This paper was prepared for presentation at the 2000 SPE/DOE Improved Oil Recovery Sym-posium held in Tulsa, Oklahoma, 3–5 April 2000.

This paper was selected for presentation by an SPE Program Committee following review ofinformation contained in an abstract submitted by the author(s). Contents of the paper, aspresented, have not been reviewed by the Society of Petroleum Engineers and are subject tocorrection by the author(s). The material, as presented, does not necessarily reflect any posi-tion of the Society of Petroleum Engineers, its officers, or members. Papers presented at SPEmeetings are subject to publication review by Editorial Committees of the Society of PetroleumEngineers. Electronic reproduction, distribution, or storage of any part of this paper for com-mercial purposes without the written consent of the Society of Petroleum Engineers is prohib-ited. Permission to reproduce in print is restricted to an abstract of not more than 300 words;illustrations may not be copied. The abstract must contain conspicuous acknowledgment ofwhere and by whom the paper was presented. Write Librarian, SPE, P.O. Box 833836,Richardson, TX 75083-3836, U.S.A., fax 01-972-952-9435.

AbstractA novel fiber optic downhole fluid analyzer has been devel-oped for real-time determination of the oil, gas and waterfractions of fluids from different zones in a multizone or mul-tilateral completion environment. A near-infrared attenuationmeasurement provides differentiation among oil, water andgas at all but the highest water cuts. An induced fluorescencemeasurement unambiguously determines the oil fraction of thefluid as a validity check on the attenuation measurement. Theonly downhole components of the system are the fiber opticcable, lenses and windows, which may be installed in multiplelocations in the well and operated with a single surface unit.

IntroductionAs well completions become more complex, including multi-ple zones and multilateral legs, downhole monitoring of theproduction from individual zones becomes more essential.Intelligent completions give the operator the means to makechanges in production rates, but to do so requires real-time in-formation about fluid types. In particular, determination of theoil, gas and water fractions is necessary to make informed de-cisions on changes in production controls.

The system described in this paper involves a combinationof two optical techniques to determine the mass fractions ofoil, water and gas at remote locations within a well. Thesemeasurements are carried out remotely through the introduc-tion of optical sensors into the production tubing; the sensorsconsist solely of inert optical components and are, therefore,extremely robust.

Initial testing of the two methods in the laboratory showedthat the output signals produce excellent correlations with theknown percentages of oil, gas and water (for the attenuationmeasurements,) and oil (for the fluorescence measurement.)

The second phase of testing is being conducted in a low-pressure multiphase flow loop constructed for the purpose.Data are being obtained on system performance over a widerange of inclinations, flow rates and flow regimes.

Laboratory Testing & ResultsNear-infrared attenuation.

Apparatus & Measurements. The NIR attenuation meas-urements were carried out in an analogous manner using theapparatus shown in Fig. 1. Light from a broad band sourcecovering the near infrared wavelength range of at least 1000 –1700 nm is sent down an ~ 1 mile long, to simulate field de-ployment, to a reflectance probe, which is immersed in the oil-water mixture. The reflected light is carried by a second fiberof the same length to the detector system.

The NIR absorption method relies on differences in theopacity of oil and water to the transmission of infrared light.As illustrated in Figs. 2 and 3, crude oil absorbs light prefer-entially at 1220 and 1390 nm; water has a very strong andbroad absorption between 1400 and 1500 nm. It is, therefore,possible to distinguish between them based upon variation ofthe transmitted light intensity as a function of wavelength.

A key element of this apparatus is the solid state InGaAsspectrograph. This device permits the simultaneous determi-nation of the intensity at all wavelengths of interest. Standardscanning techniques sample different wavelengths sequen-tially. Since the local composition and scattering are expectedto vary rapidly with time, appropriate correction for scatteringrequires that the entire spectrum be acquired at once.

Two titrations were performed: water was titrated into oilto 50%, and oil was titrated into water to 50%, in steps of2.5%. The fluid is constantly stirred to prevent separation. Foreach mixture, a spectrum was gathered over 0.1 sec, and 100samples were averaged. Each titration was independently re-peated ten times.

Analysis. The results from each titration are shown inFigs. 4 and 5. The data are plotted after the normalization de-scribed below. A Partial Least Squares (PLS) fit was per-formed to each data set, with standard errors, as determined bythe “leave one out” method of 1.61 and 1.06%, respectively.An additional PLS fit was made to the entire range of concen-trations, and is shown in Fig. 6; the standard error for theoverall fit was 3.36%. Therefore, it is more appropriate to use

SPE 59303

Preliminary Testing of a Novel Downhole Fiber Optic Fluid AnalyzerMartin E. Cobern, SPE & William E. Turner, APS Technology, Inc.; John Cooper & Jeffrey F. Aust,Old Dominion University

2 M.E. COBERN, W.E. TURNER, J. COOPER & J.F. AUST SPE 59303

a fit optimized to the particular range. In the field implemen-tation of the system, a SIMCA (Soft Independent Modeling byClass Analogy) technique will be used to identify the appro-priate region and model to use for the conversion of measuredvalues to component fraction readings.

Simulation of response to natural gas. A critical featureof the downhole fluid analyzer will be its ability to identifyand quantify the presence of natural gas. Under typical down-hole conditions, natural gas is likely to be either in liquid formor in solution. As replication of the downhole conditions re-quires a high-temperature, high-pressure test apparatus, weelected to study the gas response via the use of a proxy

Natural gas consists primarily of methane (CH4), ethane(C2H6) and other small chain hydrocarbons (e.g., propane andbutane), which are characterized by the predominant presenceof methyl groups (-CH3). Crude oil, on the other hand, iscomposed primarily of longer hydrocarbon chains and aro-matics, which include some methyl groups, but predominantlymethylene groups (-CH2). Each of these radicals has a dis-tinctive NIR absorption band. Evans and Hibbard1 used theratio of these two absorption bands to determine the number ofmethyl and methylene groups per molecule in paraffins andlubricating oils. The liquid isooctane (2,2,4-trimethylpentane)was, therefore, chosen as a proxy for natural gas because of itshigh fraction of methyl groups and its ease of handling in thelaboratory.

The effect of adding isooctane to crude oil is illustrated inFig. 7, which plots the NIR signals detected as a function ofthe isooctane content. As the isooctane increases, the meas-ured intensity at the methyl absorption peak (~1195 nm) de-creases, while the intensity at the methylene peak (~1210 nm)increases.

In these simulated calibrations, isooctane was titrated intoa mixture of crude oil and water. The isooctane percentagewas varied from 0 to 20%; 100 spectra of 0.1 sec acquisitiontime were averaged for each data point, and the titration wasrepeated five times. After normalization of the data, as de-scribed below, a PLS fit was made to the data, and is shown inFig. 8. The standard error was determined to be 0.57%.

These measurements give confidence in the ability to dis-tinguish natural gas, whether in solution or in a liquid state,from crude oil in the downhole environment.

Fluorescence measurements.Apparatus and measurements. A schematic diagram of

the laboratory fluorescence test arrangement is shown in Fig.9. Light from a distributed Bragg reflector (DBR) diode laserat 852 nm is transmitted via an ~ 1 mile long optical fiber, to alaboratory probe. This probe, equipped with an appropriatefilter, allows the light to enter the oil/water mixture. The fluidis constantly stirred to prevent separation. A second mile-longfiber collects the light from both the input beam and fluores-cence and returns it to an optical spectrograph with a charge-couple device (CCD) sensor on the output. The CCD gener-ates a spectrum of the returning light, an example of which isshown in Fig. 10. The x-axis is given in pixel number, andcorresponds to a range of wavelengths of ~700 – 1300 nm.

The fluorescent light is at wavelengths longer than that of theincident laser.

As in the case of the attenuation measurement, two titra-tions were studied: water into oil and oil into water. In thefirst, the water fraction was increased in steps of 2.5% from 0to 50%; in the second, the oil fraction was increased in similarsteps from 0 to 50%. For each mixture, data were acquired for0.3 sec, and 100 samples were averaged for each data point.Each titration was repeated five times.

Analysis. Data from each set of measurements were nor-malized by dividing by the measured intensity of the trans-mitted laser light. This is a critical step, since both thetransmitted and fluorescent light are reduces in essentiallyequal amounts by the effect of scattering in the downhole flu-ids. Without this step, the measured fluorescence signalwould be dependent on the highly variable scattering mecha-nisms. The normalization technique is described in more de-tail below.

The resulting responses were fit to the known oil fractionsusing a partial least squares (PLS) method. Each half rangewas fitted independently, with the results shown in Fig. 10 andFig. 11; the full range fit is shown in Fig. 12. The range ofdata points for each composition is an indicator of the repeat-ability of the measurements. The standard errors were deter-mined by the “leave one out” algorithm. For the fits in Figs.10, 11 and 12, the standard errors were 1.87%, 3.31% and4.58%, respectively.

Normalization and Elimination of Scattering EffectsOne of the difficulties in making an optical measurement in anoil well or similar environment is that there are other phenom-ena that can interfere with the desired effect. For example,Raman scattering can generate secondary light at wavelengthswhich are longer than the incident light’s, which would over-lap with the light generated by fluorescence. By choosing anexcitation wavelength in the NIR region, 852 nm, the intensityof Raman scattering is greatly reduced, to the point of beingnegligible.

A more significant problem is the effect of scattering on alloptical measurements. Any measurement that depends uponthe intensity of transmitted or generated light will be influ-enced by the scattering in the fluid. Scattering will be highlyvariable with time as the composition of the fluid, or the flowregime, changes. Differences in solids content, or the size ofzones of a particular phase, can result in significantly differentlevels of scattering, which can generate large errors if propercorrections are not made.

There is one feature of scattering which aids in its elimi-nation – the scattering cross section is a slowly-varying andpredictable function of the wavelength. Over the rather nar-row bands of wavelength used in these two methods, it can beconsidered to be virtually wavelength-independent. By per-forming an overall normalization of the measured spectra, andthereby basing the analysis on the shape, rather than the over-all magnitude of the detected light, we can greatly reduce oreliminate the effect of scattering upon the determination of thecomposition.

SPE 59303 PRELIMINARY TESTING OF A NOVEL DOWNHOLE FIBER OPTIC FLUID ANALYZER 3

There are a number of possible means of normalizing themeasured spectra, Ii. For the fluorescence measurement, thearea of the transmitted laser peak gives an accurate measure-ment of both the effects of scattering in the fluid and anyvariations in transmission efficiency of the optical fiber. Forthe NIR absorption measurements, a more elaborate method isrequired. After surveying a number of possible techniques, wechose to use the vector length, f, as the normalization factor:

∑=

=m

iiIf

1

2 .............................................................(1)

The spectrum is replaced by the normalized spectrum. INi:

fIIN i

i = ................................................................(2)

Once the spectrum is properly normalized, the partial leastsquares fitting technique is applied to determine the appropri-ate weights for each component, as described below.

Calibration of the PLS ModelsRegardless of whether the attenuation or fluorescence methodof analysis was used, the concentration of each constituent(oil, water, gas) of interest is determined from the equation:

kin

m

iikkn bINC i +⋅= ∑

=

αβ1

..........................................(3)

That is, the concentration Ckn of the kth component in the nth

sample fluid is expressed as a weighted sum of the normalizedintensities INin at the ith wavelength in the sample. The coef-ficients, $ik are the weights, and bk is an additive constant.The exponents, "i, are generally taken to be 1, for a linear fit.(Note: For the attenuation measurements, the fit is performedto the logarithms of the intensities, IN.)

The weighting factor, $ik, measures the extent to which theintensity of the light at a given wavelength is a predictor of theconcentration of oil, water, or gas. These factors are deter-mined by a PLS regression from the calibration measurementson the titrated sample sets. PLS regression is a procedure thatsimultaneously estimates the eigenvectors in both the spectraldata and the sample property data. A weighting factor,$ , isobtained for each of the wavelengths to be used in the algo-rithm. The normalized intensity (IN) of the light componentat each wavelength is multiplied by the $ for the particularwavelength. The normalized and weighted intensities aresummed to calculate the concentration of oil, water, or gas.While there are a number of techniques available for solvingthese types of problems, the PLS gave the most consistent re-sults in determining the appropriate weights.

A “leave one out” validation technique was employed tocheck the accuracy of the calibration. Specifically, the PLSregression was run for each mixture used in the calibration,except one, and the resulting algorithm was then used to cal-culate the concentration of oil in the mixture omitted, and this

computed value was compared to the actual value. The qual-ity of the fits can be seen in Figs. 4-6, 8 and 11-13.

Flow Loop Testing & Results

Description of multiphase flow loop.A small-scale flow loop (shown in Fig. 14) was built to testthe effect of various flow conditions that resembled downholeflow patterns on the sensor response. The design of the flowloop was loosely based on an experimental multiphase facilityat the University of Tulsa2. While bench top testing in abeaker can produce mixtures with varying proportions of oil,water and "gas", the macroscopic phase properties can not becontrolled. The mixture is typically well mixed or begins toseparate. With the flow loop, the proportions of the phases canbe varied independently of variation in the multiphase proper-ties (e.g., slug flow, bubble flow, annular flow, etc.).

The flow loop consists of feed tanks, centrifugal pumps,flow meters, 2-inch PVC pipe and a settling tank. The loop isoperated in batch mode. Tap water and refined mineral oil(ρo/ρw=0.85, µo/µw=13) are separately pumped from their re-spective feed tanks and measured before being combined andcirculated through the loop. The fluid emerging from the loopenters the mixture tank where it is allowed to separate viagravity.

The key feature of the loop is a movable section (Fig. 15)which can operate at any inclination between horizontal andvertical. This leg is composed of several easily interchange-able sections to facilitate the rapid placement of sensors, mix-ers, etc. in different orientations. It is made of clear PVC toenable the observation and recording of the actual flow condi-tions at the measurement points. Typical operating conditionsinclude:

total flow rates: 10 to 60 gpmvelocities: 0.5 to 6 ft/secReynolds numbers: 500 to 100,000

Produced multiphase conditions range from very fine dis-persions to large bubbles or churn flow to stratified flow. It isrecognized that the conditions at which each of these multi-phase flow regime is produced will be different in the flowloop than in downhole situations. These differences are notsignificant, given that the objective of the flow loop testing isto track the response downhole fluid analyzer to each condi-tion, model the variations, and determine the operating limitsof the system, as well as the averaging necessary to obtain re-liable data.

Given the limited objective above, some approximationswere made which facilitate the observations. Mineral oil wassubstituted for crude oil. While the response of the NIR at-tenuation measurement will be different for mineral oil, wemay track the variation of this response with changing flowregimes and conditions. Air bubbles, rather than the danger-ous natural gas, are used to see the effect of bubble flow onthe responses, rather than to measure the absolute detection ofnatural gas.

4 M.E. COBERN, W.E. TURNER, J. COOPER & J.F. AUST SPE 59303

Finally, in testing the fluorescence measurement, we notethat mineral oil does not fluoresce under infrared excitation.To track the variation of the fluorescence reading, we add afluorescent dye to the water component, and track the inverseresponse (i.e., the water fluoresces, rather than the oil) to seethe effect of flow conditions. These compromises are neces-sary expedients to allow the timely optimization of the sensorgeometries, mixers, etc. More realistic testing is planned forthe next phase (see below.)

Conclusions & Future PlansBased on the laboratory and flow loop testing, a field proto-type sensor assembly will be designed and assembled. Thisunit will be used first in one or more high-temperature, high-pressure multiphase flow loops to verify the performance andaccuracy of the sensors under more realistic field conditions.Once the design has been properly qualified, prototype sys-tems will be installed in producing wells of increasing com-plexity. These tests will be run for extended periods to verifynot only the performance, but also the long-term reliability ofthe system and its ability to avoid fouling and damage.

Nomenclaturebk = additive constant for kth componentf = vector length of measured spectrum (counts)"i = order of fit for ith component (usually = 1)$ik = weighting factor for ith wavelength contribution to

the kth componentµ = viscosity (cp)ρ = density (kg/m3)II = intensity of ith component of spectrum (counts)

INi = normalized intensity of ith component (counts)m = number of wavelength components used in analysis

Subscriptsi = counter indicating wavelength component

k = fluid component (oil, water or gas)o = oilw = water

AcknowledgementsThe authors would like to thank the U.S. Department of En-ergy Federal Energy Technology Center for its financial sup-port of this research effort (Contract DE-AC26-98FT40481.)They would also like to thank the State of Pennsylvania for theBenjamin Franklin Grant that was essential for the initial ef-forts on this program.

References1. Evans A. and Hibbard, R.R.: “Determination of Carbon-

Hydrogen Groups in High Molecular Weight Hydrocarbons byNear Infrared Absorption,” Analytical Chemistry, vol. 23, no.11 (1951), 1604-1610.

2. Flores, J., et al., “Characterization of Oil-Water Flow Patterns inVertical and Deviated Wells,” SPE 38810, 1997

SI Metric Conversion Factorscp % 1.0* E–03 = Pa.sin % 2.54* E–02 = m

gpm % 6.309 E–05 = m3/smi % 1.6093 E+03 = m

*Conversion factor is exact

Solid-stateSpectrograph

Fiber Optics

Light source

2-fiber Reflectance Probe

Fig. 1: Instrumental Arrangement for Measuring NIR Absorption of Crude Oils

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6 M.E. COBERN, W.E. TURNER, J. COOPER & J.F. AUST SPE 59303

201510

Isooctane fraction (%)

40

5

10

15

20

50

Pred

icte

dV

al

Fig. 8: PLS fit to NIR absorbance data from isooctane titrationinto oil-water mixture. Isooctane fraction: 0 – 20%.

Spectrograph

CCD

DBR Laser (852 nm)

Stir Plate

Oil

Fiber Optics (1 Mile)

Probe w/ filters

Computer

Spectral Output

Fig. 9: Instrumental Arrangement for Measuring Fluorescence of Crude Oil – Water Mixtures

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3000

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4000

4500

5000

5500

6000

6500

7000

7500

8000

Inte

nsity

(A

rb. U

nits

)

0 100 200 300

Pixel Number

Laser

Fig. 10: Fluorescence spectrum of crude oil - 852 nm excitation

90

80

70

60

50

8060

5

100

Oil Fraction

100

Pred

icte

dV

al

50 70 90

Fig. 11: Partial Least Squares (PLS) fit to measured fluorescencedata (Oil Concentration: 50-100%)

SPE 59303 PRELIMINARY TESTING OF A NOVEL DOWNHOLE FIBER OPTIC FLUID ANALYZER 7

4020

5

10 30 50

Oil fraction

0

20

40

Pred

icte

dV

al

10

30

50

Fig. 12: PLS fit to measured fluorescence data (Oil Concentration:0-50%)

40

60

80

0

7

20 40 60 80 100

Oil fraction

0

20

Pred

icte

dV

al

100

Fig. 13: PLS fit to measured fluorescence data (Oil Concentration:0-100%)

Fig, 14: Multiphase flow loop for testing sensors. From left toright, tanks are for mineral oil, water and collection (mixture).

Fig. 15: Movable section of flow loop showing fluorescence testfixture.

Fig. 16: Example of flow pattern observed in test section while invertical orientation; oil droplets suspended in water.

Copyright 2000, Society of Petroleum Engineers Inc.

This paper was prepared for presentation at the 2000 SPE/DOE Improved Oil RecoverySymposium held in Tulsa, Oklahoma, 3–5 April 2000.

This paper was selected for presentation by an SPE Program Committee following review ofinformation contained in an abstract submitted by the author(s). Contents of the paper, aspresented, have not been reviewed by the Society of Petroleum Engineers and are subject tocorrection by the author(s). The material, as presented, does not necessarily reflect any positionof the Society of Petroleum Engineers, its officers, or members. Papers presented at SPEmeetings are subject to publication review by Editorial Committees of the Society of PetroleumEngineers. Electronic reproduction, distribution, or storage of any part of this paper forcommercial purposes without the written consent of the Society of Petroleum Engineers isprohibited. Permission to reproduce in print is restricted to an abstract of not more than 300words; illustrations may not be copied. The abstract must contain conspicuous acknowledgmentof where and by whom the paper was presented. Write Librarian, SPE, P.O. Box 833836,Richardson, TX 75083-3836, U.S.A., fax 01-972-952-9435.

AddendumIn the months since the paper was submitted, additional testinghas been performed at APS, both in the multiphase flow loopand on the benchtop. A brief summary of these results ispresented here.

Using the flow loop shown if Figs. 14 – 16, tests wereperformed at a variety of flow rates and conditions. As is shownin Fig. 17, a correlation between calculated and actual oilfraction was obtained in a vertical section. Ongoing tests areevaluating the ability of the system to make measurements atdiffering inclinations and flows, and whether it will benecessary to include diverters, mixers or multiple sensors tomake accurate measurement under these conditions.

During the course of discussions with major producers,another potential application for this technology was raised – themonitoring of the residual oil fraction in the water phase after adownhole separation. To evaluate this possible use, a low oilfraction titration was performed using Pennsylvania light crudeoil. The results, shown below in Fig. 18, show thatdetermination of the oil fraction to ± ~300 ppm is possible in therange of 0 – 2.5% oil. This is consistent with the performancespecifications for this application.

0 40 80

Oil Fraction

0

40

80

Pre

dict

ed

Val

ue8

Fig. 17: PLS fit to NIR absorbance measured in APS flow loop withmeasurement section vertical.

0 1 2

Oil fraction (%)

0

1

2

Pre

dict

ed V

alue

Fig. 18: PLS fit to NIR absorption results for low oil titration usingPennsylvania light crude: oil fraction 0 – 2.5%

SPE 59303

Preliminary Testing of a Novel Downhole Fiber Optic Fluid Analyzer [ADDENDUM]Martin E. Cobern, SPE & William E. Turner, APS Technology, Inc;John Cooper & Jeffrey F. Aust, Old Dominion University