SummarySelection of the best drill-in fluid for drilling horizontal wells isessentially based on the characteristics of the filter cake formed inthe near-wellbore region. Minimizing filtrate loss into the formationby forming a thin filter cake with low porosity and permeability isthe key to managing formation damage problems.

In this paper, the effects of drill-in fluid components and theirinteractions in the formation of a filter cake, which provides aneffective caking process with reduced filtrate loss, have been evalu-ated. Statistically designed experiments carried out with a dynamicfilter press apparatus were used to identify which variables had themost significant effect on filtrate loss and cake permeability so thatthe optimum fluid composition could be determined. These variablesinclude the formation characteristics (permeability and pressure values) as well as the type and amount of the fluid components.

Data obtained in this experimental design study were analyzedwith the multiple-linear-regression method, which allowed us tomodel the filtrate loss and cake permeability. The analysis showedthat the most important factors are the type and the concentrationof the polymer. In particular, when the formation temperature is ashigh as 90°C, we can reduce the cake permeability and the filtrateloss by increasing the concentration of scleroglucan. An interactioneffect between the concentration of scleroglucan and the morehighly crosslinked starch was also identified, and none of the othervariables showed any significant effects within the range of exper-imentation. This fact can be considered as an advantage because itallows flexibility in the choice of other factors when appropriatefor the cost reduction.

IntroductionControl of fluid filtration has long been recognized as a part ofgood drilling practices.1 Adequate control of drilling-fluid filtration characteristics, both the filtrate volume that enters the formation and the quality of the resulting filter cake formed in thewellbore, is needed to limit borehole instability, excessive torqueand drag, pressure-differential sticking, and formation damage.This concern is even more important in drilling horizontal wellswith water-based muds where the fluids remain in contact with thepay zone for a long period. Therefore, selection of the appropriatedrilling-fluid composition is considered key to minimizing drillingproblems and obtaining desired productivity levels.2

Development of specialized drill-in fluids3 (i.e., fluid formula-tions suitable for drilling reservoirs) has allowed better control offiltration phenomena during drilling operations. To limit filtration,these drill-in fluids can build up a thin filter cake with low permeability near the wellbore. As a consequence, the invasion ofsolid particles and mud filtrate into the formation is reduced to aminimum, and the permeability impairment is minimized.

To evaluate the drill-in fluid candidates for field application, arapid laboratory investigation was undertaken using a statisticalapproach. It allowed us to quantify the effects of fluid componentsand some operating conditions on filtrate-loss and filter-cake prop-erties. Selecting the correct chemicals and defining their concen-trations is paramount to obtaining the desired properties. Until

now, unfortunately, relatively little attention has been given to themutual interactions that may occur unintentionally betweendrilling-fluid components and the consequences for the propertiesof these complex fluids.

This paper focuses on a new, experimental method to approachthe selection and optimization of drill-in fluid compositions tominimize wellbore problems associated with filtration. The inves-tigation concerns the biopolymer/CaCO3 drill-in fluids proposed ascandidates for field operations in Italy.

Statistically Designed ExperimentsBy the phrase “statistical design of experiments,” we refer to theprocess of planning experiments that will ensure that the collecteddata can be analyzed by statistical methods. The statistical methodfor the experimental design is usually the most efficient approachwhen the effect of several variables has to be estimated simultane-ously, minimizing the number of experiments. It allows us to drawcorrelations when a lot of data are available, and it is useful inunderstanding what variables involved are the most important andif there are interactions among them. For every experimental problem, it is essential to consider two aspects—the design of theexperiments and the statistical analysis of the results. The twobasic principles of experimental design are replication and ran-domization. Replication allows us to estimate the experimentalerror and have a measure of the precision; randomization guaran-tees inferential validity in the face of unspecified disturbances.

The traditional one-variable-at-a-time (OVAT) approach modi-fies one variable with the remainder held constant and requires alot of experiments before obtaining conclusions. The method pro-vides an estimate of the effect of a single variable with selected,fixed conditions of the other variables.

Additional details on experimental design can be found elsewhere.4,5

ExperimentalWater-Based Polymer Systems. The investigations of thebiopolymer/CaCO3 fluids have been conducted on both scleroglucan-and xanthan gum-based drill-in fluids.

The fluid formulations can be represented as:• Brine.• Viscosity-inducing polymer.• Fluid-loss reducer.• Solid bridging particles.The viscosity-inducing agents are xanthan gum and scleroglu-

can, the most common biopolymers (especially xanthan gum) usedin drilling fluids. The concentration levels are 0.25 to 1%; the minimum polymer concentration was chosen on the basis of theminimum effective amount necessary to form a good gel structure.

Two starches with different crosslinking degrees and excellentfluid-loss performance were selected as fluid-loss reducers, and theirconcentration range is 1 to 3%. The crosslinking degree of the twoproducts was characterized from a semiquantitative point of view bymeans of solid-state1,3 nuclear magnetic resonance (C-NMR).

Sized acid-soluble calcium carbonate (CaCO3) was chosen asthe solid bridging particle, with a particle-size distribution suitableto the permeability of the rock-filter medium employed in thedynamic filtration tests. The two particle-size distributions wereoptimized following the D1,2 rule6 for high and low rock perme-ability (1,000 and 100 md, respectively). The concentration rangeof CaCO3 is 5 to 20%.

How To Manage Drill-In Fluid CompositionTo Minimize Fluid Losses

During Drilling OperationsS. Cobianco, SPE, M. Bartosek, SPE, and A. Lezzi, EniTecnologie SpA, and A. Guarneri, Eni-Agip Div.

Copyright © 2001 Society of Petroleum Engineers

This paper (SPE 73567) was revised for publication from paper SPE 57581, first presentedat the 1999 SPE/IADC Middle East Drilling Technology Conference, Abu Dhabi, UAE, 8–10 November. Original manuscript received for review 24 February 2000. Revised man-uscript received 4 December 2000. Paper peer approved 31 July 2001.

154 September 2001 SPE Drilling & Completion

Because density is a very important factor in fluid formulations,we included two formulation density levels, 1.1g/cm3 and 1.25 g/cm3,in the experimental plan. Minimum density was achieved byadding potassium chloride (KCl) brine, while calcium chloridebrine was used to increase the density by up to 1.25 g/cm3.

Experimental Design. After the initial step to evaluate the exper-imental filtration conditions and the suitable drill-in fluid compo-nent concentrations,7 a statistical experimental design was performed to optimize the filtration properties of the biopoly-mer/CaCO3 formulations. The variables investigated are the viscosity-inducing polymers, the fluid-loss additives, the bridging-particle concentration, the fluid density, the rock permeability, andthe applied differential pressure. The experimental plan wasdesigned with the STATISTICA* v. 5.0 software package (seeTable 1), which is the result of a D-optimal factorial design con-sisting of 12 experiments plus three centered points to estimate thereproducibility and the experimental error of two experiments withall the variables at the maximum and minimum levels, respectively.The design supported all the linear terms and some interactions inthe response model. The responses of the experiments are thedynamic filtration curves; from these curves, we considered thecumulative filtrate volume after 30 minutes, the final filtrate volume after 240 minutes, and the fluid-loss coefficient (Cw)8,9 fora statistical analysis (see Table 1).

Because the variables have a large range of values, an autoscalingtransformation of the variables was performed before the design.This transformation provided homogeneous variables in the rangeof 0 to 1 and could be expressed as follows:

where x�ij�the transformed variable, xi�the original variable, andxj,min and xj,max�the minimum and maximum values, respectively,of the variable xj.

Dynamic Filtration Experiments. The experiments included inthe plan in Table 1 consisted of dynamic filtration tests of drill-influid formulations performed on rock slices using a dynamic filterpress. The experimental equipment is illustrated schematically inFig. 1. This type of device is an improved OFI HP** filtration cellfitted with a motor-driven shaft and propeller to provide dynamicerosion of the filter cake. The unit can operate at up to 150°C and70 bar working pressure. The rock filter media are natural sand-

stone disks ¼ in. thick and 2½ in. in diameter with a high and lowpermeability of 1,000 and 100 md, respectively. The dynamic filtration unit was used to study filtration rates under different conditions and evaluate filter-cake quality.

The fluid formulations were prepared according to AmericanPetroleum Inst. (API) recommended practices. Rock slices weresaturated with brine (3% KCl) before the filtration experiments.The cell was then filled with 300 g of water-based muds and heatedat 90°C with 300 rotations per minute (rpm) as the stirring rate.When the temperature achieved 90°C, the pressure drop wasincreased until the desired value, 10 or 50 bar (as reported in Table1) was reached, and the stirring rate was increased to 700 rpm. Thedynamic filtration data were then collected by computer. Thecumulative filtration volume was monitored as a function of timefor a period of 240 minutes.

Results and Discussion Filtration Results. The filtration experiments were run in randomorder with the fluid formulations, rock permeability, and pressureconditions in accordance with the experimental plan in Table 1.The dynamic filtration results are the filtration curves. For all thetests performed, the filtration volume, plotted as a function of thesquare root of time, shows an upward trend in the first filtrationperiod and then a linear trend (see Fig. 2).

, . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . (1) ,min

,max ,min

i j

ij

j j

x xx

x x

−′ =

−

*StarSoft Co., Tulsa, Oklahoma.

**Dynamic Filtration Cell, OFI Testing Equipment, Houston.

TABLE 1—STATISTICAL EXPERIMENTAL PLAN

Input Variables Output Responses

ID

run

CX(%)

CS(%)

CST1

(%)

CST2

(%)

CCaCO3

(%)

Core

(md)

∆p(bar) (g/cm

3)

Spurt

loss(mL)

Vf(mL)

VFf(mL)

Cw(ft/min

1,2)

1 0.25 0 3 0 5 100 50 1.25 1.214 3.453 13.892 7.01 10-4

2 0.25 0 0 3 5 1,000 10 1.1 1.510 6.949 32.510 1.85 10-3

3 1 0 1 0 20 100 10 1.1 0.539 6.720 33.118 1.92 10-3

4 1 0 3 0 20 1,000 10 1.25 1.429 2.281 6.930 2.82 10-4

5 1 0 0 1 5 50 1.1 1.951 11.32 28.998 1.12 10-3

6 1 0 0 3 20 100 50 1.25 2.458 4.977 12.578 4.43 10-4

7 0 0.25 3 0 20 1,000 50 1.1 2.453 6.385 18.516 6.61 10-4

8 0 0.25 0 1 20 100 10 1.25 1.383 5.468 17.104 7.84 10-4

9 0 1 1 0 20 1,000 50 1.25 1.672 5.276 15.488 6.17 10-4

10 0 1 3 0 5 100 10 1.1 2.132 8.126 18.245 7.14 10-4

11 0 1 0 3 5 1,000 10 1.25 1.645 2.904 7.932 3.69 10-4

12 0 1 0 3 20 100 50 1.1 2.586 5.768 13.378 4.67 10-4

13 0 0.5 0 2 12 100 30 1.1 1.960 5.220 15.023 5.90 10-4

14 0 0.5 0 2 12 100 30 1.1 1.726 6.765 16.541 5.95 10-4

15 0 0.5 0 2 12 100 30 1.1 1.468 6.486 16.996 6.20 10-4

16 0 0.25 0 1 5 100 10 1.1 2.336 14.478 46.251 2.13 10-3

17 0 1 0 3 20 1,000 50 1.25 1.406 2.751 8.146 3.42 10-4

ρ

×××××××××××××××××

1,000

Fig. 1—Schematic drawing of the dynamic filter press used forthe dynamic filtration experiments. M�motor, P�pressure sen-sor, T�temperature sensor, and N2�pressurized nitrogen.

Data

Acquisition

Heating

jacket

Mu

d

Core

P

N 2

M

P T

Backp

ressu

re

reg

ula

tor

September 2001 SPE Drilling & Completion 155

To analyze the filtration results by statistical methods, however,we needed one or more numerical responses. Therefore, we drewthe filtrate volume after 30 minutes and after 240 minutes from thefiltration curves and the slope of the filtration curves in volume vs.square root of time after 100 minutes, the zone where there isalways a linear trend. The slope normalized when the filtration areaof the rock-filter medium gave the Cw. The Cw is a measure of thefiltration velocity of the fluid and the filter-cake permeability. Thelower the Cw, the lower the fluid-invasion velocity, the cake permeability, and the amount of potentially damaging filtrate.Although the values for all the experiments performed are report-ed in Table 1, we could not select the spurt loss volume as a validresponse for the statistical analysis. Before beginning the plan, wecalculated the experimental error for each response by replicatingone experiment three times (Table 1, experiments 13, 14, and 15)and found that the spurt loss value was affected by too high of anexperimental error; its reproducibility was not good enough toallow its use as a significant response in a statistical treatment.

The chosen filtration data were then analyzed with the multiple-linear-regression method. The general model that fit for eachresponse under investigation is as follows:

Ym ��c ��a1x1 ��a2x2 ��anxn ��b1x1x2 ��b2x1x3 ��bnx n�1xn ��e,

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

where c�a constant, an�the coefficients of the linear terms, bn�the coefficients of the interaction terms, e�the unexplained error,Ym�the responses (the dependent variables), and xn�the independent variables.

Multiple-linear-regression analysis allowed us to model theresponses independently. In this manner, the three responses couldbe compared by contrasting the coefficients, and the relative effectthat each common term had on the respective response could beidentified. With a 95% probability, the variables that have a signif-icant effect on the filtrate volume and the permeability of the cakewere the type and the concentration of the viscosity-inducing poly-

mer, the formulation density, and the interaction of the viscosity-inducing polymer with the fluid-loss reducer. The results indicatethat the other variables do not have any significant effects withinthe experiment range; this can be considered an advantage becauseit allows flexibility in the choice of the values of the other variableswhen appropriate for cost reduction. Different performances havebeen observed by comparing the scleroglucan fluid to the xanthangum system at 90°C.

Scleroglucan/CaCO3 Drill-In Fluid. The correlations for the scle-roglucan system with scaled coefficients are given in Table 2.

The adequacy of the models is evaluated by the correlation fac-tor (R2) and the trend of the residuals, which is the differencebetween the calculated response and the experimental response.The correlation factors are obtained from the plots of Figs. 3through 5, and the residual analyses are plotted in Figs. 6 through8. The same values of the correlation factor determined for both thescleroglucan and xanthan gum models depend on the algorithmused in the statistical analysis that permits evaluating both correla-tions simultaneously. The normal distributions, centered at zero ofthe residuals calculated for Vf, VFf, and Cw, indicate that the mod-els are adequate (i.e., the linear and interaction terms have beencorrectly introduced). The random distributions depend only on theexperimental error and not on the type of the selected models.

The variable that most strongly influences the filter-cake per-meability and filtrate volume is the scleroglucan concentration.

Fig. 2—Typical dynamic filtration curve for a polymer/CaCO3 fluid.Cumulative filtrate volume as a function of square root of time.

Fig. 5—Plot of the calculated Cw as a function of the experi-mental Cw.

Fig. 4—Plot of the calculated final filtrate volume (240 minutes) asa function of the experimental final filtrate volume (240 minutes).

Fig. 3—Plot of the calculated cumulative filtrate volume (30 min-utes) as a function of the experimental cumulative filtrate volume (30 minutes).

R 2 = 0.8991

0

2

4

6

8

10

12

0 2 4 6 8 10 12

Calculated Vf, mL

Observ

ed Vf, m

L

2 0.82R =Cw = 1.74(0.18) – 1.19(0.28)CS + 0.41(0.26)CST2 * ∆p

2 0.79R =

2 0.89R =

VFf = 20.46(0.31) – 3.23(2.58) ρ – 6.56(3.58)CS

Vf = 6.93(0.31) – 2.12(0.53) ρ – 1.89(0.66)CS * CST2

TABLE 2—CORRELATION MODEL FOR

SCLEROGLUCAN SYSTEMS

0

2

4

6

8

10

12

14

16

0 2 4 6 8 10 12 14

Time, minutes 0.5

Cum

ula

tive F

iltra

te V

olu

me, m

L

R 2 = 0.8206

0.00 10

5.00 10-4

1.00 10-3

1.50 10-3

2.00 10-3

2.50 10-3

0.00 10 5.00 10 -4 1.00 10 -3 1.50 10 -3 2.00 10 -3 2.50 10 -3

Calculated Cw, ft/min 0.5

Observ

ed C

w, ft/m

in0

.5

×

×

×

×

×

×× × × × × ×

156 September 2001 SPE Drilling & Completion

An increase in the viscosity-inducing polymer concentrationreduced the filtrate volume and the cake permeability (negativecoefficient in the models). The scleroglucan fluids allowed thebuildup of a very homogeneous and compact filter cake, whichprevented deep filtrate invasion and probably severe damage to theformation. The filtration properties also depend on the concentra-tion of the more highly crosslinked starch, essentially on the syn-ergistic interaction of scleroglucan-starch.2 A simultaneousincrease of the scleroglucan and the more highly crosslinked starchconcentrations decreases the filtrate volume, especially in the firstperiod of the filtration test (negative coefficient in the Vf model),when the formation and erosion processes are still not at equilibri-um. As a consequence, a more highly crosslinked starch is usefulfor obtaining a filter cake with lower permeability.

Xanthan Gum Drill-In Fluid. The variables that influence theperformance of the fluids containing xanthan gum as a viscosity-inducing polymer are summed in Table 3.

The xanthan gum concentration negatively influences the filtra-tion properties at 90°C. The positive coefficient (+11.74) indicatesthat an increase of the polymer concentration provides an increaseof the filtrate volume. A synergistic interaction of xanthan gum andCaCO3 is also obtained (+1.35) in the model of Cw. A simultaneousincrease of polymer and solid particle concentrations causes anincrease of the Cw value, which indicates a filter cake with higherpermeability.

After the filtration test, visual analysis and microscopic charac-terization (scanning electron microscope, or SEM, analysis) of thefilter cake showed that the filter cake formed with scleroglucan and

the more highly crosslinked starch showed as more homogeneous,compact, and tight than the ones containing xanthan gum or thestarch with a lower crosslinking degree.

Density always shows a relevant effect on filtration propertiesfor the drill-in fluids containing both scleroglucan and xanthangum. The negative coefficients in the models of the filtrate volumeindicate that fluids with higher density values have better filtrationproperties. The higher viscosity of the fluids can explain thisbehavior (Table 4). Under the same density conditions, the filter-cake formation could depend on both the viscosity and the bridg-ing solids, but after the first few minutes, the viscosity seems to bemore important for improving the filtration properties.

Bridging Particles. Solid bridging particles are usually added todrill-in fluid formulations to improve the sealing properties of thefilter cake, but it is common practice to keep them at minimumconcentration. During fluid optimization, the obvious question is:“Does the bridging-particle concentration really influence the fil-tration performance of drill-in fluid?”

From our statistical analysis of the dynamic filtration data, theanswer is “no” in the concentration range from 5 to 20%. Thebridging-particle concentration does not appear to affect the filtra-tion properties of the drill-in fluid formulations tested in our studywhen the particle-size distribution is correct and specific for thepermeability of the filter medium. Therefore, to minimize prob-lems resulting from the solid particles, it is possible to use drill-influids containing the minimum amount (5%) of CaCO3.

Formation Damage Results. Formation damage tests were per-formed to evaluate the damage potential of the two different for-mulations containing scleroglucan and xanthan gum as viscosityinducers. Tests were conducted in a Hassler sleeve flow cell at90°C and 10 bar of differential pressure with both high and lowpermeability cores. The fluids used in the coreflooding tests wereformulated with 0.5% of the viscosity inducer, 1.5% of the fluidloss reducer, and 7% of sized CaCO3. The results of the return per-meability tests show that scleroglucan/CaCO3 drill-in fluid exhib-ited the best performances with a complete permeability recovery,while the xanthan gum/CaCO3 system appeared to be less effectiveat this temperature with only a 75% return permeability.

Conclusions 1. A statistical approach has proved useful for optimizing drill-in

fluid formulations with dynamic filtration tests.2. The type and concentration of the viscosity-inducing polymer

are the factors that most strongly influence the filtration prop-erties and the cake permeability.

Fig. 6—Plot of the filtrate-volume (30 minutes) residuals (Vfcalc�Vfexp) as a function of the experimental cumulative filtrate volume (30 minutes).

Fig. 8—Plot of the Cw residuals (Cwcalc�Cwexp) as a function ofthe experimental Cw.

Fig. 7—Plot of the filtrate-volume (240 minutes) residuals(Vfcalc�Vfexp) as a function of the experimental cumulative filtrate volume (240 minutes).

10-4

10-4

10-4

10-4

-1.00 10-4

0.00 100

1.00 10-4

2.00 10-4

3.00 10-4

0.00 100

5.00 10-4 1.00 10

-3 1.50 10

-3 2.00 10

-3 2.50 10

-3

Experimental Cw, ft/min 0.5

Resid

ual C

wcalc–C

we

xp

-2.00

-3.00

-4.00

-5.00

×

×

×

×

×

×

×

×

×

× × × × × ×

10-4

10-4

10-4

10-4

-1.00 10-4

0.00 100

1.00 10-4

2.00 10-4

3.00 10-4

0.00 100

5.00 10-4 1.00 10

-3 1.50 10

-3 2.00 10

-3 2.50 10

-3

Experimental Cw, ft/min 0.5

Resid

ual C

wcalc–C

we

xp

-2.00

-3.00

-4.00

-5.00

×

×

×

×

×

×

×

×

×

× × × × × ×

2 0.82R =Cw = 1.74(0.18) – 0.51(0.47)CX * ρ + 1.35(0.41)CX * CCaCO3 + 0.41(0.26)CST2 * ∆p

2 0.79R =

2 0.89R =

VFf = 20.46(0.31) – 3.23(2.58) ρ – 19.39(5.05)CX * ρ + 11.74(4.06)CX

Vf = 6.93(0.34) – 2.12(0.53) ρ + 3.70(0.77)CX * ∆p – 3.21(0.91)CX * ρ

TABLE 3—CORRELATION MODELS FOR XANTHAN GUM SYSTEMS

September 2001 SPE Drilling & Completion 157

3. Scleroglucan formulation provides better filtration propertiesand a better filter cake than xanthan gum fluids at 90°C.

4. The fluid-loss-reducer performance of starches depends greatlyon their crosslinking degree. Above all, at 90°C, fluids contain-ing starches with a higher crosslinking degree allow more com-pact and less permeable filter cakes.

5. If the particle-size distribution of the bridging solids is opti-mized for the formation characteristics, the steady-state filtra-tion properties of drill-in fluids are independent of the bridging-particle concentration. The minimum amount of CaCO3 isenough to minimize fluid invasion and formation damage.

Nomenclature an � coefficients of the linear termsbn � coefficients of the interaction terms

CCaCO3� sized calcium carbonate concentration, %

CS � scleroglucan concentration, %CST1 � concentration of the starch with lower crosslinking

degree, %CST2 � concentration of the starch with higher crosslinking

degree, %Cw � fluid-loss coefficient, ft/min1/2

CX � xanthan gum concentration, %e � unexplained error

R2 � correlation factor, dimensionlessVf � filtrate volume (after 30 minutes), mL

VFf � final filtrate volume (after 240 minutes), mLxn � independent variablesx�ij � transformed variablexi � variable with possible dimensions of CS, CST 1, CST 2,

CCaCO3, Core, �p, �

xj � variable with minimum and maximum valuesYm � responses (dependent variables)� � density, g/cm3

�p � differential pressure, bar� � viscosity, Pa·s

AcknowledgmentsThe authors wish to thank the management of Eni-Agip Div. forpermission to publish this paper.

References1. Rojas, J.C. et al.: “Minimizing Downhole Mud Losses,” paper SPE

39398 presented at the 1998 SPE/IADC Drilling Conference, Dallas,3–6 March.

2. Aziz, T., Jin, W., and Rahman, S.S.: “Management of FormationDamage by Improved Mud Design,” paper SPE 38039 presented at the1997 SPE Asia Pacific Oil and Gas Conference, Kuala Lumpur, 14–16 April.

3. Davidson, E. and Stewart, S.: “Openhole Completions: Drilling FluidSelection,” paper SPE 39284 presented at the 1997 SPE/IADC MiddleEast Drilling Technology Conference, Bahrain, 23–25 November.

4. Box, G.E.P., Hunter, W.G., and Hunter, J.S.: Statistics forExperimenters—An Introduction to Design, Data Analysis and ModelBuilding, first ed., John Wiley & Sons, New York City (1978).

5. Kirk, R.E.: Experimental Design: Procedures for the BehavioralSciences, third edition, Brooks/Cole Publishing Co., Stamford (1995).

6. Kaeuffer, M.: “Determination de l’Optimum de RemplissageGranulometrique et Quelques Proprietés S’y Rattachant,” presented atCongrès International de l’A.F.T.P., Rouen, France (October 1973).

7. Eriksen, O.I. et al.: “Gel Formation and Thermal Stability of Gels MadeFrom Novel Water-Soluble Polymers for Enhanced Oil RecoveryApplications,” paper SPE 37247 presented at the 1997 SPEInternational Symposium on Oilfield Chemistry, Houston, 18–21 February.

8. Dawari, D.C. and Xie, Xiaopeng: “Effectiveness of Fluid LossAdditives in Laboratory Dynamic Fluid Loss Experiments,” paper SPE29498 presented at the SPE 1995 Production Operations Symposium,Oklahoma City, Oklahoma, 2–4 April.

9. Lord, D.L. et al.: “An Investigation of Fluid Leakoff Phenomena byUse of a High-Pressure Simulator,” SPEPF (November 1998) 250.

SI Metric Conversion Factorsbar 1.0* E � 05 � Pacp 1.0* E � 03 � Pa·s°F (°F�32)/1.8 � °Cin. 2.54* E � 00 � cm

*Conversion factor is exact.

Sandra Cobianco is currently a senior researcher atEniTecnologie SpA, the corporate research company of theENI Group. e-mail: scobianco@enitecnologie.eni.it. She joinedEniTecnologie in 1991, participating in projects concerningpolymer chemistry. She has been working in the upstream fieldon a sand consolidation project in the drilling fluids area, espe-cially dealing with drill-in fluid systems. Cobianco holds a PhDdegree in chemistry from the U. of Torino. Martin Bartosek iscurrently a senior researcher at EniTecnologie SpA. e-mail:mbartosek@enitecnologie.eni.it. He has been involved porousmedia and water shut-off studies since 1991. He was responsi-ble for the experimental work and setup of the facilities forporous media studies at high temperature and pressure inseveral upstream projects. Bartosek holds a degree in industrialchemistry from the U. degli Studi di Milano and joinedEniTecnologie's colloid science and chemical synthesis groupin 1990. Alessandro Lezzi is currently a senior project managerat EniTecnologie SpA. e-mail: alezzi@enitecnologie.eni.it. Hejoined EniTecnologie in 1986 and has participated as aresearcher on projects concerning polymer chemistry. He hasbeen working for 8 years in the upstream field, leading projectsconcerning exploration and production technologies. Lezziholds a degree in industrial chemistry from the U. of Pisa.Alberto Guarneri is currently a drilling and completion researchengineer at ENI Agip Div. e-mail: alberto.guarneri@agip.it. Hehas been working in ENI Agip since 1977, first as the drilling flu-ids rigsite engineer for 6 years, then the drilling fluids districtsuperintendent until 1996, and he has operated onshore andoffshore in Italy, West Africa, and the United States (Gulf ofMexico). Since 1997, he has been the drilling and completionresearch engineer in ENI Headquarters in Milano, involved inprojects concerning underbalanced drilling and well-controlsimulators, hole stability control, DIF, and drilling fluids. He holdsa degree in chemistry.

SPEDC

TABLE 4—RHEOLOGICAL PARAMETERS OF

SCLEROGLUCAN/CaCO3 AND XANTHAN

GUM/CaCO3 FORMULATIONS

ID formulation (5.01s-1)

Pa•s(501 s-1)

Pa•s(1,000 s-1)

Pa•s

1 1.71 0.153 0.1122 1.63 0.057 0.038

3 5.32 0.010 0.0624 10.90 — —5 3.56 0.078 0.048

6 69.6 32.6 —7 1.07 0.066 0.0488 1.52 0.076 0.057

9 6.23 0.161 0.11410 5.21 0.013 0.07311 18.80 0.461 0.266

12 10.60 0.203 0.12413 2.43 0.059 0.03714 2.45 0.057 0.037

15 2.24 0.053 0.03216 0.42 0.017 0.01217 18.70 — —

µ µ µ

158 September 2001 SPE Drilling & Completion