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DOWNHOLE FLUID ANALYSIS AND ASPHALTENE NANOSCIENCE

FOR RESERVOIR EVALUATION MEASUREMENT

Oliver C. Mullins1, Julian Y. Zuo

1, Chengli Dong

2, A. Ballard Andrew

1,

Hani Elshahawi2, Thomas Pfeiffer1, Myrt E. Cribbs3, Andrew, E. Pomerantz1

1. Schlumberger, 2. Shell Exploration and Production Inc., 3. Chevron North America

Society of Petrophysicists and Well Log Analysts

Copyright 2012, held jointly by the Society of Petrophysicists and Well Log

Analysts (SPWLA) and the submitting authors

This paper was prepared for presentation at the SPWLA 53rd Annual Logging

Symposium held in Cartagena, Colombia, June 16-20, 2012.

ABSTRACT

In recent years, several major advances have taken

place in asphaltene science and have been codified in

the Yen-Mullins Model. Specifically, these advances

embody the characterization of the nanocolloidal

structure of asphaltenes in crude oil. They also are

applicable to surface science at the molecular level and

provide a foundation for understanding wettability. This

nanoscience also establishes the foundation for the

gravity term enabling the development of the

industrys first predictive equation of state of

asphaltene gradients in the Flory-Huggins-Zuo (FHZ)equation of state. The FHZ equation coupled with

downhole fluid analysis (DFA) data has been used to

address major reservoir concerns including reservoir

connectivity, heavy oil columns, tar mats, and reservoir

fluid disequilibrium in many case studies. This paper

provides an overview of the developments in asphaltene

science, surface science and the development of the

FHZ EoS. We review the many classes of case studies

linking the FHZ EoS with DFA, with emphasis on the

corresponding significant improvement of capability in

each focus of study. The coupling of new science and

new technology is shown to yield tremendousimprovements in reservoir characterization.

INTRODUCTION

An ancient truism taught in elementary school is

matter is composed of solids, liquids and gases. True

to form, reservoir crude oils contain dissolved gases,

hydrocarbon liquids and solids, the asphaltenes.

Petroleum gases and liquids have been relatively

straightforward to analyze by standard analytical

chemistry techniques, and there has been no

fundamental disagreement about their chemical nature.

In stark contrast, asphaltenes have been the subject of

enormous debate; even molecular weight was disputedby afactorof one million![1] The cost of this scientific

deficiency on all aspects of the oil industry has been

severe. For example, in reservoir engineering, reservoir

fluids are often modeled using cubic equations of state.

However, cubic equations of states were developed,

initially by Van der Waals in 1873, to treat gas-liquid

equilibria. As such, the use of a cubic EoS to treat

petroleum solids has been grossly inadequate. However,

asphaltenes cannot be ignored. One of the most

economically important hydrocarbon fluid properties,

viscosity, depends exponentially on asphaltene content.

It is the asphaltene content, after all, that gives asphalt

its desired rheology for paving materials.

In recent years, asphaltene science has advanced

tremendously.[2] In particular, for crude oils and

laboratory solvents, a simple picture of the asphaltene

molecular and colloidal nanoscience has emerged [3,4]

and is now [5] called the Yen-Mullins model (cf. Fig.

1). (Prof. Teh Fu Yen was the founder of modern

asphaltene science.)

Fig. 1 The Yen-Mullins model; asphaltenes are

dispersed as molecules (left) in condensates, as

nanoaggreates (center) in black oils and as clusters

(right) in heavy oils.[3,4]

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Figure 1 shows the predominant molecular and

colloidal species of asphaltenes in crude oil. Asphaltene

molecules are somewhat small with predominantly a

single polycyclic aromatic hydrocarbon ring (PAH) per

molecule.[3-5] The center PAH is the site of relativelystrong intermolecular attraction, while peripheral

alkanes yield steric (spatial) repulsion. This molecular

architecture dictates that the asphaltene nanoaggregate

cannot consist of more than a few molecules as

depicted in Fig. 1, and as shown by numerous

experiments.[2] Asphaltene clusters can form from

nanoaggregates again with very small aggregation

numbers (less than 10).[3,4] The Yen-Mullins model

has recently been validated in a publication with 16

coauthors from 12 different institutions.[6]

All three species of asphaltenes depicted in Fig. 1 are

routinely encountered in reservoir crude oils. True

molecular solutions of asphaltene molecules are found

in condensates, while asphaltene nanoaggregates are

found at higher concentrations, such as in black oils.

Asphaltene clusters are found at even higher asphaltene

concentrations present in heavy oils or in unstable black

oils.[7,8]

Asphaltene gradients can now be modeled by inclusion

of the gravity term in the Flory-Huggins model; this

new equation is now [6]known as the Flory-Huggins-

Zuo Equation of state or FHZ EoS.[9,10] The FHZ EoS

requires accurate measurement of GOR, relative

asphaltene content and fluid density which can all be

measure by DFA.[11] For low GOR fluids such as

virtually all heavy oils, the FHZ EoS reduces

predominantly to the gravity term which is given

below.[12]

1

where ODhi is the optical density from oil color

measured at height hi in the oil column, Chi is the

corresponding asphaltene concentration, V is the

asphaltene particle size, is the density difference

between asphaltene and the bulk liquid, g is earths

gravitational acceleration, k is Botzmanns constant and

T is temperature. The optical densities are measured

using downhole fluid analysis (DFA).[13] The only

unknown in this equation is V the asphaltene particle

size; this is given in Fig.1.

This same Eq. 1 is used to describe the reduction of the

earths atmospheric pressure (or density) with height.

The small size of air molecules yields a small gradient

of a factor of two reduction in pressure (or density) in

~5 km of height.

In this paper, we describe how asphaltene gradients in

reservoirs can now be readily understood within a

proper physical chemistry perspective; also tar mat

formation can be treated within this formalism. Surface

science and wettability can also now be studied with

this asphaltene science foundation. In an auspicious

development, advances in reservoir evaluation and in

asphaltene nanoscience are augmenting each other in

spite of the 13 orders of magnitude difference in size

between colloidal asphaltenes and oilfield reservoirs.

We also provide an outline of the power of this new

formalism to address many diverse reservoir concerns.

Work flows are presented to exploit this formalism

especially with DFA to evaluate reservoirs in various

settings. Areas of future focus are clarified.

RESULTS AND DISCUSSION

Interfacial Science: Much of the interfacial science

approach to crude oils and asphaltenes has been

phenomenological such as measurement of contact

angle or wettability. However, with the development of

the nanoscience model of asphaltenes shown in Fig. 1, a

1stprinciples approach is now all but mandated.

Fig. 2 Schematic representation of the results of the

first direct measurements of asphaltene molecular

orientation in Langmuir films on water. Left: model

compounds with their PAH transverse to the interfacial

plane and (blue) oxygen atoms at the interface. Right:

asphaltenes with their PAH in the interfacial plane and

their alkane substituents perpendicular to the

plane.[14]

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Figure 2 shows results from the first direct

measurements of the molecular orientation of

asphaltenes at an asphaltene-water interface.[14] The

optical technique sum frequency generation (SFG) was

used; an IR and visible laser overlap at the interface,undergoing nonlinear mixing and creating a UV beam.

The IR laser is tuned through vibrational resonances.

Molecular orientation is determined by controlling

polarizations of the optical beams.[14]

Both asphaltenes and model compounds were

measured. Toluene solutions containing asphaltenes or

individual model compounds were placed on a water

surface, and the toluene was evaporated creating

Langmuir films. Concentrations were adjusted to yield

monolayer coverage. The film was transferred onto a

silica slide for orientation measurements (Langmuir-

Blodgett film). Figure 2 shows a schematic of the

results.[14] The asphaltenes are very highly aligned

with their single PAH in the plane of the interface (Fig.

2, Right). Model compounds of known chemical

structure showed a polarization with the PAH

transverse to the interfacial plane (Fig. 2, Left) due to

peripheral oxygen containing groups which seek the

interface. These pendant oxygen containing groups are

uncommon in asphaltenes. The asphaltene results from

this molecular orientation study are in strong agreement

with the asphaltene molecular architecture proposed in

Fig. 1.[14]

Fig. 3. Atomic Force Microscopy image of a Langmuir-

Blodgett film of asphaltene nanoaggregates. As

expected the film thickness is ~2nm and is consistent

with the Yen-Mullins model of Fig. 1.[15]

A Langmuir film was prepared from a toluene solution

containing asphaltene nanoaggregates; a Langmuir-

Blodgett film was then prepared to determine the layer

thickness. Figure 3 shows the corresponding image

from Atomic force Microscopy (AFM).[15] The filmthickness determined by AFM in Fig. 3 is ~2 nm as

expected for the asphaltene nanoagggregate.[14]

At higher concentrations, the asphaltene Langmuir

films are formed from asphaltene clusters. There is a

huge difference in interfacial morphology between

films formed from asphaltene nanoaggregates versus

those formed by clusters.[15]

Fig. 4.Brewster Angle Microscopy images of Langmuir

films of asphaltenes. Left: prepared from asphaltene

clusters (spreading concentration = 4 g/l). Right:

prepared from nanoaggregates (spreading

concentration = 100 mg/l).[16]

Langmuir films of nanoaggregates versus clusters are

quite distinct as shown in Fig. 4.[16]Langmuir films of

asphaltene nanoaggregates on water show good

coverage and appear to be compliant while Langmuir

films of asphaltene clusters on water do not show good

coverage and appear rigid.[16] The strong contrast in

these films corresponding to nanoaggregates versus

clusters reinforces the validity of the Yen-Mullins

model.[3,4]

To be sure, asphaltene interfacial science is not a

resolved issue. Nevertheless, the value is evident of

interpreting interfacial results through the 1stprinciples

model in Fig. 1. Wettability and enhanced oil recovery

studies can now incorporate these new advances

thereby improving efficiency and predictability.

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Asphaltene Gradients:One of the primary benefits of

the Yen-Mullins model of asphaltene nanoscience is to

enable development of the first and currently only

asphlatene equation of state, the FHZ EoS, predicting

asphaltene gradients in all reservoir fluids fromcondensates to mobile heavy oil.[6,7] The accurate

predictions of concentration gradients of heavy resins

as measured by DFA in a light condensate that has no

asphaltenes confirms the validity of our approach.[7] It

has now become commonplace to observe asphaltene

gradients associated with nanoaggregates in black oil.

Still, the first study of this type, the Tahiti field study,

remains the best to date because both 1) the data sets

are extensive and 2) the Tahiti crude oil is a low GOR

black oil so the gravity term dominates.[12] Without

knowing the size of the asphaltenes as given in Fig. 1, it

would have been impossible to quantify the gravity

term.

Fig. 5. The Chevron Tahiti crude oils. The red and

blue stacked sands are each laterally connected

across the reservoir.[12]The asphaltenes in each of

these sands (and in the smaller green sand) are

equilibrated within the sand and match Eq. 1 with a

particle size of ~2 nm, the nanoaggregate.

The Tahiti study proves that the laboratory asphaltene

science that gave rise to the Yen-Mullins model can

also be applied to reservoir crude oils. Because the

GOR is low (~500 scf/bbl), the solubility term of theFHZ EoS is small, and the asphaltene gradient becomes

dominated by the gravity term, Eq. 1. The observed

equilibration of the asphaltenes in the red and blue

sands of Fig. 5 is critical for evaluation of reservoir

connectivity. The only way for asphaltenes to be

equilibrated is for the reservoir to have good

connectivity.[17]

The concept of equilibration of reservoir fluids

mandates that the spatial distribution of the fluids,

including their composition, does not change with time.

Equilibration also mandates that small changes of

condition (e.g. T, P) yield only small changes of theequilibrium. (This condition differentiates equilibrium

from metastability). There are many factors that can

preclude reservoir fluid equilibration. First, reservoir

fluids cannot possibly charge into reservoirs in any

equilibrated sense; the composition of the charge can

change with time, and the charge cannot initially reflect

ultimate equilibrium gradients.(ref. 13 and references

therein). In addition, reservoirs can be subject to many

dynamic processes at various points in geologic

(including recent) times. For example, a second, totally

different charge such as biogenic gas can occur. Often,

this is accompanied by some asphaltene phase change

and/or asphaltene migration. Biodegradation and water

washing can alter oil composition and grading. Leaky

seals can alter reservoir composition, shifting equilibria.

Inorganic gases such as H2S and CO2 can charge into

the reservoir at times and pathways very different than

the hydrocarbon charge.

In addition, baffles can hinder equilibration and barriers

essentially preclude equilibration. Molecular diffusion

which is required to equilibrate reservoir fluids is

geologically slow at reservoir length scales.[17]

Asphaltenes, especially in colloidal species, have by far

the smallest diffusion constant of any oil component.

The enormous time required to equilibrate asphaltenes

in a reservoir is incompatible with significantly

restricted connectivity.[17] Very slow reservoir fluid

equilibration is in dramatic contrast to pressure

equilibration which is far more rapid due to the tiny

mass flow required. In many cases, the constraint of

fluid equilibration is ten million times better (more

stringent) than pressure communication to establish

reservoir connectivity.[17] Indeed, in the Tahiti

reservoir, production proved the accuracy of fluidequilibrium to predict connectivity. Equilibration of

asphaltenes does not prove reservoir connectivity.

Nevertheless, if asphaltene equilibration, pressure

analysis and geochemistry all point to connectivity,

then probably connectivity prevails. Also, note that

connectivity does not mandate fluid equilibration.

Nevertheless, continuous fluid gradients, even if not

equilibrated, indicate connectivity. Generally more

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DFA data is needed in such cases to test dynamic fluid

models.

When the GOR is higher, then there is a gradient of

GOR, thus a gradient of the solubility term. Then, thesolubility term also becomes important in establishing

the asphaltene gradient. A recent study highlights this

fact with the corresponding data shown in Fig. 6.[18]

With a GOR in the range of 1100 scf/bbl, the

asphaltene gradient is larger than that of Tahiti;

nevertheless, the gravity term with the asphaltene

nanoaggregate (2nm) contributes to the gradient.

In the case study shown in Fig. 6, the pressure survey

indicated compartmentalization. However, the

asphaltene gradient matches the FHZ EoS with ~2nm

particle size, thus indicating connectivity. Production

proved connectivity. Classic pressure surveys do have

great value in all settings as has long been known.

Nevertheless, integrating pressures with DFA surveys

along with the FHZ EoS has proven to be greater value.

Fig. 6.A deepwater reserovir. Left: Laboratory GOR is

useful but not for establishing potential fluid gradients

here. Center: Pressure surveys indicated that the sands

in the red well and the blue wells are not connected.

Right: Asphaltene gradient in the two wells matches the

FHZ EoS with an asphaltene particle size of 2 nm.

Equilibration of asphaltenes indicates connectivity and

was proven in production.[18]

For low GOR oils, the gravity term dominates as has

been noted. For nanoaggregates, the gravity term of Eq.

1 produces an increase in asphaltene concentration of a

factor of 2 in ~1000 meters as shown in Fig. 5 for the

Tahiti reservoir. For heavy oils, with asphaltenes in

clusters, the gradient is ~ 50 times larger. The first field

demonstration of this was in Ecuador (cf. Fig. 7).[19]

The much larger size of the asphaltene cluster (5 nm)

compared to the nanoaggregates (2 nm) produces thisfactor of 50 increase. The much larger size of the

cluster prevents thermal energy from lifting the more

massive clusters as high in the reservoir as the

nanoaggregates. Again, Eq. 1 is virtually the same as

that used to model the pressure (or density) reduction of

earths atmosphere with height. Gravity tries to pull

all air molecules down to the surface, while thermal

energy (kT) provides energy to lift the small air

molecules higher.

Fig. 7Asphaltene content versus height. The asphaltene

content is very high as in all heavy oils and there is a

very large asphaltene gradient in this sand a factor of

two increase in ~55 feet. The fit of Eq. 1 to the field

data gives a particle size of 5.0 nm exactly matching

expectations for clusters in Fig. 1.[19]

This figure shows that there is a large asphaltene

content (>10%) in this heavy oil. The GOR for this oil

is quite low, less than 100 scf/bbl. In addition, Fig. 3

shows that there is a huge asphaltene concentration

gradient, with a two-fold increase in asphaltene content

over ~55 feet. Because viscosity depends exponentiallyon asphaltene content, the viscosity increase in this

column goes from 6cP at the top to 200cP at the base at

reservoir conditions. This column is high viscosity, but

below 1000 cP so might be termed mobile heavy oil

and can often be produced conventionally.[19]

Figure 8 shows a very similar gradient in a mobile

heavy oil column.[20]Recently, very similar gradients

have been found in similar crude oils in Russia [21]and

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Saudi Arabia.[22]These mobile heavy oil columns are

nearly identical in asphaltene gradients with

concomitant huge gradients in viscosity. Having similar

gradients in such diverse geographic locations does

indicate that the gradients are established by an intrinsicoil property (Fig. 1), not by some idiosyncrasy of a

particular crude oil. In all these cases, the GOR is low,

so Eq. 1 applies with use of the cluster for the

asphaltene particle size. These heavy oil gradients are

fundamentally different than the nanoaggregate

gradients shown in Figures 5 & 6. Thus, the validity of

the Yen-Mullins model is reinforced numerous times.

Fig. 8 Mobile heavy oil, deepwater Gulf of Mexico

(from ref. [20], Fig. 5.) The gradient in this column is

almost identical to that in Fig. 7. Consequently fitting

with Eq. 1 gives a similar asphaltene cluster size.

Nanoaggregates or Clusters? A question arises as to

when a crude oil is expected to have nanoaggregates

and when it should have clusters. An oil column in

Canada helps establish that complexities can be

observed. A particular Canadian oil column was

observed to have both nanoaggregates and clusters.[23]

DFA OD at 1070 nm

Nanoaggregate

Cluster

N

Molecule

&

x00

x50

x00

x500.0 0.5 1.0 1.5 2.0 2.5 3.0

Fig. 9. A black oil that had been subjected to a late gas

and condensate charge. Modest asphaltene instability

resulted yielding some cluster formation in this black

oil.[23]

Geochemical analysis showed that the oil column in

Fig. 9 had been subjected to some gas and condensate

charging. This addition of light alkane resulted in some

modest asphaltene instability leading to cluster

formation from nanoaggregates.[23] The clusters

naturally accumulated much more towards the base of

the oil column. The point is that the asphaltene

concentration alone is not sufficient to determine

whether nanoaggregates, clusters or some mixture

prevails. The liquid phase properties of the crude oil are

an equally important factor.

For example, laboratory measurements demonstrating

the transition from nanoaggregate to cluster dispersion

of asphaltenes in toluene (we call this the critical cluster

concentration) is approximately 2 to 5 grams of

asphaltenes per liter of toluene. Figure 10 clearly shows

this transition as determined by flocculationkinetics.[24]

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Fig. 10 The aggregation number N as a function of

the scaled time *. Flocculation data for the addition of

n-heptane to different asphaltene/toluene solutions.Orange circles represent data for a 10 g/L

asphaltene/toluene solution that exhibits reaction-

limited aggregation (RLA). Blue squares represent data

for a 1 g/L asphaltene/toluene solution that exhibits

diffusion-limited aggregation (DLA). Red circles

represent data for a 5 g/Lasphaltene/toluene solution

that exhibits crossover aggregation kinetics.[24]

Figure 10 shows data acquired for different

asphaltene/toluene solutions. Upon n-heptane addition

to these solutions, asphaltenes were destabilized and

flocculated and the flocculation kinetics were

determined. Diffusion limited aggregation (DLA)

applies for floc formation from nanoaggregate

solutions; the nanoaggregates stick to each other upon

contact. Reaction limited aggregation (RLA) applies for

flocs formed from clusters. The fractal clusters need

morphological change at the interface in order to stick;

this mimics RLA.[25] Figure 10 finds the transition

from nanoaggregate to cluster at 5 g/liter in toluene.

Other studies obtain similar or slightly smaller critical

cluster concentrations.[26] The sizeof clusters has been

determined by various methods in addition to the field

studies shown in Figs. 7 & 8. DC-conductivity obtains

aggregation numbers less than 10.[26] Integrated smallangle x-ray scattering and small angle neutron

scattering studies also yield nanoaggregates and clusters

with similar aggregation numbers as in Fig. 1.[27,28]

The conclusion is that the nanoaggregate-cluster

transition occurs at ~0.5 mass% asphaltene in toluene

whereas in black crude oils such as in the Tahiti

reservoir, nanoaggregates prevail even at several

mass% asphaltene. It is no surprise that the solution

chemistry is very important in solubility. In addition, it

is plausible that the heaviest resins might play in

stabilizing the asphaltenes in crude oil.[29,30]

Asphaltene-resin interaction has been postulated for

over half a century. Some association was foundbetween asphaltenes and heavy resins in live black oil

centrifugation studies.[29]. Asphaltene stability is

impacted by the presence of resins.[30] Moreover, there

is no question that bulk solvency properties of the

solution impact asphaltene solubility. Thus, there

should be some dependence on the SARA fractions in

addition to asphaltene concentration for the critical

clustering concentration. This is in concert with the

significant difference of the concentration of CCC

between toluene versus crude oils.

At this juncture, a rough guideline is that the critical

cluster concentration in crude oils is roughly 10% mass

fraction but could vary substantially (eg 50% relative)

dependent on 1) the saturate, aromatic and resin

fractions 2) GOR and 3) whether the reservoir crude oil

had undergone mixing with light alkanes. The could

also be a temperature dependence. The clear

recommendation is to make DFA measurements to

determine the asphaltene and GOR profiles vertically

and laterally in the reservoir in order to determine the

asphaltene colloidal dispersion. These gradients

establish the relevant fluid models, which in turn are

used to understand production concerns.

Tar Mats. The treatment of asphaltenes in this paper is

within standard physical chemistry precepts. In addition

to finding similarities of crude oil columns around the

world, this formalism also treats tar mats and

corresponding oil columns within a single formalism.

Two distinct types of tar mats have been found. One

occurs at the base of a mobile heavy oil column and

represents a continuous extension of large asphaltene

gradients in the oil column, details will be discussed

elsewhere.[22] Essentially, if one were to extenddownward the asphaltene gradient present in Fig. 7, the

asphaltene content would increase to very high values

and the corresponding hydrocarbon would be immobile.

Again, this has been observed.[22]

The second type of tar mat occurs at the base of a

relatively light oil column. This tar mat represents a

discontinuous increase of asphaltene content in going

from oil to tar.

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Fig. 11. Core sections in the oil zone (up

zone (lower) under both visible

illumination.[31] The core shows a fairly li

with brown color in the visible and brig

fluorescence. The tar zone is black

illumination.

Figure 11 shows what happens when sig

charges into a reservoir containing blac

generally the case, the gas charges along t

reservoir, then diffuses down into the oil

the solution gas increases, asphaltene is

migrates lower in the oil column. If metha

continues over sufficient time, then the so

elevated even at the base of the oil colum

to the observation in Fig. 11, the asphal

longer migrate downwards at the base of th

it undergoes phase separation forming a

This process is tractable from a 1stp rincipl

relying on the Yen-Mullins model and

Huggins-Zuo EoS. Many oil columns

examined in this manner with successful a

oil gradients in both equilibrium and dicolumns.[32]

CONCLUSIONS

After a lengthy period of inexorabl

asphaltene science has undergone a re

recent years. This new science is being lin

new technology Downhole Fluid Analysi

long standing formerly unsolved reservoir c

, June 16-20, 2012

8

er) and tar

and UV

ht crude oil

ht yellowish

under all

nificant gas

oil. As is

e top of the

column. As

xpelled and

ne diffusion

ution gas is

. This leads

tene can no

column, so

tar mat.[31]

es approach

the Flory-

have been

counting of

sequilibrium

e advance,

aissance in

ed with the

s to address

omplexities.

It is now evident that treating only the g

of reservoir fluids while ignoring th

achieve broad scale understandin

asphaltenes are properly treated speci

Flory-Huggins-Zuo EoS explicitly inYen-Mullins model of asphaltenes, a

reservoir concerns are being address

exciting ways. This theoretical f

specified asphaltene nanoscience fa

purview of standard physical chemistry

extremely powerful. From that persp

surprising that many enigmatic reserv

are rapidly becoming resolved in

constructs. Understanding reservoi

translates to reducing risk and cost in

Indeed, the recommendation follows tha

should be utilized for virtually any

complexity that is encountered. Unexp

these endeavors is becoming the norm.

REFERENCES SECTION

[1] O.C. Mullins, B. Martinez-Haya,

Contrasting perspective on asphalt

weight; this Comment vs. the Overview

K.D. Bartle, R. Kandiyoti, Energy &

1773, (2008)

[2] O.C. Mullins, E.Y. Sheu, A. H

Marshall, (Editors), Asphaltenes, H

Petroleomics, Springer, New York, (20

[3] O.C. Mullins, The Asphaltenes, An

Analytical Chemistry, 4, 393418, (201

[4] O.C. Mullins, The Modified Yen

Fuels, 24, 21792207, (2010)

[5] H. Sabbah, A.L. Morrow, A.E. P

Zare, Evidence for Island Structures aArchitecture of Asphaltenes, Energy

1604, (2011)

[6] O.C. Mullins, H. Sabbah, J. E

Pomerantz, L. Barr, A.B. Andrews, Y

F. Mostowfi, R. McFarlane, L. Goual, R

Cooper, J. Orbulescu, R.M. Leblanc, J.

Zare, Advances in Asphaltene Scienc

Mullins Model, accepted, Energy & Fue

ases and liquids

solids cannot

. Now that

ically with the

orporating thewide array of

d in new and

rmalism with

lls within the

, which itself is

ctive, it is not

ir complexities

fairly simple

complexities

oil production.

t this formalism

reservoir fluid

cted success in

A.G. Marshall,

ene molecular

of A.A. Herod,

uels, 22, 1765-

ammami, A.G.

avy Oils and

7)

nual Review of

1)

odel, Energy &

omerantz, R.N.

s the DominantFuels, 1597-

yssautier, A.E.

. Ruiz-Morales,

. Lepkowicz, T.

Edwards, R.N.

and the Yen-

ls

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[7] J.Y. Zuo, H. Elshahawi, C. Dong, A.S. Latifzai, D.,

Zhang, O.C. Mullins, DFA Assessment of Connectivity

for Active Gas Charging Reservoirs Using DFA

Asphaltene Gradients, SPE #145438, ATCE, (2011)

[8] H. Elshahawi, R. Shyamalan, J.Y. Zuo, C. Dong,

O.C. Mullins, D. Zhang, Y. Ruiz-Morales, Advanced

Reservoir Evaluation Using Downhole Fluid Analysis

and Asphaltene Flory-Huggins-Zuo Equation of State,

Cartagena, Colombia, SPWLA, (2012)

[9] D. Freed, O.C. Mullins, J. Zuo, Asphaltene

gradients in the presence of GOR gradients, Energy &

Fuels, 24 (7), pp. 3942-3949, (2010)

[10] J.Y. Zuo, D. Freed, O.C. Mullins, D. Zhang, A.

Gisolf, Interpretation of DFA Color Gradients in Oil

Columns Using the Flory-Huggins Solubility Model,

SPE 130305, Int. Oil & Gas Conf. Beijing, China, June

(2010)

[11] O.C. Mullins, D.E. Freed, J.Y. Zuo, H Elshahawi,

M.E. Cribbs, V.K. Mishra, A. Gisolf, Downhole Fluid

Analysis coupled with Asphalene Nanoscience for

Reservoir Evaluation, Presented in Perth, Australia,

SPWLA, (2010)

[12] S.S. Betancourt, F.X. Dubost, O.C. Mullins, M.E.

Cribbs, J.L. Creek, S.G. Mathews, Predicting

Downhole Fluid Analysis Logs to Investigate Reservoir

Connectivity, SPE IPTC 11488, Dubai, UAE, (2007)

[13] O.C. Mullins, The Physics of Reservoir Fluids;

Discovery through Downhole Fluid Analysis,

Schlumberger Press, (2008). The Spanish language

version of this book will be released at the SPWLA

meeting in Cartagena.

[14] A.B. Andrews, A. McClelland, O. Korkeila, A.Krummel, O.C. Mullins, A. Demidov, Z. Chen, Sum

frequency generation studies of Langmuir films of

complex surfactants and asphaltenes, Langmuir, 27,

6049-6058, (2011)

[15] J. Orbulescu, O.C. Mullins, R.M. Leblanc, Surface

chemistry and spectroscopy of UG8 asphaltene,

Langmuir film, Part 1, Langmuir, 26(19), 15257

15264, (2010)

[16] M.D. Lobato, J.M. Pedrosa, D. Mobius, S. Lago,

Optical characterization of asphaltenes at the air-water

interface. Langmuir 25, 137784, (2009)

[17] T. Pfeiffer, Z. Reza, D.S. Schechter, W.D.

McCain, O.C. Mullins, Fluid Composition Equilibrium;

a Proxy for Reservoir Connectivity, SPE Offshore

Europe Oil and Gas Conference and Exhibition held in

Aberdeen, UK, (2011)

[18] C. Dong, D. Petro, A. Latifzai, J.Y. Zuo, D.

Pomerantz, O.C. Mullins, Ron S. Hayden, Reservoir

Characterization of from Analysis of Reservoir Fluid

Property and Asphaltene Equation of State, Cartagena,

Colombia, SPWLA, (2012)

[19] W. Pastor, G. Garcia, J.Y. Zuo, R. Hulme, X.

Goddyn, O.C. Mullins, Measurement and EoS

Modeling of Large Compositional Gradients in Heavy

Oils, Cartagena, Colombia, SPWLA, (2012)

[20] N. R. Nagarajan, Reservoir Fluid Sampling of a

Wide Spectrum of Fluid Types Under Different

Conditions: Issues, Challenges, and Solutions, IPTC,

14360, Bangkok, Thailand, 1517 November (2011)

[21] A. Tsiklakov, P. Weinheber, W. Wichers, S.

Zimin, A. Driller, R. Oshmarin, The Characterization of

Heavy Oil Reservoirs Using Downhole Fluid Analysis

to Determine Fluid Type and Reservoir Connectivity,

SPE 150697, Heavy Oil Conference & Exhibition,

Kuwait, (2011)

[22] D.J. Seifert, M. Zeybek, C. Dong, J.Y. Zuo, O.C.

Mullins, Black Oil, Heavy Oil and Tar In One Oil

Column Understood By Simple Asphaltene

Nanoscience, submitted ADIPEC 2012

[23] V. Mishra, N. Hammou, C. Skinner, D.MacDonald, E. Lehne, J. Wu, J.Y. Zuo, C. Dong, O.C.

Mullins, Downhole Fluid Analysis & Asphaltene

Nanoscience coupled with VIT for Risk Reduction in

Black Oil Production, SPE ATCE, accepted (2012)

[24] I.K. Yudin, M.A. Anisimov, Dynamic light

scattering monitoring of asphaltene aggregation in

crude oils and hydrocarbon solutions. See Ref. 2, pp.

43966, (2007)

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Dr. Chengli DSpecialist with Shell International

he was Senior Reservoir Dom

Schlumberger. He has been a ke

development of downhole fluid an

extensive spectroscopic studies o

gases, and he led the developm

algorithms on the downhole flui

addition, Dr. Dong has extensive

and interpretation of formation te

their applications on reservoir cha

published more than 50 technica

invented 15 granted US pa

applications and one trade secret a

degree in chemistry from Beijing

in petroleum engineering from th

at Austin.

Dr. A. Balla

principal scientist at Schlumberg

spent nearly a decade workin

Synchrotron Light Source at Broo

where he completed his PhD i

Physics with the University of

pursued post-doctoral research wi

Alamos National Lab. Dr. Andre

50 articles in peer reviewed ph

energy journals. He has a total of

filed, and has presented at over 35

conferences. He co-authored a cha

of Physics and Chemistry of the

worked for many years on co

visualization, and his work ap

American and Nature. Dr. Andr

laboratory and downhole o

measurements. His latest interest

optical techniques for downh

composition analysis.

SPWLA 53rd

Annual Logging Symp

11

ng is a Senior FluidE&P, and previously

ain Champion with

y contributor on the

alysis. He conducted

live crude oils and

ent of interpretation

d analysis tools. In

experience on design

sting logs as well as

racterization. He has

papers, and he co-

ents, eight patent

ward. He holds a BS

University, and PhD

University of Texas

rd Andrews is a

er-Doll research. He

g at the National

haven National Lab

Condensed Matter

exas at Austin and

h Bell Labs and Los

s has published over

sics, chemistry and

16 patents granted or

external international

pter in the Handbook

are Earths. He also

putational scientific

peared in Scientific

ws is an expert on

ptical fluorescence

focus on improved

le fluid and gas

Hani

Deepwater Technology Advi

FEAST, Shells Fluid Eva

Technologies centre of excelle

15 years in Schlumberger i

Africa, Asia, and North Amer

held various positions in in

operations, marketing,

development. He holds se

authored close to a hundred te

areas of petroleum egeosciences. He was the 200

SPWLA and was distinguished

the SPWLA 2010-2011 an

SPWLA Distinguished Techni

ThomasReservoir Domain Champi

Wireline in Stavanger. As

Thomas provides technical

formation testing services an

data in reservoir engineerin

authored 7 publications on do

coinvented one US patent appl

his B.S. in electrical engineeri

in electrical engineering in 2

University of Munich,

Schlumberger as a wireline fi

2002. Assigned locations incluand eastern Europe and the G

2009 Schlumberger sponsored

A&M. He received his Masters

2010.

sium, June 16-20, 2012

Elshahawi is Shell

sor. Previously, he led

luation and Sampling

nce and before that spent

over 10 countries in

ica during which he has

terpretation, consulting,

and technology

eral patents and has

hnical papers in various

gineering and the9-2010 president of the

lecturer for the SPE and

is recipient of 2012

al Achievement Award.

Pfeiffer is a Senioron for Schlumberger

subject matter expert

support to wireline

integrates the acquired

g workflows. He co-

nhole fluid analysis and

ication. Thomas received

ng in 1996 and his M.S.

01 from the Technical

ermany. He joined

eld engineer in January

de the North Sea, centrallf of Mexico. In August

his education at Texas

of Science in December

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SPWLA 53rd


12

M. E. (Bo) Cribbshas 31 years

of Reservoir and Production Engineering experience

working for Chevron. His expertise is in general

Reservoir Engineering with emphasis in deep water

evaluations, well logging, well testing and fluid

sampling. Bos assignments have spanned the Middle

East, the Gulf of Mexico, Offshore West Africa, Offshore

Canada and Offshore Brazil. His current assignment is to

Chevrons Deepwater Gulf of Mexico Appraisal Team

working on Deep Water Exploration and Appraisal data

evaluation programs. Bo is a member of SPE, AAPG and

SPWLA and serves as an SPE Technical Editor.

Dr. Andrew E. Pomerantzis

the Geochemistry Program Manager at Schlumberger-

Doll Research. His research focuses on thedevelopment of novel techniques to characterize the

chemical composition of kerogen and asphaltenes,

including methods in mass spectrometry and X-ray

spectroscopy. That molecular information is used to

understand fundamental physical and chemical

processes in petroleum such as asphaltene

compositional grading. He graduated from Stanford

University with a PhD in chemistry in 2005 and has co-

authored 30 peer-reviewed publications.

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