.g., phase envelope, bubble- or dewpoint, solution gas/oil ra-tio (GOR), density, viscosity, and formation volume factor]. Allessential uid properties are dened after PVT properties areknown. Properties such as gravity and GOR are derived from thecomposition and the PVT analysis. On the basis of the reservoir temperature in respect to the critical-point temperature, we candifferentiate single-phase gas reservoirs, gas/condensate reser-voirs, and dissolved-gas reservoirs (volatile oil and black oil). The

denition of a reservoir uid as wet or dry gas depends on theconditions at surface (Whitson and Brule 2000).Fluid differentiation on the basis of solely conventional logs

(bulk density, neutron porosity, sonic, and resistivity) can be dif-cult. Bulk density is sensitive to the hydrocarbon density, whereasneutron porosity is sensitive to the hydrocarbon hydrogen index.Hence, the comparison of the density and neutron porosities pro-vides a qualitative differentiation of gas from oil. However, thereis no unique relationship between hydrocarbon density and hydro-gen index for properties such as hydrocarbon gravity and GOR.The sonic quicklook on the basis of Vp/Vs comparison to the em-

pirical Vp/Vs wet-sand trend (Brie et al. 1995) can provide a qual-itative differentiation of liquid from gas (the presence of hydrocarbon in the reservoir is indicated when Vp/Vs falls belowthe wet-sand trend; the larger the separation between Vp/Vs andthe wet-sand trend, the lower the water saturation and the lighter the hydrocarbon). It is, however, also a qualitative method, andsome of the limitations include the effect of clay and the presenceof residual gas (which will also show separation on the Vp/Vsquicklook method). Resistivity is indirectly sensitive to the uidtype through the sensitivity to irreducible water saturation, butknowledge of the rock capillary properties may be necessary tomake these inferences regarding the uid type. In short, the analy-sis of reservoir uids is best achieved by methods that are sensi-tive to those uids while being relatively insensitive to rockproperties.

This explains why other measurements are required to gainmore insight into the uid-type variations across a reservoir. Atypical method for obtaining reservoir uid PVT information is toacquire downhole formation-uid samples by use of a WFT. Cap-turing a representative sample (i.e., the correct proportion of gasto oil) can be challenging when the pressure falls below the bub-blepoint or the dewpoint (saturation pressure). Other challengesinclude reducing ltrate contamination to the lowest possiblelevel or acquiring enough samples to cover the uid composi-tional variations within the reservoir. This latter challenge can belightened by acquiring saturation-proling data from an NMR dif-fusion-based tool. This approach provides uid-typing informa-tion as a continuous depth log. It can, however, be limited byinvasion because the NMR depth of investigation typically doesnot exceed 4 in.

This case study illustrates how formation-tester data and sam-ples, as well as NMR diffusion-based data, can complement eachother to describe reservoir-uid-property variations. Techniquelimitations will also be discussed.

Geological SettingThe well analyzed in this case study was the rst in the structuretargeting potential gas and gas condensate reservoirs thought tobe present in the area. The structure is formed by a two-way foldbounded by major steep extensional faults, which have throws in

excess of 200 m. The well was targeting a variety of depositionalenvironments including levee/sheets, channel sands, and incisedvalley cuts. The primary targets were stacked levee/sheets acrossthe crest of the structure. There was also minor faulting, with thefaults thought to be sealing. This faulting and stratigraphic com-plexity increases the likelihood of numerous isolated compart-ments. The evaluation of these compartments and their hydrocarbon properties is important for both petroleum-systemsunderstanding and evaluation of development options.

Fluid Typing From Nuclear and Sonic LogsPreliminary understanding of uid-type distribution is based onbulk density, neutron porosity, and sonic data. Fig. 1 shows thethree sections of the well that are discussed in this paper.

In the reservoir section below X200 m in the left log on Fig. 1,the presence of gas at the top of the column and oil at the base of

Copyright VC 2013 Society of Petroleum Engineers

This paper (SPE 150886) was accepted for presentation at the North Africa TechnicalConference and Exhibition, Cairo, 2022 February 2012, and revised for publication. Originalmanuscript received for review 7 November 2012. Revised manuscript received for review 27February 2013. Paper peer approved 20 May 2013.

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the hydrocarbon column, below X237 m, can be inferred from theconventional logs. Water is found below X256 m.

In the middle log section in Fig. 1, the reservoir below X961m seems to contain liquid hydrocarbon on the basis of bulk den-sity and neutron-porosity data. The density-neutron crossover could be reduced by the presence of clay. However, the sonicVp/Vs quicklook seems to indicate light hydrocarbon.

In the reservoir sections displayed on the right in Fig. 1,increased density-neutron separation and Vp/Vs quicklook separa-tion between measured Vp/Vs and Vp/Vs wet-sand trend correla-tion seem to indicate dryer gas than what is found in the deeper sections of the well.

As mentioned in the Introduction section, this approach isqualitative at best. It depends not only on the uid properties butalso on the effects of lithology (principally the clay content) andporosity.

Formation-Tester Sampling and Fluid AnalysisDFA with a uid analyzer module of a WFT tool provides uid-property information in real time and at downhole conditions. TheDFA techniques use the absorption spectroscopy properties of hydrocarbons and carbon dioxide (CO 2 ) to derive reservoir-uidcomposition on the basis of the mass percentage of methane (C 1 ),ethane through pentane (C 2 C5 ), hexane and heavier hydrocar-bons (C 6 ), and CO 2 (Mullins et al. 2004). The GOR of reservoir uid is also estimated with the DFA techniques in real time with-out ashing the uid sample.

Fluid-type analysis based on WFT pressure data can presentsignicant uncertainties, because small uid-type variations or uid anomalies are undetectable in many cases. These uncertain-ties could be caused by, for example, depth and pressure-sensor inaccuracy or low resolution, cable creep, and presence of lamina-tions in the reservoir. The benets of the use of DFA techniqueshave been well-documented in the literature. With enlightened res-ervoir-uid information, the sampling process is highly optimizedin terms of where and when to sample and how many samples totake. In addition, the DFA techniques are used to monitor uid-

phase separation and mud-ltrate contamination, to detect uidanomalies early (e.g., uid grading, GOR inversion, and uid-con-

tact validation), and to ensure that representative high-quality res-ervoir-uid samples are acquired in single phase and with lowltrate contamination, and to determine that these samples arevalid for accurate reservoir characterization (Dong et al. 2002).

Furthermore, uid properties from the downhole measurementcan be a conrmation of the results of subsequent sample analysisin a surface laboratory, because laboratory analysis results maynot be representative of formation uids for reasons such asimproper sample handling, sample-bottle leakage during transpor-tation, and delayed evolution or scavenging of hydrogen suldeand CO 2 . In these cases, uid properties from DFA are particu-larly useful to identify questionable results, help reconcile anydiscrepancy, and prevent nonrepresentative results from beingused in reservoir evaluation and management.

Fig. 2 shows the typical tool conguration used to acquire thepressure and DFA data. The two DFA tools in the string are a liveuid analyzer and a composition uid analyzer. The live uid ana-lyzer determines GOR for black oils (0 to 2,000 scf/bbl) anddetermines the percentage of oil-based-mud (OBM) ltrate con-tamination by use of the OBM contamination monitoring algo-rithm (Dong et al. 2002). The live uid analyzer also performsgas detection by an index-of-refraction method. The compositionuid analyzer determines the C 1 , C2 C5 , and C 6 hydrocarbonfractions and CO 2 and partial mass densities for hydrocarbons inthe range of 1,500 to 20,000 scf/bbl. GOR is also given, but thisquantity becomes less well-dened for higher-GOR uids. Thecomposition uid analyzer also detects retrograde dew formationby uorescence methods (Mullins et al. 2004).

The density (DV) sensor is based on the measurement of theresonance characteristics of a vibrating rod inside a uid. The res-onator (rod) is resistant to corrosive uids, is small and compactin design, has no dead volume, and is easily integrated in the toolowline because no electrical elements are in contact with theuid (Ardila et al. 2008). The DV sensor can be inserted into ei-ther the probe or DFA module of the WFT.

A central feature of DFA is to make uid comparisons fromone DFA station to the next. It is the variation of compositionwith spatial location that DFA must delineate. DFA at different

stations within a well has the same tool, same calibration, sameoperator, same temperature, and same time but different uids.

Fig. 1Conventional logs for three sections of the well. For each section, the tracks are as follows. Track 1: gamma ray, caliper;Track 2: resistivity; Track 3: bulk density, neutron porosity, photoelectric factor, and density correction; Track 4: sonic Vp/Vs com-pared with Vp/Vs wet-sand trend; Track 5: lithology from spectroscopy.

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Consequently, DFA is very sensitive to uid variationsevenmore so than the laboratory. And it is the real-time delineation of uid variations that is essential for optimally understanding theuid column. Furthermore, DFA acts to ngerprint the hydrocar-bon uid, enabling the validation of laboratory samples by labora-tory conrmation of this ngerprint. This chain of custodyvalidation has been demonstrated successfully in eld trials(Betancourt et al. 2006).

To validate the uid measurement and to collect samples withthe lowest contamination, the tool was congured with thefocused-sampling technique (Weinheber and Vasques 2006). Sub-sequently, the laboratory PVT analysis of the samples showedmud-ltrate contamination levels to be less than 5% by weight(with respect to the total reservoir uid) for all the samples. Thisdemonstrates the efciency of the focused-sampling technique for achieving low contamination levels. In addition, the sampling-tool string was congured with reverse low-shock sampling.

NMR Saturation-Profiling PrinciplesNMR data were acquired by the latest generation of NMR tools.The NMR tool was run in saturation-proling mode at two inde-pendent depths of investigation (DOIs) (in this paper, the datafrom these two DOIs are called Shell 1 and Shell 4, with respec-tive DOIs of 1.5 and 2.7 in.) and a 9-ft vertical resolution.

The saturation-proling mode allows a model-independentmeasurement of formation-uid volumes. No external informa-tion input is required except for gas (methane) hydrogen index,pressure, and temperature. This is possible because the saturation-proling mode of this NMR tool not only measures longitudinal-relaxation-time ( T 1 ) and transverse-relaxation-time ( T 2 ) informa-tion, but also diffusion. Diffusion allows water, oil/OBM ltrate,

and gas signals to be differentiated, which is not always possiblewith T 1 or T 2 information alone. The ability to compare measure-

ments at different DOIs (radial proling) enables the quantica-tion of uid-property changes occurring in the rst few inches of formation away from the wellbore. Borehole rugosity and thickmudcake can invalidate shallow NMR measurements but onlyrarely affect the readings from the deeper DOIs. Radial prolingalso provides valuable insight into uid invasion and formationdamage. Fluid-property changes resulting from mud-ltrate inva-sion may also be observed and quantied by use of radial prol-ing. Whole mud and mud solids can replace existing uids in thenear-wellbore region. Radial proling identies and overcomesthese effects.

From the depth-based saturation-proling data, 2D maps can beproduced for each shell over stacked intervals. These maps plot dif-fusion vs. T 1 or T 2 (D-T maps). The intervals are selected becausethey present relatively homogeneous petrophysical properties. Thedata in these intervals are stacked to reduce the amount of noise bya factor proportional to the square root of the number of stackedlevels. Thus, the 2D maps provide a very good way to interpret thedata to determine the uid types and to extract information fromthe radial proling by comparing shells at different DOIs.

As an aid to interpreting the 2D maps, uid-diffusion coef-cients are typically superimposed on the maps (e.g., see Fig. 3 ).The magnetic-resonance uid model for oil, gas, and water statesthat the water- and gas-diffusion constants are independent of T 1or T 2 , and depend on temperature and pressure (for gas). The gas-diffusion values are typically represented by a red horizontal line,

and the water-diffusion values are typically represented by a bluehorizontal line (i.e., constant diffusion coefcient). The oil line(green) is derived from the estimated dead-oil response at down-hole conditions. The oil line drawn on the D-T maps shows thetheoretical position of oil at different viscosities, with the lower left as heavy oil, trending to light oil and rich gas/condensate atthe upper right. Deviations from the ideal uid responses are evi-dent in the maps because the data are away from the overlay lines.Some causes of the deviations from ideal responses are discussedby Akkurt et al. (2009).

Formation oil and OBM ltrate both have long relaxationtimes, so separating them accurately is not simple. T 1 relaxationtimes in excess of 2 seconds have, however, been observed in thiswell, and these reveal the presence of formation oil. On the depthlog, OBM ltrate and formation oil volumes have been computedand presented on the basis of setting a (arbitrary) cutoff of T 1 2seconds to separate them (on the log plots, OBM ltrate is shownwith black shading and formation oil is shown with green shading).No base-oil surface T 1 measurement is available. However, base-oil samples at surface measured in other wells with similar mudtypes have given OBM base-oil T 1 values at approximately 1 sec-ond at 80 F. This translates into T 1 of approximately 1.5 secondsat 160 F. Thus, a T 1 cutoff of 2 seconds to separate OBM ltrateand formation oil appears sensible. There is uncertainty in thismethod, but it provides the identication of the zones in which thepresence of formation oil is likely. Increasing oil volumes withDOI also give additional information of the presence of formationoil. To the contrary, decreasing oil volumes with DOI are morelikely to indicate mud ltrate. Fluid identication in poorer-quality

reservoirs is more difcult; thus, some uncertainty exists.In the case study that follows, the maps are presented with T 1as the horizontal axis because T 1 is better suited for highly diffu-sive uids such as gas and light oil (Heaton et al. 2004).

Also see Cao Minh et al. (2003) and Heaton et al. (2004) for more information about the 2D-map principles and interpretation.

Case StudyThis case study analyzes the NMR data in parallel with the forma-tion-tester results to identify the uid distribution in the well andto quantify the uid properties. The review of the data takes placezone by zone.

Zone 1. Fig. 3 shows NMR saturation-proling data over the bot-

tom part of the well. The left-hand side of Fig. 3 shows the con-ventional logs together with the results of the NMR saturation

MRPO

MRPQ1

MRHY1

MRPQ2

MRHY2

MRPCEDTA-A

EDTA-B

Run 1 - Pressures Run 2,3 - Sampling

Length - 18 m

Length - 35 m

MRP02

MRPQ2

MRHY2

MRPQ1

MRHY1

MRPCEDTA-A

EDTA-B

MRBA

LFA

MRPO

CFA

MRMS2

MRMS1

CFA2

Fig. 2Typical WFT tool conguration used to acquire pres-sure and DFA data.


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proling for the two independent DOIs at 1.5 and 2.7 in. (last twotracks on the right-hand side). The output of the saturation prol-ing is the uid volumesfrom right to left, gray is the bounduid, light blue is the free water, green is the formation oil, blackis the OBM ltrate, and red is the gas. The red boxes illustratethree zones over which the data have been stacked to create the2D maps shown on the right for the two DOIs.

The initial observation of the maps in Fig. 3 for Zone 1 revealsthe presence of a signal similar to that of water (medium T 1 valuebetween 10 and 100 ms, diffusion coefcient similar to that of water). This is, in fact, the invasion of solids carried by the mud.These solids could have their origin in mud weighting agents, drillcuttings, or in unconsolidated formation, they could be pushed bythe mud from the very near borehole into the formation. Thismud-solids invasion is partly masking the hydrocarbons seen bythe NMR. The peak with diffusion similar to that of water isaccompanied by a very high diffusion peak with a slightly longer T 1 . This signature is associated with the OBM signal (it can alsobeen seen on the shallow shells in washed-out zones). The mud-solids invasion can also be deduced from the bound-water volume,because it is higher than expected when considering the quality of the sand (as indicated by the spectroscopy data). The excessivebound-water volume is clearly visible on Shell 1. The mud-solidsinvasion was also observed on the conventional core.

The mud-solids invasion occurred because of the high perme-ability of the sands (reaching up to several darcies) and the rela-tively high mud weight (11.3 lbm/gal). Although the caliper shows some borehole rugosity, it does not appear that the signalidentied as mud solids could, in fact, be attributed to the bore-hole condition, because this would translate into excessive poros-ities, which is not the case here.

Among other sources, evidence for the downhole NMR patternof OBM was found in another well, in a fractured shale interval inwhich losses had been observed. The NMR radial prole in this

shale over three DOIs is shown in Fig. 4. A T 1 vs. diffusion pat-tern similar to that caused by the mud solids invasion is visible.

The fact that the deepest shell is unaffected by the phenomenonconrms that it is related to the borehole uid.

The mud-solids invasion was incorporated in the water volumeon the depth-log interpretation because water and mud-solidsinvasion cannot be differentiated. The resistivity indicates that thezone is above the oil/water contact.

OBM ltrate is seen on the shallowest shell. On the deeper shell, the oil signal could be a mix of native formation oil andOBM ltrate.

Fig. 5 shows the pressure and sampling results from the WFTover the bottom part of the well, including pressure and draw-down mobility data, Timur-Coates permeability from NMR Shell4, and DFA data from both live uid analyzer and compositionuid analyzer tools. The last four tracks on the right, respectively,show the DV-rod sensor uid density corrected by equation of state (EOS) (see Zuo et al. 2008; Godefroy et al. 2008), EOS-cor-rected GOR from the composition uid analyzer, live uid ana-lyzer uid fractions, and EOS-corrected composition uidanalyzer compositional fractions. No samples were acquired inZone 1, and only pressure data are available (because of the lossof seal while attempting to sample). The pressure points acquiredat this zone t on an oil gradient of 0.66 g/cm 3 .

Zone 2. In Zone 2 (Fig. 3), formation oil, with its long T 1 signalin excess of 1 second, is visible on the deepest shell. OBM ltrateinvasion is visible on the shallowest shell (or possibly a mix of l-trate and formation oil), and some mud-solids invasion is presentalso. However, the invasion is not as deep as in Zone 1. The OBMinvasion is decreasing with DOI, as expected. Over Zones 1 and2, the average oil viscosity computed on the basis of the NMRdata is approximately 0.65 cp, and the OBM-ltrate viscosity isapproximately 2.3 cp.

A uid sample was taken in this zone (indicated by a black doton Fig. 3) with the formation tester. Fig. 6 shows the density mea-

surement. The uid density was reported as 0.676 g/cm3

vs. 0.66g/cm 3 from the pressure gradient.

VXOBMF_SH1 VXOBMF_SH4

Oil

Oil

OBMF

Mud fines invasion

Mud fines invasion

Zone 1

Zone 2

Zone 3

RichGas

Fig. 3Saturation-proling depth log for two DOIs (shown as last two tracks on the right, on a scale of 0.4-0 v/v) and stacked 2Dmaps (the stacking interval for each set of maps is shown by a red box on the depth log). Zone 1, above the OWC, shows the pres-ence of formation oil despite the mud-solids invasion seen on both shells. In Zone 2, the formation oil is visible on both shells. InZone 3, gas is clearly identied, with very little invasion on the deeper shell. The gas appears as rich gas, because it has a lowerdiffusion coefcient than that of methane (it plots below the red line).


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The composition uid analyzer log station (Fig. 7) conrmedthe presence of oil. At 1,750 seconds, the bypass between thesampling owline and the guard owline was closed for focusedsampling, and a jump in the GOR measurement was observed,indicating that the OBM-ltrate fraction dropped after closing theguard line. Especially at longer times, the GOR and uorescence

signals (see Fig. 7) are seen to change in concert, with both track-ing the owline cleanup (reduction of ltrate contamination).

Zone 3. In this zone (Fig. 3), gas presence is very clear from the2D maps. The gas is a rich gas, and as such, it has a lower diffu-sion coefcient than that of methane (it plots below the theoretical

Zone 3

Zone 2

Zone 1No samples acquired in this zone

Zone 3aX180

X200

X220

X240

X260

X280

X300

X290

X270

X250

X230

X210

X190

Fig. 5Pressure and sampling results from WFT runs over the bottom part of the well. DFA demonstrated the presence of oil insamples from Zone 2 and rich gas from Zone 3. No samples were acquired on Zone 1 because of hole conditions. The red boxesshow the zonation as presented in the NMR gures (Figs. 3 and 8). Tracks 3 and 4, respectively, show the pressure and drawdownmobility data as well as the Timur-Coates permeability from NMR Shell 4. Tracks 5 and 6 show the conventional openhole logs (re-sistivity and density-neutron, respectively). DFA data from both the live uid analyzer and composition uid analyzer tools are

shown in the last four tracks, respectively, as the DV-rod sensor uid density corrected by EOS, composition uid analyzer EOS-corrected GOR, live uid analyzer uid fractions, and EOS-corrected composition uid analyzer compositional fractions.

10 1

10 0 10 1 10 2 10 3

10 2

10 3

10 4

10 5

Longitudinal Relaxation Time (ms)

D-T1

2D Map plot (1.5 in)Total NMR porosity:0.51 v/v

2D Map plot (2.7 in)Total NMR porosity:0.39 v/v

2D Map plot (4 in)Total NMR porosity:0.218 v/v

D i f f u s i o n

C o n s t a n

t ( m

2 / s )

10 1

10 0 10 1 10 2 10 3

10 2

10 3

10 4

10 5


D-T1

D i f f u s i o n

C o n s t a n

t ( m

2 / s )

10 1

10 0 10 1 10 2 10 3

10 2

10 3

10 4

10 5


D-T1

D i f f u s i o n

C o n s t a n

t ( m

2 / s )

Fig. 4Evidence for downhole signal associated with OBM in a fractured shale zone. OBM has a similar T1 as that of free water(T1 ~ 10100 ms) but it is also clearly identiable from the associated high diffusion peak with a slightly longer T1. Only the twoshallowest shells are affected by the OBM signal. Excessive porosity on the shallow shells also points towards borehole effect.


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gas-diffusion line). Relatively little OBM-ltrate invasion is seen,but a large volume of mud-solids invasion is visible on Shell 1.This invasion is very shallow, because Shell 4 appears relativelyunaffected. The bound-uid volume from Shell 4 seen on thedepth log appears to be in line with the amount of clay seen byspectroscopy, unlike in the zones below. The bound-uid volumefrom Shell 1 is clearly too high, and this conrms mud-solidsinvasion.

The DFA results (Fig. 5) show uid compositional gradingfrom X180 to X234 m, as observed on the uid-density variationfrom 0.18 to 0.20 g/cm 3 and on the GOR variations (qualitativevalues, because the tool has low resolution at high GOR values,as discussed in a previous paragraph). Assuming one hydraulicunit and one uid density, the uid gradient from pressure datawas computed as 0.21 g/cm 3 .

The DFA conrms that the uid is a rich gas. A sample wastaken below Zone 3 at X227 m. The composition as measured byPVT analysis is very close to the composition of the sample atX205 m, whereas the composition uid analyzer uid density andGOR data show small variations, which is consistent with compo-sitional equilibrium. Similarly, the diffusion coefcient from the

NMR map at this depth is the same as measured in the interval sit-uated between Zones 2 and 3.

Zone 3a. This zone is immediately above Zone 3 (Fig. 8). Littleor no nes invasion is visible, possibly because of the lower po-rosity and permeability of this zone. A compositional gradient isvisible on Shell 4. In the lower part of the reservoir, very light oilis observed, with a long T 1 and a relatively low diffusion coef-cient, just higher than that of water. As depth decreases, the lightoil becomes rich gas, and a mud-ltrate signal appears. OBM l-trate is clearly seen on Shell 1, in addition to a rich-gas signal.

The DFA results conrm a subtle compositional gradient: Thesample at X191.1 m has slightly less C 1 and more C 6 than thesample at X182.5 m. The same trend is reported on the PVTresults. Such a compositional gradient could be consistent withthe reservoir being connected and in equilibrium (Mullins et al.2005 and 2010).

Zones 4 and 5. In Zone 4 (Fig. 9), the presence of gas dominatesthe NMR data. Formation oil is also clear on the deeper shell,

0

0.70.80.91.01.01.21.31.4

500 1000 1500

Mud filtratedensity of 1.35

g/cc

Oil densityof 0.676

g/cc

RODRHO_PQ1(g/cm 3), MRPQ 1 DV-Rod Fluid Density

2000 2500 3000 3500 4000 4500 5000 5500 6000 6500ETIM (s)

g / c m

3

Fig. 6DV-rod uid-density data for Zone 2.

00.0

0.550.600.650.700.750.800.850.90

0.0

1100

1150

1200

1250

1300

1350

f t 3 / b b l

0.10.20.30.40.50.60.70.80.91.0

u n

i t l e s s

uni t l e s s

0.20.40.60.81.01.21.4

500 1000 1500

FLD0_CGA(V), CGA Fluorescence Channel 0

CHCR_CGA(0), CFA Cumulative Hydrocarbon Composition Ratio, C1

G OR _C GA (f t3 /b bl ), C GA GA S Ol R at io H ig h Q ua li ty M ed iu m Q ua li ty L ow Qu al it y

Flow Split

for focusedsampling Flow ratesadjusted

CFA

CHCR_CGA(1), CFA Cumulative Hydrocarbon Composition Ratio, C2-C5CHCR_CGA(2), CFA Cumulative Hydrocarbon Composition Ratio, C6+

FLD1_CGA(V), CGA Fluorescence Channel 1 FLRA_CGA, CGA Fluorescence Ratio

2000 2500 3000ETIM (s)

v

Fig. 7Compositional uid analyzer station logs acquired in Zone 2. The upper part of the plot shows the GOR, the middle partshows the uid-composition fractions (C 1 , C2 C 5 , and C 6 1 ), and the lower part shows the uorescence measurement. The dataconrm the presence of oil. At 1,750 seconds, the bypass between the sampling owline and guard owline was closed for

focused sampling, and a jump in the GOR measurement indicates that the OBM-ltrate fraction dropped after closing the guardline.


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with a signal with a very long T 1 (longer than that of OBM ltrate,which is expected to have an average value of 1.5 seconds). How-ever, the presence of gas is unquestionable because the NMRdetects a bigger volume of gas than oil (from the deep shell, gas

volume is approximately 10 p.u. although the oil volume isapproximately 5.6 p.u.).

The long T 1 signal observed in Zone 4 is not seen in Zone 5.Thus, the oil observed in Zone 5 could be composed of a large

X175

X186 m

X187 m

X184.6 m

X182 m

Zone 3a

Fig. 8Saturation-proling depth log for two DOIs and 2D maps (these maps are for single depth and are not stacked). Both oiland gas clearly coexist in this interval. A compositional gradient is visible on Shell 4. In the lower part of the reservoir, very lightoil is observed, with a long T 1 and a relatively low diffusion coefcient. As depth decreases, the light oil becomes rich gas, and amud-ltrate signal appears. OBM ltrate is clearly seen on Shell 1. Such a compositional gradient could be consistent with the res-ervoir being connected and in equilibrium. The gure description is the same as for Fig. 3.


Zone 4Zone 5

Gas

Oil

Oil

OBMF

Mud fines invasion

Mud fines invasion

Gas

Fig. 9Saturation-proling depth log for two DOIs and stacked 2D maps (the interval stacked for each set of maps is shown by ared box on the depth log). Both oil and gas clearly coexist in this interval. This coexistence could result from capillary effects.

Zone 5 could possibly have deeper OBM-ltrate invasion, and the oil signal could contain a large fraction of OBM ltrate. Mud-sol-ids invasion is observed in Shell 1 in both zones and in Shell 4 in Zone 4. The gure description is the same as for Fig. 3.


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proportion of mud ltrate, possibly indicating a deeper invasionthan in Zone 4. Less nes invasion is seen in this zone comparedwith Zone 4. It is not possible that the gas observed in Zones 4and 5 is only associated with gas dissolved in the oil phase. In thisscenario, the presence of two separate peaks, one for the oil andone for the dissolved gas, has been demonstrated in the laboratory(Hurlimann et al. 2008). However, because the observed gas vol-ume is larger than the oil volume, it is unlikely that all the gasobserved is dissolved in the oil. Thus, we have evidence that bothoil and gas are coexisting in this part of the reservoir. Capillaryeffects could explain the coexistence of both phases.

OBM ltrate is seen in both shells, as well as some mud-solidsinvasion, in particular in Zone 4. OBM-ltrate invasion appearslarger when oil is present in the reservoir, and one can observethat OBM-ltrate volume is typically lower in gas zones (becauseof buoyancy segregation).

Above Zone 5, a thin bed interval is present up to X918 m.The NMR identies a large fraction of gas in this interval. How-ever, formation oil as well as OBM ltrate are also both identi-ed; because of the low volumes of oil/OBM ltrate, theuncertainty regarding the exact proportions of each is high. TheOBM imager highlights the presence of thin laminations acrossthe same interval. The triaxial induction tool conrms the pres-ence of hydrocarbon by detecting high anisotropy levels.

Two DFA stations and sampling were taken. DFA results aswell as gradient results can be seen on Fig. 10. Oil was observedin the owline, and light oil was interpreted from both zones.While pumping formation uid at X980.4 m and X972 m, theDFA (Figs. 11a and 11b) not only shows mostly oil in the ow-line, but also shows spikes in the GOR and a decrease in uores-cence between strokes. This indicates hydrocarbon segregation inthe pumpout module. This also indicates that the reservoir is atthe bubblepoint and that the oil is saturated, because a small draw-

down causes the hydrocarbon to segregate into two phases. Theamount of gas increases as the drawdown pressure increases.

The main conclusion from the analysis of this zone is that bothDFA and NMR agree on the coexistence of two phases.

Zone 6. Fig. 12 illustrates the NMR results for Zone 6. From theNMR data, the gas appears drier than in all other zones: it plots onthe theoretical gas line, and there is very little OBM-ltrate inva-sion. Indeed, small invasion levels are usually observed on theshallow NMR data in the dry-gas case, which can be linked tobuoyancy segregation. A stronger separation on the Vp/Vs quick-look is seen, also pointing toward dry gas.

As seen on Fig. 13, two DFA stations were acquired in thiszone, at X704 m and X723.5 m. For the station at X704 m (Fig.13), the analysis revealed that the gas had a high C 1 concentrationand a small fraction of C 2 C5 , without C 6 . Traces of water wereobserved that affected mostly the uid-composition computation.At this station, no density measurement was available.

The uid-composition computation at the station at X723.5 mwas affected by window-coating effects, and thus the composition

is unreliable. However, on the basis of Fig. 14, the density sensor computed a uid-density value of 0.18 g/cm 3 , which shows alighter gas than what was observed on the gas sections at the bot-tom of the well. No valid uid gradient from pressure points wasobtained because of data scattering.

Technology Applicability, Limitations, andAdditional ConsiderationsThis case study demonstrated the value of combining the discretemeasurements of uid properties by use of DFA with continuousdepth-based NMR measurement.

The DFAs provide very detailed uid-property informationobtained directly from the reservoir uid at downhole conditionsbut only at selected depths. Capturing a representative uid sample

can also be challenging when the pressure falls below the bubble-point or the dewpoint (saturation pressure). The results can be

Zone 5

Zone 4

X970

X975

X980

X985

Fig. 10Pressure and sampling results from the WFT runs over Zones 4 and 5. DFA provides evidence for the presence of lightoil in both zones. No density data from the DV-rod sensor were acquired in these zones. The gure description is the same as forFig. 5.


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affected by OBM contamination or by the inability to extract uidfrom the formation when permeability is low. This can result in adata gap and the failure to recognize that a compositional gradientexistswithin the reservoir. Focused sampling was applied to addressthe issue of contamination and effectively resulted in low contami-nation levels, demonstrating the efciencyof the technique.

NMR complements DFA because it provides a continuous mea-surement of uid properties vs. depth. It sees the uid in situ, beforeany pressure drawdown is applied that could change the uid prop-erties. It is thus ideal to highlight uid-property variations. As avolumetric measurement able to differentiate productive from non-productive uids, it is sensitive to uid properties even in poor res-ervoir facies (from which it could be difcult to extract a uidsample). This paper illustrated this fact with an extreme case of complex reservoir (i.e., a thinly laminated section) (see intervalabove Zones 4 and 5, Fig. 9). In this latter case, uncertainties onuid-type determination increase, and we highlighted, in particular,that differentiating OBM ltrate from light oil became difcult.

One of the main limitations of NMR tools is their relativelyshallow DOI, which subjects them to borehole rugosity and bore-hole uid-invasion effects. This is, however, mitigated in this casestudy by multiple independent measurements at different DOIs.

The technologies presented in this paper have clear applicationsin the exploration phase of a eld, in which the uncertainties onuid types are highest and in which uid-property knowledge

affects facility design, reservoir management, and production strat-egies, and is thus important for planning the appraisal and develop-ment stages. These technologies also have applications at thedevelopment stage of a eld, when production has caused changesin uid distribution and properties that require recharacterization.

ConclusionsIt is generally accepted that DFA is a reliable source of informa-tion for reservoir-uid typing. However, because of the discretenature of the measurement, the combination of the formation tes-ter with diffusion-based NMR data has proved to be valuable inthis case study. The following conclusions could be obtained fromNMR and formation-tester data regarding the hydrocarbon typespresent in this well. Pressures for the oil zones are close to the bubblepointgas

segregation was observed in the pumping module while acquir-ing the downhole sample. This also correlated with a GORincrease between pump strokes.

The presence of oil is conrmed by the uid observed from thedownhole sampling process and by the presence of a long T 1signal on the NMR diffusion-based data.

Hydrocarbon-types variation has been observed across the res-ervoirs found in the well. Volatile oil and rich gas are found atthe bottom (Zones 1 through 3); toward the middle of the


Zone 6Gas

OBMFMud fines invasion

X730

Fig. 12Saturation-proling depth log for two DOIs and stacked 2D maps (the interval stacked for each set of maps is shown by ared box on the depth log). Zone 6 indicates dry gas. The gure description is the same as for Fig. 3.

Station @ X980.4 m Station @ X972 m

Fig. 11DFA station logs at (a) X980.4 m and (b) X972.0 m in Zones 4 and 5. Both stations showed the presence of free gasbetween strokes while pumping oil, indicating segregation in the pumpout module and that the reservoir is very close to thebubble point.


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section (Zones 3a, 4, and 5), the coexistence of oil and gas isseen by the NMR and the DFA. Dry gas is found at the top of the section (Zone 6).

Compositional gradients are seen by both NMR and the DFAacross the well.

Density measurements were critical to validate the pressure gra-dient and to determine uid-composition grading across themain gas zone. Pressure-gradient analysis did not allow a simi-larly detailed characterization. The uid grading and GORinversion were later conrmed by laboratory PVT analysis of the samples.

Hydrocarbon in thin beds/thin layers was conrmed by theNMR analysis, as well as high-resolution resistivity images andtriaxial induction resistivity data.

Mud-solids invasion has been observed in most of the reser-voirs, with varying depths of penetration. Mud-solids invasionseems deeper in the zones in which oil is present. The OBM-l-trate fraction is lower in the gas zones than in the oil zones.

OBM-ltrate contamination levels from PVT analysis of thesamples were less than 5% by weight, conrming the benet of using the focused-sampling technique to reduce contamination.

This enables quantitative uid-composition interpretation inreal time and valid comparison between zones.

ReferencesAkkurt, R., Bachman, H.N., Cao Minh, C. et al. 2009. Nuclear Magnetic

Resonance Comes Out of Its Shell. Oileld Rev. 20 (4): 423.Ardila, M., Hegeman, P., Dong, C. et al. 2008. Applications of Enhanced

Downhole Fluid Analyzer for the North Sea Operations. Paper pre-sented at the SPWLA 49th Annual Logging Symposium, Edinburgh,Scotland, 2528 May.

Betancourt, S.S. Bracey, J., Gustavson, G. et al. 2006. Chain of Custodyfor Oileld Samples Using Visible-Near-Infrared Spectroscopy. Applied Spectroscopy 60 (12): 14821487.

Brie, A., Pampuri, F., Marsala, A.F. et al. 1995. Shear Sonic Interpretationin Gas-Bearing Sands. Paper SPE 30595 presented at the SPE AnnualTechnical Conference and Exhibition, Dallas, Texas, 2225 October.http://dx.doi.org/10.2118/30595-MS.

Cao Minh, C., Heaton, N.J., Ramamoorthy, R. et al. 2003. Planning andInterpreting NMR Fluid-Characterization Logs. Paper SPE 84478 pre-sented at the SPE Annual Technical Conference, Denver, Colorado,58 October. http://dx.doi.org/10.2118/84478-MS.

Dong, C., Mullins, O.C., Hegeman, P.S. et al. 2002. In-Situ ContaminationMonitoring and GOR Measurement of Formation Fluid Samples. Pa-per SPE 77899 presented at the SPE Asia Pacic Oil and Gas Confer-

ence and Exhibition, Melbourne, Australia, 810 October. http:// dx.doi.org/10.2118/77899-MS.

X700

X720

0.18

Zone 6

Fig. 13Pressure and sampling results from the WFT runs over Zone 6. DFA provided evidence for the presence of a dry gas fromboth DFA stations in this interval. Density data from the DV-rod sensor were acquired only at the station at X723.5 m. The gure

description is the same as for Fig. 5.

0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

500 1000 1500

RODRHO_PQ1(g/cm 3), MRPQ 1 DV-Rod Fluid Density

2000 2500 3000 3500

0.18 gr/cc gas

1.35 gr/cc mud filtrate

4000ETIM (s)

g / c m

3

Fig. 14Composition uid analyzer data at X723.5 m below Zone 6uid-density measurement from the DV-rod sensor showsgas.


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Godefroy, S., Zuo, J.Y., Fujisawa, G. et al. 2008. Discussion on FormationDensity Measurements and Their Applications. Paper SPE 114648 pre-sented at the SPE Annual Technical Conference and Exhibition, Denver,Colorado. 2124 September.http://dx.doi.org/10.2118/114648-MS.

Heaton, N.J., Cao Minh, C., Kovats, J. et al. 2004. Saturation and Viscos-ity From Multidimensional Nuclear Magnetic Resonance Logging. Pa-per SPE 90564 presented at the SPE Annual Technical Conference andExhibition, Houston, Texas, 2629 September. http://dx.doi.org/ 10.2118/90564-MS.

Hurlimann, M.D., Freed, D.E., Zielinski, L.J. et al. 2008. HydrocarbonComposition From NMR Diffusion And Relaxation Data. Paper pre-sented at the SPWLA 49th Annual Logging Symposium, Edinburgh,Scotland, 2528 May.

Mullins, O.C., Fujisawa, G., Elshahawi, H. et al. 2005. Identication of Vertical Compartmentalization and Compositional Grading by Down-hole Fluid Analysis; Toward a Continuous Downhole Fluid Log. Paper presented at the 46th SPWLA Annual Logging Symposium, New Orle-ans, Louisiana, 2629 June.

Mullins, O.C., Hashem, M., Elshahawi, H. et al. 2004. Hydrocarbon Com-positional Analysis in-situ in Openhole Wireline Logging. Paper pre-sented at the 45th SPWLA Annual Logging Symposium, Netherlands,69 June.

Mullins, O.C., Zuo, J., Freed, D. et al. 2010. Downhole Fluid AnalysisCoupled With Novel Asphaltene Science for Reservoir Evaluation. Pa-per presented at the SPWLA 51th Annual Logging Symposium, Perth,Australia, 1923 June.

Weinheber, P. and Vasques, R. 2006. New Formation Tester Probe Designfor Low-Contamination Sampling. Paper presented at the 47thSPWLA Annual Logging Symposium, Veracruz, Mexico, 47 June.

Whitson, C.H. and Brule, M. 2000. Phase Behavior , Vol. 20, 117.Richardson, Texas: Monograph Series, SPE.

Zuo, J.Y., Zhang, D., Dubost, F. et al. 2008. EOS-Based Downhole FluidCharacterization. Paper SPE 114702 presented at the SPE Asia PacicOil and Gas Conference and Exhibition, Perth, Australia, 2022 Octo-ber. http://dx.doi.org/10.2118/114702-MS.

Marie Van Steene is currently Petrophysics Domain Championfor Schlumberger Egypt. She earned MSc degrees in mechani-cal engineering from E cole Centrale Paris (France) and Univer-site Libre de Bruxelles (Belgium). Van Steene started in 2000with Schlumberger as a wireline field engineer. She worked in

Australia, New Zealand, and India. In 2006, Van Steeneworked as a log analyst in Malaysia. She has been posted inCairo since 2007, working as a senior petrophysicist. VanSteenes interests include formation evaluation in open hole

and cased hole, NMR interpretation, and geomechanicalstudies. She is currently serving as secretary of the Society ofProfessional Well Log Analysts (SPWLA) Egypt Chapter.

Mario Ardila is a principal reservoir engineer with Schlumbergerin Houston. He holds a BS degree in petroleum engineeringfrom the Universidad Industrial de Santander in Colombia.Ardila spent the last 20 years with Schlumberger working in dif-ferent positions/areas (production engineering, reservoir engi-neering, well completion, well testing, cased-hole logging andinterpretation, and WFT and downhole fluid sampling), andhe has international experience in North and South America,Africa, Europe, and Asia. He is currently working as Director

of Curriculum-Reservoir Engineering/Production TechnologiesRapid Training Manager for Schlumberger PetroTechnicalServices Headquarters and in Houston (since August 2011).

Rick Nelson is a petrophysical consultant for BP. He is currentlyin the BP Egypt office in Cairo, where he is focused on explora-tion prospects in the Nile delta, with emphasis on operationspetrophysics, coring and core analysis, seismic rock properties,and general petrophysical integration. Nelsons previousassignments for BP included BPs London Sunbury campus,where he was working in the Azerbaijan Business Unit, and theTechnology Group in Houston involving a variety of projects inboth the US and abroad. Nelson holds a Bachelor of Engineer-ing Sciences degree from Johns Hopkins University and hasheld positions with Schlumberger/Geoquest and Oryx Energy(formerly Sun Oil and now Kerr-McGee). He has authored sev-eral SPWLA papers on a wide range of petrophysical topics.

Nelson has previously held chapter offices in Dallas and Hous-ton, served on the SPWLA Technology committee and Boardof Directors, and currently is one of the Petrophysics Journal associate editors.

Amr Fekry is a petrophysicist with BP working in exploration inEgypt. He holds a BSc degree in physics from the AmericanUniversity in Cairo. Fekry held the role of wireline engineer withHalliburton working in Saudi Arabia before joining BP in 2006.

Adel Farghaly works as a senior petrophysicist for RWE Deaand is currently working on assignment with BP West Nile DeltaProject in Sunbury, UK. He previously worked for the Gulf ofSuez Petroleum Co (Gupco) and with Amoco Egypt. He holdsa BSc degree in geology and holds a master studies degree ingeology and a master studies degree in petrophysics from AinShams University, Cairo. Farghaly specializes in thin bed and

core analysis. Farghaly has special interest and experience inprocessing and interpretation of NMR, triaxial induction, neu-tron spectroscopy and imaging data. He is a member ofSPWLA.

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