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The Impact of Surfactant Imbibition and Adsorption for Improving Oil
Recovery in the Wolfcamp and Eagle Ford Reservoirs
J. O. Alvarez, I. W. R. Saputra, and D. S. Schechter, Texas A&M University
Copyright 2017, Society of Petroleum Engineers
This paper was prepared for presentation at the SPE Annual Technical Conference and Exhibition held in San Antonio, Texas, USA, 9-11 October 2017.
This paper was selected for presentation by an SPE program committee following review of information contained in an abstract submitted by the author(s). Contents
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consent of the Society of Petroleum Engineers is prohibited. Permission to reproduce in print is restricted to an abstract of not more than 300 words; illustrations may
not be copied. The abstract must contain conspicuous acknowledgment of SPE copyright.
Improving oil recovery from unconventional liquid reservoirs (ULR) is a major challenge and knowledge
of recovery mechanisms and interaction of completion fluid additives with the rock is fundamental in
tackling the problem. Fracture treatment performance and consequent oil recovery can be improved by
adding surfactants to stimulation fluids to promote imbibition by wettability alteration and interfacial tension
(IFT) moderate reduction. Also, the extent of surfactant adsorption on the ULR surface during imbibition
of completion fluids is an important factor to take into account when designing frac jobs. The experimental
work and modeling presented in this paper focuses on analyzing alteration of wetting behavior of Wolfcamp
and Eagle Ford reservoir rock with the introduction of surfactants additives. We focus on effectiveness
of surfactant additives for improving oil recovery as well as the extent of surfactant loss by adsorption
during imbibition of surfactant-laden completion fluid. Altering the wettability with the use of surfactant
additives is accompanied by alteration of the IFT as well as surfactant adsorption. We carefully evaluate
these interactive variables as key constituents of imbibition capillary pressure to improve oil recovery. We
assume this is a free imbibition process with no confining pressure on the rock sample. During imbibition
spontaneous imbibition, as the sign of the capillary pressure changes from negative (oil wet) to positive
(water wet). Original rock wettability is determined by contact angle (CA) at reservoir temperature. Then,
different types of surfactants, anionic, anionic-nonionic, and cationic, at concentrations utilized in the field,
are evaluated to gauge their effectiveness in altering wettability and IFT. Wettability is also studied by zeta
potential to address water film stability on the shale rock surface as an indication of wetting fluid affinity
and to determine the surfactant electrostatic charges. Moreover, surfactant adsorption measurements are
performed using an ultraviolet–visible spectroscopy. Calibration curves for surfactants are determined by
relating their concentration to light absorbance and used to calculate the amount of surfactant adsorption into
the shale rock. Next, potential for improving oil recovery via surfactant additives in ultralow permeability
Wolfcamp and Eagle Ford shale core is investigated by spontaneous imbibition experiments at reservoir
temperatures. In order to visualize the movement of fluid as it penetrates into liquid rich shale samples, we
use computed tomography (CT) methods to determine fluid imbibition in real time. In addition, oil recovery
is recorded with time to compare the performance of surfactants and water alone. Finally, laboratory data are
used in numerical simulation to model laboratory results and upscale these findings to the field. The results
showed that aqueous solutions with surfactants altered rock wettability from oil-wet and intermediate-wet to
water-wet and reduced IFT to moderately low values. In addition, cationic surfactant presented the highest
adsorption capacity following a Langmuir type adsorption profile. Spontaneous imbibition results showed
that aqueous solutions with surfactants had higher imbibition and were better at recovering oil from shale
core compared to water without surfactants, which agrees qualitatively with wettability and IFT alteration.
However, rock lithology and surfactant type play an important role in adsorption capacity and oil recovery.
Our upscaling result shows that compared to a well that is not treated with surfactant, a 24% increase on
the initial peak oil rate as well as a 8% increase on the 3-year cumulative oil production are observed. For
the results obtained, we can conclude that the addition of surfactants to completion fluids can improve oil
recovery by wettability alteration and IFT reduction, maximizing well performance after stimulation from
Wolfcamp and Eagle Ford unconventional reservoirs.
Unconventional liquid reservoirs (ULR) have become an important source of energy in the United States.
The increasing hydrocarbon exploitation of liquid rich shale reservoirs has positioned the country as one
of the biggest oil producers on the planet (Doman 2015). The two most current productive regions in the
United States are the Permian Basin and the Eagle Ford with more than 300 rigs on Permian and 75 rigs
on Eagle Ford (EIA 2017). The use of multiple hydraulic fracture treatments in horizontal wells in these
ULR has boosted their production. Hence, the Permian Basin oil production has increased from less than
900 thousand barrels per day in 2008 to currently more than 2.5 million barrels per day whereas the Eagle
Ford has increased its production from 100 thousand barrels per day in 2008 to more than 1.2 million
barrels per day nowadays (EIA 2017). However, ULR petrophysical characteristics of low porosity, ultralow
permeability, heterogeneity and high total organic content (TOC) create a challenge for oil exploitation.
Thus, current recovery factors for ULR do not exceed more than 10% of the original oil in place (OOIP)
with average values of 5 to 6% (Alharthy et al. 2015; Wang et al. 2016).
Multistage hydraulic fracturing allows ULR to produce at commercial flow rates by creating effective
paths for hydrocarbons to flow towards the wellbore. The effectiveness of fracture treatment in increasing
recovery and consequently current low oil recovery factors may be improved if proper surfactants are
added to completion fluids, thereby altering wettability, reducing interfacial tension (IFT) and consequently
improving water imbibition. Imbibition is largely dependent on the capillary forces, which are defined by
the Young-Laplace equation (Eq. 1) relating capillary forces (Pc) with wettability as contact angle (θ), IFT
(σ), and pore radius (r). Hence, capillary forces are significant in organic liquid rich shale nanopores and
complex as the contact angle and IFT varies simultaneously.
In petroleum systems, wettability is the affinity of either water or oil to spread onto a rock surface. The
fluid that has higher affinity to the rock is then called the wetting phase and the non-wetting phase is the
other fluid (Anderson 1986a). Thus, rock surface can be oil, water or intermediate-wet. Wettability can be
measured quantitatively by contact angle (CA), Amott-Harvey index, and US Bureau of Mines (USBM)
methods, and qualitatively by nuclear magnetic resonance (NMR), relative permeability determination and
zeta-potential methods (Alvarez and Schechter 2017; Anderson 1986b; Wang et al. 2012). All these methods
have been successfully used to measure wettability in conventional reservoirs; however, in unconventional
reservoirs, many of these techniques have limited application. Methods such as Amott-Harvey index and
USBM require acquisition of fluid saturation changes by displacement of brine by crude for the drainage
cycle into the matrix. Without direct injection to cover the imbibition and drainage cycles, these rocks cannot
be utilized for special core analysis in the conventional manner. The lack of direct injection necessitates
more modern core-handling techniques as described in this paper. Hence, for this study we chose the CA
method for being the most viable way to quantitatively determine wettability alteration in ULR. Unlike
conventional reservoir rocks, shale chips provide ample, almost molecularly smooth, surfaces to measure
directly the contact angle of reservoir fluids at reservoir temperature. In addition, we used zeta-potential
measurements to qualitatively investigate the wetting affinity of these ULR based on the dependency of
wettability on the stability of the double-layer between oil and the shale rock surface. The layer thickness and
stability is determined by relative charge of the surface and the fluids interacting with the surface (Hirasaki
1991). Thus, stable solution film gives an indication of water-wet systems whereas unstable solution film
is considered oil or intermediate-wet. Also, the strength and nature of the rock and the aqueous solution
charge can be gauged by zeta-potential measurements.
The Young-Laplace equation (Eq. 1) also considers the IFT as an important parameter in capillarity.
IFT is the force that holds a phase in the pore space in which oil, water and gas coexist. Depending on its
value and application, IFT can be measured by sessile drop, spinning drop and pendant drop methods. We
measured IFT using the pendant drop method, which relates the deformation of a drop in another liquid
phase and is very reliable for values larger than 0.2 mN/m. Finally, the last parameter affecting capillary
pressure is the mean pore radius, which we determined from pore throat distribution using mercury injection
capillary pressure (MICP) analysis.
Due to the mixture of water-wet inorganic pores and oil-wet organic pores in ULR, wettability in
these unconventional rocks is originally oil and intermediate-wet. Alvarez and Schechter (2016a) compiled
the different wettability measurements for different ULR available in the literature showing that most
of the results reported intermediate to oil-wet affinities originally. In addition, Alvarez and Schechter
(2016b) performed several more wettability studies in the Bakken, Eagle Ford, Wolfcamp and Barnett
ULR concluding that their original wettability was mostly intermediate towards oil-wet with the Wolfcamp
exhibiting the greatest degree of oil-wetness.
In order to let capillarity favor imbibition, capillary pressure must be positive. Thus, ULR wettability must
be altered to water-wet when original wettability is oil and intermediate-wet. Also, IFT should be moderately
reduced to favor water imbibition, but not to ultra-low values which would make capillary pressures
negligible (Alvarez et al. 2017). Wettability and IFT can be modified by surfactants. Typically, we work with
commercial products containing blends of which we have no precise information on the molecular structure,
only the general charge of the surfactant solution utilized. As surface-active agents, they contain two groups,
a lipophilic group that has a strong attraction for the solvent phase and a lipophobic group that tends to repel
the solvent phase molecules. In oil-water systems, surfactants generally consist of a hydrophilic head that
is an ion bearing positive charged (cationic surfactants), negative charged (anionic surfactants) or neutrally
charged (nonionic surfactants), and a hydrophobic tail composed of various hydrocarbon chain lengths and
isomer groups. Some surfactants consist of hydrophilic heads bearing both positive and negative charges,
and they are characterized as amphoteric or zwitterionic surfactants.
Wettability alteration coupled with reduction in interfacial tension at the oil-water fluid interface have
been the focus of various enhanced oil recovery (EOR) studies in conventional reservoirs as they affect
the imbibition profile and consequent oil recovery. In conventional reservoirs, altering the wettability of
the rock to water-wet helps recover additional oil by mobilizing oil trapped in fine channels after primary
recovery, which is a strong motivation behind the research of EOR techniques (Guo et al. 1998; Schechter
et al. 1991; Schechter et al. 1994). However, these methods have limited application in ULR due to their
unique petrophysical properties such as low porosity and permeability, mixed lithology and elevated total
organic carbon (TOC) content. Hence, the use of surfactant as well as recovery mechanisms may change
between conventional and unconventional reservoirs. For example, the forces that determine imbibition
and drainage in porous media in both conventional and unconventional reservoirs are capillary, gravity and
viscous forces. However, in conventional reservoirs, reduction of capillary forces related to viscous forces
via capillary number is the primary mechanism whereas improvement of adhesion-repulsion forces at the
surface thereby altering capillary forces is hypothesized to be the driving force in ULR.
In addition to the role of surfactants as wettability and IFT modifiers, the effect of adsorption in ULR
must be studied. Currently, there are very limited investigations on surfactant adsorption in ULR and, to our
knowledge, none for the Wolfcamp and Eagle Ford formations. Using Marcellus shale outcrops, Zelenev
et al. (2011) studied nonionic surfactant static adsorption by measuring surface tension of diluted solutions
before and after crushed shale equilibrium. The resulting adsorption values for nonionic surfactant were
close to 15 mg/g of rock at surfactant concentration of 3000 mg/L. Next, using ultraviolet-visible (UV-Vis)
spectroscopy in an undisclosed crushed calcite and clay-rich ULR sample, Mirchi et al. (2014) performed
static adsorption measurements on anionic surfactant, noticing very low adsorption values (0.508 mg/g
at CMC of 0.03 wt.%) and Langmuir type adsorption behavior. They suggested that these results were
caused by shale surface capacity for attracting predominately cations instead of anions. Zhang et al. (2016)
used anionic, nonionic and blended surfactants to measure surfactant adsorption in siltstone Middle Bakken
by UV-Vis spectroscopy. Their results showed adsorption capacities of 0.62 mg/g of rock for the blended
surfactant and 11.91 to 33.08 mg/g for nonionic and anionic surfactants. However, the authors attributed the
latter elevated values to unreliable measurements caused by solution turbidity. Finally, Alvarez et al. (2017)
measured anionic and complex nanofluid (CNF) dynamic adsorption in siliceous and carbonate cores from
Three Forks formation in the Bakken using UV-Vis spectrophotometry. Their results showed surfactant
adsorption ranges from 6.2 to 8.9 mg/g of rock at concentration of 2 gallons per thousand gallons (gpt)
with a Langmuir-type adsorption mechanism on the Bakken samples. In addition, they found that lithology
and surfactant type influences adsorption capacity with anionic surfactant absorbing more on siliceous rock
whereas positively charged CNF shows higher adsorption capacity in carbonate-rich rocks (Alvarez et al.
Currently, there is very scant literature on the study of combined effect of wettability and IFT alteration
on imbibition process on the Wolfcamp and the Eagle Ford ULR. However, the recent use of ULR as a
source of liquid hydrocarbons has caught the attention of the industry in regards to wettability alteration
and imbibition in ultralow permeability reservoirs. Xu and Fu (2012) used oil saturated crushed Eagle
Ford sample in a packed pressure column. Surfactant solutions were flooded through this arrangement to
evaluate oil recovery. The results showed that weakly emulsifying surfactant recovered more oil than nonemulsifying surfactant by reducing capillary pressure. The authors determined that rock wettability was
altered by surfactants using the Washburn method, but no direct wettability measurement was performed.
Nguyen et al. (2014) experimented with outcrops from Eagle Ford. They used two cationic, three nonionic,
two zwitterionic, three anionic and blends of surfactants at concentration from 0.1 to 0.2 wt.% and in a 2
wt.% brine. Spontaneous imbibition experiments were performed in Amott cells at reservoir temperature.
The results showed that anionic surfactants recovered 48% of the original oil in place (OOIP) and cationic
surfactants 38% and 23% of OOIP. However, for the second cationic surfactant, brine alone was better in
recovering oil (30% of OOIP). Also, CA was not properly measured as they were qualitatively measured
just by dispensing a brine drop to the shale surface. Such measurements are not analogous to recovery of oil
on an initially oil-wet surface by dislodging that oil via wettability alteration. The authors concluded that
wettability alteration is the main mechanism for oil recovery because they did not find correlation with IFT
and recovered oil. Finally, Alvarez and Schechter (2017) performed spontaneous imbibition experiments
in siliceous core samples from the Wolfcamp using anionic and nonionic-cationic surfactants in modified
Amott cells tracking oil movement by CT scan time-lapse sequences. Their results showed oil recoveries
up to 33.9 % of OOIP for anionic surfactant and up to 19.7 % of OOIP for nonionic-cationic surfactant with
water only recovering up to 10.5 % of the OOIP.
This study aims to close the current gaps in the literature by evaluating the role of surfactants to
completion fluids in improving oil recovery when fracturing Wolfcamp and Eagle Ford ULR by a correlated
set of experiments. First, ULR original wettability and wettability alteration by surfactants is studied by
CA and zeta-potential measurements. Then, additives capacity in decreasing oil/brine IFT is addressed
by IFT measurements. Next, surfactant adsorption measurements are performed using ultraviolet-visible
spectroscopy to address the extent of surfactant loss by adsorption during imbibition of completion fluids.
Then, spontaneous imbibition experiments coupled with CT scan technology is used to analyze the impact
of surfactants on water imbibition and consequently oil recovery, which holds the key to design chemical
treatment for improving oil recovery. Finally, laboratory results are simulated using reservoir modeling
to reproduce experimental set-up and findings and upscale these results to estimate field production.
The uniqueness of this work is that it evaluates a holistic range of parameters the impact rock-fluid and
fluid-fluid interactions by studying the effect of surfactant additives on wettability, IFT and adsorption
and their implications for improving oil recovery under multiple scenarios. To our knowledge, this has
not been rigorously performed in the Wolfcamp and Eagle Ford unconventional reservoirs. The results
showed that surfactant are capable of altering wettability from intermediate and oil-wet to water-wet in
Wolfcamp and Eagle Ford core as well as simultaneously reducing water-oil IFT. Moreover, in spontaneous
imbibition experiments, aqueous solutions with surfactants imbibed further, as measured by CT scanning,
and recovered more oil than water alone. These findings are consistent with CA, zeta potential, and IFT
measurements. On the field-scale simulation, adding surfactant into the system is observed to increase the
initial oil production rate and the cumulative oil production. From these results, we can conclude that the
addition of surfactants to completion fluids alter wettability and reduce IFT, thereby improving oil recovery
in Wolfcamp and Eagle Ford core. Thus, we begin to lay the foundation of the necessary tests and significant
parameters that determine the optimum exchange of fluids during aqueous phase treatments in multiple
This study investigates the interaction of completion fluids, with and without surfactants, and ULR. In
addition, it addresses the effect of wettability, IFT, adsorption and imbibition on recovering hydrocarbons
from liquid-rich shale cores from the Wolfcamp and Eagle Ford formations. These objectives are achieved
by performing contact angle, zeta potential, adsorption and IFT measurements, as well as spontaneous
imbibition monitored by computer tomography (CT) methods. Hence, this chapter describes a novel set
of correlated experiments to evaluate and compare the efficiency of surfactants in altering wettability and
recovering hydrocarbons from ULR core. Finally, wettability, IFT, adsorption and spontaneous imbibition
results are used as inputs for a reservoirs simulation to reproduce laboratory experiment and scale the results
to the field.
Rock and Fluid Properties
Sidewall core plugs received from the liquid-rich portion of the Wolfcamp and the Eagle Ford play were
used. Wolfcamp samples were taken from well W-1 at depths from 7,850 to 7,900 ft. whereas Eagle Ford
samples were from well EF-1 at depths from 13,000 to 13,050 ft. Cores are 1-inch in diameter and 1.5 to
2.5-inches in length. Wolfcamp samples show porosity from 6 to 7 %, permeability to air of 200 to 300
nD, and median pore radii of 0.005 microns all measured by mercury injection capillary pressure analysis
(MICP). Similarly, Eagle Ford samples show porosity of 9 to 12 %, permeability to air of 100 to 300 nD,
and median pore radii of 0.007 microns. Total organic carbon (TOC), measured on a LECO C230 Carbon
Analyzer is from 5 to 6 wt.% for Wolfcamp and 6 to 6.5 wt.% for Eagle Ford. ULR rock sample lithology
for the intervals studied is shown in Table 1. The X-Ray Diffraction (XRD) analyses for both Wolfcamp
and Eagle Ford demonstrate that the samples are predominately carbonaceous.
Table 1—Lithological composition of rock samples from wells W-1 and EF-1
Mineral Composition (wt.%)
Relative Clay (%)
Wolfcamp crude oil from well W-1 was used with density of 0.82 g/cm3 and 32.4° API at reservoir
temperature of 165 °F. On the Eagle ford, crude oil from well EF-1 was used with density of 0.72 g/cm3
and 52.61° API at testing temperature of 180 °F. Oil total acid number (TAN) and total base number (TBN)
was determined by titration methods in a Metrohm 905 Titrando apparatus. Wolfcamp oil TAN and TBN
are 0.09 and 0.12 mg KOH/g oil, respectively whereas Eagle Ford oil TAN and TBN are 0.02 and 0.61 mg
KOH/g oil, respectively.
Surfactants and Brine
Four different surfactants, which are commercially available and commonly used as additives in completion/
fracture fluids were used. In order to evaluate a broad range of surfactant types, we tested two anionic, one
blended anionic-nonionic and one cationic surfactant at field used concentration of 2 gallons per thousand
gallons (gpt). Surfactant descriptions are in Table 2.
Table 2—Description of the surfactants used in the experiments
Anionic 1
Anionic 2
Primary Components
Composition (wt.%)
Methyl alcohol
Proprietary sulfonate
Methyl alcohol
Sulfonate A
Sulfonate B
Ethoxylated alcohol
Isopropyl Alcohol
Citrus Terpenes
Isopropyl Alcohol
Ethoxylated alcohol
Quaternary Ammonia Compound
Citrus Terpenes
Specific Gravity
0.866 - 0.892
0.974 - 0.999
0.953 - 0.956
Aqueous solutions were prepared with distillated water and 4 wt.% potassium iodide (KI) brine solution
(named as Water on this study). KI was added as a dopant to increase the contrast between oil and aqueous
phases on the CT scanner, a needed procedure to observe fluid penetration during spontaneous imbibition
experiments. The effect of KI on sample wettability was found to be negligible, so it is not considered for
comparative analyses. Moreover, pH values remained constant for all surfactant solutions and brine in the
experiments executed in this study.
Contact Angle Measurements
CA experiments were performed on a Dataphysics OCA 15 Pro apparatus using the captive bubble method.
Wolfcamp and Eagle Ford core samples were carefully cut, to fit inside the measuring device, polished, to
minimize measurement errors related to surface roughness, and cleaned in toluene and methanol to remove
any impurities due to sample handling. Then, core trims were aged in Wolfcamp and Eagle Ford oil for
more than 4 weeks at reservoir temperature.
Wolfcamp and Eagle Ford samples were then submerged in water alone as well as surfactant aqueous
solutions at concentration of 2 gpt. Wolfcamp and Eagle Ford oil is dispensed bottom up using a capillary
needle. As the droplet of oil slowly attaches to the shale surface forming an angle, the shape of the oil's
droplet is analyzed by enhanced video-image digitalization technique. Further details are in Alvarez et al.
(2014). In order to represent as accurate as possible the liquid phases on the reservoir, oil and water phases
are present and the contact angle is formed on the rock surface. Contact angles ranging from 0° to 75°, 75°
to 105° and 105° to 180° are employed for water, intermediate and oil-wet as defined by Anderson (1986b).
Moreover, CA measurements for Wolfcamp samples were performed at reservoir temperature of 165 °F;
similarly, Eagle Ford experiments were performed at 180 °F, which is the closest experiment temperature
to reservoir temperature (220 °F) that avoids bubble movement, which might affect the reliability of our
results. Error bars are assigned based on the experiment confidence level with upper and lower bounds of
3 degrees.
Zeta Potential Measurements
Zeta potential measurements were performed on a NanoBrook ZetaPALS device using the Phase Analytical
Light Scattering (PALS) method. The device measures the electrophoretic velocity of the particles in the
solution and use this value to calculate the electrophoretic mobility. Measurements were performed in
aqueous solution with and without surfactants, at concentrations of 2 gpt, and ULR rock samples from
wells W-1 and EF-1 (Wolfcamp and Eagle Ford). Aqueous solutions were prepared and triple filtered before
placing them into the vial for measurement. Moreover, core trims were finely crushed and screened in an
ASTM 325 sieve of 45-μm diameter. Rock and aqueous solutions were mixed in a shaker for 1 minute.
The sonicated solution was left to stabilize by letting it sit for 5-10 hours for the heavy insoluble particle
to settle down. Then, the solution was placed in the zeta potential measuring device. Further details are in
Alvarez and Schechter (2017). Error bars are assigned based on the experiment confidence level with upper
and lower bounds of 2 mV.
IFT Measurements
IFT measurements were performed in a Dataphysics OCA 15 Pro apparatus using the pendant drop method.
Wolfcamp and Eagle Ford oil is dispensed through the capillary needle, which is submerged into the aqueous
solution with and without surfactants at concentration of 2 gpt. The experiment is recorded by a highresolution video camera and the image of when the drop is about to leave the needle is analyzed by enhanced
video-image digitalization technique. IFT experiments were performed at the same temperature as the CA
experiments of 165 °F and 180 °F for Wolfcamp and Eagle Ford, respectively. Finally, to calculate the brine/
oil IFT, the droplet shape profile is matched to the Laplace equation by the device software, using the density
of the oil and aqueous solutions at testing temperature. Further details are in Alvarez et al. (2014). Error
bars are assigned based on the experiment confidence level with upper and lower bounds of 0.2 mN/m.
Surfactant Adsorption Measurements
Surfactant adsorption on the Wolfcamp and Eagle Ford rock surface was measured by UV-Vis
spectrophotometry. A Hitachi U-4100 UV-Vis-NIR spectrophotometer was used to calculate the
concentration of the surfactant as time progresses. The device produces light with specific wavelength
that is shined through the tested solution. Water without additive added was used as the reference solution
and aqueous solution with surfactants are used from calibration curve and adsorption experiments. The
calibration curves for each surfactant were done by correlating the amount of light adsorbed on that
wavelength to the surfactant concentration in the solution. The wavelength scan range used was 190 to 300
After the calibration curves were constructed, dynamic adsorption measurement was performed. To that
end, Wolfcamp and Eagle Ford samples were cleaned in toluene then methanol, for 3 days and 2 days
consecutively, then vacuum-dried for 3 days. Cleaned samples were crushed and passed thru a 300 μm sieve.
Aqueous solution with surfactants were mixed in a 1:20 weight ratio with the rock samples. During the
experiments, fluid samples were taken at different times from 10 minutes to 24 hours and filtered through
a 20 μm syringe filter before measuring the light adsorption to remove rock particles and consequently
stopping the adsorption reaction. Lastly, using the calibration curve for each surfactant, surfactant dynamic
adsorption was calculated at each time step using Eq. 2 (Alvarez et al. 2017).
where θA is the amount of surfactant, ϕisurf and ϕfsurf the initial and final surfactant concentrations, respectively,
Vsurf and ρsurf the surfactant volume and density, respectively, and Wrock the weight of rock. Further details
are in Alvarez et al. (2017). Error bars are based on the UV-Vis spectrophotometer precision of 0.05 light
absorbance for the range of wavelength utilized in the experiments. This error was used when calculating
surfactant adsorption.
Spontaneous Imbibition Experiments Monitored by CT Scan Methods
The potential of surfactants in imbibing Wolfcamp and Eagle Ford cores and recover liquid hydrocarbons is
studied by spontaneous imbibition experiments. Wolfcamp and Eagle Ford cores were aged for more than 6
months at experimental temperature to reconstitute them with the missing liquid hydrocarbons due to sample
handling. Modified Amott cells were designed to allow their use on the CT scanner. The modified Amott
cell consists of a temperature resistant glass base with a graduated measuring scale at the top to measure oil
recovery with time. Error bars are assigned based on the measuring scale precision of 0.01 ml. Then, this
error was used when calculating oil recovery as function of the OOIP. Cores were placed horizontally in
a Plexiglas core base, at the bottom of the cell, to trace radial fluid imbibition toward the core center. The
same surfactants used in previous experiments and shown in Table 2 as well as water without additives were
tested at field-used concentration of 2 gpt inside an environmental chamber to have a constant temperature
of 165 °F for the Wolfcamp samples and 180 °F for the Eagle Ford samples. Further details are in Alvarez
and Schechter (2017).
In order to observe fluid penetration into the ULR core in real time, a Toshiba Aquilion TSX-101A
CT scanner was used as X-rays produce tomographic images of specific areas of the cores, allowing us to
see inside them. Helical scans were set on 135 kV and 350 mA with a rotation time of one second and a
slice thickness of 0.5 mm with intervals between each slice of 0.3 mm. Initial and final core wettability
was determined by CA measurements, and the cores’ average initial and final CT numbers were calculated
using CT scan methods. The cores were scanned periodically throughout the experiments to trace fluid
imbibition. Moreover, oil production was monitored recurrently using the graduated scale on the modified
Amott cell. CT data was processed using an open source software package called ImageJ to generate colorcoded relative density images, and fluid imbibition as penetration magnitude was calculated using the core
average initial and average final CT numbers as determined by Eq. 3 (Alvarez et al. 2014).
Numerical Modeling of Experimental Results
Upscaling the result from the laboratory-scale to field-scale provides a more thorough view on the effect of
surfactant imbibition on the oil recovery in shale oil reservoir. In this work, we used the commercial reservoir
simulator CMG®. Numerical modelling was divided into two parts, the laboratory-scale and the field-scale.
The first part of the simulation was done to model the results from the spontaneous imbibition experiments.
A grid model of the core plug used on the tests was constructed and the experiment was modeled by placing
the core grid in the middle of a water bath with the same laboratory conditions. Then, history matching on
different properties was done to obtain the oil production curve observed in the experiments. All imbibitionrelated properties applied on the core-scale model that provide the best match were applied on the fieldscale model. The field-scale system was a mechanistic model consisting of single hydraulic fracturing stage
with the starting conditions that mimic the reservoir on shut-in stage after hydraulic fracturing.
The change in capillarity caused by surfactants was modeled by providing two capillary pressure curves
representing the two-wettability and IFT stages. For each grid block, a new capillary pressure curve was
calculated by averaging the two curves with the amount of surfactant adsorbed as the weighting value.
Adsorption data of each surfactant was used in the function of surfactant concentration. Shift from the initial
capillary pressure curve to the final curve changed capillary equilibrium, resulting in grid water imbibition
accompanied by oil release. Hence, capillary pressure curve was constructed by matching the oil recovery
from the numerical simulation to the laboratory experiment result.
Next, to model the heterogeneity of the core used in the spontaneous imbibition experiment, the core
grid was constructed using the CT-scan rock digitalization method. Each core was scanned using the CTscan, which produces a matrix of CT numbers that can be used to reconstruct the core digitally. The CT
number matrix was converted to density matrix (ρ) using Eq. 4 (Massicano et al. 2009), and by converting
these matrices of CT number to matrices of density, the porosity distribution (ϕ) of the core was derived
by Eq. 5, where ρr and ρfl are the density of the rock and fluid, respectively. We assumed that ρfl is equal to
zero due to the rigorous cleaning process that the core undertook before CT scanning. The cleaning process
consisted of performing dean stark with the core plug in toluene and methanol consecutively followed by
vacuum drying for an extensive period.
A mechanical model was used for the field-scale simulation. The model consisted of single stage
hydraulic fracture on a dual porosity grid system. We assume the surfactant solution was introduced into
the reservoir during the hydraulic fracturing process as completion fluid; therefore, the initial condition of
the simulation was set to begin at well shut-in. Then, surfactant were added into both fracture and matrix
system, where we assumed that fractures were filled with only completion fluid and matrix had a mixture
of completion fluid and in-place brine resulting in the reduction of surfactant concentration in the matrix
system. The simulation was run with the assumption of 30-days shut-in followed by production for three
years period using the water without surfactant as the base case and surfactants to compare the oil production
in term of peak oil rate, 1-year cumulative recovery, and 3-years cumulative recovery on a single well basis.
Results and Discussion
The results and observations from the proposed correlated set of experiments to evaluate surfactant
performance in altering wettability and IFT, adsorbing on the rock surface and recovering hydrocarbons
from Wolfcamp and Eagle Ford ULR are presented in this section. In addition, results are discussed to
show consistency in the workflow proposed and reproduced by reservoirs modeling tools to upscale the
experimental results to the field.
Contact Angle Results
CA measurements were performed in carbonate samples from the Wolfcamp (well W-1) and Eagle Ford
(well EF-1) as described in Table 1. Original wettability for both ULR as well as the extent of wettability
alteration by the use of surfactants, described in Table 2, are shown in Fig. 1. Wolfcamp initial CA shows
its original wettability as oil to intermediate-wet with a CA of 121°, as shown in Fig. 1, left. Similarly,
Eagle Ford initial wettability, shown in Fig. 1, right, is also oil to intermediate-wet (CA of 127°). This initial
rock wettability of oil to intermediate-wet is due to the mixture of organic and inorganic matter in ULR.
Wolfcamp and Eagle Ford samples have TOC of 5 to 6.5 wt.% as an indication of the presence of organic
matter. This organic matter is oil-wet whereas the inorganic matter is water-wet and their combination gives
ULR surface intermediate toward oil-wetting affinity. These results are consistent with other researchers
who measured Wolfcamp, Bakken and Eagle Ford original wettability by NMR methods (Odusina et al.
2011) and contact angle methods (Alvarez et al. 2017; Alvarez and Schechter 2016b; Alvarez and Schechter
2017; Morsy and Sheng 2014; Nguyen et al. 2014).
Figure 1—CA results for well W-1 (left) and well EF-1 (right) for four surfactants at concentration of 2 gpt.
After determining ULR initial wettability, surfactants were added, at concentration on 2 gpt, to evaluate
their effect on wettability alteration. The results showed that all surfactants were capable of altering
Wolfcamp and Eagle Ford rock surface wettability from oil and intermediate-wet to water-wet. In addition,
both reservoirs presented similar performance for different groups of surfactants. Cationic surfactant altered
wettability of both Wolfcamp and Eagle Ford samples in higher amount. Bear in mind that among the
surfactants tested, the cationic is the only one that has a positive charge on its head, and all others (anionic
1, anionic 2, and anionic-nonionic) are mostly anionic. We suggest that the cationic surfactant performed
better than the other surfactants due to the electrostatic interactions between its positively charged heads and
the negatively charged oil compounds, mostly acid compounds, attached to positively charged carbonate
surfaces presented in both Wolfcamp and Eagle Ford rocks. Hence, wettability alteration takes place when
the oil molecules attached to the rock surface are stripped and moved to the oil phase. Similarly, negatively
charged surfactants such as anionic 1, anionic 2 and anionic-nonionic lacked these electrostatic interactions,
changing CA in lesser amounts by hydrophobic interactions. In addition, the presence of nonionic surfactant
in the anionic-nonionic blend improved its efficacy as compared to the anionic surfactants alone. For the
Wolfcamp, the effect of electrostatic interactions can be confirmed when revising the findings reported by
Alvarez and Schechter (2017). In that case, Alvarez and Schechter (2017) used siliceous cores from the
Wolfcamp showing that anionic surfactants were better in altering CA than positively charged surfactants.
The results presented in this study showed better performance in carbonate cores with positively charged
surface-active agents.
In summary, additive the cationic surfactant reduced CA more in carbonate cores from Wolfcamp and
Eagle Ford. These findings suggest that lithology and surfactant type have a direct impact on surfactant
performance in altering rock wettability. Next, to determine the charges of the surfactant solutions as well
as the stability of the water films on the Wolfcamp and Eagle Ford rock as an indication of wettability
alteration, zeta potential experiments are performed.
Zeta Potential Results
Zeta potential measurements were performed to further study wettability alteration in these ULR. Film
aqueous solution instability, referenced as zeta potential values between −30 to + 30 mV, is an indication
of intermediate or oil-wetness whereas zeta potential values more positive than +30 mV or more negative
than −30 mV can be interpreted as stable indicating water-wet behavior. In addition, this technique gives us
an indication of the surfactant electrostatic charges. Zeta potential results are shown in Fig. 2. Initially, zeta
potential values for water alone for Wolfcamp (Fig. 2, left) and Eagle Ford (Fig. 2, right) samples showed
an unstable water film as an indication of intermediate to oil-wet behaviors. These results are consistent
with original wettability determined by CA.
Figure 2—Zeta potential results for well W-1 (left) and well EF-1 (right) for four surfactants at concentration of 2 gpt.
Conversely, when surfactants were added at a concentration of 2 gpt, aqueous film stability on the rock
surface increased as a sign of water wetness. In addition, zeta potential values showed the nature of the
additives evaluated. Negatively charged surfactants (anionic 1, anionic 2 and anionic-nonionic) showed
negative zeta potential magnitudes whereas the cationic surfactant demonstrated its positive charges as its
zeta potential values were found to be positive. These changes in zeta potential values when surfactants are
added to water are consistent with CA measurements as wettability alteration, and they may favor imbibition
in these Wolfcamp and Eagle Ford rocks by shifting capillary pressure signs from negative to positive. In
the next section, the effect of surfactants in reducing IFT is studied.
IFT Measurement Results
Fluid-fluid interactions between Wolfcamp and Eagle Ford oil and aqueous solutions with and without
surfactants were investigated via IFT measurements. The same surfactants used in CA and zeta potential
experiments were used at a concentration of 2 gpt. IFT results are shown in Fig. 3. Original IFT between
water and Wolfcamp oil had an initial value of 21.8 mN/m (Fig. 3, left) whereas Eagle Ford oil showed
an initial IFT of 34.4 mN/m (Fig. 3, right). Then, as surfactants were added to the aqueous solutions, oilbrine IFT was reduced, in some case by more than one order of magnitude. This reduction in IFT is due
to the alignment of surfactant molecules on the oil-brine interface. As a result of its amphiphilic nature,
surfactant molecules placed themselves at the interface facing the different phases, the tail group with the
hydrophobic oil phase and head group with the hydrophilic water phase. Thus, the surfactant lowered the
surface energy and decreasing IFT.
Figure 3—IFT results for well W-1 (left) and well EF-1 (right) for four surfactants at concentration of 2 gpt.
Fig. 3 also shows that anionic and anionic-nonionic surfactants reduced IFT the most, being the surfactant
anionic 1 the one with the largest reduction. This is caused by the presence of sulfonates on their formulation.
Sulfonates are highly polar and negatively charged functional groups which reduce IFT by creating a strong
affinity between the surfactant head and the water phase and consequently a poor arrangement in the wateroil interface. On the other hand, the cationic surfactant showed the lowest reduction in IFT, which is a typical
behavior by surfactants that have quaternary ammonia compounds on their composition. Hence, the IFT
results indicate that surfactant efficacy in reducing IFT depends on the surfactant nature. In addition, the
oil type plays a role in fluid-fluid interactions as IFT reduction. As reported on the methodology section,
Wolfcamp oil TAN and TBN are 0.09 and 0.12 mg KOH/g oil, respectively whereas Eagle Ford oil TAN
and TBN are 0.02 and 0.61 mg KOH/g oil, respectively. These values suggest that Wolfcamp oil is slightly
basic and Eagle Ford oil is basic in nature. These positively charged Wolfcamp and Eagle Ford oil interact
better with anionic surfactants, as negatively charged compounds, favoring IFT reduction.
IFT reduction by surfactants also favors wettability alteration in these ULR. Due to ULR very small pore
sizes (0.005 microns for Wolfcamp and 0.007 for Eagle Ford), capillary pressures are high and the effect
of decreasing IFT by surfactants aids fluid imbibition and consequently surfactant interaction with the rock
surface. Once in contact with the rock, surfactants solubilize the oil attached to the rock altering wettability.
This is the main reason why all surfactants used in these study, regardless of their charge, altered wettability
at the concentrations tested. Thereby, a moderate IFT reduction is desired to favor wettability alteration
in tight pores and reduce capillary pressures. However, contrary to conventional EOR techniques such as
surfactant flooding, in ULR ultralow IFT should be avoided to prevent total elimination of capillary forces,
which plays a vital role in imbibition and oil recovery in ULR.
Surfactant Adsorption Measurements
Surfactant dynamic adsorption was measured by evaluating the difference in surfactant concentration
before and after the specified time of reaction. The concentration was measured using the UV-Vis
spectrophotometer, which requires a calibration curve correlating the light adsorption on each surfactant's
specific wavelength with the surfactant concentration to be constructed first. Fig. 4 shows the measured
calibration curve that was used in the dynamic adsorption experiments for the four surfactants tested. In
addition, Fig. 4 shows that light adsorption and surfactant concentration are related in a linear trend where
the trend deflects as it approaches certain concentration, mostly between 1.5 to 2.0 gpt. We suggest that this
trend change in is caused by the aggregation of the surfactant molecules to form micelles. These micelles
have different light adsorptions from the individual surfactant molecule. Thus, the change in trend line was
observed as surfactant critical micelle concentration (CMC) was reached.
Figure 4—Calibration curve correlating the amount of light adsorbed
to the concentration of the four surfactants used in the experiment.
Next, surfactant adsorption on rock samples from wells W-1 (Wolfcamp) and EF-1 (Eagle Ford) is shown
on Fig. 5. For well W-1, the cationic surfactant adsorbed the most, followed by anionic 1 and anionicnonionic surfactant, then surfactant anionic 2 as the least adsorbed on W-1 surface. Most of the adsorption
took place in the first six hours of reaction time followed by either a plateau or more adsorption with slower
rate. This trend showed that a reduction of adsorption site occurred implying that most of the surfactants
were adsorbed on the rock surface in a monolayer configuration with some surfactant-surfactant interaction
as the adsorption continues but at slower rate.
Figure 5—Surfactant dynamic adsorption for well W-1 (left) and well EF-1 (right) for four surfactants.
Surfactant adsorption highly depends on both the additive type and rock composition. The results showed
that the cationic surfactant adsorbed with substantially higher quantity compared to the other surfactants
tested. By correlating these results to the rock mineralogical analysis shown on Table 1 and the composition
of the surfactants shown on Table 2, we suggest that the amount of clay in the sample could be the cause
of higher cationic surfactant adsorption. The quaternary ammonia compound in the cationic surfactant
adsorbed strongly on clay mineral, especially in those belong to illite group (Sánchez-Martín et al. 2008). On
the other hand, both surfactants anionic 1 and anionic-nonionic were adsorbed more compared to surfactant
anionic 2 since they both have sulfonate compounds which known to be reactive to the carbonate mineral
in Wolfcamp and Eagle Ford samples (Sheng 2015).
The result of surfactant dynamic adsorption on sample EF-1 are shown on Fig. 5, right. Similar adsorption
results on well W-1, the cationic surfactant adsorbed the most, followed by anionic 1, anionic-nonionic,
and anionic 2. The adsorption on EF-1 also showed the significance of rock and surfactant composition to
surfactant adsorption. As shown on Table 1, rock sample EF-1 has more than 30 wt.% clay mineral which
explains the high adsorption nature of the cationic surfactant. High carbonate content would also explain
the relatively high adsorption showed by the anionic surfactants as sulfonate compound adsorbed strongly
on carbonate minerals. Surfactant adsorption would cause loss of these additives in the reservoir. Different
surfactant composition and rock mineralogy have a considerable influence on the amount of surfactant
adsorbed on the rock. Therefore, when designing stimulation treatments using surfactants as additives,
surfactant adsorption must be considered. Next, we evaluate the impact of wettability and IFT alteration as
well as surfactant adsorption in recovering oil by spontaneous imbibition experiments.
Spontaneous Imbibition Experiment Results Monitored by CT Scan Methods
In the previous sections, we demonstrated that surfactants are capable of altering wettability, reducing brineoil IFT and adsorbing in ULR samples from the Wolfcamp and Eagle Ford. These changes in wettability and
IFT modify capillary pressures. Thus, in this section, we are going to evaluate the impact of these variables
in oil recovery from Wolfcamp and Eagle Ford sidewall cores by spontaneous imbibition experiments.
Table 3 shows the well, core dimensions, initial properties, and type of fluid used. These values, along
with initial water saturations, are used to calculate core initial oil in place (OOIP) and to relate the oil
recovered as experimental time elapsed, to the amount of oil initially on each core. Initial water saturations
were determined by mercury intrusion and extrusion analysis and the results showed a Wolfcamp initial
water saturation (Swi) for well W-1 of 0.15 whereas Eagle Ford, well EF-1 initial water saturation of 0.1. In
addition, Table 3 also exhibits the initial CA as wettability measurement for the cores used showing that all
cores are initially intermediate and oil-wet due to the extended aging period.
Table 3—Properties of cores used in spontaneous imbibition experiments
Eagle Ford
Porosity (%)
Diameter (in)
Length (in)
Initial CA (°)
Type of Fluid
Anionic 1
Anionic 2
Anionic 1
Anionic 2
Imbibition experiments for the Wolfcamp formation were performed with cores from well W-1. Cores
1 to 5 were submerged in aqueous solution with and without surfactants as indicated in Table 3. When
surfactants were used, the concentration utilized was 2 gpt. Expelled oil from the Wolfcamp cores was
collected at the top of the modified Amott cell with time to construct the recovery curves shown in Fig.
6. Consistent with CA, zeta potential, IFT and adsorption experiments, spontaneous imbibition results for
the Wolfcamp carbonate cores clearly indicate that aqueous solution with surfactants as additives recovered
more oil than water alone. This correlates with the potential of surfactants of altering wettability (Fig. 1, left)
and moderately reducing IFT (Fig. 3, left). IFT reduction favored water penetration in the ULR pores shifting
wettability and capillary pressure sign. Capillary pressure not only changed from negative to positive, but
also its value was reduced due to IFT alteration. Hence, this combined effect in capillary pressure favored
water imbibition and oil expulsion from the core in a countercurrent movement.
Figure 6—Oil recovered for Wolfcamp well W-1 by spontaneous imbibition.
In addition, the core submerged in positively charged additive cationic surfactant (Core 4) produced
more oil than the other cores in different surfactants. We suggest that this better performance is caused by
electrostatic interactions as determined in zeta potential and adsorption experiments. Rock-fluid interactions
between the negatively charged oil compounds attached to the Wolfcamp carbonate samples and positively
charged cationic surfactant heads remove oil from the core surface, favoring water imbibition; thus, oil
recovery. These rock-fluid interactions are also evidenced in the time in which cores began to produce oil.
Conversely, the cores submerged in anionic 1 and anionic-nonionic surfactants (cores 1 and 2), which are the
most negatively charged surfactants, as determined in zeta potential experiments (Fig. 2, left), recovered the
least amount of oil among all surfactants. These results also confirm the impact of electrostatic interaction
in surfactant efficacy where repulsive force between the negatively surfactant heads and negative charges
of the oil attached to the positive core surface prevented oil on the rock to fully leave the pores.
As shown in Fig. 6, the core 4 (cationic surfactant) not only recovered more oil, but also began producing
oil a few hours before the other cores demonstrating that wettability alteration took place faster and more
effectively. In the same way, it can be seen that core 5 (water) began to produce oil more than 18 hours
after the cores in surfactants. This is because water alone is not capable of shifting wettability and reducing
IFT. At the end of the experiments, Core 4 (cationic surfactant) recovered 47.3% of the OOIP, followed by
core 3 (anionic 2) with 32.6%, and cores 1 and 2 (anionic 1 and anionic-nonionic) with 24.3% and 18.9%
of the OOIP, respectively. Finally, aided only by gravity forces, the core submerged on water alone (core
5) marginally recovered only 7.6% of the OOIP due to water lack of potential of changing wettability or
reducing IFT.
Moreover, the oil recovered as a function of the OOIP from Eagle Ford ULR cores is shown in Fig.
7. Similar to the results from the Wolfcamp cores, the cores in contact with surfactants had higher oil
productions than the one in water alone due to additives capability of altering wettability (Fig. 1, right)
and reducing IFT (Fig. 3, right). The high carbonate content in the Eagle Ford samples favored better
electrostatic interactions between the positively charged cationic surfactant and the negatively charged
oil compounds attached to the carbonate surface. Thus, core 9 (cationic surfactant) recovered the highest
amount of oil among all Eagle Ford cores tested. Also, core 9 began to produce in less than one hour
whereas other cores began to expel oil two or more hours after. Cores 6 to 8 (anionic 1, anionic-nonionic
and anionic 2) recovered less oil than core 9 due to electrostatic repulsions that retarded and repressed
an effective interaction of surfactants with the rock-oil system. Therefore, wettability alteration and IFT
reduction induced by surfactants aided core 9 (cationic surfactant) to have a final recovery of 9.0% of the
OOIP whereas cores 6 to 8 recovered 6.5%, 4.5% and 5.8%, respectively. Lastly, consistent with Wolfcamp
results, the core submerged in water alone (core 10) produced only 2.1% of the OOIP due to negative
capillary pressures that prevented oil recovery by imbibition.
Figure 7—Oil recovered for Eagle Ford well EF-1 by spontaneous imbibition.
From the oil recovery results in both the Wolfcamp and Eagle Ford cores, we highlight two important
findings. First, the potential that surfactants have when added to completion fluid to improve oil recovery by
imbibition due to their capability of altering wettability and moderately reducing IFT. Second, the vital role
in imbibition of rock-fluid electrostatic interactions. From spontaneous imbibition results, it can be clearly
seen that the positively charged cationic surfactant recover oil faster and in higher amounts than the other
chemical tested regardless of its lower IFT reduction compared to anionic surfactants.
Next, CT scan technology was utilized to observe spontaneous imbibition inside the Wolfcamp and Eagle
Ford cores. Also, CT scans were used to correlate oil recovery with water imbibition. To that end, the
modified Amott cells were periodically scanned during the experiments to see fluid movement inside the
cores. The resulting CT numbers can be related to water imbibition by knowing the CT numbers of the
phases present. Thus, Wolfcamp and Eagle Ford oil CT number is close to −150 and −100 HU, respectively,
and aqueous solutions CT number are approximately 800 HU due to the use of KI as dopant. The CT
number difference between the oil and the aqueous solutions allow us to trace imbibition into the cores while
water occupies pores originally filled with oil. Hence, in our experiments, fluid imbibition is reached when
increasing CT numbers are observed. CT scan images at progressive times for Wolfcamp cores (cores 1-5)
during spontaneous imbibition experiments are shown in Fig. 8. Consecutive images for Wolfcamp cores
submerged in surfactant solutions (cores 1-4) showed visible changes in colors as CT numbers increased
with time. Color changes from red to green and dark blue to light blue demonstrate water imbibition and
consequently oil displacement. Contrarily, the core in water without surfactants (core 5) showed lesser
changes as an indication of limited water penetration. These observations qualitatively agreed with oil
recovery profiles showed in Fig. 6, in which cores submerged in surfactant solutions produced up to four
times more oil than the core in water alone, confirming our theory that oil recovery increases when water
imbibition is promoted by wettability and IFT alteration.
Figure 8—CT images for Wolfcamp, well W-1 as a function of time in spontaneous imbibition experiments.
Furthermore, CT scan images with time for Eagle Ford cores (cores 6-10) during spontaneous imbibition
experiments are shown in Fig. 9. Same as Wolfcamp cores, consecutive CT images showed clear changes in
color for cores submerged in surfactant solutions (cores 6-9) changing from red to green and dark/light blue
to yellow as evidence of water imbibition. On the other hand, the Eagle Ford core submerged in water alone
showed inferior water imbibition as determined by timid color changes. In addition, CT scan results for
cores 6 to 10 shown in Fig. 9 correlate with the oil recovery performance in Fig. 7 where higher imbibition
in cores 6 to 9 led to higher oil recovery for cores in surfactant solutions whereas lower imbibition in core
10 resulted in lower oil recovery.
Figure 9—CT images for Eagle Ford, well EF-1 as a function of time in spontaneous imbibition experiments.
CT scan images allow seeing fluid movement inside the cores as well as core heterogeneities such
as bedding planes and natural fractures. ULR commonly present with these types of heterogeneities that
dominate fluid flow and oil production in shale systems. Hence, as shown in Fig. 8 and Fig. 9, fluid
flow was not radially homogeneous towards the core center. These heterogeneities present an important
challenge when attempting to model laboratory results and upscaling them to the field. For that reason,
our numerical modeling considers these heterogeneities by creating the grids from CT scan images. By
CT scan technology, we observed that imbibing fluids moved throughout less resistant pathways inside
the core, displacing hydrocarbons. In addition, during the experiments, countercurrent fluid movement
was evidenced where oil was expelled from the core surface as water imbibed due to changes in capillary
The results for the spontaneous imbibition experiments performed in Wolfcamp and Eagle Ford cores
are summarized in Table 4. Aqueous solution imbibition was quantified as penetration magnitudes using
CT scan technology and Eq. 3. For Wolfcamp cores (cores 1-5), penetration magnitude were clearly
higher for cores submerged in surfactant solutions (core 1-4) compared to core in only water (core 5).
Moreover, the Wolfcamp core that exhibited the highest penetration magnitude (core 4) also had the highest
oil recovery confirming the hypothesis that higher imbibition leads to higher oil recovery in these ULR
cores. In addition, the role of rock surface and surfactant charges as rock-fluid interactions was evidenced
when comparing these carbonate core Wolfcamp results to the siliceous Wolfcamp results documented
in Alvarez and Schechter (2017). Alvarez and Schechter (2017) showed that Wolfcamp siliceous cores
had higher penetration magnitudes (imbibition) and oil recoveries when negatively charged surfactants
(anionic surfactants) where used whereas our results showed that Wolfcamp carbonate cores exhibited
higher penetration magnitudes and oil recoveries when positively charged surfactants are used (cationic
surfactant). Similarly, the Eagle Ford cores exposed to surfactant additives (cores 6-9) showed higher
penetration magnitudes and oil recovery than the cores in water without additives (core 10). Next, final
IFT values were also measured showing that aqueous solutions with surfactants reduced IFT in almost
two orders of magnitude for anionic and anionic blended surfactants and one order of magnitude for the
cationic surfactant. It is important to highlight that IFTs were not reduced to ultra-low values as conceived
in conventional EOR. In ULR, capillary forces play a big role in imbibition and oil recovery; hence, they
should not be eliminated by reaching ultra-low IFT values.
Table 4—Spontaneous imbibition experiment results
Type of Fluid
Final IFT
Final CA (°)
Initial Pc (psi)
Final Pc (psi)
Oil Recovery
Wolfcamp (Well W-1)
Anionic 1
Anionic 2
Eagle Ford (Well EF-1)
Anionic 1
Anionic 2
Regarding wettability alteration determined by contact angle methods, Table 4 shows rock wettability
before and after spontaneous imbibition experiments. All cores from Wolfcamp (cores 1-4) and Eagle
Ford (cores 6-9) submerged in surfactant solutions altered wettability from oil-wet (Table 3) to waterwet; whereas Wolfcamp (core 5) and Eagle Ford (core 10) cores submerged in water without surfactants
did not change the CA significantly enough to change wettability to water-wet. Surfactants capability of
reducing IFT and altering wettability allowed capillary pressures to shift from high negative values to
moderate positive magnitudes as shown in Table 4 and calculated using Eq. 1. These fluid-fluid and rockfluid interactions in ULR favored changes in capillary forces for cores exposed to surfactants, favoring
imbibition and improving oil recovery as demonstrated in the last column of Table 4. Conversely, the cores
submerged in water alone were barely able to alter capillary pressure sign to positive, thus marginally
favoring imbibition and consequently insignificantly recovering oil by the aid of fluid densities difference
as gravity forces inside the modified Amott cell.
In summary, the proposed set of correlated experiments used in this investigation allows us to evaluate in
the laboratory the impact of surfactant imbibition and adsorption on improving oil recovery in the Wolfcamp
and Eagle ford unconventional reservoirs. This study evaluated rock-fluid and fluid-fluid interactions of
aqueous solution, with and without surfactants, and their impact on imbibition and oil recovery. The results
showed that wettability was altered and IFT was moderately reduced when chemical additives are used in
completion fluid. These wettability and IFT alterations changed capillary forces favoring water imbibition
and oil explosion from ULR cores. In addition, these set of experiments give us the necessary parameters
to be used in numerical simulation to model laboratory results and upscale these findings to the field as
shown in the next section.
Numerical Modeling of Experimental Results
With all the data gathered from the correlated set of experiments showed previously, a numerical simulation
to model the process of surfactant imbibition was created. The goal of the numerical modelling is to provide
an estimation for oil recovery aided by fluid imbibition when using aqueous solutions with and without
surfactants on a field-scale application. Upscaling was done by implementing the capillary pressure curve
built from history-matching our laboratory data to a mechanistic field-scale model. Spontaneous imbibition
results from Eagle Ford core 10 (water) and core 9 (cationic surfactant) were used on the numerical
simulation. The objective is to compare oil productions from a core without chemical additives (core 10) to
create a baseline and a core submerged in surfactants to assess improved oil recovery by imbibition. Since the
cationic surfactant was observed to give the best performance in producing oil on the Eagle Ford formation
(Fig. 7), the numerical modelling was done on upscaling these results, along with the water without additive
results, to the field-scale.
The core grid model was built using CT scan based rock digitalization method to ensure the incorporation
of core heterogeneities into the model. As shown in Fig. 8 and Fig. 9, ULR cores are highly heterogeneous,
thus, in order to guarantee the validity of the rock grids, rock digitalization from CT scan images was
considered. From Table 3, Eagle Ford cores 9 (cationic surfactant) and 10 (water) were used on the numerical
simulation. To that end, Fig. 10 shows the comparison of the grid model and the CT scan 3D reconstruction
images for core 10 and core 9. Moreover, Fig. 10 shows marked heterogeneity in both cores, emphasizing
the need of building the numerical simulation with the original cores used on the laboratory. By employing
CT scan technology, we successfully captured core heterogeneities in the grid model. The color on the grid
model represents porosity whereas the color on the CT scan image represents the CT number, which is
linearly related to density. Therefore, the inverted relation between density and porosity causes the color
difference between the grid and the CT image (Eq. 4 and Eq. 5). As shown on the color-scale, darker color
on the CT scan image shows lower density, which means a higher porosity, represented by brighter color
on the grid model.
Figure 10—Grid models and CT scan images for the Eagle Ford core 10 (left) and for core 9 (right).
Next, history-matching for the laboratory result was done in two steps. First, to obtain the original
unaltered capillary pressure curve core 10 was used. Then, we used core 9 to obtain the cationic surfactant
altered capillary pressure curve. Capillary pressure curve endpoints on both cases were calculated from the
measured IFT and contact angle of Eagle Ford oil and rock samples using water and the cationic surfactant,
as shown in Table 3 and Table 4. Thus, the history-match method was only used to build the curvature of
the capillary pressure profile throughout the saturation change. Fig. 11 shows the best-matched capillary
pressure curve and oil production curve from our laboratory experiment and numerical simulation. As
expected, higher positive capillary pressures were evidenced when the cationic surfactant was used. Another
prominent comparison of the two curves is the intersection point at capillary pressure equal to zero, which for
the cationic surfactant is further to the right compared to the unaltered capillary pressure curve. We believe
that this difference is the manifestation of wettability alteration in our numerical model, and we predict
that stronger wettability alteration would move the intersection further to the right and weaker alteration
would move the intersection to the left. Moreover, production curve of both cases showed a good agreement
between numerical simulation and laboratory result with some difference in the middle part of the curve.
We believe that these differences are due to immeasurable amount of oil stuck onto the core walls that was
released in later times of the experiments by gravity forces.
Figure 11—Capillary pressure curves for Eagle Ford water and cationic surfactant (left) and simulation
and spontaneous imbibition experiment result for Eagle Ford water and cationic surfactant (right).
Next, with the capillary pressure curve successfully constructed from the core-scale simulation, we
applied the same modelling mechanism to the field-scale model. The mechanistic model used properties
collected from the general average properties that are commonly observed on the Eagle Ford. To save
running time, the mechanistic model consists of only one stage of hydraulic fracture and the result will be
multiplied by twenty assuming the well was completed with twenty stages. The dimension, configuration
and main properties of the model are on Fig. 12.
Figure 12—Mechanistic model schematic and field-scale model properties.
The results of the field-scale simulation are shown in Fig. 13. Well performance using completion fluids
with and without cationic surfactant was simulated. The results showed that adding the cationic surfactant
to the frac fluid had a positive impact on oil rate and cumulative oil production of the well. In fact, the
cationic surfactant increased the peak oil rate of the well by 24% resulting in 8% addition of cumulative
oil recovery for a three years production period.
Figure 13—Comparison of oil cumulative and rate of production of well completed with and without cationic surfactant.
By examining the change in oil saturation distribution during the whole simulation runtime, we noticed
that the mechanism of production enhancement is consistent with what we observed in the laboratory
experiment, imbibition of water coexisting with oil expulsion. However, this process mostly occurred during
the shut-in period. At this stage, an exchange of oil and water occurred where the reservoir matrix took
water and oil was expelled out to the fracture system. After the shut-in period was finished, this mechanism
was overshadowed by the pressure drainage activity of the well. Therefore, although that 24% increment
in peak oil rate and 8% addition of three years cumulative oil production is comparatively significant on
this ultra-tight reservoir, we believe that additional increment is possible on a longer shut-in time. A more
insightful study on the effect of shut-in time and different operating condition will be covered on a future
work. Nevertheless, the result of the field-scale numerical simulation in this work proved our hypothesis
that by modifying the capillary state of the oil, water, rock system in a ULR by altering wettability and
moderately reducing IFT with chemical additives, an improvement of oil recovery can be achieved.
The results from this work have practical implications on the design of stimulating fluids to improve
oil recovery in ULR. Thus, completion fluid additives should be carefully selected while taking into
consideration surfactant, oil and rock type. These considerations can reduce completion costs and improve
oil recovery after flowback as compared to adding an unknown chemical that may not effectively
promote imbibition into the rock. Moreover, experimental and simulation results showed that soaking and
flowback schedules may be beneficial when using surfactants. Lastly, field-testing is recommended to
reproduce laboratory and simulation results. However, laboratory and field results may differ due to ULR
heterogeneities, rock lithologies and fluids proportions. Nevertheless, the comprehensive correlated set
of experiments and results reported in this study can serve as a prescreening tool as the beginning of a
successful field trial. However, we must emphasize that these wettability studies encompass a tiny fraction
of the heterogeneity that truly exists in the field. Subtle improvements in petrophysical properties from one
core sample to the next may significantly enhance or reduce imbibition rate relative to other tests. Therefore,
instead of observing a chemical phenomenon, we may simply be lucky on the petrophysical properties of
one sample to the next. The unfortunate fact of not being able to measure standard values like permeability
will always limit the efficacy of these tests. However, creation of new techniques like the ones described
in this manuscript and given enough benchmarking from different wettability scenarios will doubtless lead
to providing useful methods for industry to screen various chemicals additives in the near future. In this
paper, we have concluded:
Original wettability, measured by CA methods, for the Wolfcamp and Eagle Ford cores showed
intermediate to oil-wet affinity due to ULR mixture of oil-wet organic pores and water-wet
inorganic pores.
All surfactants tested, at concentrations on 2 gpt, altered the wettability of the shale samples from
intermediate and oil-wet to water-wet, but wettability alteration strongly depended on rock mineral
composition and surfactant type.
Consistent with wettability measurements by CA, zeta potential results showed lower double layer
stability for rock in contact with aqueous solutions without surfactants. Conversely, more stable
water films on rock surface, and consequently more water-wetness, were evidenced in aqueous
solution with surfactants.
All surfactants added to completion fluids moderately reduced IFT. Anionic surfactants decreased
IFT further than cationic surfactants.
The relation between rock mineralogy and surfactant charges determines surfactant adsorption
on the rock. This information is crucial in determining the selection of the additive on different
reservoir. The cationic surfactant was found to be adsorbed the most compared to other chemicals
tested on both Eagle Ford and Wolfcamp rock samples.
Spontaneous imbibition results showed higher imbibition and improved oil recoveries for cores
submerged in surfactants compared to water alone. This better performance was achieved by
wettability and IFT alteration, which changed capillary forces to favoring water imbibition and
releasing trapped hydrocarbons in the rock pores. Spontaneous imbibition using surfactants occurs
on impressively rapid time scales despite immeasurable permeability.
Changes in wettability and IFT reductions induced by surfactants in completion fluids improve
matrix penetration favoring imbibition and increasing oil recovery from the Wolfcamp and Eagle
Ford ULR.
In spontaneous imbibition experiments, the majority of the oil produced by imbibition was within
3-5 days from the start of experiments. This suggest the possibility of designing and optimizing
treatment duration and flowback schedules.
Upscaling using numerical simulation provides an insight on the field-scale impact of the surfactant
imbibition method. Incorporating surfactant into the stimulation fluid was found to be beneficial
as shown by the increment of both initial peak oil production rate and 3-year cumulative oil
The results from this study give valuable insights on designing a chemically compatible and better
performing stimulating fluid at affordable costs, which can recover additional oil in unconventional
liquid reservoirs.
The authors would like to thank the Department of Petroleum Engineering, Texas Engineering Experimental
Station (TEES), and Crisman Institute for Petroleum Research at Texas A&M University for funding this
work. Also Rodolfo Marquez, John Maldonado and Don Coleen for their collaboration on the experimental
cm =
cm3 =
CT =
CTinitial =
CTfinal =
ft =
HU =
gpt =
gr =
mV =
mm =
mN/m =
Nm =
ϕm =
ϕf =
Pi =
Swi =
μD =
km =
kf =
khf, int =
khf, mod =
mg/g =
mg/L =
μm =
xf =
wf =
wf, mod =
Cubic centimeter
Computer tomography
Average CT number of the core before spontaneous imbibition experiments
Average CT number of the at the end of spontaneous imbibition experiments
Hounsfield unit
Gallons per thousand gallons
Millinewton per meter
Matrix porosity
Fracture porosity
Initial reservoir pressure
Initial water saturation
Micro Darcie
Matrix permeability
Fracture permeability
Hydraulic fracture intrinsic permeability
Hydraulic fracture modeled permeability
Milligrams per grams
Milligrams per liter
Unconventional liquid reservoir
Hydraulic fracture half-length
Hydraulic fracture intrinsic width
Hydraulic fracture modeled width
° = degrees
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