Ogiesoba and Eastwood-libre

Seismic multiattribute analysis for shale gas/oil within the AustinChalk and Eagle Ford Shale in a submarine volcanic terrain,Maverick Basin, South Texas

Osareni C. Ogiesoba1 and Ray Eastwood1

Abstract

We conducted seismic multiattribute analysis by combining seismic data with wireline logs to determine

hydrocarbon sweet spots and predict resistivity distribution (using the deep induction log) within the Austin

Chalk and Eagle Ford Shale in South Texas. Our investigations found that hydrocarbon sweet spots are char-

acterized by high resistivity, high total organic carbon (TOC), high acoustic impedance (i.e., high brittleness),

and low bulk volume water (BVW), suggesting that a combination of these log properties is required to identify

sweet spots. Although the lower Austin Chalk and upper and lower Eagle Ford Shale intervals constitute hydro-

carbon-sweet-spot zones, resistivity values and TOC concentrations are not evenly distributed; thus, the rock

intervals are not productive everywhere. Most productive zones within the lower Austin Chalk are associated

with Eagle Ford Shale vertical-subvertical en echelon faults, suggesting hydrocarbon migration from the Eagle

Ford Shale. Although the quality factor (Q) was not one of the primary attributes for predicting resistivity, it

nevertheless can serve as a good reconnaissance tool for predicting resistivity, brittleness, and BVW-saturated

zones. In addition, local hydrocarbon accumulations within the Austin Chalk may be related to Austin TOC-rich

zones or to migration from the Eagle Ford Shale through fractures. Some wells have high water production

because the water-bearing middle Austin Chalk on the downthrown side of Eagle Ford Shale regional faults

constitutes a large section of the horizontal well, as evidenced by the Q attribute. Furthermore, the lower Austin

Chalk and upper Eagle Ford Shale together appear to constitute a continuous (unconventional) hydrocarbon

play.

IntroductionHydrocarbon exploration in the Austin Chalk began

when Udden and Bybee (1916) first described hydrocar-

bon traps located in and around volcanic centers (ser-

pentine plugs) encased by the formation (Ewing and

Caran, 1982). Owing to the occurrence of hydrocarbons

in and around these serpentine plugs, exploration was

focused on locating outcrops of volcanic centers using

geological mapping methods. Later, seismic and mag-

netic methods were employed to search for buried vol-

canic plugs. As years went by, more than 200 volcanic

centers within the formation were found (Ewing and

Caran, 1982). However, not every volcanic mound held

hydrocarbons. Hydrocarbons within the Austin Chalk

lie not only around volcanic plugs but also in fracture

zones within the formation itself. With the realization of

the existence of a fault-related fractured reservoir

within the formation in the 1980s, operators made fault

zones the main target of exploration and the drilling

spree started, ignited by the newly developed horizontal

drilling technology involving several lateral wells

(Durham, 2012). Although some successes were re-

corded, most of these wells failed they were either

uneconomic producers or dry holes. The failure of these

wells is due to the lack of understanding of the litho-

logic variations within the Austin Chalk, lack of aware-

ness of the important connection between fractures and

hydrocarbon source rocks, and unknown hydrocarbon

source-rock distribution within and outside the forma-

tion. Because of these and other factors, operators were

unable to locate hydrocarbon sweet spots, and the Aus-

tin Chalk continued to disappoint oil prospectors.

Several authors have discussed the importance of

source-rock distribution within the Austin Chalk. For

example, Grabowski (1981) discusses the source-rock

potential of the formation. The author notes that the

Austin Chalk contains 0.5% to 3.5% total organic carbon

(TOC), the richer part lying at depths exceeding 5000 ft

(1524 m) and the peak of hydrocarbon generation at

depths between 6000 and 8000 ft (1828 and 2438 m).

1The University of Texas at Austin, Jackson School of Geosciences, Bureau of Economic Geology, Austin, Texas, USA. E-mail: osareni.ogiesoba@

beg.utexas.edu; [email protected].

Manuscript received by the Editor 26 February 2013; revised manuscript received 8 July 2013; published online 24 October 2013. This paper

appears in Interpretation, Vol. 1, No. 2 (November 2013); p. SB61SB83, 24 FIGS., 6 TABLES.

http://dx.doi.org/10.1190/INT-2013-0019.1. 2013 Society of Exploration Geophysicists and American Association of Petroleum Geologists. All rights reserved.

t

Special section: Interpretation for unconventional resources

Interpretation / November 2013 SB61Interpretation / November 2013 SB61

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On the basis of extractable organic matter and TOC

from core analysis, Hinds and Berg (1990) classify

source-rock maturity in the Austin Chalk into three

zones immature, accumulation, and mature zones.

According to these authors, the immature zone lies at

depths less than 6000 ft (1828 m) and contains nocommercial hydrocarbons. The zone of accumulation

lies at depths between 6000 and 7000 ft (1828 and2134 m) and is an interval of hydrocarbon generation

and accumulation containing a commercial quantity

of hydrocarbons. The mature zone is at depths exceed-

ing 7000 ft (2134 m). In this zone, hydrocarbons aregenerated but expelled from the rock matrix into adja-

cent fractures. This zone, therefore, indicates a level of

potential oil production (Hinds and Berg, 1990). How-

ever, the oil found within the Austin Chalk may have

had some contributions involving migration through

fault zones from the underlying Eagle Ford Shale, which

is rich in TOC (Grabowski, 1981; Hinds and Berg, 1990;

Dawson et al., 1995). In a formation such as the Austin

Chalk, knowing only the vertical distribution of TOC-

prone zones is not enough. Knowledge of the lateral dis-

tribution of high-TOC zones is a critical factor in success-

ful exploration for hydrocarbons within the formation.

Kuich (1989), working with seismic data, notes the

key role fracture zones play in hydrocarbon production

within the Austin Chalk. He describes how to identify

fracture zones on the basis of pertinent seismic attrib-

utes (e.g., low frequencies, low amplitudes, etc.) asso-

ciated with the zones and notes the existence of major

and minor faults within the formation. Whereas minor

faults are abundant within the formation, major faults

involve older (Eagle Ford Shale) and younger (Austin

Chalk) formations (Kuich, 1989). Although these frac-

ture zones became the targets of horizontal drilling,

most of these wells involving minor fractures within

the Austin Chalk were not successful. These wells failed

because they were located in high-water-bearing zones

instead of within the hydrocarbon sweet spots. In this

paper, we combined petrophysical data from wireline

logs with seismic attributes and used multiattribute

analysis to identify the hydrocarbon sweet spots.

Geologic backgroundCovering a distance of 806 mi (1300 km) across

southeast Texas (Figure 1), the Austin Chalk is cut

by several northeastsouthwest-trending en echelon

faults (Weeks, 1945; Hanna, 1953; Reaser and Collins,

1988; Ewing and Lopez, 1991; Dawson et al., 1995)

and has an estimated four billion barrels of oil in place

(Galloway et al., 1983). In the East Texas Basin, the for-

mation is bounded at the top by the Santonian-Campa-

nian unconformity, with the Taylor Group sitting on top

of the Austin Chalk. In South Texas, it is bounded by the

Austin-Anacacho or Austin-Upson contact, also of San-

tonian-Campanian age (Figure 2). The Austin Chalk,

which is of Late Cretaceous age, was deposited with in-

terbedded volcanic ash (marl) in shallow-marine water

depths between 30 and 300 ft (9 and 90 m) (Pearson,2010; Martin et al., 2011). The formation covers an area

of about four million acres in South Texas, its thickness

ranging from 150 to 800 ft (46 to 244 m), and isdivisible into three lithostratigraphic units the

upper, middle, and lower Austin Chalk (Dawson and

Reaser, 1996; Martin et al., 2011). The upper and lower

Austin Chalk are composed of alternately bedded chalk

and marl and constitute a resistant bench, whereas the

middle Austin Chalk consists mainly of marl (Dawson

and Reaser, 1996). Underlying the Austin Chalk is the

Eagle Ford Shale of Turonian age. It is separated from

the Austin Chalk by the Turonian-Coniacian (Eagle

FordAustin) disconformity (Grabowski, 1981; Ewing

and Caran, 1982; Reaser and Collins, 1988; Dawson

and Reaser, 1996) (Figure 2). The Eagle FordAustin

and Austin-Taylor contacts are disconformities that

exhibit characteristics typical of condensed sections

surfaces are bioturbated and contain phosphatic

nodules and fossils (Dawson and Reaser, 1996). The Ea-

gle Ford Shale, like the Austin Chalk, is divisible into

lithostratigraphic units the upper and lower Eagle

Ford Shale, both of which are rich in fossils (Martin

et al., 2011). Whereas the lower Eagle Ford Shale is

richer in shale content, the upper Eagle Ford Shale is

richer in carbonate materials to such an extent that

the boundary between the Austin Chalk and the Eagle

Ford Shale is not easily discernible in some areas. The

Eagle FordAustin contact is therefore regarded as a

paraunconformity an omission surface involving

relatively minor erosion (Ewing and Caran, 1982; Daw-

son and Reaser, 1996). Because of the uncertainty in

placing the Eagle FordAustin contact, the highly fos-

siliferous and carbonate-rich upper Eagle Ford Shale

is sometimes grouped with the lower Austin Chalk.

In terms of reservoir characteristics, the Austin

Chalk can be regarded as a low-porosity, low-per-

meability reservoir having a dual pore system that

is, microporous matrix and fractures (Dawson et al.,

1995). Matrix porosity within the Austin Chalk is gener-

ally low, with an average of 4% (Stapp, 1977; Hindsand Berg, 1990); however, it can be as high as 6% in

some localities, such as Giddings field (Kuich, 1989).

Reported average permeability ranges from 0.02 to

1.27 md (Martin et al., 2011). Although matrix per-

meability is low, it can be enhanced locally by tectonic

fracturing to values as high as 2000 md (Snyder and

Craft, 1977).

Database and methodologyOur database is composed of 3D seismic data cover-

ing an area of 437 mi2 (1132 km2), having a stacking-bin size of 33 33 m and a sampling interval duringacquisition of 2 ms. Well data consist of nine wells hav-

ing requisite log suites: gamma-ray, sonic, density, resis-

tivity (deep induction), neutron porosity, density

porosity, etc. The first step in our procedure was to

implement a poststack seismic filtering process to

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attenuate random noise by applying the 3D trace-mix

technique to the seismic data (Figure 3).

Seismic filtering was followed by petrophysical analy-

sis from which we computed TOC, Vclay, and other nec-

essary log curves. The filtered seismic data were later

integrated with wireline logs via a synthetic seismogram

followed by mapping of key stratigraphic surfaces.

Resultant maps, together with well log data, were used

to perform model-based acoustic-impedance (AI) inver-

sion to identify zones of high acoustic impedance (zones

of high brittleness) and predict pertinent rock properties

such as porosity, Vclay, TOC, and bulk volume water

(BVW), using seismic attributes. These rock properties

were then used as external attributes, together with

other trace attributes, to perform seismic multiattribute

analysis to predict resistivity. Because this paper is about

resistivity prediction, and also because the method used

in generating the external attributes is the same as that

employed in generating the resistivity volume, details of

prediction of external attributes are not discussed except

for AI results. However, results from these volumes are

presented to buttress the outcomes from AI and resistiv-

ity volumes. The objective of our approach is to identify

the brittle hydrocarbon-rich layers inwhich to place hori-

zontal wells for optimal hydrocarbon recovery.

ResultsPoststack filtering

Although ideally seismic multiattribute analysis re-

quires noise-free data, such data are difficult to obtain

in practice. Nevertheless, by careful selection and appli-

cation of noise-attenuating algorithms, removal of most

noise from the data while preserving useful signals is

possible. In this project, we applied a 3D trace-mix al-

gorithm to the original data to minimize loss of real

signals. This algorithm removes random noise while

preserving dips and faults, resulting in a better data

Figure 1. Map of Western Gulf Province showing subsurface occurrence of Austin Group (gray area), location of study area (redrectangle) southwest of the Frio River line, and en echelon fault zones Balcones fault zone (BFZ), Luling fault zone(LFZ), Charlotte-Jourdanton fault zone (CJFZ), Karnes fault zone (KFZ), and Mexia-Talco fault zone (MTFZ). Orange triangles subsurface volcanic mounds. The figure is modified from Condon and Dyman (2003).

Interpretation / November 2013 SB63

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set (Landmark PostStackmanual, 2003). Comparison

of original data with filtered seismic data (Figure 3a and

3b) shows that filtered data are cleaner than original

data. Similarly, comparison of time slices extracted

at 1100 ms from the original and filtered data (Figure 3c

and 3d) shows that slices obtained from the filtered

data exhibit better fault definition and clarity of events

than do equivalent slices from the original data (Fig-

ure 3c). Note that random noise that appears as spotted

events throughout the original data slice has been

attenuated in the filtered data slice.

StructureSix horizons were interpreted (Figure 4; Table 1);

two of these, the base Eagle Ford Shale and the top Aus-

tin Chalk, are presented showing fault orientation at

these levels. In Figure 4, whereas faults at the base Ea-

gle Ford Shale range from vertical to subvertical, those

at the top Austin Chalk dip at (45) and die within themiddle Austin Chalk (Figure 4, line 1). Some of the

45-angle faults that penetrated the middle AustinChalk terminated just before reaching the lower Austin

Chalk (Figure 4, line 1). The Eagle Ford Shale faults in

some cases cut into the middle Austin Chalk and inter-

sect with the 45-angle faults (Figure 4, line 1). The zone

of intersection of these two faults has positive hydro-

carbon implications addressed later in this paper. At

the intersection, faults are sometimes displaced in op-

posite directions. For example, the Eagle Ford Shale

fault (Figure 4, red line, blue arrow) is downthrown

to the east, whereas the 45-angle fault (Figure 4, dotted

black line, blue arrow) is downthrown to the west. A

map of the base of the Eagle Ford Shale shows that

the regional faults trend northeastsouthwest, the faults

occurring in an en echelon pattern (Figure 5a). In

the south part of the survey, although the dominant

fault trend is approximately N51E, three of the faults

(white arrows) have almost an eastwest orientation

(Figure 5a). Fault throws range from little or no offset

to as much as 150 ft (045 m) offset. In the north part,

some faults appear to be associated with volcanic-ash

mounds, their orientations ranging from about N28E to

N31E (Figure 5a). Fault displacements are about the

same as those seen in the south; however, fault throws

can be as much as 225 ft (68 m). Several other minorlinear features that look like faults exist within the

lower Eagle Ford Shale, as revealed by the curvature

attribute extracted along the base Eagle Ford Shale sur-

face (Figure 5b). While some of these features are mi-

nor faults having minor displacements, others are fold

bends having insignificant or no displacement along the

surface; these represent areas susceptible to fault, and

all are oriented northeastward.

We mapped a horizon (near top Austin Chalk) just

above the top Austin Chalk because it is more continu-

ous than the top Austin Chalk (Figure 4). We created a

phantom map at the top Austin Chalk from the near top

Austin Chalk by adding 30 ms to the near top Austin

Chalk horizon. The top Austin Chalk and near top Austin

Chalk horizons are intensively faulted (Figure 6a). More

than 250 faults were mapped at this level. Although the

faults are mostly linear and have a northeast trend, some

exhibit semicircular geometry (Figure 6a, yellow arrows;

6b, red arrows). Some other faults in the acreage exhibit

a northwest trend (Figure 6a and 6b). Fault throws at this

level range from 30 to 150 ft (945 m). As seen fromthe curvature attribute extracted from a strata slice

along the top Austin Chalk, faults at this level appear

to be mostly extensional polygonal faults (Figure 6b).

Although polygonal features are seen everywhere along

the horizon, they are more pronounced northeast of the

volcanic mound (Figure 6b). Major differences exist be-

tween faults seen at the top Austin Chalk and those at the

base Eagle Ford Shale. For example, whereas the longest

fault at the base Eagle Ford Shale is 2 mi (3.2 km) inlength, the longest fault at the top Austin Chalk is 5 mi(8 km). In addition, fault orientations at the top AustinChalk are mostly random, whereas orientations at the

base Eagle Ford Shale are essentially northeast; further-

more, whereas almost all the linear features seen in

the curvature slice at the near top Austin Chalk are faults

and can bemapped (e.g., Figure 7a, black arrows, line 2),

most of those seen at the base Eagle Ford Shale curva-

ture slice are fold bends. For example, the strong linear

feature seen at the extreme southeast (Figure 7b, black

arrow, line 2) corresponds to a low on the seismic

section. Examples of faults having some amount of dis-

placements are indicted by yellow arrows (Figure 7b,

line 2). It is not easy to distinguish between fold bends

and faults on curvature slices without incorporating

the seismic sections that cut across the linear features

Figure 2. Schematic diagram showing stratigraphic succes-sion in South Texas during the Late Cretaceous beginningfrom Eagle Ford Shale.


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(e.g., Figure 7b). Thus, by using the seismic section,

we were able to identify the feature indicated by the

black arrow in Figure 7b as a fold bend rather than

a fault.

Petrophysical analysisIn this study, we performed petrophysical analysis

to generate pertinent log data (Figure 8) that were used

as external attributes in the analysis for resistivity.

Figure 3. Poststack processing: (a) original seismic data (line 1) before 3D trace mix filtering, (b) the same seismic line afterapplication of a 3D trace mix algorithm, (c) time slice from original seismic data, and (d) time slice from 3D tracemix filtered data. Note clearer fault definitions in (d) compared with those of (c), which exhibit blurred images.TSL time slice location. TWT two-way traveltime. See location of line 1 in Figure 5.

Figure 4. Seismic line (line 1) showing dif-ferent fault types that cut Eagle Ford Shaleand Austin Chalk. Note Eagle Ford Shalesubvertical to vertical faults (red lines) andAustin Chalk (45-angle) faults (dottedblack lines). TWT two-way traveltime. SeeTable 1 for key to abbreviations. Note:Horizontal scale 179;650; Vertical scale 19418; Vertical exaggeration VE 8.5.


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We used the log R method (Passey et al., 1990, 2010)

to compute TOC from sonic and resistivity logs. The in-

terval used for log normalization includes the middle

Austin Chalk as well as the uppermost lower Eagle Ford

Shale. An estimate of the level of organic maturity (LOM

equal to 9) was obtained using this method for a single-

cored well a limited number of TOC data. For com-

parison, TOC was also calculated using the multiple

minerals (MultiMin method). The MultiMin log model

is similar to that of Eastwood and Hammes (2010), ex-

cept that input logs have a limestone basis and, given

the limited X-ray diffraction data, the V quartzVclay ratio

is taken to be one-third (Passey et al., 2010). Whether

this characterization of the Eagle Ford Shale is appro-

priate for the apparent siliciclastic component in the

upper Austin Chalk (which may be palagonitic) is un-

known. Although comparison of results from both

methods (Figure 8, track 6) shows good agreement, sug-

gesting that either of the log-derived TOC values can be

used in the prediction exercise, we used the TOC log

that had been calculated by the log R method (Fig-

ure 8, track 6, green curve). In addition to TOC, BVW

(product of water saturation Sw and porosity, phi)

Figure 6. (a) Time structure map at near top Austin Chalkshowing fault orientation at this level. (b) Most positive cur-vature strata slice extracted along top Austin horizon. Notepolygonal fault pattern seen at this level. Red and yellowarrows discussed in text; yellow outlines discussed in theVolcanic-ash mounds section. TWT two-way traveltime.

Figure 5. (a) Time structure map at base Eagle Ford horizonshowing fault orientations and well locations. Dotted yellowoutline outline of volcanic mound seen at near top AustinChalk. (b) Most positive curvature strata slice extracted alongbase Eagle Ford horizon showing more faults associated withhorizon in contrast to structure map. Most faults are orientednortheastward. Area in white rectangle and solid yellowcircles and dotted yellow outline are discussed in the Vol-canic-ash mounds section. TWT two-way traveltime.

Table 1. List of abbreviations used within AustinChalk and Eagle Ford Shale.

Abbreviation Meaning of abbreviation

NAU Near Austin Chalk horizon

TAU Top Austin Chalk horizon

TLAU Top lower Austin Chalk horizon

TEF Top Eagle Ford horizon

TLEF Top lower Eagle Ford horizon

BEF Base Eagle Ford horizon

AUC Austin Chalk interval

UEF Upper Eagle Ford interval

LEF Lower Eagle Ford interval

LAU Lower Austin Chalk interval

MAU Middle Austin Chalk interval

UAC Upper Austin Chalk interval


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and Vclay curves were computed. The last track shows a

summary of the petrophysical analysis. In this track,

note that the Eagle Ford Shale is rich in carbonate, par-

ticularly the upper Eagle Ford Shale, which has as much

as 50% calcite, whereas the lower Eagle Ford Shale is

richer in clay than the upper Eagle Ford Shale. In the

Austin Chalk, clay (siliciclastic) content is high within

the upper Austin Chalk but gradually decreases down-

ward toward the lower Austin Chalk. Correspondingly,

porosity is high in the upper Austin Chalk but low in the

lower Austin Chalk, with values ranging from 0 to 0.45

porosity units (Figure 8, track 3); V clay and BVW range

from zero to one (Figure 8, tracks 4 and 7, respectively).

It is important to note that kerogen (TOC) is radio-

active and associated radioactivity (gamma ray) in-

creases with increasing amount of kerogen (e.g.,

Sondergeld et al., 2010). In track 4 (Figure 8), we show

the overlay of V clay calculated from gamma ray (Vclay-

GR) and Vclay calculated from neutron density (Vclay-

ND). The amount of TOC is indicated by the separation

of the two curves where V clay-GR leads Vclay-ND. In-

creasing separation suggests an increasing amount of

TOC. Because TOC is a poor conductor of electricity,

conductivity decreases with an increase in TOC. On

the basis of log R response modeling results (Passey

et al., 1990), resistivity also increases with decreasing

matrix porosity. However, as seen in Figure 8, although

the upper and middle Austin Chalk intervals are rich in

calcite with low matrix porosity ranging from 0.03 to

0.06 porosity units (Figure 8, track 3), both exhibit low

resistivity (Figure 8, track 2). In contrast, the lower Aus-

tin Chalk and upper Eagle Ford Shale intervals with ma-

trix porosity ranging from 0.03 to 0.15 porosity units

(Figure 8, track 3) have very high resistivity (Figure 8,

track 2). Examination of Vclay-GR and V clay-ND separa-

tion and TOC (tracks 4 and 6, respectively) in these in-

tervals shows that the upper and middle Austin Chalk

have low to zero V clay-GR and Vclay-ND separation and

low to zero TOC. In contrast, the lower Austin Chalk

and upper Eagle Ford Shale have high V clay-GR and

Vclay-ND separation and high TOC. Therefore, the high

resistivity exhibited by the lower Austin Chalk and upper

Eagle Ford Shale is related to TOC content resistivity or

a combination of matrix resistivity and TOC content, and

the low resistivity seen in the upper and middle

Austin Chalk is due to the absence of or low TOC.

Figure 7. (a) Curvature attribute map at top Austin Chalk horizon through seismic volume along line 2 and (b) curvature attributemap at base Eagle Ford horizon through seismic volume along line 2. Blue outlines in (a) and black ellipse and black circle in(b) indicate poor-data zone. See Table 1 for key to abbreviations.


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Acoustic impedanceWe used a model-based inversion procedure to gen-

erate AI volume and employed interpreted horizons to

guide the interpolation process. The differences be-

tween the inverted trace (red) and the actual log and

between the synthetic (red) and seismic trace (black)

at well C1 are shown in Figure 9a. In this figure, it

can be seen that the inverted trace closely matches

the actual log and there is a high degree of correlation

between the synthetic trace and the seismic trace.

Although there are some differences between the syn-

thetic and seismic trace, they are very minimal and did

not affect the overall results. To examine results from

the AI volume, we generated a horizon slice at 15 msbelow the top Austin Chalk (Figure 9b). In this slice, it

can be seen that areas east of the dotted white line are

composed mostly of lower AI materials compared with

areas west of it. An examination of the corresponding

slice from the V clay volume (Figure 10a), shows that

areas east of the dashed white line (dotted white line

in Figure 9b) are composed mostly of higher Vclay val-

ues compared with areas west of it that is, the east

areas are richer in clay content. A corresponding slice

from the instantaneous frequency volume (Figure 10b)

shows similar observations. In Figure 10b, events to the

east of the black solid curve are composed mostly of

lower frequencies ranging from 5 to 37 Hz (Figure 10b,

blue to light-blue regions), whereas areas west of the

black solid curve are composed of higher frequencies

that range from 37 to 75 Hz (Figure 10b, light-red to

red regions). Thus, the AI slice (Figure 9b) shows the

lithologic variations from high-AI calcite-rich rocks in

the west to low-AI clay-rich rocks in the east at this

level. Note that some fault zones are composed mostly

of clay-rich, lower frequency, and lower AI materials,

whereas others are filled with high-AI materials. A com-

parison of Figures 9b and 10b shows that high-AI rocks

have higher frequencies, whereas low-AI rocks have

lower frequencies. The zone of lowest impedance is the

area around well C1 (denoted in magenta and red) that is

occupied by the volcanic-ash mound of high clay content

formed by altered volcanic materials. Although there is a

general dip to the northeast, a major collapse of beds ap-

pears at about the center of the acreage that is probably

due to two major down-to-the-southwest Eagle Ford

faults (white arrows) and intrusion of magma (Figure 11,

line 3). The collapsed zone was later

filled with sediments from volcanic rocks

and later carbonate and siliciclastic de-

posits. The zone is therefore richer in

clay content than are the areas to the

northeast and southwest. Along this tran-

sect, the high-impedance, northeast-dip-

ping Austin Chalk intertongues with

the low-impedance Austin Chalk and

low-impedance volcanic sediments near

the faults and volcanic mound. Note that

high-impedance sediments directly be-

low the volcanic mound exhibit chaotic

features Beds are disrupted without

any stratification. In contrast, at loca-

tions to the southwest and northeast of

well C1, sediments are well bedded, sug-

gesting that the high-impedance chaotic

sediments at well C1 are probably shat-

tered carbonate rocks that were redepos-

ited along with the volcanic ash during

magma eruption. Overall, there is agree-

ment between AI and Vclay results

High AI corresponds to low V clay, and

high Vclay corresponds to low AI. In ad-

dition, high AI suggests high frequencies,

whereas high Vclay suggests low frequen-

cies, indicating that the high frequencies

have been absorbed by the clay-rich

interval.

Resistivity predictionA summary of pertinent information

with respect to the physical basis under-

lying rock physical-property prediction

Figure 8. Results from petrophysical analysis showing log-calculated Vclay,TOC, and BVW curves (tracks 4, 6, and 7, respectively). Note BVW same as watersaturation. Other curves are discussed in the text. L lower, U upper,M middle, N near. In track 6, TOC_S refers to TOC log (green) obtainedfrom use of the sonic and resistivity in the method of Passey et al. (1990),and TOC_MM refers to TOC log (black) obtained from the MultiMin methodof Eastwood and Hammes (2010).


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using seismic attributes is in order (Table 2) (Faust,

1953; Grant and West, 1965). Consider a rock rich in

TOC/hydrocarbon that also has fractures in some zones

(Table 2, row 3). A wireline log fromwithin the rock will

show high-resistivity (deep-induction) log values that

are partly the result of resistivity of carbonate rock be-

cause of low matrix porosity and the presence of high

TOC/hydrocarbon. Because it is a carbonate rock, seis-

mic waves propagating through the rock will have a rel-

atively high velocity, reduced traveltime (t), and higher

instantaneous frequency as shown in Figures 9b and

10b. The observed higher frequencies are attributed

to the absorption coefficient of the rock. Robinson

and Treitel (2008) note that although there is a large

variation of absorption characteristics, rocks with high

velocity such as granite are less absorptive than are

sedimentary rocks with low velocity. Because velocity

is high, AI is high, and the quality factor (Q) will also be

high because rocks having higher velocity generally

have higher Q (Hamilton, 1972a, 1972b; Johnston and

Toksoz, 1980; Johnston, 1981). Treadgold et al. (2011)

note that rocks that have a high elastic modulus are

more brittle than those that have a lower elastic modu-

lus. Because rocks that have a high elastic modulus are

high-velocity (i.e., high-AI) rocks, AI can be used to

identify brittle zones within a rock layer. Similarly,

the Q attribute can also be used to identify brittle zones

Figure 9. Acoustic-impedance-model-based results showingcorrelations between actual (black) and inverted (red) imped-ance logs and between synthetic (red) and seismic (black)traces at well C1 (a). Horizon slice through AI volume takenat 15 ms below top Austin Chalk showing volcanic mound out-line in red and magenta (b). See Table 1 for the key to theabbreviations.

Figure 10. Horizon slice taken at 15 ms below top AustinChalk through (a) Vclay volume and through (b) instantaneousfrequency volume.

Figure 11. Vertical transect (line 3) generated from AI vol-ume through wells C1 and D1. Volcanic mound characterizedby low impedance (yellow, red, magenta). In addition, loca-tion of Eagle Ford vertical to subvertical faults (white ar-rows). VM volcanic mound. TWT two-way traveltime.


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because high-Q rocks have high modulus. For example,

Q was featured as one of the key attributes employed in

predicting porous dolomite within the Trenton-Black

River limestone (Ogiesoba, 2010). In fractured zones be-

cause porosity is relatively high, a seismic wave will

undergo a longer traveltime and lower frequency be-

cause higher frequencies are absorbed by the more ab-

sorptive, porous, fractured zones. The wave will also

undergo a phase change, and the associated Q would

be low (Table 2, row 3, column 2). Corresponding

relevant seismic attributes for characterizing such

carbonate rock will include instantaneous frequency,

instantaneous Q, cosine of phase, instantaneous ampli-

tude envelope, and integrated amplitude (Table 2, row

3, column 3). Therefore, for resistivity distribution

within this rock type to be predicted using multiattri-

bute and neural-network analysis, some of these attrib-

utes could be selected by a multiattribute analysis

program. Similarly, for P-wave velocity to be predicted,

relevant seismic attributes that relate to P-wave velocity

must also be selected by the program, and so on, for any

other rock properties.

Seismic-attribute selection

The first step in seismic multiattribute analysis is to

select relevant seismic attributes to be used in the

analysis process by employing a stepwise regression

approach (Hampson et al., 2001; Ogiesoba, 2010). Se-

lected attributes are then used to form a linear equation

that can be applied to estimate a given rock property,

which in our study corresponds to resistivity (Hampson

et al., 2001). To implement the selection process, a host

of computed trace attributes (considered as internal

attributes) can be supplied to the multiattribute analysis

algorithm, as well as additional attributes generated

externally. In our case, these external attributes are

model-based AI, P-wave sonic log, Vclay, porosity, and

TOC volumes; they were generated using the same

multiattribute analysis procedures. Using these attrib-

utes and the nine wells discussed earlier, we performed

stepwise regression. Out of these attributes, six were

selected by the algorithm. In Figure 12a, we show

the plot of average error between the predicted and

actual resistivity versus the number of attributes.

Although a minimum error value is seen at attribute

2 along the red curve; however, the error starts to de-

crease again after attribute 3 until attribute 6 where it

begins to increase. The increase continued without any

further decrease. Therefore, attribute 6 represents

the point at which the error stops decreasing convinc-

ingly; suggesting that the number of attributes required

to predict resistivity is six. These six attributes are clas-

sified into two groups physical properties and

frequency-related attributes (Table 3). The most signifi-

cant attribute out of the six was TOC (Table 3). Physical

properties involve four attributes TOC, impedance,

P-wave velocity, and V clay. TOC refers to the organic

nature of the rock, whereas impedance and P-wave

velocity relate to the compactness of the rock. Although

increasing Vclay does not necessarily suggest increasing

TOC and, therefore, increasing resistivity, within the

lower Austin Chalk and Eagle Ford Shale, TOC does ap-

pear to increase with an increase in Vclay (Figure 12b).

TOC increases because the separation between V clay-GR

and V clay-ND increases; hence, resistivity also increases.

High values of TOC, AI, and P-wave attributes indicate

high resistivity (Table 2). Frequency-related attributes

narrow bandpass filter 510 1520 and average

frequency are both low-frequency attributes that

define fracture zones characterized by low frequencies

(Table 2). The high degree of correlation between

TOC and resistivity can be seen in the crossplot of

TOC and actual log resistivity (Figure 12c), in which

the correlation coefficient is 0.8. Hence, TOC was

chosen as the most significant attribute. The plot was ob-

tained from an interval starting from the near top Austin

Chalk to the base Eagle Ford Shale.

Neural-network prediction

Once attributes had been selected, the next step was

to perform neural-network analysis so that resistivity

could be predicted. In this process, selected attributes,

together with wells that have requisite log suites, were

Table 2. Summary of pertinent information underlying physical basis of prediction of physical log properties suchas resistivity using seismic attributes.

Rock type Seismic response Seismic attribute

Competent rock: zero/low porosity,relatively high resistivity

High velocity, decrease in two-waytraveltime (t), high frequency, highamplitude

Instantaneous frequency, averagefrequency, high instantaneous Q, highamplitude envelope, acoustic impedance,integrated amplitude

High TOC/hydrocarbon rock: highporosity, high resistivity

Low velocity, increase in two-waytraveltime (t), low frequency, phase change

Instantaneous frequency, averagefrequency, low bandpass filter, lowinstantaneous Q, amplitude envelope

Fractured carbonate rock with highTOC/hydrocarbon: high resistivity,relatively high porosity, facies change

Phase change, low velocity, increase intwo-way traveltime (t), low frequency infractured zones, but high velocity and, thus,high frequency in zones with no fractures

Instantaneous phase, cosine of phase,instantaneous Q, instantaneous frequency,dominant frequency, integrated amplitude,average frequency


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used to train the neural network. The process involves

linear combination of the attributes through application

of appropriate weights to derive a linear equation for

computing resistivity away from the wellbore at every

seismic-trace location. The result was an estimated resis-

tivity volume. The derived linear equation in this case is

given as

predicted resistivity 0.74 0.64 TOC 1.46

filter 510 1520 1.35

average frequency 0.69

impedance^2 0.45

P-wave^2 1.23 Vclay^0.5: (1)

A crossplot of actual resistivity versus predicted

resistivity (Figure 12d) shows high correlation with a co-

efficient of 0.97. Results from the resistivity volume

along line 4 through well F1 (Figure 13a and 13b) show

that the upper Austin Chalk has low to moderate resis-

tivity and is not continuous; the middle Austin Chalk has

low resistivity, whereas the lower Austin Chalk has high

resistivity. The upper Eagle Ford Shale and the lower

Austin Chalk constitute a continuous and high-resistivity

interval. The lower Eagle Ford Shale is characterized by

high to moderate resistivity, and it appears continuous.

Separating the upper and lower Eagle Ford Shale is an

interval of low resistivity. A 3D-volume rendering (Fig-

ure 13c) shows the areal extent of the high-resistivity

zone within the Austin Chalk and Eagle Ford Shale.

The areal extent depends on the cutoff value of resistiv-

ity used in the opacity the lower the resistivity value,

the larger the areal extent. Note that the area of highest

resistivity is close to the center of the acreage, particu-

larly near well F1 (Figure 13). TOC and Vclay are similarly

estimated and the attributes used to predict them are

listed in Tables 4 and 5, respectively.

Horizontal-well drilling results BVW versus Q and oil

production.A horizon map at the near top Austin

Chalk shows the location of horizontal wells drilled

in the acreage (Figure 13b) that were unavailable to

us prior to the prediction exercise. Wells shown in solid

yellow circles are horizontal wells, and those in solid

white circles are the nine wells that we used in the pre-

diction exercise. Four profiles numbered one through

four (Figure 13b, white lines) through the trajectories

of some of the horizontal wells are introduced to exam-

ine the validity of our analysis results, demonstrate rea-

sons behind successful and failed wells, and provide

possible underlying reasons for high-water-producing

wells. Gardner et al. (1964) and Johnston et al. (1979)

demonstrated that fluid-saturated (in particular water-sa-

turated) rocks have lower Q than dry rocks and that Q

decreases as BVW increases. This finding suggests that

instantaneous Q could be used to identify water-bearing

rocks. Hamilton (1972a, 1972b) and Toksoz et al. (1979)

noted that high-velocity rocks (those having high elastic

modulus and high AI) have highQ. Because high-velocity

(high-AI) rocks are more brittle than low-velocity rocks,

the instantaneous Q attribute, like AI, could be used to

Table 3. Six selected attributes from multiattributeanalysis. Number in parenthesesorder in which theyoccur.

Physical-property-related Frequency-related

TOC (1) Filter 510 1520 Hz (2)

(Impedance)^2 (4) Average frequency (3)

(P-wave velocity)^2 (5)

Sqrt (Vclay) (6)

Figure 12. Results from resistivity predic-tion: (a) Plot of average error between pre-dicted and actual resistivity logs. Blackcurve generated curve using all wells; redcurve generated curve removing one wellat a time. (b) Crossplots of log-calculatedTOC and log-calculated Vclay. (c) Crossplotsof actual resistivity (deep induction) andlog-calculated TOC and (d) crossplots of pre-dicted and actual resistivity.


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identify brittle zones, particularly in a mixed setting such

as the Austin Chalk and Eagle Ford Shale. We first exam-

ined the correlation between the Q attribute section and

the BVW curve (Figure 14a). We computed Q from the

seismic data using a 50-ms sliding window and employ-

ing Barnes (1992, 1993) definitions of Q shown below:

qt f t

2t; (2)

where t 1

2pi

d

dtloge At; (3)

and

qt pif t

ddtlogeAt

pif t

AtddtAt

pif t

stored energy

rate of energy loss

: (4)

Figure 13. Results from resistivity predic-tion: (a) transect from resistivity volumethrough well F1 showing upper, middle, andlower Austin Chalk. (b) Time structure mapat near top Austin Chalk showing drilled hori-zontal wells (yellow circles), four horizontal-well trajectories (white lines), and line 4through well F1 (magenta line). (c) Volumerendering of resistivity showing areas of highresistivity within Austin Chalk and Eagle FordShale. TWT two-way traveltime. See Table 1for key to abbreviations.


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In the above equations, t is the instantaneous band-width, f t is the instantaneous frequency, and At isthe instantaneous amplitude envelope. Equation 4 is

consistent with the standard definition of Q (Johnston

Toksoz, 1981).

Note that low Q (green-yellow) correlates with

higher BVW as well as higher porosity curves. In addi-

tion, high Q (red and magenta) correlates with low-

BVW, low-porosity, and high-resistivity curves, sug-

gesting that high-water-bearing and high-porosity zones

can be identified using the Q attribute. Because the

BVW curve is a product of Sw and porosity, both curves

are almost identical in shape. Thus, where the BVW is

high, porosity is high and where the BVW is low, poros-

ity is also low. Hence, low Q correlates with high BVW

and high porosity. In Figure 14b, we show a transect

(line 4) through the porosity volume. A comparison

of this figure with the Q transect (Figure 14a), shows

reasonably good correlation between Q and porosity

Areas having high porosity (green and red) corre-

spond to low-Q areas (green). For example, fault zones

(black ellipses) characterized by low Q (green) in

Figure 14a, correlate with zones of porosity (green to

red) relatively higher than the porosity (blue and cyan)

of the surrounding rocks in Figure 14b. A crossplot of

porosity versusQ extracted fromwithin the lower Eagle

Ford Shale at well F1 (Figure 14c) shows that there is

an inverse linear relationship between Q and BVW; sug-

gesting that Q can be used to identify porous and water-

saturated zones.

Next, we examined horizontal drilling results against

our predicted resistivity volume. The first horizontal

trajectory considered is trajectory 1, a resistivity sec-

tion through three horizontal wells (Figure 15a). The

production well (H-1, on the left) has most of the hori-

zontal length in the low-Q zone that was downthrown

by the Eagle Ford major fault (Figure 15b and 15c).

Because low Q correlates with high-water-saturated

zones, only a small section of the horizontal well is

in the high-resistivity zone. Hence, the well has pro-

duced a high volume of water more than four times

the amount of oil (Table 6). The other horizontal well

(H-2, Figure 15a) to the northwest within the high-

resistivity zone is not producing owing to a mechanical

problem. The horizontal sidetrack (H-3, Figure 15a) to

the northwest within the upper Austin Chalk failed be-

cause hydrocarbon accumulation is insignificant within

the zone, as shown by the low resistivity values associ-

ated with the zone (Figure 15a). In addition, the low Q

values associated with the sidetrack (Figure 15c) indi-

cate that the zone is also probably saturated with water.

On the other hand, trajectory 2 (well H-4, Figure 16a),

although the well also encountered the Eagle Ford

Shale large fault, has almost the entire length of the

horizontal section in the high-resistivity zone. The result

is the high volume of oil production Water produc-

tion is less than oil production. In addition, the well has

produced more gas (354,877 ft3) than trajectory 1 has,

which has produced only 34,000 ft3 (Table 6). Although

well H-5 found hydrocarbons, the well was not put on

production. In the case of trajectory 3 (well H-6,

Figure 16b) because the well has its entire horizontal

section in the high-resistivity zone, it has not produced

water since it was put in production. The well has pro-

duced 45,105 bbl oil and no gas (Table 6). Finally, tra-

jectory 4 (wells H-7 to H-9, Figure 17a) is an example of

a failed horizontal well drilled in the middle Austin

Chalk. The correspondingQ section (Figure 17b) shows

the low-Q interval in which the well was drilled.

Although the well was sidetracked three times to dif-

ferent directions, each time the kick-off depth was

about the same and remained horizontal in the low-Q,

Table 4. Nine selected attributes from multiattribute analysis used to predict TOC. Number in parenthesesorderin which they occur.

Physical-property-related Frequency-related Amplitude-related Phase-related

1/P-wave (7) Filter 5101520 (2) Integrated absolute amplitude (1) Instantaneous phase (9)

Sqrt Vclay (4) Dominant frequency (3) Amplitude envelope (5)

Quality factor (6) Derivative (8)

Table 5. Six selected attributes from multiattribute analysis used to predict Vclay. Number in parenthesesorder inwhich they occur.

Physical-property-related Frequency-related Amplitude-related

1/(P-wave) (1) Filter 15202530 Hz (3) Integrated absolute amplitude (2)

Quality factor (5) Apparent polarity (4)

Amplitude weighted frequency (6)


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low-resistivity, and high-water-saturated zone. Hence,

no hydrocarbons have been produced from this well

(Table 6).

DiscussionHydrocarbon sweet spots

As can be seen in Figure 18, porosity decreases as AI

increases; therefore, the low- to zero-porosity zones

(Figure 19a, blue zones) correspond to high-AI zones.

These zones are interpreted to be the calcite-rich inter-

vals that are more brittle than the surrounding rocks.

For optimal hydrocarbon recovery, the sought-for

zones in which to drill horizontal wells within hydrocar-

bon sweet spots are the brittle zones (Treadgold et al.,

2011). Hydrocarbon sweet spots, as defined from our

resistivity analysis, are the brittle zones that are charac-

terized by high resistivity, high TOC, and low water sat-

uration. In this regard, a combination of resistivity,

TOC, porosity, and AI would be required to determine

sweet spots that would yield higher hydrocarbon pro-

duction. Defining sweet spots on the basis of high

TOC and high resistivity but ignoring the other variables

would yield inadequate drilling locations such as shale-

dominated zones that would lead to production dif-

ficulties. On the other hand, a zone of high AI but

Figure 14. (a) Line 4 showing quality factor(Q) attribute transect through well F1; tran-sect demonstrates correlation between Qand water saturation and porosity. Blackcurve bulk volume water saturation log;red curve resistivity log; and bluecurve porosity log. Deflections to the rightsuggest increasing log property; deflections tothe left suggest decreasing log property.(b) Transect through predicted porosity vol-ume. (c) Crossplots of porosity and Q ex-tracted within the lower Eagle Ford Shale atwell F1. Note that hot colors red to lightred high porosity and cool colors blueto light blue low porosity. TWT two-way traveltime. See Table 1 for the key tothe abbreviations.


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low resistivity and low TOC, such as the areas indicated

by the black dashed outline in Figure 19, would produce

few or no hydrocarbons. Figure 19 shows areas of high

TOC with the corresponding high resistivity and brittle

(low-porosity) zones. Although the lower Austin Chalk

and the Eagle Ford intervals constitute the sweet-spot

zones, resistivity and TOC decrease significantly at the

extreme southwest corner within the lower Austin

Figure 15. Drilling results along horizontalwell trajectory 1: (a) resistivity transect,(b) normal seismic transect, and (c) Qtransect. TWT two-way traveltime. PW production well. See Table 1 for the key tothe other abbreviations.


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Chalk and upper Eagle Ford intervals (Figure 19);

hence, the most prolific zones are located to the north-

east, particularly around well F1.

Faults, fractures, and hydrocarbon saturationAnother focal point of discussion is the effect of

faults and fractures on hydrocarbon production. Al-

though both play key roles in the successful recovery

of hydrocarbons from the Austin Chalk and Eagle Ford

Shale, they can sometimes have negative economic con-

sequences. For example, a down-to-the-southeast major

Eagle Ford Shale fault along trajectory 1 (Figure 15)

shifted the water-saturated middle Austin Chalk down-

ward to juxtapose the high-resistivity, oil-saturated

lower Austin Chalk. Drilling horizontally through the

downthrown middle Austin Chalk so as to encounter

fracture zones that would enhance porosity and

permeability, without regard to the nature of the down-

thrown block, led to a high-water-producing well

the volume of water being four times that of oil. The

well was shut in after four years of production owing

Table 6. Volume of liquids produced from four horizontal well trajectories beginning from when the wells were putin production to when they were shut in. The length of each horizontal section is also shown as well as productionstart and shut-in dates.

Well trajectory no.Volume ofoil (bbl)

Volume ofgas (ft3)

Volume ofwater (bbl) Start date Shut-in date

Length of horizontal section (ft)

1 17,658 34,000 70,632 08/01/2007 12/31/2011 3467

2 382,060 354,877 376,128 10/06/2006 06/30/2012 2164

3 45,105 0 0 04/01/2007 05/31/2012 825

4 0 0 0

Figure 16. Drilling results from horizontalwells: (a) resistivity transect along trajectory2 and (b) resistivity transect along tra-jectory 3. TWT two-way traveltime. PW production well. See Table 1 for the key tothe other abbreviations.


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to the high volume of water. The negative role that

faults, particularly large faults, play within the Austin

Chalk and Eagle Ford Shale underscores the impor-

tance of knowing where sweet spots are located. In ad-

dition, it is important to point out that not all faults and

fractures are associated with hydrocarbons within the

upper and middle Austin Chalk. In this study, several

faults were identified within the Austin Chalk, but most

of the horizontal wells drilled to target these fault zones

either found few hydrocarbons having high water satu-

ration or no hydrocarbons. The failure to find produc-

tive intervals could be attributed to the fact that most of

Figure 17. Drilling results along horizontal well trajectory 4showing example of failed well: (a) resistivity transect and(b) equivalent Q transect. TWT two-way traveltime. SeeTable 1 for the key to the abbreviations.

Figure 18. Crossplots of actual acoustic impedance and ac-tual porosity; note that porosity decreases as acoustic imped-ances increases. Crossplots were obtained from between topAustin Chalk and base Eagle Ford Shale interval using all thewells in the study area.

Figure 19. Hydrocarbon sweet spots identified using a com-bination of porosity, TOC, and resistivity transects: (a) tran-sect from porosity volume, (b) transect from TOC volume,and (c) transect from resistivity volume. Note hydrocarbon-sweet-spot zones are areas defined by high TOC, high resistivity,and low-moderate porosity (high-moderate AI) found within thelower Austin Chalk and Eagle Ford Shale, particularly aroundwell F1. Note low-porosity (i.e., high-AI) zones (black dottedoutline); the corresponding TOC, and resistivity are low and in-dicate low hydrocarbon saturation. TWT two-way traveltime.See Table 1 for the key to the abbreviations.


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the these faults terminated within the middle Austin

Chalk before reaching the high-resistivity lower Austin

Chalk or upper Eagle Ford Shale that are rich in oil and

gas. Another observation is that some fault zones are

characterized by high AI while others are characterized

by low AI (Figure 9b), suggesting that the fault zones are

not all filled with the same materials. Those with high AI

are probably filled with calcite, while those with low AI

are filled either with clay, water, or hydrocarbons.

Length of horizontal well versushydrocarbon production

In addition to faults and fractures, it is important to

consider the length of the horizontal section of the well

versus hydrocarbon production. From production re-

sults, the length of the horizontal section seems to mat-

ter only within the sweet spot. That is, within the sweet

spot, the longer the horizontal section, the higher the

amount of oil produced. Outside the sweet spot, the

length of the horizontal section does not contribute

to the volume of oil or gas produced. For example, both

production wells along trajectories 2 and 3 are located

within the high-resistivity zones. The length of the hori-

zontal section of the trajectory 2 well is approximately

two and half times the length of the trajectory 3 well.

Corresponding volumes of oil produced are approxi-

mately 382,100 and 45,100 bbl, respectively. On the

other hand, although the length of the horizontal sec-

tion of the production well along trajectory 1 is about

four times that of trajectory 3 (Table 6), most of the

horizontal length is located within the water-saturated

middle Austin Chalk outside the sweet spot. In spite of

the short length of the trajectory 3 well, it has produced

more oil than the trajectory 1 well (Table 6). Addition-

ally, the usefulness of the Q attribute in hydrocarbon

exploration within the Austin Chalk and Eagle Ford

Shale should be noted. Once a correlation has been

established between water saturation and Q, the Q

attribute can then be used together with the resistivity

volume to plan horizontal-drilling operations so as to

avoid high-water-saturated zones and achieve optimal

hydrocarbon production.

Volcanic-ash moundsIt is generally thought that the feeder pipe or vent of

volcanic-ash mounds is located directly below the

center of the mound (e.g., Tyler and Ambrose, 1986).

However, volcanic-ash mounds found in our study area

do not appear to have vents or major faults directly be-

low the mounds. Rather, the major faults that appear

to be associated with the mounds are located

0.6 2.5 mi (14 km) away from the center of theash mounds (Figure 20). Two of the volcanic-ash

mounds (red and green dotted outlines) are small, with

an area of 0.3 mi2 (0.8 km2) and a diameter of0.6 mi (1.0 km). The mound depicted by the red dot-ted outline has a height of 220 ft (67 m), whereas themound depicted by the green dotted outline is 185 ft(56 m) high. The third and largest mound (yellow dot-ted outline) has an area of 2 mi2 (3.2 km2), with adiameter of 1.9 mi (3 km) and a height of 876 ft(267 m). Faults that are in close proximity to themounds are labeled F1 through F6; F1 through F4

are associated with the largest mound, whereas F5

and F6 are associated with the small mounds. The larg-

est mound is located between F2 and F4 in the NE di-

rection (Figure 20), and the center is 1.2 mi (2 km)from the north tip of F2 and the south tip of F4. Faults

F1 and F3 are 4 and 3 km (2.5 and 2 mi) from thecenter of the mound, respectively. F1 and F2 are down-

thrown to the southwest, whereas F3 and F4 are down-

thrown to the northeast. It is not clear from which of

these four faults the largest mound could have devel-

oped. However, because of the nearness of F2 to the

mound, and because it is larger than F4, the mound

could have probably been emplaced by F2.

Seismic lines that cut through these faults (Figures 20

and 21; lines 1 and 5, respectively), show bed displace-

ments from the end of record time (4.0 s), to 1.2 s,where they are capped by the Austin Chalk Formation.

In addition, the faults appear to be associated with

zones of deformed rocks that extend nearly vertically

downward, suggesting altered sediments. Faults F1

and F2 in particular exhibit zones with the most defor-

mation; suggesting that the largest volcanic mound

probably formed from the magma that came through

these faults. An arbitrary line (Figures 20 and 22, line

6) connecting the three mounds shows fault F1 with

a displacement of 225 ft (68 m) at base Eagle FordShale level (Figure 22). The fault bifurcates at 1.8 s.Figure 22 has been enlarged to emphasize pertinent fea-

tures within the interval between 0.9 and 2.0 s. The

northeast section of line 6 (Figure 22) that connects

Figure 20. Enlarged version of area defined by white rectan-gle in Figure 5 showing (1) the seismic profile through iden-tified volcanic mounds and (2) seismic profiles through faultsassociated with the mounds. The map is at base Eagle Ford.TWT two-way traveltime.


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the two small mounds runs parallel to F5 and F6 and

through the saddle on the downthrown side of the

faults. As can be seen along this section (Figure 22),

no significant bed displacement is associated with

the faults because the line runs parallel to the faults.

However, the fault zone can still be identified and is

characterized by some broken events (see the dotted

vertical black line). Between 1.2 and 1.5 s, the fault zone

is characterized by a velocity pushdown that created a

saddle defined by F6 and F6A. The sad-

dle is similar to those defined by F3 and

F3A and F4 and F4A, which also occur

between 1.2 and 1.5 s (Figure 21a and

21b). The fault zone associated with

F1 is characterized by clear bed dis-

placement (Figure 22) and can be seen

up to 4 s (Figure 21a), suggesting that

the fault still continued downward and

perhaps into the basement. In contrast,

directly below the mounds there are no

faults; only the largest mound displays

some minor fault displacements that

do not extend down to the end of record

(Figure 22). Clearly, there are no direct

pathways (vents) below the mounds

that could have led to their emplace-

ment; suggesting that the mound prob-

ably formed from the magma that

came through any of the nearby faults

(F1 through F6) by explosive mecha-

nism, as is suggested by Ewing and

Caran (1982). According to these re-

searchers, as the magma came to the

seafloor, it reacted violently with the

cold water and created an explosion

that blew out the magma and deposited

the ashes some distance away from and

around the vent. Present-day submarine

volcanic eruption in the South Pacific

shows that resultant mounds are located

some distance away from the vent,

where the magma is actively being

ejected into the sky from under the

sea (Shukman, 2009). Each of the small

mounds is 1 km (0.6 mi) away fromfault F6, which is thought to be the vent

responsible for emplacement of the

small mounds (Figure 22).

It is useful to consider the time of

emplacement of the largest and smallest

volcanic mounds. The base of the larg-

est appears to be within the Austin

Chalk and is capped by top Austin

Chalk. Sitting on the Austin Chalk is

the Anacacho Formation (Figure 22).

However, the two small mounds are

completely encased by the Anacacho,

with one of the Anacacho beds acting

as their base (Figure 22), suggesting that

volcanic activities continued during deposition of the

Anacacho Formation and that the two small mounds

are younger than the largest mound. Given the strati-

graphic positions interpreted from the seismic data,

the relative ages are interpreted to be about middle

Campanian for the small mounds and late Santonian

to early Campanian for the largest mound. The largest

mound (yellow dotted outline) and the small mound

(red dotted outline) have been penetrated by wells

Figure 22. Seismic transect (line 6) that connects identified three volcanicmounds.Black log curve SP log; red log curve sonic log; LVM largest volcanicmound;and SVM small volcanic mound. TWT two-way traveltime.

Figure 21. Seismic transects through faults associated with largest volcanicmound: (a) line 1 transect through faults F3, F4, and F6 and (b) line 5 transect through faults F1 and F2. Top map map of near Austin Chalk hori-zon; lower map map at base Eagle Ford. Both seismic lines corendered withcoherence attribute. TWT two-way traveltime.


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C1 and J1, respectively (Figure 20). Both

wells have found similar rock materials

within the mounds, with approximately

the same interval velocity of approxi-

mately 11,400 fts. This velocity is lowerthan that of the encasing carbonates,

which range from 14,500 to 16,500 fts.Ewing and Caran (1982) note that the

lower interval velocity found to be asso-

ciated with the volcanic mounds oc-

curred because volcanic magma from

which the mounds were created was al-

tered by diagenetic processes to palagon-

ite, which has a lower interval velocity.

Also note that, although the mounds

are composed of high-porosity materials,

they appear to be devoid of hydrocar-

bons. Therefore, not every volcanic

mound within the Austin Chalk and the

Anacacho is hydrocarbon bearing.

An oblique line that cuts across fault

F6 midway between the two small

mounds clearly shows that F6 is prob-

ably the pathway through which the

magma came to the seafloor (Figure 23,

line 7). The fault zone (dashed white

outline in Figure 23a) can clearly be

seen beginning at 4.0 s and ending at1.2 s at the top, where it is cappedby the Austin Chalk. Events within the

zone are composed of a mix of convex

and concave but mostly convex-upward

reflections (Figure 23a). In general, re-

flected events within the entire zone ap-

pear to exhibit disorderly arrangement

compared with events outside the

dashed white outline, which exhibit ap-

proximately parallel bedding reflec-

tions. The corresponding Q-attribute

section (Figure 23b) shows that events

within the dashed white outline are

composed mostly of low-Q materials

(mostly cyan to dark-blue), particularly

between 1.2 and 3.3 s, whereas the ap-

proximately parallel bedded events out-

side the zone are composed of high-Q

(hot colors and dark-blue) materials that

terminate against the dashed white out-

line (Figure 23b). The width of the fault

zone varies with depth; it is narrower

at the top 0.44 mi (0.7 km) than atthe base 0.94 mi (1.5 km). Becauselow-Q values indicate lower velocities,

the magma within the vent (fault zone)

also could have been altered to lower

velocity materials, such as serpentine

or marl, by diagenetic processes. The

low-Q values are therefore found to

be associated with materials within

Figure 23. Northwestsoutheast seismic transect (line 7) through fault F6.(a) Normal seismic section corendered with coherence attribute and (b) corre-sponding Q attribute section. Horizon map near top Austin Chalk time map.TWT two-way traveltime.

Figure 24. Profiles (line 3) (a) through resistivity and (b) through TOCvolumes showing multiattribute analysis results within the section Volca-nic-ash mounds. See Table 1 for the key to the abbreviations. TWT two-way traveltime.


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the fault zones (vents). However, from 3.3 to 4 s, high-Q materials become dominant within the fault zones

(Figure 23b), suggesting that the magma at deeper lev-

els was less affected by diagenesis.

Volcanic-ash mound Multiattribute analysis results

Seismic multiattribute analysis results show that the

volcanic-ash mound is characterized by low to zero re-

sistivity (Figure 24a, line 3). The resistivity spike seen at

the boundary that separates the mound from the over-

lying Anacacho Formation (Figure 24a, black dashed

arrow; line 3) is not hydrocarbon-related, but rather

it is related to some Anacacho carbonate hard streaks.

However, along the flanks of the mound representing

the top of Austin Chalk, some low-moderate resistivity

values can be seen (Figure 24a). Within the core of the

mound, the resistivity value is zero. The corresponding

TOC section (Figure 24b, line 3) shows similar results;

low-moderate TOC values are seen along the flanks of

the volcanic cone, whereas, within the core of the cone,

the TOC value is zero. It is important to note that at the

location of the resistivity spike (Figure 24a, white

dashed arrow), the corresponding TOC value is zero

(Figure 24b, white dashed arrow), suggesting that

the spike is not hydrocarbon-related. We attribute

the TOC and resistivity low-moderate values along

the flanks to the presence of organic matters within

the Austin Chalk that were deposited on top of the

mound when deposition of Austin Chalk resumed after

the abatement of volcanic activities. However, the vol-

canic mound itself is devoid of any organic matters.

ConclusionsIn the foregoing, we have discussed several pertinent

points about the Austin Chalk and the Eagle Ford Shale.

Slices from the V clay and AI volumes show that the Aus-

tin Chalk interval is not of uniform composition but has

significant lithologic variations in temporal and lateral

directions. Our multiattribute analysis results show that

the hydrocarbon sweet spots are the brittle zones char-

acterized by high resistivity, high TOC, high AI, and low

water saturation. In addition, the productive wells were

drilled in the lower Austin Chalk where the resistivity

and TOC values are high, confirming our analysis re-

sults. Furthermore, our investigations show that more

than 90% of productive zones within the lower Austin

Chalk are associated with Eagle Ford vertical-subvert-

ical en echelon faults, suggesting hydrocarbon migra-

tion from the Eagle Ford Shale. Some of these faults

are oriented N28E to N31E, whereas others are ori-

ented N51E. Although the Q attribute was not selected

as one of the primary attributes for predicting resistiv-

ity, it nevertheless appears to be a good reconnaissance

tool for predicting resistivity and brittle zones, as well

as zones of high water saturation.

In addition, local accumulations within the Austin

Chalk may be related to Austin Chalk TOC-rich zones

or migration from the Eagle Ford Shale through faults.

Some wells have high water production because the

water-bearing middle Austin Chalk that sits on the

downthrown side of Eagle Ford Shale regional faults

constitutes a large section of the horizontal well, as evi-

denced by the Q attribute. The lower Austin Chalk and

upper Eagle Ford Shale together appear to constitute a

continuous (unconventional) hydrocarbon play. Fi-

nally, the submarine volcanic mounds found within

the acreage do not have the feeder vents (feeder faults)

directly below them; rather, such vents appear to be

0.6 2.5 mi (1 to 4 km) away from the center ofthe mounds. From the stratigraphic positions of the

mounds, we conclude that volcanic activities continued

up till the middle Campanian during the deposition of

the Anacacho Formation.

AcknowledgmentsWe thank our industry partner CML Exploration for

supplying the data. We also thank Landmark Graphics

and Hampson-Russell for supplying the software used in

this study. Publication is authorized by the director of the

Bureau of Economic Geology, The University of Texas at

Austin. We thank the reviewers O. Rehkopf, P. Rodrick,

two anonymous reviewers, and also the associate editor,

J. OBrien, for critically reviewing the manuscript and for

their useful comments and suggestions. We also thank S.

Doenges and C. Parker for editing this manuscript and J.

Ames for preparing the figures.

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