American Oil and Gas Reporter - January 2016 - 62

FIGURE 1

Permeability

Permeability and Flow Network

2

6

8
10
Porosity (%)

12

14

16

18

SEM Image from Pommer 2014
Normalized Porosity Distributions (n=100)

Ro = ~1.0%

16
14

60

12

6

7

content averages 5-6 percent, and porosity
averages 10-12 percent. In the bioclastic
marl facies, TOC averages 2-3 percent
and porosity averages 8-10 percent. This
suggests different pore networks in each
facies.
In the non-reservoir facies, higher clay
or carbonate content dilutes TOC and/or
destroys porosity. These facies are chalks,
recrystalized limestones, bioturbated marls,
and clayey mudstones. In the case of the
bioturbated marl, TOC is more likely to
be lower or nonproductive. The clayey
mudstone, which is most likely prodelta
in origin, does not have suitable mechanical properties to be a reservoir.
The different facies have variable pore
networks, but porosity and permeability
follow a trend in the GRI (crushed core)
data used in the study. Facies that are
dominantly carbonate with a moderate
amount of clay (approximately 10-30
percent) maintained their pore networks
more reliably. Facies with less clay were
often calcite-cemented. Facies with more
than 40 percent clay also had poorer
reservoir quality. Figure 1 shows plots of
these properties.
In addition, scanning electron microscopy (SEM) analysis demonstrates
that both interparticle and organic pores
are significant in the Eagle Ford. The
SEM image of a broken core chip in the
upper right of Figure 1 shows that at the
nanoscale level, the grains have largely
intact depositional fabric holding porosity
and permeability pathways open. Additional modeling and reservoir observations
have failed to show that the Lower Eagle
Ford is fractured in much of the region
apart from specific structural settings.
Therefore, it is concluded that the Eagle
Ford produces largely from matrix permeability and porosity rather than fracture
porosity.
62 THE AMERICAN OIL & GAS REPORTER

Bioturbated
Marl

0
6

5

8
810
10
-1
2
12
-1
4
14
-1
6
16
-1
8

3
4
TOC (wt%)

4

2

Organic Marl

10

6-

1

20

30

Bioclastic
Marl

4-

0

Recrystallized
Limestone

2-

Bioclastic Marl
Bioturbated Marl
Chalk
Clayey Mudstone
Organic Marl
Recrystallized Limestone

4

Frequency

6

40

2

8

2

Chalk

50

10

0-

Porosity (ft)

4

Bioclastic Marl
Bioturbated Marl
Chalk
Clayey Mudstone
Organic Marl
Recrystallized Limestone

surfaces with abundant accumulations of
phosphate, foraminifera, or a marked increase in bioturbation.
Numerous other possible tops are present, but many of these are deemed to be
locally variable, inconsistent, or diagenetic
in origin. All the key tops were tied to
well logs and correlated across the model
area Figure 2. After correlation, the stratigraphic architecture is supported by differences in petrophysical property trends
such as porosity, water saturation, and
clay volume.

Clayey
Mudstone

Maturity And Stratigraphy
For OOIP volumes from static earth
models and dynamic reservoir simulations,
maturity is the primary driver for hydrocarbon fluid properties across the Eagle
Ford trend. Based on pyrolysis and vitrinite
reflectance data from core, pressure-volume-temperature (PVT), and production
data, maturity maps show a northwestto-southeast progression of hydrocarbon
fluid properties from black oil (updip) to
dry gas (downdip).
Correlations in the Eagle Ford are
based on both core and logs. Six tops are
carried across the core data: the top of
the Upper Eagle Ford Marl, the top of
the Upper Eagle Ford Shale, the top of
the Lower Eagle Ford, an internal top in
the Lower Eagle Ford, the top of the
Pepper/Maness Shale, and the top of the
Buda. The tops are commonly flooding

Petrophysical Model
The Eagle Ford petrophysical model
was developed using core data from wells
in the area. The primary objective was to
utilize a minimum "triple combo" wireline
log dataset consisting of gamma ray, resistivity, neutron, density, and photoelectric
(PE) absorption to compute mineral and
fluid volumes. Mineralogy, TOC, water
saturation, and porosity were calibrated
to core.
Understanding the solids was the first
step in developing the model. This was
challenging because barite in the mud
and other complications affected PE measurement. First, clay volume was calibrated
to core using a weighted average of the
difference between neutron and density
porosity and deep resistivity. Second,
TOC was determined using a modified
Schmoker equation (a function of bulk
density). Finally, these core-calibrated
inputs were used to develop a synthetic
PE curve to derive the carbonate, siliciclastic, and pyrite components.
Porosity calibration was a challenge
because core bulk density (RHOB) measurements were lighter than log RHOB
measurements. This may be because fluid

FIGURE 2
Stratigraphic Cross-Section Oriented along Strike Between
Karnes and Lavaca Counties (Flattened on Buda)

A

Anacacho
Austin
Chalk
UEGFD Marl
UEGFD Sh
LEGFD
LEGFD 2
Pepper Sh
Buda

A'



American Oil and Gas Reporter - January 2016

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