Comprehensive Approach to Select Fracturing Fluids and Additives for Fracture Treatments

8/12/2019 Comprehensive Approach to Select Fracturing Fluids and Additives for Fracture Treatments

1/9

rI Societyof PetroleumEngineersSPE 36603A Comprehensive Approach to Select Fracturing Fluids and Additives for FractureTreatmentsHongjie Xiongl Brian Davidson, Bryan Saunders, and Steve A. Holditch, S. A. Holditch & Associates

Copyright 1996 Soaety of Petroleum Engineers IncTh s paper was prepared for presentahca at the 1996 SPE Annual Technta Conference andExhlb$tDnheld m Denver Colwado U S A 6-9 Oclotmr 1996Thm paper was Selectm for presentat ion by an SPE Program Comm tlue Idlowmg rewaw ofn fo fmatum conl amed In an abs lraci sub fmtted by the Wthor (s} Contents C4 the pape l aspresented have not been rev iewed by the Soaefy ofPetroleum Engineers and are sub@ tocor rec tnn by the author (s) The ma te ri al as presen fed does no t fwcessanly ref lect anyposmon of the SocIa fy of Petro leum Engineers I ts offuws of mambers Papers presanted alSPE meetmgs are -@ect to pubhcalmn revunv by Eddortal Cwnmtttees of the Sme y ofPetro leum Ertgmeers PermIss Ion 10CWY ISrestr c wdto an abstract of not more than 300words Illustrations may not ta c@led The abslracl should contain cnnsplcuousacknowledgmen t of where and byworn the paper was presen led VWe L ibrar ian SPE P OBM 83383$ RKhardson TX 75083 -3836 U S A fax01-214-952 -9435

AbstractThe paper describes a new approach used to select fracturefluid systems by applying fuzzy logic for fracture treatments.Based on the given formation information, the system firstdetermines base fluid, viscosifying method, and energizationmethod, Secondly, the system chooses the 3 to 5 bestcombinations of the possible fluids. Then. the systemdetermines polymer type and loading, crosslinker, gas type ifnecessary, and other additives for the fluid systems. At thesame time, the system also checks the compatibility of thefluid and additives with formation fluids and composition.

The fuzzy logic system described in this paper, which isconsisted of several fuzzy logic evaluators, can be applied tostudy, evaluate. and determine the best fluid systems tostimulate oil and gas production or water injectivity in wells.

The approach can be extended to the solution of manyother similar problems associated with drilling, completing.and working over wells.

IntroductionHydraulic fracturing is one of major methods to increasereservoir production, The success or failure of a fracturetreatment heavily depends on the fracturing fluids andadditives used in the treatment. Choosing the correct fluid andadditives is extremely important to ensure that the formation isnot damaged, proppan: is placed in formation as designed, andthe fluid breaks and cleans up properly.

Fracturing fluids are used to create fractures and totransport proppant down the tubular goods, through the

perforations, and deep into the fracture. To pump a successfulfracture treatment, an ideal fracturing fluid should have thefollowing characteristics,

The fluid should be compatible with the formation andthe reservoir fluids.The fluid should be able to maintain sufficient viscosity atreservoir temperature, so it can suspend proppant andtransport i t deep into the fracture.The fluid should be capable of developing the necessaryfracture width to accept proppants or to allow deep acidpenetration.The fluid should have low fluid loss properties or highfluid efficiency.The fluid should be easy to remove from the formationand have minimal damaging effects on both the proppantand the formation.The fluid should be easily pumped down the wellbore andexhibit minimal friction pressure losses in both the pipeand the fracture.The fluid should be easy to prepare and safe to use.The fluid should be low cost.

Currently available fracturing fluids seldom satisfy all ofthe above requirements. Of these. however. the mostimportant requirements that we have to consider whenselecting a fracturing fluid are ( I ) the ability to maintainsufficient viscosity at reservoir temperature and (2)compatibil ity with the formation and reservoir fluids.

Fracture fluids can be divided into four groups: ( I ) water-based fluids, (2) oil-based fluids, (3) foam-based fluids. and(4) alcohol-based fluids. Table i describes these fluid types,and the conditions under which they are most often used.

The selection of optimal fracturing fluids for a formation isbased on consideration of the following factors: formationpressure, water sensitivity of the formation, formationtemperature, permeability, and the fracture half-length to becreated. Laboratory testing and field experience provideimportant information that must be considered when choosinga fracture fluid.

These decisions are crucial to the success or failure of thestimulation treatment, and require comprehensive data sets,knowledge, and experience. Few engineers possess all the

293


2/9

2 H. XIONG, B. DAVIDSON, B. SAUNDERS, AND S. A. HOLDITCH SPE 36603

skills ancilor all the data required to make the decisions withconsistency.

Though we can use flow-charts and rule-based systems torepresent rules and experience to select proper fluids fordifferent situations. (For example, SPE monograph No.12 listssome of rules used to select fluids), the value combinations ofmany parameters for different situations, which are used toselect fluid systems. almost prohibit us to compile those rulesand experience into rule-based systems or flow-charts. Therule-based systems or flow-charts may also be hard to rankpotential candidates. Lack of sufllcient data is always a

describe reservoir characteristics. Some of the rules thatexperts use to make decisions are also fuzzy - not clearlydefined. Designing the optimal stimulation treatments withconsistency is important, yet very difficult to accomplish,

This paper presents the issues and the logic that anengineer must apply to make correct decisions during fracturefluid selection. This paper concludes that fuzzy logic theory~can be used to build evaluators to help an engineer to not onlyselect proper fracture fluids, but also rank all possible fluidcandidates. The methodology is clearly explained and expertknowledge is recorded for ail parties to use in their job.

problem, and many fuzzy linguistic terms are often used to

Table I - Fracturing Fluids and Conditions for Their UseFluid Base Main Composition

I Linear fluids I Gelled water, HPG, HEC,

IOil-based Crosslinked I Crosslinker + Oil

fluidsWater external Emulsifier + Oil + WaterpolyemulsionAcid-based Acid + Foamer + N2foam

Foam- Water-based Water + Foamer + C02 orbased foam N?

Alcohoi- Methanol + Foamer + N2based foamAlcohol- Linear system Gelled water + Alcohol

based Crosslinked Crosslinked system +

Generally Used forShort fractures, low temperatures

Long fractures, high temperatures

Water sensitive formations, short fractures

Water sensitive formations, long fractures

Good for fluid-loss control

Low pressures, water sensitive formations

Low pressure formations

Low pressure formations with waterblocking problemsRemoval of waterblocks

system Alcohol

familiar with;

MethodologyFuzzy logic has been applied in the petroleum industry tosolve numerous problems, including those associated withwell stimulation. Several fuzzy logic systems have beendeveloped4 for selecting the best treatment candidate,evaluating tubular condit ions, selecting the optimal treatmenttype, evaluating potential barriers, diagnosing formationdamage mechanisms, and selecting optimal treatment fluidsand additives.

Those fuzzy logic systems are very useful for followingsituations: When an engineer designs a stimulation treatment in a

frontier area or in a formation where the engineer is not

When an engineer does not have much knowledge andexperience in well stimulation treatment; or

When reservoir condit ions have changed duringdevelopment or a history pattern has been broken, whichmeans that the previous rules or experience for thereservoir may not be re-used.

A procedure has been developed to build a fuzzy logicsystem for typical well stimulation problems.~ As shown inFigure 1, the procedure consists of seven steps. For moredetails about the methodology, please see the reference No.4.

The objective of our fuzzy logic system is to select optimalfluid systems for any formation situation. The output of thefuzzy system is the components of fluids.

Then we identify all important parameters (fuzzy

294


3/9

SPE 36603 A COMPREHENSIVE APPROACH TO SELECT FRACTURING FLUIDS AND ADDITIVES FOR FRACTURE TREATMENTS 3

variables) that affect the fluid selection, and build membershipfunctions and weighting factors the variables. Using themembership functions and weighting factors (they arematrices), we compute the evaluation values, which are usedto rank options. Following sections detail the process.

Determine Objectives of the FuzzyEvaluatorf

Identify and Structure the Output/ Decisionfrom the Evaluator

7Identifi All Prameters (Fuzzy Variables)

That Affect the Output

vBuild Membership Functions For All FuzzyVariables (Jsing Domain Knowledge and

Expertise7Determine the Weighting Factorsv

Determine the evaluation procedurev

Adjust the Fuzzy Membership Functionsand Weighting Factors If Required BasedUpon Comparison Computer Output WithFiled Results

STEP I

STEP 2

STEP 3

STEP 4

STEP 5

STEP 6

STEP 7

Principle of Fluid Selection Fuzzy SystemThe process of selecting fracture fluids is divided into two

sections: the fluid type determination and fluid specification(see Figure 2).

Fluid type contains the base fluid (water, oil, or alcohol),the viscosifying method - the consideration of viscosity(crosslinked. linear, or polyemulsion), and the energizationmethod - the consideration of fluid clean-up (foamed,energized, or normal fluid without any energizer). Forexample, crosslinked water gel, energized polyemulsion.and foamed oil.

After the fluid type is determined, we specify the polymertype (HPG, CMHPG, Guar, or HEC.), polymer loading,crosslinker (if necessary), and the gas type and quality (ifnecessary).

Based on the formation condition, we apply the followingProcedure:i,2.

3.4,

Determine the possibility for every option in theviscosifying method, base fluid, and energizer;Form all combinations (see Table 2 for all possiblecombinations) and a combination consists of aviscosifying method, a base fluid, and an energizationmethod;Rank all combinations and take three to five highest-ranking combinations as the recommendations; thenSpecify crosslinker, polymer type and concentration, gastype and quality (if necessary), and other additives for therecommended combinations.

Figure 1- The Methodology to Built A Fuzzy Evaluator

Table 2 - The Possible Combinations of Base fluid, Viscosifying Method, and Energization Method.~ Viscosifying Base Fluid Energizat ion

Oil Alcohol Foamed Energized NormalCrosslinked x x x x x

Viscosifying Linear x x x x x xPolyemulsirm x x x xWater x x x x x x

Base Fluid Oil x x x x xAlcohol x x x x xFoamed x x X1X x1nergization Energized I x I xNm-rnal x x ; IIT TII I

295


4/9

*t Temperature2 Fracturelength3 Fracturehcighr4 Trea tment we

11 Crosslmkcd2 Linear3 Polmlsnm

Need

crosslinker qYes1Arossl nkert

I Temperature2 TreatmentMm1 COW4 Clean

TI Bomm2 Tmnium) Ztrwn um

Legend

stall3+Z.IIWaterrwtiwy2 Oepth I Pwswe3 Fracture Ienglh 2 Tempcmtum4 Temperature 3 Fracture length5 FOMMI , (XI f lu ,d 4 Depth6 Crx

1

IFoamedI waler 2 Energtzcd2 0,1 J None3 Alcohol

& J3=.1I Permeabll ty -2 cost3 Temperature

1

m 1 5 P ESTER,I Temperawe 1 Ewe Fl,d1 Fracture length

:;,,fl,;;,h J&-12 Ocplh

3 Pressure., 7

I Temperaturef T 2 Treatmcm s,?e70 3 PolymertypeNZ15 C02IW, ?30to to

lbm/10COualfor

J.2_.l anners OptionFigure 2- The Procedure to Select Fluids and Additives

For each step in Figure 2, we build a fuzzy evaluator torank the possible options.

In a fuzzy evaluator, we first identify the most importantparameters (fuzzy variables) that affect the primary decisions.

Then, we build membership functions (All theknowledgeh-ules and memberships are presented in theAppendix) and weighting factors.

Weighting factors (in the following Tables 3 to 9)represent the importance of all fuzzy variables in a fuzzy logicevaluator. The weighting factor of a fuzzy variable indicatesits contribution to the decisions of system. The weight factorsare extracted from human expertise (or experience) and can beadjusted for different situations in a fuzzy system.Finally, using the membership functions (F) and weightingfactors (W), we compute the evaluation values (Fb), which areused to rank options.

,=]For example, to rank the viscosification methods for a

specific formation situation, we have to consider formationtemperature, fracture length, and fracture height. We use themembership functions and the weighting factors listed inTable 3 to compute the evaluation values. Then we rank thepossible options of the viscosification method (Crosslinked,Linear, and Polyemuision) based on the evaluation values.

Viscosification Method We consider three options used toviscosify the fracture fluids: Crosslinked, Linear, andPolyemulsion. When determining the viscosifying method, weconsider formation temperature, fracture length, and fractureheight (see Table 3) (note: in this paper, fracture length andfracture height referring to the propped fracture length andpropped fracture height for proppant fracturing, or etchedfracture length and etched fracture height for acid fracturing.).

Crosslinked fluids are usually used in the highertemperature formations and/or in large size treatments. Linearfluids are used in low temperature and medium or small sizetreatments. Polyemulsions are used when moderate viscosityis needed without the requirement for high temperaturestability.

Table 3 - Parameters for Crosslinked, Polyemulsion, andLinear Fluids.Parameter ] Symbol I Unit I Weighting IFactorTemperature T F 0.4Fracture Height H ft 0.2

II Fracture Len~th I Lf I fl I 0.2 IYoungs Modulus I E [ psi I 0.1Fluid Complexity I Cx I 0.1 IIBase Fluids There are two kinds of base fluid: water and oil.Water based fluids are used more frequently than oil-basedfluids. Oil based fluids are advantageous in certain situationsto avoid formation damage to water-sensitive oil-producingformations. To choose water or oil as the base fluid, weconsider formation-water sensitivity, formation temperature,formation depth, fracture length, and cost (Table 4). Alcohol(methanol/water) as a base fluid is usually used in very watersensitive gas formations. No oil-based fluid is allowed for gasformations.

Energization Method The options considered here are: (1)foamed fluids, (2) energized fluids, (3) fluids without gas.Usually, we use foamed fluids in very low pressureformations. Energized fluids are used in low to mediumpressure formations. For normal or high pressure formations,liquid fracture fluids without gas are normally pumped.Formation pressure, temperature, depth, and fracture length

296


5/9


are taken into account when we choose the energizationmethod (Table 5).

Table 4- Parameters for Water, Oil, and Alcohol FluidsParameter Symbol Unit Weighting

Factor .Water Sensitivity Ws - 0.35Fracture Length Lf R 0.10Formation T F 0.15TemperatureCost and Safety c - 0.20Formation Depth D ft 0.10Formation FluidType *Fluid Complexity Cx [- I 0.1*. no oil base fluids for gas forrllations.

Table 5- Parameters for Foam/Energized/Normal Fluids.Parameter I Symbol I Unit I Weighting

FactorPressure Gradient pg psilfi 0.4Formation T F 0.15TemperatureFracture Length Lf ft 0.20Formation Depth D ft 0.15Fluid Complexity Cx - 0. I

Polymer Concentration Polymer concentration varies withformation temperature, treatment size, and polymer type (seeTable 7). The polymer concentration decides the viscosity ofa fluid system, and the requirement on viscosity depends onthe formation temperature and the proposed treatment size.

Table 7- Parameters for Polymer Loading.Parameter I Symbol I Unit

rreatment Size I s I ftA2 I 0.5Formation IT I F 0.5Temperature IPoivmer TvrIe 1- 1

Foam Quality or Gas Quantity For foams, we usually use70 to is%. quality depending on the pressure and treatmentsize. For energized fluids, the gas quantity is about I So/O

Gas Type For foamed or energized fluids, the energizedagents are usually Nitrogen (N2, and Carbon Dioxide (C02).C02 is not compatible with oil-based fluids. N2 is typicallynot used in deep or hot formations. If the base fluid is water,we have to consider all parameters listed in Table 8 whenchoosing N2 or C02.

Table 8- Parameters for Gas Type (Nz and COZ).Polymer Type There are several polymers available for water Parameter Symbol Unit Weightingbase fluids in the industry, such as, Guar, HPG, CMHPG, FactorHEC, and Xanthan. Guar and HPG are two types of polymer Formation Tused in water-based fluids. HEC is chosen when the fluid F 0.35Temperatureinvasion and cleanup are more important, We also have to Formation Depth Dconsider the cost, residue, and fracture length when selecting a ft 0.35Fracture Length Lfpolymer (see Table 6). For oil base fluids, phosphate ester is ft 0.25oflen used. Cost Index c 0.05

Table 6 - Parameters for Polymer Type Selection.

FactorFormation T F 0,45TemperatureCost Index c - 0.35Permeability k md 02(JBase Fluid

Crosslinker There are three commonly used crosslinkers:Borate, Titanium, and Zirconium. The selection of acrosslinker depends on the formation temperature, cost, and[reatment size (see Table 9).

297


6/9


Table 9- Parameters for Crosslinkers. Example 2 This is a typical low-permeability, lowParameter Symbol Unit Weighting

FactorFormation T F 0.45

Application ExamplesHere we present two examples to illustrate how this fuzzy

logic system is used to choose fracture fluids. Table 10 liststhe data for the three examples.

Table 10 - Data for ExamplesExample No. 1 2Pressure (psi) 6,200 1,080Temperature (F) 345 I 20

Example I This case is a deep and thick gas formation withvery high temperature and normal pressure, The fonrnation isnot water sensitive. Because of formation depth and hightemperature, the best choice is 60 Ibm crosslinked CMHPGwater gel (see Table I l).

Table I I - Recommendations for Example 1Fluid I Fluid I Rank 1Viscosifying Method crosslinkedEnergizing Method normalBase Fluid waterPolymer Type CMHPG/HPGPolymer Loading 60 lb/1000 galGas Type NAGas Quantity NACrosslinker Zirconium/BoratePossibility Value 1

temperature, and very low pressure gas formation, which isnot water-sensitive. There are three possible fluidsrecommended in this situation (Table 12). Because of a longrequired-fracture length, crosslinked fluids are recommended.

Table 12 - Recommendations for Example 2Fluid Fluid 1 Fluid 2 Fluid 3Rank 1 2 3Viscosifying crossl inked poly - cross linkedMethod emulsionEnergizing foamed energized energizedMethodBase Fluid water water water

(external)Polymer Type HPG/ HPG/ HPG/

CMHPG CMHPG CMHPGPolymer 20 Ib/ 30 lb/ 30 IblLoading 1OOOgal 1000gal I OOOgalGas Type NJCOz NJCOJ NJCOlGas Quantity 75 15 15Cross linker Borate/ NA Borate/

Zirconium ZirconiumPossibility 0.538 0.478 0.434Value

Conclusions1. The fuzzy logic system described in this paper can beapplied to study, evaluate, and determine the best fluidsystems to stimulate oil and gas production or waterinjectivity in wells.

2. The technique presented in this paper can be extended tothe solution of many other similar problems associatedwith drilling, completing, and working over wells,

3. Fuzzy logic is an excellent tool to represent domainexpertise and knowledge in computer codes, which makesmore it easier to apply and transfer domain knowledgeand expertise. We have found that quantifying theproblem is much easier using fuzzy logic rules, ratherthan production (IF-THEN) rules.

4. Developing a fuzzy logic system involves substantialknowledge acquisition activities. Domain expertsavailable is crucial to develop a fuzzy logic system.Identifying fuzzy variables and fuzzy sets, anddetermining the base of membership functions andweighting factors are very important. Building andtuning membership functions could be time consuming.

298


7/9


References1. Gidley, J. L., Holditch, S. A., Nierode, D. E., and Veatch

Jr., R. W.: Recent Advances in Hydraulic Fracturing SPEMonograph Volume [2, SPE, Richardson, TX, 1989

2. Zimmerman, H. J.: FUZ.T Set Theo~ and ItsApplications Kluwer Academic Publishers, Boston,(1991).

3. Kosko, B.: Neural Networks and FUZ T Systems Prentice-Hall, (1992).

4. Xiong, H. and Holditch, S, A.: An Investigation Into theApplication of Fuzzy Logic to Well StimulationTreatment Design, SPE Computer Applications (Feb.1995) 18.

AppendixThere are two types of membership functions as shown asfollows (see also Figure 3):

Type I - Membership value increases as the parameter:0 x


8/9


Rules for the FUZV Eva[uator Base Fluids Rules for the FUZV Evaluator Gas Type

Table 14- The Rules Used to Select Base Fluids Table 16- The Rules Used to Select Gas Type I Parameter Func. IDo Not IUse 1

II Type Use IWater Sensitivity II I=1.() 15000 1250 800 Ioo(l 0,48 and 1500 2000 20000 0.4 360 750 I 0000 275 8000 600 2@3 300 5(3 450 lo 50


9/9


Rules for the Fuqv Ewduator Crossiinker Type

Table 18-

Borate

Titanium

Zirconium

The Rules Used to Select Crosslinker Type

k F %(lo ftA2) IClean Break I

Cost Index

301

Comprehensive Approach to Select Fracturing Fluids and Additives for Fracture Treatments

Documents

Transcript of Comprehensive Approach to Select Fracturing Fluids and Additives for Fracture Treatments