The Practical Application of Ion Association Model
Saturation Level Indices to Commercial Water Treatment Problem Solving
R.J. Ferguson,
French Creek
Software, Kimberton, PA 19442 USA
A.J. Freedman,
Arthur Freedman Associates, East Stroudsburg, PA
18301-9045 USA
G. Fowler, Nederlandse Aardolie Maatschappij,
Schoonebeek, Netherlands
A.J. Kulik, LEPO Custom Manufacturing, Midland, TX 79702
USA
J. Robson, Chemco, Vancouver, WA 98682 USA
D.J. Weintritt, Weintritt Consulting Services,
Lafayette, LA 70503-5603 USA
American Chemical Society 1994
ABSTRACT
The availability of fast personal computers has
allowed ion association models to be developed for the
relatively inexpensive and widely available "PC"
platforms.
Ion association models predict the equilibrium
distribution of species for a cooling water, oil field
brine, waste water, or other aqueous solution of
commercial interest. Scale potential indices based upon
the free ion concentrations estimated by ion association
models have been used extensively in the past decade to
predict scale problems in industrial cooling water
systems.
Indices calculated by the models have been found to
be transportable between waters of diverse composition
and ionic strength. They have overcome many of the
problems encountered with simple indices which do not
account for ion pairing. This paper discusses the
application of ion association model saturation level
indices to predicting and resolving scale formation
problems in cooling water systems, oil field brines, and
for optimizing storage conditions for low level nuclear
wastes.
Examples are presented in case history format which
demonstrate the use of the models in field applications.
INTRODUCTION
Simple indices are widely used by water treatment
personnel to predict the formation of scale. In many
cases, simple indices are used as the basis for
adjusting controllable operating conditions such as pH
to prevent scale formation.
Simple indices include the Langelier Saturation
Index,1 Ryznar Stability
Index,2 Stiff-Davis
Saturation Index,3 and
Oddo-Tomson index4 for
calcium carbonate. Indices have also been developed for
other common scales such as calcium sulfate and calcium
phosphate.
The simple indices provide an indicator of scale
potential, but lack accuracy due to their use of total
analytical values for reactants. They ignore the reduced
availability of ions such as calcium which occurs due to
association with sulfate and other ions.5
The simple indices assume that all ions in a water
analysis are free and available as a reactant for scale
forming equilibria.
For example, the simple indices assume that all
calcium is free. Even in low ionic strength waters, a
portion of the analytical value for calcium will be
associated with ions such as sulfate, bicarbonate, and
carbonate (if present). This leads to over-prediction of
the scaling tendency of a water in high ionic strength
waters. The impact of these "common ion" effects can be
negligible in low ionic strength waters. They can lead
to errors an order of magnitude high in high ionic
strength brines. Table 1 outlines some of the ion
associations which might be encountered in natural
waters.
THE CONCEPT OF SATURATION
A majority of the indices used routinely by water
treatment chemists are derived from the basic concept of
saturation. A water is said to be saturated with a
compound (e.g. calcium carbonate) if it will not
precipitate the compound and it will not dissolve any of
the solid phase of the compound when left undisturbed,
under the same conditions, for an infinite period of
time.
A water which will not precipitate or dissolve a
compound is at equilibrium for the particular compound.
By definition, the amount of a chemical compound which
can be dissolved in a water and remain in solution for
this infinite period of time is described by the
solubility product (Ksp). In the case of calcium
carbonate, solubility is defined by the relationship:
(Ca)(CO3)
= Ksp
where
(Ca) is the calcium activity
(CO3) is the carbonate activity
Ksp is the solubility product for calcium carbonate at
the temperature under study.
In a more generalized sense, the term (Ca)(CO3)
can be called the Ion Activity Product (IAP) and the
equilibrium condition described by the relationship:
IAP = Ksp
The degree of saturation of a water is described by
the relationship of the ion activity product (IAP) to
the solubility product (Ksp) for the compound as
follows: If a water is undersaturated with a compound:
- IAP < Ksp (It will tend to dissolve the
compound).
If a water is at equilibrium with a compound:
- IAP = Ksp (It will not tend to dissolve or
precipitate the compound).
If a water is supersaturated with a compound:
- IAP > Ksp (It will tend to precipitate the
compound).
The index called Saturation Level, Degree of
Supersaturation, or Saturation Index, describes the
relative degree of saturation as a ratio of the ion
activity product (IAP) to the solubility product (Ksp):
Saturation Level= IAP/Ksp
In actual practice, the saturation levels calculated
by the various computer programs available differ in the
method they use for estimating the activity coefficients
used in the IAP; they differ in the choice of solubility
products and their variation with temperature; and they
differ in the dissociation constants used to estimate
the concentration of reactants (e.g. CO3
from analytical values for alkalinity, PO4
from analytical orthophosphate).
Table 2 defines the saturation
level for common scale forming species encountered in
industrial applications. These formulas provide the
basis for discussion of these scales in this paper.
ION PAIRING
The Saturation Index discussed can be calculated
based upon total analytical values for the reactants.
Ions in water, however, do not tend to exist totally as
free ions.6,7,8 Calcium, for
example, may be paired with sulfate, bicarbonate,
carbonate, phosphate and other species. Bound ions are
not readily available for scale formation. The computer
program calculates saturation levels based upon the free
concentrations of ions in a water rather than the total
analytical value which includes those which are bound.
Early indices such as the Langelier Saturation Index
(LSI) for calcium carbonate scale, are based upon total
analytical values rather than free species primarily due
to the intense calculation requirements for determining
the distribution of species in a water. Speciation of a
water is time prohibitive without the use of a computer
for the number crunching required. The process is
iterative and involves:
- Checking the water for a electroneutrality via a
cation-anion balance, and balancing with an
appropriate ion (e.g sodium or potassium for cation
deficient waters, sulfate, chloride, or nitrate for
anion deficient waters).
- Estimating ionic strength, calculating and
correcting activity coefficients and dissociation
constants for temperature, correcting alkalinity for
non-carbonate alkalinity.
- Iteratively calculating the distribution of
species in the water from dissociation constants (a
partial listing is outlined in Table 1).
- Checking the water for balance and adjusting ion
concentrations to agree with analytical values.
- Repeating the process until corrections are
insignificant.
- Calculating saturation levels based upon the
free concentrations of ions estimated using the ion
association model (ion pairing).
The use of ion pairing to estimate the free
concentrations of reactants overcomes several of the
major shortcomings of traditional indices. Indices such
as the LSI correct activity coefficients for ionic
strength based upon the total dissolved solids. They do
not account for "common ion" effects.
Common ion effects increase the apparent solubility
of a compound by reducing the concentration of reactants
available. A common example is sulfate reducing the
available calcium in a water and increasing the apparent
solubility of calcium carbonate. The use of indices
which do not account for ion pairing can be misleading
when comparing waters where the TDS is composed of ions
which pair with the reactants versus ions which have
less interaction with them.
Pitzer Coefficient Estimation Of Ion Pairing
Impact
The ion association model provides a rigorous
calculation of the free ion concentrations based upon
the solution of the simultaneous non-linear equations
generated by the relevant equilibria.5,6,7,8
A simplified method for estimating the effect of ion
interaction and ion pairing is sometimes used instead of
the more rigorous and direct solution of the equilibria.9
Pitzer coefficients estimate the impact of ion
association upon free ion concentrations using an
empirical force fit of laboratory data. This method has
the advantage of providing a much less calculation
intensive direct solution. It has the disadvantage of
being based upon typical water compositions and ion
ratios, and of unpredictability when extrapolated beyond
the range of the original data.
The use of Pitzer coefficients is not recommended
when a full ion association model is available.
CASE 1: OPTIMIZING STORAGE CONDITIONS FOR LOW LEVEL
NUCLEAR WASTE
Storage costs for low level nuclear wastes are based
upon volume. Storage is therefore most cost effective
when the aqueous based wastes are concentrated to occupy
the minimum volume. Precipitation is not desirable
because it can turn a low level waste into a much more
costly to store high level waste. Precipitation can also
foul heat transfer equipment used in the concentration
process.
The ion association model approach has been used at
the Oak Ridge National Laboratory to predict the optimum
conditions for long term storage.10
Optimum conditions involve the parameters of maximum
concentration, pH, and temperature. Figure 1
and Figure 2 depict a profile of the
degree of super saturation for silica and magnesium
hydroxide as a function of pH and temperature. It can be
seen that amorphous silica deposition may present a
problem when the pH falls below approximately 10, and
that magnesium hydroxide deposition is predicted when
the pH rises above approximately 11. A pH range of 10 to
11 is recommended based upon this preliminary run for
storage, and concentration.
Other potential precipitants are screened using the
ion association model to provide an overall evaluation
of a waste water prior to concentration.
CASE 2: LIMITING HALITE DEPOSITION IN A WET HIGH
TEMPERATURE GAS WELL
There are several fields in the Netherlands that
produce hydrocarbon gas associated with very high total
dissolved solids connate waters. Classical oilfield
scales problems are minimal in these fields (e.g.
calcium carbonate, barium sulfate, and calcium sulfate).
Halite (NaCl), however, is precipitated to such an
extent that production can be lost in hours. As a
result, a bottom hole fluid sample is retrieved from all
new wells. Unstable components are "fixed" immediately
after sampling and pH is determined under pressure. A
full ionic and physical analysis is carried out in the
group central laboratory.
The analyses are run through an ion association model
computer program with the objective of determining
susceptibility of the brine to halite (and other scale)
precipitation, If a halite precipitation problem is
predicted, the ion association model is run in a
"mixing" mode to determine if mixing the connate water
with boiler feed water will prevent the problem. The
computer program used estimates the chemical and
physical properties of mixtures over the range of ratios
specified, and then calculates the degree of
supersaturation for common, and not so common scale
forming species.
This approach has been used successfully to control
salt deposition in the well with the composition
outlined in
Table 3. Originally, production on this well was on
a test basis. This allowed fluid chemistry and scale
data to be studied. Ion association model evaluation of
the bottom hole chemistry indicated that the water was
slightly supersaturated with sodium chloride under the
bottom hole conditions of pressure and temperature. As
the fluids cooled in the well bore, the production of
copious amounts of halite was predicted.
The ion association model predicted that the connate
water would require a minimum dilution of 15% with
boiler feed water to prevent halite precipitation (figure
3). The computer model also predicted that
over-injection of dilution water would promote barite
(barium sulfate) formation (figure
4). Although the well produces H2S
at a concentration of 50 mg/l, the program did not
predict the formation of iron sulfide due to the
combination of low pH and high temperature (figure
5).
Boiler feed water was injected into the bottom of the
well using the downhole injection valve that was
normally used for corrosion inhibitor injection.
Injection of dilution water at a rate of 25 to 30% has
allowed the well to produce successfully since start-up.
Barite and iron sulfide precipitation has not been
observed, and plugging with salt has not occurred.
CASE 3: IDENTIFYING ACCEPTABLE OPERATING RANGE FOR
OZONATED COOLING SYSTEMS
It has been well established that ozone is an
microbiological control agent in open recirculating
cooling water systems (cooling towers). It has also been
reported that commonly encountered scales were not
observed in ozonated cooling systems under conditions
where scale would be expected. The water chemistry of 13
ozonated cooling systems was evaluated using an ion
association model.11 Each system was
treated solely with ozone on a continuous basis at the
rate of 0.05 to 0.2 mfg/l based upon recirculating water
flow rates.
The saturation levels for common cooling water scales
were calculated, including calcium carbonate, calcium
sulfate, amorphous silica, and magnesium hydroxide.
Magnesium hydroxide saturation levels were included due
to the potential for magnesium silicate formation from
the adsorbtion of silica upon precipitating magnesium
hydroxide.
Each system was evaluated by:
- Estimating the concentration ratio of the
systems by comparing recirculating water
chemistry to makeup water chemistry;
- Calculating the theoretical concentration of
recirculating water chemistry based upon makeup
water analysis and the apparent, calculated
concentration ratio from step 1;
- Comparing the theoretical and observed ion
concentrations to determine precipitation of
major species;
- Calculating the saturation level for major
species based upon both the theoretical and
observed recirculating water chemistry;
- Comparing differences between the
theoretical and actual chemistry to the observed
cleanliness of the cooling systems and heat
exchangers with respect to heat transfer surface
scale buildup, scale formation in valves and on
non-heat transfer surfaces, and precipitate
buildup in the tower fill and basin.
Three categories of systems were encountered:
- Category 1: Those where
the theoretical chemistry of the concentrated water
is not scale forming (is under-saturated) for the
scale forming species evaluated.
- Category 2: Those
systems where the concentrated recirculating water
would have a moderate to high calcium carbonate
scale forming tendency. Water chemistry observed in
these systems is similar to those run successfully
using traditional scale inhibitors such as
phosphonates.
- Category 3: These
systems demonstrated an extraordinarily high scale
potential for at least calcium carbonate and
magnesium hydroxide. These systems operated with a
theoretical recirculating water chemistry more like
that of a softener than of a cooling system. The
Category 3 water chemistry is above the maximum
saturation level for calcium carbonate where
traditional inhibitors such as phosphonates are able
to inhibit scale formation.
Ozonated Systems Study Results
Table 4
outlines the theoretical versus actual water chemistry
for the thirteen (13) systems evaluated. Saturation
levels for the theoretical and actual recirculating
water chemistries are presented in table 5.
A comparison of the predicted chemistries to observed
system cleanliness revealed the following:
- Category 1 - (Recirculating
Water Chemistry under-saturated):
Category 1 systems showed no scale formation.
- Category 2 - (Conventional
Alkaline Cooling System Control Range):
Scale formation was observed in eight (8) of the
nine (9) category 2 systems evaluated.
- Category 3 - (The
Cooling Tower As A Softener):
Deposit formation on heat transfer surface was not
observed in most of these systems.
Rationale For Results
Category 2 systems fall into the general operating
range for alkaline cooling systems. typical calcite
saturation levels for such systems fall into the range
of 10 to 150 ( [Ca][CO3]/Ksp).
In the absence of chemical treatment, scale would be
expected, and was observed, in these systems. In this
saturation level range, only a small quantity of the
total reactive calcium and carbonate in the system is
precipitated.
By comparison, the saturation levels predicted for
the concentrated water (before precipitation) range well
above 1,000. These levels of super-saturation are
typical of softening processes. Under these conditions
calcite tends to precipitate as finely divided seed
crystals in the bulk solution, rather than by growth on
existing active sites. Once such bulk precipitation
begins, calcite formation on metal surfaces is greatly
reduced because of the overwhelming surface area of
suspended calcite crystals. The high flow velocities
through heat exchangers in these systems tends to keep
the crystals in suspension.
This is the rationale proposed for the unexpectedly
low level of scale observed on heat transfer surfaces in
the extremely saturated category 3 systems in comparison
to the category 2 systems, where scale formation on heat
transfer surfaces occurred. It must be noted that
precipitation was observed in low flow areas of the
Category 3 systems.
Conclusions From The Ozonated Systems Study Analysis
of the water chemistry and system cleanliness data from
a number of recirculating cooling systems treated solely
with ozone show that calcium carbonate (calcite) scale
forms most readily on heat transfer surfaces in systems
operating in a calcite saturation level range of 20 to
150 - the typical range for chemically treated cooling
water.
At much higher saturation levels, in excess of 1,000,
calcite precipitated in the bulk water. Because of the
overwhelming high surface area of the precipitating
crystals relative to the metal surface in the system,
continuing precipitation leads to growth on crystals in
the bulk water, rather than on heat transfer surfaces.
The presence of ozone in cooling systems does not
appear to influence calcite precipitation and/or scale
formation.
CASE 4: OPTIMIZING CALCIUM PHOSPHATE SCALE INHIBITOR
DOSAGE IN A HIGH TDS COOLING SYSTEM
A major manufacturer of polymers for calcium
phosphate scale control in cooling systems has developed
laboratory data on the minimum effective scale inhibitor
(copolymer) dosage required to prevent calcium phosphate
deposition over a broad range of calcium and phosphate
concentrations, and a range of pH and temperatures, The
data was developed using static tests, but has been
observed to correlate well with the dosage requirements
for the copolymer in operating cooling systems. The data
was developed using relatively low dissolved solids test
waters. Recommendations from the data were typically
made as a function of calcium concentration, phosphate
concentration, and pH. This data base was used to
project the treatment requirements for a utility cooling
system which used a geothermal brine for make-up water.
An extremely high dosage (30 to 35 mg/l) was recommended
based upon the laboratory data.
It was believed that much lower dosages would be
required in the actual cooling system due to the reduced
availability of calcium anticipated in the high TDS
recirculating water. As a result, it was believed that a
model based upon dosage as a function of the ion
association model saturation level for tricalcium
phosphate would be more appropriate, and accurate, to
use than a simple look-up table of dosage versus pH and
analytical values for calcium and phosphate. The ion
association model was projected to be more accurate due
to its use of free values for calcium and phosphate
concentrations rather than the analytical values used by
the look-up tables. Tricalcium phosphate saturation
levels were calculated for each of the laboratory data
points. Regression analysis was used to develop a model
for dosage as a function of saturation level and
temperature. Predicted versus observed dosages for the
model are depicted in Figure 6.
The model was used to predict the minimum effective
dosage for the system with the make-up and recirculating
water chemistry found in Table 6. A dosage in the range of
10 to 11 mg/l was predicted rather than the 30 ppm
derived from the look-up tables.
A dosage minimization study was conducted to
determine the minimum effective dosage. The system was
treated with the copolymer initially at a dosage of 30
mg/l in the recirculating water. The dosage was
decreased until deposition was observed. Failure was
noted when the recirculating water concentration dropped
below 10 mg/l, validating the ion association based
dosage model.
CASE 5: OPTIMIZING CALCIUM CARBONATE SCALE INHIBITOR
DOSAGE IN AN OIL-WATER SEPARATOR
It has been well established that phosphonate scale
inhibitors function by extending the induction time
prior to crystal formation and growth occurrence.12,13,14,15
The induction time extension achieved has been reported
to be a function of calcite saturation level,
temperature as it affects rate, and phopshonate dosage.
The formula for the models to which data has been
successfully fit is a modification of the classical
induction time relationship which adds dosage as a
parameter:
time=k*[DOSAGE]M
/ [SATURATION -1]N
Dosage models developed from laboratory and field
data have been used successfully to model the minimum
effective scale inhibitor dosage in cooling water
systems. These models were applied to the problem of
calcite scale control in a separator.
Carbon dioxide flashes as oil field brines pass
through a separator, and go from a high partial pressure
of CO2 to atmospheric.
Figure 7
depicts the impact of CO2
flashing upon pH, and calcite saturation levels. Dosage
were predicted from the models for the phosphonate HEDP
(1,1-hydroxyethylidene diphosphonic acid). Figure 8
depicts the dosage requirement increase as CO2
flashes, and pH rises, across the separator. The dosages
predicted by the model for this application are within
30% of those determined through field evaluations.
CONCLUSIONS
Ion association model saturation levels provide an
effective tool for predicting and resolving scale
problems in a wide variety of commercial applications.
The use of personal computer versions of the models make
their use in the field as an engineering tool practical,
and removes the restriction of their use solely as a
research tool in a laboratory environment.
1 Langelier, W.F., The
Analytical Control Of Anti-Corrosion Water Treatment,
JAWWA, Vol. 28, No. 10, p. 1500-1521, 1936.
2 Ryznar, J.W., A New
Index For Determining The Amount Of Calcium Carbonate
Scale Formed By Water, JAWWA, Vol. 36, p. 472, 1944.
3 Stiff, Jr., H.A., Davis,
L.E., A Method For Predicting The Tendency of Oil Field
Water to Deposit Calcium Carbonate, Pet. Trans. AIME
195;213 (1952).
4 Oddo,J.E., Tomson,
M.B.,Scale Control, Prediction and Treatment Or How
Companies Evaluate A Scaling Problem and What They Do
Wrong, CORROSION/92, Paper No. 34, (Houston, TX:NACE
INTERNATIONAL 1992).
5 Ferguson, R.J.,
Computerized Ion Association Model Profiles Complete
Range of Cooling System Parameters, International Water
Conference, 52nd Annual Meeting, Pittsburgh, PA,
IWC-91-47.
6 W. Chow, J.T. Aronson,
W.C. Micheletti, Calculations Of Cooling Water Systems:
Computer Modeling Of Recirculating Cooling Water
Chemistry, International Water Conference, 41rst Annual
Meeting, Pittsburgh, PA, IWC-80-41.
7 Johnson, D.A., Fulks,
K.E.,Computerized Water Modeling In The Design And
Operation of Industrial Cooling Systems, International
Water Conference, 41rst Annual Meeting, Pittsburgh, PA,
IWC-80-42.
8 Truesdell, A.H., Jones,
B.F., WATEQ - A Computer Program For Calculating
Chemical Equilibria Of Natural Waters, J. Research, U.S.
Geological Survey, Volume 2, No. 2, p. 233-248, 1974.
9 Musil, R.R., Nielsen,
H.J., Computer Modeling Of Cooling Water Chemistry,
International Water Conference, 45th Annual Meeting,
Pittsburgh, PA, IWC-84-104.
10 Fowler, V.L., Perona,
J.J., Evaporation Studies On Oak Ridge National
Laboratory Liquid Low Level Waste,ORNL/TM-12243.
11 Ferguson, R.J.,
Freedman, A.J., A Comparison Of Scale Potential Indices
With Treatment Program Results In Ozonated Systems,
CORROSION/93,Paper No. 279,(Houston, TX:NACE
INTERNATIONAL 1993).
12 Gill, J.S., Anderson,
C.D., Varsanik, R.G., Mechanism Of Scale Inhibition By
Phosphonates, International Water Conference, 44th
Annual Meeting, Pittsburgh, PA, IWC-83-4.
13 Amjad, Z., Masler,III,
W.F., The Inhibition Of Calcium Sulfate Dihydrate
Crystal Growth By Polyacrylates And The Influence Of
Molecular Weight, CORROSION/85, Paper No. 357, Houston,
TX: NACE INTERNATIONAL, 1985).
14 Ferguson, R.J.,
Developing Scale Inhibitor Models, WATERTECH, Houston,
TX, 1992.
15 Ferguson, R.J., Codina,
O., Rule, W., Baebel, R., Real Time Control Of Scale
Inhibitor Feed Rate, International Water Conference,
49th Annual Meeting, Pittsburgh, PA, IWC-88-57.
16 Ferguson, R.J.,
Weintritt, D.J., Modeling Scale Inhibitor Dosages For
Oil Field Operations, CORROSION/94, Paper No. 46,
(Houston, TX:NACE INTERNATIONAL, 1994).
Table 1: Example
Ion Pairs Used To Estimate Free Ion Concentrations
| CALCIUM |
|
|
[Calcium] = |
[Ca+II] + [CaSO4] + [CaHCO3+I] + [CaCO3] +
[Ca(OH)+I] |
| |
+ [CaHPO4] + [CaPO4-I] + [CaH2PO4+I] |
| MAGNESIUM |
|
|
[Magnesium] = |
[Mg+II] + [MgSO4] + [MgHCO3+I] + [MgCO3] +
[Mg(OH)+I] |
| |
+ [MgHPO4] + [MgPO4-I]+[MgH2PO4+I]+[MgF+I]
|
| BARIUM |
|
|
[Barium] = |
[Ba+II] + [BaSO4] + [BaHCO3+I] + [BaCO3] + [Ba(OH)+I]
|
| STRONTIUM |
|
|
[Strontium] = |
[Sr+II] + [SrSO4] + [SrHCO3+I] + [SrCO3] + [Sr(OH)+I]
|
| SODIUM |
|
|
[Sodium] = |
[Sr+II] + [SrSO4] + [SrHCO3+I] + [SrCO3] + [Sr(OH)+I] |
| POTASSIUM |
|
|
[Potassium] = |
[K+I]+[KSO4-I] + [KHPO4-I] + [KCl] |
| IRON |
|
|
[Iron] = |
[Fe+II] + [Fe+III] + [Fe(OH)+I] +
[Fe(OH)+II] + [Fe(OH)3-I] |
| |
+ [FeHPO4+I] + [FeHPO4] + [FeCl+II] +
[FeCl2+I] + [FeCl3] |
| |
+ [FeSO4] + [FeSO4+I] + [FeH2PO4+I] +
[Fe(OH)2+I] + [Fe(OH)3] |
| |
+ [Fe(OH)4-I] + [Fe(OH)2] + [FeH2PO4+II]
|
| ALUMINUM |
|
|
[Aluminum] = |
[Al+III] + [Al(OH)+II] + [Al(OH)2+I] +
[Al(OH)4-I] + [AlF+II] + [AlF2+I] |
| |
|
TABLE 2 SATURATION LEVEL
DEFINITION
- Saturation level is the ratio of the
Ion Activity
Product to the Solubility Product for
the scale
forming specie.
For calcium carbonate:
SL = (Ca)(CO3)/Ksp'
For barium sulfate:
SL = (Ba)(SO4)/Ksp'
For calcium sulfate:
SL = (Ca)(SO4)/Ksp'
Saturation Levels should be calculated
based upon free ion activities using the
solubility product for the form typical of
the conditions studied (e.g. calcite for low
temperature calcium carbonate, aragonite at
higher temperatures.)
Saturation levels can be interpreted as
follows:
- A water will tend to dissolve scale
of
the compound if the saturation level is
less than 1.0
- A water is at equilibrium when the
Saturation Level
is 1.0 . It will not tend to form or
dissolve scale.
- A water will tend to form scale as
the Saturation
Level increases above 1.0 .
Table 3: Hot Gas Well Water Analysis
|
TABLE 3: HOT GAS WELL WATER ANALYSIS
|
| Analytical Values Expressed as the Ion |
Units |
Bottom Hole Connate |
Boiler Feed Water |
| Temperature |
oC |
121 |
70 |
| Pressure |
bars |
350 |
1 |
| pH (site) |
|
4.26 |
9.10 |
| Density |
kg/m3 |
1.300 |
1.000 |
| TDS |
mg/L |
369,960 |
<20 |
| Dissolved CO2 |
mg/L |
223 |
< 1 |
| H2S (gas phase) |
mg/Nm3 |
50 |
0 |
| H2S (aqueous phase) |
mg/L |
<0.5 |
0 |
| Bicarbonate |
mg/L |
16 |
5.0 |
| Chloride |
mg/L |
228,485 |
0 |
| Sulfate |
mg/L |
320 |
0 |
| Phosphate |
mg/L |
< 1 |
0 |
| Borate |
mg/L |
175 |
0 |
| Organic Acids <C6 |
mg/L |
12 |
< 5 |
| Sodium |
mg/L |
104,780 |
< 1 |
| Potassium |
mg/L |
1,600 |
< 1 |
| Calcium |
mg/L |
30,853 |
< 1 |
| Magnesium |
mg/L |
2,910 |
< 1 |
| Barium |
mg/L |
120 |
< 1 |
| Strontium |
|
1,164 |
< 1 |
| Total Iron |
|
38.0 |
< 0.01 |
| Lead |
|
5.1 |
< 0.01 |
| Zinc |
|
3.6 |
|
Table 4: Theoretical Versus Actual Recirculating
Chemistry Values
|
Table 4: Theoretical Versus Actual
Recirculating Water Chemistry
|
| System
(Category) |
Theoretical
Recirculating Calcium |
Actual
Recirculating Calcium |
Difference in ppm |
Theoretical
Recirculating Magnesium |
Actual
Recirculating Magnesium |
Difference in ppm |
Theoretical
Recirculating Silica |
Actual
Recirculating Silica |
Difference in ppm |
System Cleanliness |
| 1
(1) |
56 |
43 |
13 |
28 |
36 |
-8 |
40 |
52 |
-12 |
No
scale observed |
| 2
(2) |
80 |
60 |
20 |
88 |
38 |
50 |
24 |
20 |
4 |
Basin buildup |
| 3
(2) |
238 |
288 |
-50 |
483 |
168 |
315 |
38 |
31 |
7 |
Heavy scale |
| 4
(2) |
288 |
180 |
108 |
216 |
223 |
-7 |
66 |
48 |
18 |
Valve scale |
| 5
(3) |
392 |
245 |
147 |
238 |
320 |
-82 |
112 |
101 |
11 |
Condenser tube scale |
| 6
(3) |
803 |
163 |
640 |
495 |
607 |
-112 |
162 |
143 |
19 |
No
scale observed |
| 7
(3) |
1,464 |
200 |
1,264 |
549 |
135 |
414 |
112 |
101 |
11 |
No
scale observed |
| 8
(3) |
800 |
168 |
632 |
480 |
78 |
402 |
280 |
78 |
202 |
No
scale observed |
| 9
(3) |
775 |
95 |
680 |
496 |
78 |
418 |
186 |
60 |
126 |
No
scale observed |
| 10
(3) |
3,904 |
270 |
3,634 |
3,172 |
508 |
2,664 |
3,050 |
95 |
2,995 |
Slight valve scale |
| 11
(3) |
4,170 |
188 |
3,982 |
308 |
303 |
5 |
126 |
126 |
0 |
No
scale observed |
| 12
(3) |
3,660 |
800 |
2,860 |
2,623 |
2,972 |
-349 |
6,100 |
138 |
5,962 |
No
scale observed |
| 13
(3) |
7,930 |
68 |
7,862 |
610 |
20 |
590 |
1,952 |
85 |
1,867 |
No
scale observed |
Table 5: Theoretical Versus Actual Recirculating
Water Saturation Level
|
Table 5: Theoretical Versus Actual
Recirculating Water Saturation Level
|
| System
(Category) |
Theoretical
Calcite Saturation |
Actual Calcite
Saturation |
Theoretical
Brucite Saturation |
Actual Brucite
Saturation |
Theoretical
Silica Saturation |
Actual Silica
Saturation |
| 1
(1) |
0.03 |
0.02 |
<0.001 |
<0.001 |
0.20 |
0.25 |
No
scale observed |
| 2
(2) |
49 |
5.4 |
0.82 |
0.02 |
0.06 |
0.09 |
Basin buildup |
| 3
(2) |
89 |
611 |
2.4 |
0.12 |
0.10 |
0.12 |
Heavy scale |
| 4
(2) |
106 |
50 |
1.3 |
0.55 |
0.13 |
0.16 |
Valve scale |
| 5
(3) |
240 |
72 |
3.0 |
0.46 |
0.21 |
0.35 |
Condenser tube scale |
| 6
(3) |
540 |
51 |
5.3 |
0.73 |
0.35 |
0.49 |
No
scale observed |
| 7
(3) |
598 |
28 |
10 |
0.17 |
0.40 |
0.52 |
No
scale observed |
| 8
(3) |
794 |
26 |
53 |
0.06 |
0.10 |
0.33 |
No
scale observed |
| 9
(3) |
809 |
6.5 |
10 |
<0.01 |
0.22 |
0.27 |
No
scale observed |
| 10
(3) |
1,198 |
62 |
7.4 |
0.36 |
0.31 |
0.35 |
Slight valve scale |
| 11
(3) |
1,670 |
74 |
4.6 |
0.36 |
0.22 |
0.44 |
No
scale observed |
| 12
(3) |
3,420 |
37 |
254 |
0.59 |
1.31 |
0.55 |
No
scale observed |
| 13
(3) |
7,634 |
65 |
7.6 |
0.14 |
1.74 |
0.10 |
No
scale observed |
Table 6: Calcium Phosphate Inhibitor Dosage
Optimization Example
| Water Analysis at 6.2 Cycles |
|
Deposition Potential Indicators |
|
| CATIONS |
|
SATURATION LEVEL |
|
| Calcium (as CaCO3) |
1,339 |
Calcite |
38.8 |
| Magnesium (as CaCO3) |
496 |
Aragonite |
32.9 |
| Sodium (as Na) |
1,240 |
Silica |
0.4 |
| ANIONS |
|
Tricalcium phosphate |
1,074 |
| Chloride (as Cl) |
620 |
Anhydrite |
1.3 |
| Sulfate (as SO4) |
3,384 |
Gypsum |
1.7 |
| Bicarbonate (as HCO3) |
294 |
Fluorite |
0.0 |
| Carbonate (as CO3) |
36 |
Brucite |
< 0.1 |
| Silica (as SiO2) |
62 |
SIMPLE INDICES |
|
| PARAMETERS |
|
Langelier |
1.99 |
| pH |
8.40 |
Ryznar |
4.41 |
| Temperature (oC) |
36.7 |
Practical |
4.20 |
| 1/2 Life (hours) |
72 |
Larson-Skold |
0.39 |
| TREATMENT RECOMMENDATION |
|
|
|
| 100% Active Copolymer (mg/L) |
10.53 |
|
|
