Determination of rock core wettability by NMR

Technical Paper

Introduction
One of the most important parameters in predicting the output of an oil reservoir is wettability. This parameter can vastly affectthe ease with which the reservoir can be produced; but despite its importance, there are very few methods for getting an accurate
wettability measurement. In this technical paper, a new method for measuring wettability using NMR is presented.
Wettability can be thought of as the tendency of a surface to maintain contact with a fluid. Inside the pores of a rock, this tendencyof the surface can favor either water or oil adherence to the surface of the pores. Quantitatively this can be defined as [1],Aw – AoIw =Aw + Ao[1]

where Iw is the wettability index, Aw is the surface area wetted by water and Ao is the surface area wetted by oil. From theequation it is obvious that if more surface area is wetted by water then Iw = 1 to 0 and the rock is said to be water wet.
Conversely, if there is more surface area wetted by oil then Iw = 0 to -1 and the rock is said to be oil wet. Wettability is a
crucial petrophysical parameter for determining accurate production rates in oil and gas reservoirs. However, industry standard
wettability measurements (Amott Test and USBM) are expensive and time consuming.
It is known that NMR response varies as a function of wettability change in rock core plug samples [1-5]. This information wasused to develop an NMR wettability index (NWI) based on T2 distributions [6,7]. This NWI
is also capable of measuring changes in wettability as a function of oil/water saturations
unlike traditional methods which are based on measurements at Swi and Sor only. Inaddition, these oil/water saturations are determined without the aid of any special oil orbrine, such as D2O. This allows the NMR method to nondestructively monitor changes inwettability in real time (i.e. during a flooding experiment or an aging procedure).
In order to derive this NWI based on T2 distributions, the NMR T2 spectra of 100% brine
saturated, 100% oil saturated, bulk oil and bulk brine are needed. Thesespectra are then mixed to give a predicted T2 spectrum which is compared (viaa least squares fit) to a T2 spectrum recorded from a sample partially saturated
with both water and oil and whose wettability is to be determined. In thisapplication note, we present a new method which couples this T2-based NWI
to spatially resolved T2 NMR measurements to monitor changes in wettability
and saturation along rock core plugs.

Determination of rock core wettability by NMR

MethodTo determine the spatially resolved NWI of a sample whose wettability is unknown, the following procedure was followed.
1. Record T2 and spatial-T2 spectra of the mixed saturation (i.e. brine/oil) sample whose wettability is to be determined. Forexample, an “as received” sample or one which was saturated in the lab with both oil and brine.
2. Clean and dry the sample. Saturate the sample to 100% with brine. Record the T2 and spatial-T2 spectra of the 100%water saturated sample (Sw-100%).
3. Clean and dry the sample. Saturate the sample to 100% with oil of interest. Record the T2 and spatial-T2 spectra of the100% oil saturated sample (So-100%).
4. Record the T2 spectra of bulk brine and oil (Sw-bulk and So-bulk).
For this work, a sample of mixed saturation and unknown wettability was created by first saturating a sandstone to 100% watersaturation. The Sw-100% sample was then centrifuged for approximately 12 hours surrounded by dodecane. This resulted in asample of mixed saturation (Smix) and spinning the same sample at different speeds resulted in samples of differing dodecane/brine saturations. All NMR measurements were completed on an Oxford Instruments GeoSpec 2+-75 rock core analyser [8].
Acquisition and processing of the NMR data was achieved via Green Imaging Technologies software, GIT Systems Advanced [9].

Data Analysis
Figure 1 shows the 100% oil saturated (orange trace), 100% brine saturated (blue trace), bulk brine (red trace) and bulk
dodecane (green trace) T2 distributions for the sandstone sample analysed in this work. Also shown in Figure 1 is the T2
distribution of the sample of mixed saturation and unknown wettability (brown trace).
The predicted T2 distribution (Figure 1 – black trace) is generated by varying the contributions from the 100% oil saturated,
100% brine saturated, bulk brine and bulk dodecane T2 distributions via the following equation:

Spred = WHSw–100% + (1–W)(1–H)So–100%+(1–W)HSw–bulk +W(1–H)So–bulk[2]

The contributions from each T2 distribution are controlled by the H and W functions. The typical forms of these equations
are plotted as the light blue (H) and pink lines (W) in Figure 1. These functions are like step functions, where, for example, allpores to the left of the inflection point of the W function are wetted by water and all the pores to the right of the inflection
point of the W function are wetted by dodecane. Conversely all the pores to the left of the inflection point of the H function
are occupied by brine and all the pores to the right of the inflection point of the H function are occupied by dodecane. In aleast-squares fit, the position of these functions is allowed to vary (left and right on the T2 axis) until there is good agreement
between the predicted and measured T2 distributions of the sample of mixed saturation and unknown wettability. Figure 2
shows the contributions to the final predicted T2 distribution (Figure 1) from the Sw-bulk, So-bulk, Sw-100% and So-100% T2 distributions.
Once the final H and W functions are known they are used to generate the predicted saturation and wettability index for theTechnical Paper

sample of mixed oil/brine saturation. For the data shown in Figure 1 and 2, this corresponds to a water saturation of 13% andwettability index equal to 0.89 (water wet). The data analysis was initially done in Matlab but was later implemented into Green
Imaging Technologies software [9].

Figure 1: Typical bulk-T2 spectra usedfor wettability determination. The brown
T2 spectrum is recorded from the mixedwettability sample whose wettability
is to be determined. The 100% brine
saturated (blue), 100% dodecane
saturated (orange), bulk dodecane(green) and bulk brine spectra (red) arethen combined to give the predicted T2
distribution (black). The combination
is done via use of the water (light blue)
and wettability fraction functions (pink).

Figure 2: Bulk T2 spectrum (black)predicted from wettability fitting alongwith the measured bulk T2 spectrum(brown) are shown. Also shown are thecontributions to the predicted spectrum
from the bulk dodecane (green), 100%
dodecane saturated (orange) and 100%brine saturated (blue) spectra are also
shown. The water fraction (light blue)
and wettability fraction (pink) are also
shown.

Determination of rock core wettability by NMR

Data Analysis continued
The previous explanation of the wettability analysis was for bulk T2 distributions which cover the entire length of the rock but
this explanation applies also to the spatial-T2 wettability analysis. The spatial analysis proceeds in the same manner as the bulk
analysis but the 100% oil saturated, 100% brine saturated, and mixed saturation T2 distributions are for a given slice of therock. Figure 3 shows a typical stack plot for a Smix spatial-T2 distribution along with an intensity plot (Figure 3-inset) generated
from the same data. For example, the least-squares fit is then performed, minimising the difference between Smix (slice 1) – Spredusing Equation 2 to generate Spred where Sw-100% and So-100% are now from the first slice of their spatial-T2 distributions. The leastsquares fit will result in H and W functions for slice 1. Wettability and saturation for the first slice are then derived for that slice
from these H and W functions. This procedure is repeated until each slice of the spatial-T2 distributions has been analysed and Iw
and saturations as a function of position in the rock have been created.

Figure 3: Spatial-T2 spectra for the same sample as the bulk spectra in Figure 1. The inset shows the intensity plot generated
from the spatial-T2 data. The intensity plot is a top view of the spatial-T2 data where the intensity of each pixel corresponds tothe magnitude of the T2 distribution at that position in the rock.

Technical Paper

Results
Figure 4 shows the spatial-T2 wettability analysis completed on the sandstone sample. The upper plots show the spatiallydependent wettability (blue traces) and saturation (red traces) profiles derived for each centrifuge speed tested. The rocks
began at 100% brine saturated and had dodecane spun into them from left to right on the upper plots of Figure 4. Also shownin the upper panels of Figure 4 are the saturation profiles (black traces) derived from separate measurements where the rock was
initially saturated to 100% with D2O rather than H2O before having dodecane spun into them. Employing NMR invisible D2O
allowed the saturation profiles to be derived directly from the NMR data. It should also be noted that because D2O is denser
then H2O, the centrifuge speeds were reduced to match the capillary pressures employed with H2O. These D2O profiles werecontinued overleaf

Figure 4: The predicted wettability (blue) and saturation (red) profiles for rock 109S are plotted in the upper panels. Samplesof differing saturations were manufactured by spinning dodecane into 100% brine saturated samples at differing centrifuge
speeds (800, 3000 and 7500 RPM). The dodecane entered the rock from left to right as observed on the upper plots. The black
trace corresponds to the saturation profiles measured using the same samples initially saturated with D2O in lieu of H2O. The
lower panels show the intensity plots generated from the spatial-T2 data from the mixed saturation samples.

Determination of rock core wettability by NMR

Results continued
then used to independently verify the accuracy of the profiles derived from the wettability fitting. There is no similar method
for verifying the wettability as a function of position. The lower panels of Figure 4 show the intensity plots created from thespatial-T2 data for the mixed saturation samples tested at each centrifuge speed.
For 800 RPM, the saturation profile derived from wettability fitting agrees well with that measured using D2O. There is clearly asaturation gradient along the length of the rock. The average saturation for the rock is 0.71. The wettability on the other handdoes not show the same variability with position. It is relatively constant across the rock independent of both position and water
saturation. The average wettability across the rock is 0.73 making the rock water wet. For 3000 RPM, the saturation acrossthe rock is now relatively uniform and significantly reduced as compared to 800 RPM. The average saturation is now 0.11 andthe average wettability is now 0.82. D2O data was not recorded at 3000 RPM so there is no comparison between the predicted
and measured saturation profiles. For 7500 RPM, the saturation and wettability are again uniform along the rock. The average
saturation is now 0.06 and the saturation profile agrees well with the corresponding D2O saturation profile. The average
wettability is now 0.73. Both the saturation and wettability have decreased only slightly as compared to 3000 RPM.
While no other technique exists for measuring wettability as a function of position, the average wettability derived from thespatial-T2 data can be compared with wettability determined from other methods such as the Fleury NMR method [1] and an
Amott test. These comparisons were completed for the sandstone sample and the results are summarised in Table 1. For thesake of this comparison, the 7500 RPM data was used. While there is no reason to think the absolute value for the wettabilities
derived from each method summarised in Table 1 should be equal, there should still be consistency in the wettability predicted
for each rock. This is true for the data summarised in Table 1 where each method indicates that each rock is water wet.

Wettability Technique
Average wettability from Spatial-T2 (thiswork – 7500 RPM)

Wettability
0.73

Fleury NMR Method

0.43

Amott Test

0.21

Table 1: Wettability ComparisonsTechnical PaperConclusion
A new method for determining the wettability as a function of
position in a core sample has been presented. This method couples
the wettability determination via NMR T2 distributions method firstpresented by Looyestijn et al. [6,7] with spatial-T2 data. Using thismethod, we have successfully determined the wettability as a functionof position for a sandstone sample with mixed oil/water saturations.
This new measurement opens a new range of wettability-based
experiments, including the ability to track wettability during a flooding
experiment, as well as measuring wettability at different saturation levels
during one measurement from one sample.
Signal intensive measurements such as the spatial T2 measurement used here
have been impractical on previous generations of NMR instruments due to longmeasuring times. Advancements in instrument design and performance, such as thosefound on the GeoSpec+ product line, now make these measurements possible.

References
1. Fleury, M. and Deflandre, F., “Quantitative evaluation of porous media wettability using NMR relaxometry”, Magnetic
Resonance Imaging (2003), 21, 385-387.
2. Howard, J.J., “Quantitative estimates of porous media wettability from proton NMR measurements”, MagneticResonance Imaging (1998), 16, 529-533.
3. Borgia, G. C., Fantazzini, P. and Mesini, E., “Wettability effects on oil-water configurations in porous media, a nuclear
magnetic resonance relaxation study”, J. Appl. Phys., 70, 7623-7625.
4. Hsu, W. F. and Flumerfelt, R. W., “Wettability of porous media by NMR relaxation methods”, SPE Annual TechnicalConference and Exhibition, Washington, D.C., USA, 4-7 October 1992.
5. Freedman, R., Heaton, N., Flaum, M., Hirasaki, G. J., Flaum, C. and Hurlimann, M., “Wettability, saturation and viscosity
from NMR measurements”, SPEJ, 8, 317-327.
6. Looyestijn, W.J. and Hofman, J.P., “Wettability Index Determination by Nuclear Magnetic Resonance”, SPE 93624,
presented at the MEOS, Bahrain, March 2005. Published in SPEREE April 2006, pp 146 – 153.
7. Looyestijn, W., Zhang, X., and Hebing, A., “How can NMR assess the wettability of a chalk reservori”, Society of Core
Analysts, Vienna, Austria, 27 August-1 September 2017.
8. Geo-Spec 2-75 User Manual, Version 1.8,
Oxford Instruments.
9. GIT Systems and LithoMetrix User Manual,
Revision 1.9, Green Imaging Technologies.

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