CSUG/SPE 148751

An Integrated Approach for Understanding Oil and Gas Reserves Potential in Eagle Ford Shale Formation Li Fan, SPE, Ron Martin, SPE, John Thompson, SPE, Keith Atwood, SPE, John Robinson, SPE, and Garrett Lindsay, SPE, Schlumberger

Copyright 2011, Society of Petroleum Engineers This paper was prepared for presentation at the Canadian Unconventional Resources Conference held in Calgary, Alberta, Canada, 15–17 November 2011. This paper was selected for presentation by a CSUG/SPE program committee following review of information contained in an abstract submitted by the author(s). Contents of the paper have not been reviewed by the Society of Petroleum Engineers and are subject to correction by the author(s). The material does not necessarily reflect any position of the Society of Petroleum Engineers, its officers, or members. Electronic reproduction, distribution, or storage of any part of this paper without the written 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.

Abstract Examples of an integrated approach for quantifying oil and gas production potential in different hydrocarbon windows of the Eagle Ford Shale are presented. The Eagle Ford basin is unique in that reservoir fluids range from black oil to dry gas depending on the geology, burial depth, and temperature. The main goal of this paper is to guide operators to an understanding of potential reserves and their distribution in the Eagle Ford through the use of our specialized analysis and methodology to estimate ultimate recoveries.

Data from the Eagle Ford Shale was compiled and analyzed to gain knowledge about the basin. The geology aided in indentifying “sweet spots” based on the various thermal maturation windows. Also, recent drilling and completion activities were examined in addition to the observed production from public databases. The intent was to determine curent completion practices in different parts of the Eagle Ford and also provide insight on the relationship between geologic features and production trends. A rapid asset evaluation case study is presented to demonstrate technique and workflow that uses vintage vertical well data to provide an estimate of asset value and reserves for a typical horizontal well in the Eagle Ford.

The results of the study identifies “sweet spots” of oil and gas production and indicates that 1) Eagle Ford production is related to the maturation windows, as well as structure; 2) the best wells in the Eagle Ford are in the thicker areas; 3) Austin Chalk production relates to the underlying Eagle Ford production; 4) different completions for different areas and types of hydrocarbons should be considered, and 5) data and knowledge integration is the key for rapid evaluation of asset value in the Eagle Ford Shale.

Operators can use this information and technique to help 1) better understand the uniqueness of the Eagle Ford Shale, 2) optimize their completion design and field development plan, and 3) calibrate expectations on oil and gas reserves potential under their acreage. Introduction The Eagle Ford Shale play began in 2008 with the drilling of STS First Rock #1 located in La Salle County, Texas. The play extends over an area of approximately 11 million acres—from the Texas border with Mexico to the eastern borders of Gonzales and Lavaca Counties as shown in Fig. 1. The southern border of the trend is subparallel the Sligo shelf edge.

2 CSUG/SPE 148751

Fig. 1—Area of industry activity in the Eagle Ford Shale and associated geologic features.

Stratigraphically (Fig. 2), the Late Cretaceous Eagle Ford formation (Lock and Peschier, 2006), lies un-conformably above

the Buda Limestone and is overlain by the Austin Chalk.

Cret

aceo

usEa

rlyLa

te

Fig. 2—Stratigraphic column showing the Eagle Ford Shale (Dawson 2000). The Eagle Ford varies stratigraphically through Texas as a result of several changes in both structure and depositional setting. The Eagle Ford dips from the outcrop located north of the Maverick basin to the Gulf of Mexico. Along its northeast/southwest depositional trend, the formation varies in thickness from 50 ft in the northeast to more than 300 ft in the southwest. Sedimentation was influenced by the Laramide Orogeny which shed sediments into the Maverick and Hawkville basins located between the Edwards and Sligo shelf edge (Fig. 3) (Scott 2004). The formation thins to approximately 50 ft over the San Marcos arch, which is located to the northeast and is considered the eastern limit of the play in South Texas.

The Eagle Ford Shale is one of many major source rocks that were deposited during one of two anoxic extinction events that occurred at the Cenomanian/Turonian boundary. During this event, warm seas existed throughout the world. A runaway greenhouse effect existed, which resulted in an increased carbon dioxide level and consequently increased organic productivity. Consumption by aerobic bacteria created an anoxic or oxygen-poor environment that preserved the organic material. This increase in the level of carbon accounts for the accumulation of the thick black shale deposition observed around the world.

CSUG/SPE 148751 3

Elevation variesbetween ‐1,500 ft. (yellow)and ‐13,500 ft. (dark blue)

Maverick Basin

Edwards shelf edge 

Sligo shelf edge 

Karnes Trough

Black Hawk field

Hawkville field

Fig. 3—Map of Eagle Ford Shale formation tops with key geologic features.

Identification of Sweet Spots The Eagle Ford Shale sourced the famous East Texas field (Woodbine sands) located in the East Texas Salt basin. To the south, the prolific Austin Chalk fields were also sourced by the Eagle Ford Shale. Analysis of the outcrop and samples from well control identified kerogen types II, II/III, and III. As the Eagle Ford dips south it went through the three maturation windows (Fig. 4). Pyrolysis data confirms, for example, that the Maverick Basin is in the oil window and the Hawkville basin is at the transition point between dry gas and wet gas as the San Marcos arch is approached (Tuttle 2010; Edman et al. 2010).

Analysis of dozens of geochemical logs and associated production in the three “production windows” revealed a measurement pattern that was indicative of the relative liquid yield of each well (Fig. 5). A fluid-substitution technique was used to generate a synthetic neutron response (black) in oil, gas condensate, and dry gas windows on the basis of each well’s individual mineralogic composition. When compared to the recorded neutron porosity (blue) and bulk density (red) (at the point indicated by the arrows), as can be seen in examples A, B, and C in Fig. 5, likely produced fluids are readily identifiable and indexable. Magnified inserts of the log response have been included in Fig. 5 for clarity.

The neutron density measurement is generally responsive to the type of fluid contained in the pore space. In the presence of dry gas for instance, the neutron measurement will respond to the hydrogen deficit and will provide the classical crossover signature. Theoretically, as the density of the hydrocarbon in the pore space increases, the excavation effect on the neutron will diminish. The actual response we see in the Eagle Ford is varied as a result of the variations in mineral and hydrocarbon composition. Spectroscopy data allows us to synthesize neutron responses that are calibrated to the produced fluid via fluid substitution. This provides us with a reasonable indication of what type of fluid will be produced based upon log responses.

A study of the Eagle Ford and Austin Chalk production data related to Eagle Ford thickness and geologic features identified the best producing areas and geologic controls. A public database provided the production data for this study. Gas production data from the Austin Chalk and Eagle Ford Shale were posted on an isopach map of the Eagle Ford formation(Fig. 6). The map shows geologic features and production bubbles representing an average daily rate for the maximum-production month.

4 CSUG/SPE 148751

Fig. 4—Map showing the maturation windows of the Eagle Ford.

The best Eagle Ford gas production occurs in the Hawkville basin between the Edwards and Sligo reef trends where the

Eagle Ford is relatively thick. Austin Chalk gas production is from the Pearsall and Gonzalez fields. We observed that Eagle Ford production beneath these fields is not as good as the production in the Hawkville area. Our conclusion is that Eagle Ford gas formed in the gas window and migrated northward to source the two fields. Continued gas generation combined with the trapping of gas in the Hawkville area created the current area of best gas production in the Eagle Ford.

A Oil B Heavy Liquids C Dry Gas

Fig. 5—Examples of neutron log response in the three fluid windows

Oil production for the maximum-production month (Fig. 7) was posted on the same basemap used for the gas production. Oil in the Maverick basin is found throughout the basin, with the best oil production located in the southern sector of the basin. Oil produced in the Hawkville area is from condensate-rich gas located along the northern edge of the Hawkville basin. The best oil production occurs to the northeast and is closely associated with the faulting and structuring associated with the Karnes Trough. Because of the close proximity of the Gonzalez field to the Karnes Trough, Eagle Ford oil did not migrate far from the point of generation. In the Karnes Trough, the Eagle Ford section is over 200 ft thick. Oil from continued generation in the Karnes Trough was trapped in fractured Eagle Ford Shale close to the faults and resulting in the largest accumulation of oil found in the trend.

CSUG/SPE 148751 5

Fig. 6—Gas production from horizontal wells superimposed over net pay (ft). Bubble data is an average daily rate for the maximum-

production month. Eagle Ford production is shown in red and Austin Chalk production in yellow.

Because the two areas have been buried to approximately the same depth, the occurrence of oil to the northeast versus gas to the southwest is probably caused by difference in kerogen types and their associated maturation windows. We conclude from this study that the following are probable key drivers that determine good Eagle Ford production: 1) presence of a trapping mechanism such as faults, fractures, and stratigraphic traps; 2) presence of a barrier to prevent vertical migration; 3) adequate depth of burial for maturation and accumulation; 4) thick Eagle Ford pay section; 5) presence of natural fractures; and 6) high calcite and quartz content that varies little through the trend, enabling successful fracture stimulation.

Fig. 7—Oil production from horizontal wells superimpoased over net pay (ft). Bubble data is an average daily rate for the maximum-

production month. Eagle Ford production is shown in green and Austin Chalk production in gray.

Drilling and Completion Procedures Horizontal wells in the Eagle Ford Shale are normally drilled with oil-base mud across the lateral. The average lateral length is 4,500 ft at TVD of 5,000 ft to 12,500 ft. The lateral is completed using a “plug-n-perf” system with 10 to 20 stages at 200-ft to 400-ft stage lengths. Each stage typically has 4 to 8 perforation clusters that are 1ft to 2 ft wide, shot at 4 to 6 shots per foot. Fig. 8 shows a wellbore diagram for an example Eagle Ford horizontal well with a 10-stage completion.

6 CSUG/SPE 148751

5 ½”

12345678910

Casing

Stage Length200 – 400 ft

Perforation Clusters4 – 8 clusters/stage

5,000 – 12,500 ft TVD

Lateral Length3,500 – 5,000 ft

Stages

Fig. 8—Example wellbore diagram showing a 10-stage completion in the Eagle Ford Shale.

The Eagle Ford is unique because it contains multiple types of in-situ reservoir fluids ranging from black oil to dry gas.

The hydraulic fracture treatments in the gas-rich areas are typically pumped using a slickwater fluid system similar to those used in the Haynesville Shale (Thompson et al. 2010). The liquid-rich areas require higher fracture conductivity as a result of multiphase flow and higher viscosity fluids (Bazan et al 2010). Therefore, the hydraulic fracture treatments are typically pumped with higher proppant concentrations using a hybrid (slickwater and crosslinked) or crosslink fluid system. Table 1 is a summary of the type of completions and hydraulic fracture treatments typical for the gas-rich and liquid-rich areas. The completions (stage and cluster size) do not vary much between gas-rich and liquid-rich areas; however, individual completions will vary. As discussed, the main difference in the two areas is the design of the hydraulic fracture treatment. For the liquid-rich area, a hybrid system is usually pumped with lower fluid volumes and pump rates and higher proppant concentrations.

Table 1—Typical completions for horizontal Eagle Ford wells in the gas and liquid-rich areas.

Eagle Ford Eagle Ford

Gas-Rich Area Liquid-Rich Area

Number of stages 10–20 10–20

Lateral length, ft ~4,500 ~4,500

Number of clusters per stage 4–8 4–8

Stage length, ft 200–400 200–400

Distance b/w clusters, ft 30–80 30–80

Number of clusters 50–120 50–120

Fluid total, Mgal 6,112 4,032

Fluid per stage, Mgals 509 252

Fluid per cluster, Mgal 127 50

Fluid per ft, Mgal 1.4 0.8

Proppant total, Mlbs 3,432 5,120

Proppant per stage, Mlbs 246 320

Prop per cluster, Mlbs 61 64

Prop per ft, Mlbs 0.7 1

Max prop conc, ppa 1.5 4

Average pump rate, bpm 70 51

Average pump rate per cluster, bpm 17.5 10

Pump rate per perf, bpm 1.5–2.5 1.28

CSUG/SPE 148751 7

Several papers have been written reporting the associated benefits of applying specific technology in the Eagle Ford. Baihly et al. (2010) discusses the importance of geosteering for optimum lateral placement and of lateral measurements for grouping “like” rock for selective staging and perforating. Production logging results in the Eagle Ford have shown that 21% of the perforation clusters are not producing (Miller et al. 2011). Sonic measurements have shown that the stress contrast can exceed 2,000 psi across the lateral. This contrast is the difference between the highest and lowest in-situ stress along the lateral. Selective staging and perforating can help reduce this stress contrast and thus enable more initiation into the clusters which should correspond to more effective stimulation of the lateral. For example, Fig. 9 shows the maximum stress contrast in a stage for a horizontal well in the Eagle Ford. The red bars are the stress contrast for those stages if the operator were to use geometric staging (all stages are geometrically spaced using a constant spacing). The blue bars show the stress contrast of each stage using selective staging and perforating (grouping “like” rock). The reduction in stress contrast within a stage is reduced from an average of 600 psi with geometric spacing to less than 200 psi with selective staging and perforating. In addition, the number of stages is reduced from 19 to 16, thus reducing the cost of the completion while increasing the likelihood of initiating into more perforation clusters.

Applications of new technology to the hydraulic fracture treatments have also been reported in an effort to more effectively stimulate the lateral. Inamdar et al. (2010) discusses how the “relax-a-frac” technique can help increase the production of the well by increasing the stimulated volume. In addition, a new fracturing technology which creates highly conductive channels is currently being applied in the Eagle Ford liquids rich-wells, with reported enhanced production (Petrohawk 2011).

Fig. 9—Maximum stress contrast between clusters in an Eagle Ford horizontal well using geometric staging (red) versus selective

staging by grouping “like” rock (blue). Production Trend Analysis We performed production data analysis on 826 horizontal wells in the Eagle Ford Shale using two public databases, IHS (2011) and DrillingINFO (2011). Oil and gas condensate are reported as “oil” in public databases; therefore, we will use “oil” to refer to oil and condensate. Public production data is also reported on a monthly basis. Since the industry typically uses daily rates for comparing production data, we converted the monthly production data to an average daily production rate for each respective month by dividing the monthly volumes by the number of days in the month. Martin et al. (2011) presented type curves for different areas in the Eagle Ford; however, this production analysis mainly focuses on current activity.

The first Eagle Ford horizontal well in the study began producing in 2008. Industry activity in the Eagle Ford has dramatically increased with the increase in oil price over the past couple of years. Fig. 10 shows the number of horizontal wells coming online each month from 2008 to April 2011. The number of new wells coming online each month is increasing with almost 100 new horizontal wells in April 2011. By April 2011, 826 horizontal wells produced more than 213 billion scf of gas and 21.9 million bbl of oil/condensate. We classified the producing horizontal wells in the trend as oil, condensate, or gas based on the cumulative gas-oil ratio (GOR) (Fig. 11). Reservoir classification using GOR should be based on production data at reservoir conditions; however, the cumulative GOR is a good approximation on a basin level when only production is available. For our analysis, oil wells are wells with a cumulative GOR less than 2,000 scf/bbl, and gas wells are wells with a cumulative GOR greater than 50,000 scf/bbl. Condensate wells have a cumulative GOR between 2,000 and 50,000 scf/bbl. Generally speaking, on the basis of production data, the distribution of oil, condensate, and gas wells appears to match the maturation windows presented previously.

8 CSUG/SPE 148751

Fig. 10—The number of new horizontal wells coming online each month (blue) and the cumulative horizontal well count (red) for the

Eagle Ford.

Fig. 11—Locations of producing oil, condensate, and gas wells based on GOR cutoff values.

• Oil Wells• Condensate Wells• Gas Wells

AtascosaDe Witt

Dimmit

Karnes

Webb

La Salle

Mc MullenLive Oak

Maverick

Gonzales

Wilson

Zavala Frio

Bee

All 826 horizontal wells had at least 1 month of production data, but only 578 had at least 3 months of production data. We

created cross-plots to compare short-term production indicators with long-term production indicators. We used the highest consecutive three months (B3) average rate of each well as a key performance indicator (KPI). Cross-plots of the B3 average rate versus the highest consecutive twelve months (B12) average rate were constructed to validate using B3 average rates as KPIs (Fig. 12). The R2 values for the oil and gas cross-plots are 0.93 and 0.92, respectively, indicating that the B3 average rate has a good correlation to longer-term production (at least up to 12 months of production).

CSUG/SPE 148751 9

Fig. 12—B3 average oil production and B3 average gas production.

y = 1.6668x + 4.3202R² = 0.9301

0

100

200

300

400

500

600

700

800

900

1,000

0 100 200 300 400 500 600

Best 3‐M

onth Average Oil, bbl/D

Best 12‐Month Average Oil, bbl/D

B3 vs B12 Oil Cross‐plot

Oil

y = 1.5523x + 150.43R² = 0.9168

0

1,000

2,000

3,000

4,000

5,000

6,000

7,000

8,000

9,000

0 1,000 2,000 3,000 4,000 5,000 6,000

Best 3‐M

onth Average Gas, M

scf/D

Best 12‐Month Average Gas, Mscf/D

B3 vs B12 Gas Cross‐plot

Gas

Bubble maps of the B3 average gas and oil production rates show areas with higher production (Fig. 13). The gas

production is located downdip and follows a trend to the southwest. The highest gas-producing wells are located in the southern part of La Salle County and in Webb County with the exception of one good well in Live Oak County. The highest producing oil/condensate wells are in the Karnes trough area in Live Oak, Karnes, and De Witt County. This area is a condensate area with relatively high volumes of gas. The mixture of poor producers and good producers in the same area are because of the varation in completion quality and rock quality.

It is difficult to compare different parts of the field because some areas are primarily oil and some are primarily gas. To compare the entire field, we calculated an equivalent dollar value for each well. We used USD 80 per bbl of oil/condensate, 45% of the oil price (i.e., USD 36) per bbl of natural gas liquids (NGL), and USD 4 per Mscf of gas. Areas with lower GORs will have a higher NGL processing yield than areas that are primarily natural gas. To account for this, we calculated the cumulative GOR for all the wells. All wells that had a GOR value greater than 20,000 scf/bbl were given a 12.5-bbl NGL/MMscf processing yield and a gas shrinkage factor of 10%, whereas wells with less than 20,000 scf/bbl were given a 60-bbl/MMscf processing yield and a gas shrinkage factor of 15% (Petrohawk 2011).

10 CSUG/SPE 148751

Fig. 13—The B3 average gas production bubble map (upper) and the B3 average oil production bubble map (lower), larger bubbles

indicate higher rates.

Atascosa De Witt

Dimmit

Karnes

Webb

La Salle

Mc Mullen

Live Oak

Maverick

Gonzales

Wilson

Zavala Frio

Bee

Best 3-Months Gas ( Mscf/D )

0 4000 8000

Atascosa De Witt

Dimmit

Karnes

Webb

La Salle

Mc Mullen

Live Oak

Maverick

Gonzales

Wilson

Zavala Frio

Bee

Best 3-Months Oil ( bbl/d )

0 500 1000

The equivalent dollar value is a gross revenue value. A bubble map showing the B3 price equivalent is shown in Fig. 14.

The areas with the highest estimated three-month average gross revenue are in the Karnes trough area of Live Oak, Karnes, and De Witt County. This is because of the high volumes of condensate and associated gas found there. This estimate is based on short-term production at surface conditions and does not take reservoir maintenance into consideration. Fig. 13 (lower) and Fig. 14 look very similar which probably reflects the stronger impact of the current prices of oil overt he current price of gas. The best wells are making an estimated gross revenue of USD 3 million per month during their best three-months of production. Operators are seeing a quick return with the average horizontal well drilling and completion costs at USD 6 to 8 million.

CSUG/SPE 148751 11

Fig. 14—The best 3-month average price equivalent bubble map shows the areas with the highest estimated gross revenue value. The

highest values are in the Karnes trough area of Live Oak, Karnes, and De Witt County.

Atascosa De Witt

Dimmit

Karnes

Webb

La Salle

Mc Mullen

Live Oak

Maverick

Gonzales

Wilson

Zavala Frio

Bee

Best 3-Months Average Price Equivalent ( K$US )

0 1500 3000

Rapid Asset Evaluation: A Case Study In this example, a small operator holding some promising Eagle Ford leases needed to make strategic economic decisions concerning these assets with limited data in a short period of time (less than a month). Questions that the senior management needed answered included 1) How much oil is in place? 2) What are the key production drivers? 3) How much oil can be recovered, and what is the effective drainage area from a typical horizontal well?

Despite the current practice of drilling horizontal laterals with multistage hydraulic fracture completions, this operator only had data for 20 vertical wells with triple-combo openhole logs. However, of these 20 wells only 8 had been produced from the Eagle Ford Shale without hydraulic fracture stimulation. Average initial producing GOR from these wells is about 275 scf/STB. A multidomain team of geotechnical specialists collected and reviewed all available data within the study area. A rapid asset evaluation workflow was developed to integrate all the available data and knowledge to create a reservoir model, which was then calibrated by the production data.

The logs were digitized, corrected, normalized, and interpreted. Public information about the Eagle Ford formation around the study area was also collected and reviewed. A 3D static model was constructed based on the petrophysical analyses. Good agreement was found between stratigraphic trends seen in the static model and expected trends from analogs. Sweet spots in the study area and different vertical pay zones were identified. The original oil in place calculated for the study area answered the operator’s first question. Fig. 15 shows effective porosity distribution in the study area.

Fig. 15—Effective porosity distribution in the study area.

12 CSUG/SPE 148751

Since there were no horizontal wells in the study area, vertical wells with production data were analyzed using reservoir simulation workflow developed by Fan et al. (2010). Production data from the eight vertical wells were normalized and averaged to create a “type well” production profile. Fig. 16 shows the average oil rate and cumulative production of this type well. These vertical wells have been flowing for more than 10 years at low rate with an openhole completion. This strongly indicates the existence of natural fractures, which is confirmed from a nearby Eagle Ford outcrop study. One of the objectives for the vertical well study was to help validate and define natural fracture properties in the study area.

Fig. 16—Average oil production profile of the type well.

A dual-porosity, vertical well simulation model was constructed using rock properties from the static model. The model was then calibrated to match historical oil, gas, and water production rates of the type well by mainly adjusting natural fracture properties and drainage size. Well productivity was adjusted (to reflect acid-wash jobs on these wells) as fine-tuning to help match early flush production rates. Matrix permeability, initially obtained from public information, was validated by history-matching the later production trend. Oil production rate was specified in the model as shown in Fig. 16. Reasonable history-match results were obtained for the type well. Fig. 17 illustrates the history match of the associated gas production and Fig. 18 illustrates the history match of the water production. The effective drainage area of this type well after history-matching is about 20 acres (933 ft × 933 ft), which in this case represents the extent of the natural fracture system that is connected to the wellbore.

Fig. 17—Gas production rate match. Fig. 18—Water production rate match.

The ultimate goal of the study was to assess production potential from a typical horizontal well in a target area of the Eagle Ford Shale formation. A 5,000-ft horizontal well model with 14 stages (4 perforation clusters per 320ft of stage length) of hydraulic fractures was constructed with model dimensions of 5,280 ft × 933 ft (about 120 acres). Formation properties (matrix + natural fracture) in the horizontal well model were inherited from the calibrated vertical well model. For each stage of the horizontal completion, average fracture geometry and conductivity obtained from various horizontal well reservoir

CSUG/SPE 148751 13

simulation studies in the Eagle Ford formation were used. A base-case production forecast was made to estimate potential ultimate oil and gas recovery.

Fig. 19 indicates that a properly designed and fracture stimulated 5,000-ft horizontal well in the area could potentially recover more than 600,000 bbls over a 30-year period. Since there is a lot of uncertainty in the model due to limited amount of data, sensitivity analysis is performed by varying certain parameters in the base model to determine their impact on ultimate recovery. Fig. 20 is a Tornado graph of the results of the sensitivity analysis for this example. In this case, the dominant production drivers were the presence of natural fractures and net pay thickness. The ultimate recovery was relatively insensitive to initial pressure and matrix permeability in this area. The results of the study indicated that the Eagle Ford acreage under consideration appeared to contain significant volumes of oil in place. It also provided a distribution of rock-quality, such as Fig 15, in the study area and estimated the average effective drainage area of 120 acres. It took only about 3 weeks to complete this asset evaluation study and have all the key questions answered. As a result, a firm plan was developed to maximize the asset’s value and meet the company’s strategic business objectives going forward.

Fig. 19—Horizontal well production forecast.

Natural fracture PERM, md

Net pay, feet

Hydraulic fracture PERM, md

Primary porosity, percent

Initial pressure, psi/ft

Matrix PERM, nd

Ref Case

Fig. 20—High-graded production drivers derived from the case study. Summary From a geology standpoint, key production drivers in the Eagle Ford trend are 1) the presence of a trapping mechanism such as faults, fractures, and stratigraphic traps, 2) the presence of a barrier to prevent vertical migration, 3) adequate depth of burial for maturation and accumulation, 4) a thick Eagle Ford pay section, 5) presence of natural fractures, and 6) a high calcite and quartz content that varies little through the trend, enabling successful fracture stimulation.

Most recent drilling and completion evaluations indicate that selective staging and perforating can help reduce stress contrast and thus enable more initiation into the clusters, which should correspond to more effective stimulation of the lateral. In addition, the number of stages can be reduced, thus reducing the cost of the completion while increasing the likelihood of

14 CSUG/SPE 148751

initiating into more perforation clusters. A new hydraulic fracturing technology, such as channel fracturing, is currently being applied in the Eagle Ford liquid-rich wells with reported enhanced production (Petrohawk 2011).

Production data analysis shows that the number of new wells coming online each month is continuously increasing with almost 100 new horizontal wells in April 2011. By April 2011, 826 horizontal wells produced more than 213 billion scf of gas and 21.9 million bbl of oil/condensate. The best 3-month average rate correlates well to longer-term production (at least up to 12 months of production). The highest gas-producing wells are located in the southern part of La Salle County and in Webb County. The highest producing oil/condensate wells are in the Karnes trough area in Live Oak, Karnes, and De Witt County.

By integrating data and knowledge in the Eagle Ford Shale play, a workflow was developed to generate a working model of an asset, estimate its long-term potential, and make a well-informed economic decision in time to meet critical deadlines. This process involves building reservoir and completion quality into a 3D static reservoir model, which was then calibrated by the well performance data observed in the field. In just a few weeks, the following key questions about the asset were addressed: 1) How much oil is in place? 2) What are the key production drivers? 3) How much oil can be recovered and what is the effective drainage area from a typical horizontal well? Acknowledgments We would like to dedicate this paper to Ron Martin who passed away earlier this year. Ron was not only an excellent oil and gas geologist but also a good friend to all of us. We will miss him and wish the best for his family that he has left behind.

References Baihly, J.D., Malpani, R., Edwards, C., Han, S.Y., Kok, J.C.L., Tollefsen, E.M., and Wheeler, C.W. 2010. Unlocking the Shale Mystery:

How Lateral Measurements and Well Placement Impact Completions and Resultant Production. Paper SPE 138427 presented at the Tight Gas Completions Conference, San Antonio, Texas, USA, 2-3 November. doi: 10.2118/138427-MS.

Bazan, L. W., Larkin, S.D., Lattibeaudiere, M.G., and Palisch, T.T. 2010. Improving Production in the Eagle Ford Shale with Fracture Modeling, Increased Conductivity and Optimized Stage and Cluster Spacing Along the Horizontal Wellbore. Paper SPE 138425 presented at the Tight Gas Completions Conference, San Antonio, Texas, USA, 2–3 November. doi: 10.2118/138425-MS.

Dawson, W. C. 2000. Shale Microfacies: Eagle Ford Group (Cenomanian-Turonian) North-Central Texas Outcrops and Subsurface Equivalents. Gulf Coast Association of Geological Societies Transactions. 50. 607-621.

Drilling-Info. 2011. Production, http//info.drillinginfo.com. Downloaded July 2011. Edman, J. D. and J. K. Pitman. 2010. Geochemistry of Eagle Ford Group source rocks and oils for the First Shot field area: Texas. Gulf

Coast Association of Geological Societies Transactions. 60. 217-234.

Fan, L., Thompson, J., and Robinson, J. 2010. Understanding Gas Production Mechanism and Effectiveness of Well Stimulation in the Haynesville Shale Through Reservoir Simulation. Paper SPE 136696 presented at the Canadian Unconventional Resources & International Petroleum Conference, Calgary, Alberta, Canada, 19–21 October. doi: 10.2118/136696-MS.

IHS Energy. 2011. Enerdeq, http//energy.ihs.com/Products/Enerdeq/. Downloaded July 2011. Inamdar, A., Malpani, R., Atwood, K., Brook, K., Erwemi, A., Ogundare, T., and Purcell, D. 2010. Evaluation of Stimulation Techniques

Using Microseismic Mapping in the Eagle Ford Shale. Paper SPE 136873 presented at the Tight Gas Completions Conference, San Antonio, Texas, USA, 2–3 November. doi: 10.2118/136873-MS.

Lock, B.E. and Peschier, L. 2006. Boquillas (Eagle Ford) Upper Slope Sediments, West Texas: Outcrop Analogs for Potential Shale

Reservoirs. Gulf Coast Association of Geological Societies Transactions. 56. 491-508.

Martin, R, Baihly, J., Malpani, R., Lindsay, G., and Atwood, W.K. 2011. Understanding Production from Eagle Ford-Austin Chalk System. Paper SPE 145117 presented at the Annual Technical Conference and Exhibition, Denver, Colorado, USA, 30 October–2 November. doi: 10.2118/145117-MS.

Miller, C., Water, G., and Rylander, E. 2011. Evaluation of Production Log Data from Horizontal Wells Drilled in Organic Shales. Paper SPE 144326 presented at the North American Unconventional Gas Conference and Exhibition, The Woodlands, Texas, USA, 14–16 June. doi: 10.2118/144326-MS.

Petrohawk. 2011. http://www.petrohawk.com/Investor-Relations/presentations.aspx. Downloaded 20 June 2011. Scott, R.J. 2004. The Maverick Basin: New Technology—New Success. Gulf Coast Association of Geological Societies Transactions. 54.

603-620.

CSUG/SPE 148751 15

Thompson, J.W., Fan, L., Grant, D., Kanneganti, K.T. and Lindsay, G.J. 2010. An Overview of Horizontal Well Completions in the Haynesville Shale. Paper SPE 136875 presented at the Canadian Unconventional Resources & International Petroleum Conference, Calgary, Alberta, Canada, 19–21 October. doi: 10.2118/136875-MS.

Tuttle, S. 2010. Oil Resource Plays – Examples and Technology. Society of Independent Professional Earth Scientists: Houston Chapter. 24 September.

SI Metric Conversion Factors acre × 4.046 873 E + 03 = m2 bbl × 1.589 873 E – 01 = m3 ft × 3.048* E – 01 = m gal × 3.785 412 E – 03 = m3 lbm × 4.535 924 E – 01 = kg psi × 6.894 757 E + 00 = kPa scf/bbl × 1.801 175 E – 01 = m3/m3

scf/D × 2.863 640 E – 02 = m3/s *Conversion factor is exact