Quantifying Commingled Oil Production from Eagle Ford and Buda Reservoirs in a South Texas Horizontal Well Using Oil Fingerprinting Technology

Transcription

1 Quantifying Commingled Oil Production from Eagle Ford and Buda Reservoirs in a South Texas Horizontal Well Using Oil Fingerprinting Technology David K. Baskin, Alan S. Kornacki, and Mark A. McCaffrey Presented by Daniel Boyde daniel.boyde@weatherfordlabs.com For contact information, please visit our website:

2 Premise: Naturally occurring geochemical differences can be used to distinguish oils (or gases) from discrete reservoirs. These geochemical differences can serve as natural tracers for the contribution of each zone to comingled production in a single well Or Contribution of each reservoir to commingled production from a group of reservoirs.

3 Thirsty? Sugar Content 50% 0% Sugar Content 10% 20% Orange/80% Water

4 Mixology Sugar Content 50% 0% 20% Ca(OH) 2 Content 0.1% 0% 0.2% 17% 0.043% 30% Orange/50% Water/20% Cranberry

5 Mocktail Night

6 Oil: Whole Oil GC Data C4 C36+ and isomers Stable Isotope Data (δ13c) Water: Major Ion Composition (Cl -, Br -, Na +, Mg 2+, etc.) Stable Isotope Data (δd, δ 18 O, 86 Sr/ 87 Sr) Gas: Gas Component Abundances (e.g., %C1, C2, CO 2, N 2, etc) Stable Isotope Data (δd, δ 13 C)

7 N C Geochemical Allocation

8 Oils in separate reservoirs with the same source will not have been generated at precisely the same maturity or from precisely the same facies. As a piece of source rock matures, the oil it generates continually changes, imparting differences to oils in separate compartments. Which interval (source facies) is generating also changes through time. Compartments differ in size and location, they will have slightly different filling histories. Inter-compartment differences in post-migration processes (water washing, biodegradation, fractional evaporation, etc.) create unique compositions. Two oils can be 99% similar, and still have 50 compositional differences, and each one of those differences can serve as a natural tracer for that oil

9 Fiscal Allocation NK-43 Sag vs NOP Oil Splits 100.0% 90.0% 80.0% 70.0% 60.0% 50.0% 40.0% 30.0% 20.0% 10.0% 0.0% 10/25/2005 2/2/2006 5/13/2006 8/21/ /29/2006 3/9/2007 6/17/2007 Sag Geochem NOP Geochem Sag PLT NOP PLT

10 Re-Application Method proved in conventional reservoirs for fiscal allocation. Transfer to Unconventional domain? Fluid migration Charging history Compartmentalisation Communication Frac integrity

11 18 Well Locations in Frio County and La Salle County, Texas

12 NC9 NC10 NC11 NC12 NC13 NC14 NC15 NC16 NC17 NC18 NC19 NC20 NC21 NC22 NC23 NC24 NC25 NC26 NC27 NC28 NC29 NC30 NC31 NC32 NC33 NC34 NC35 NC36 NC37 NC38 NC39 NC40 NC12 NC13 NC14 NC15 NC16 NC17 NC18 NC19 NC20 NC21 NC22 NC23 NC24 NC25 NC26 NC27 NC28 NC29 NC30 NC31 NC32 NC33 NC34 NC35 NC36 NC37 NC38 NC39 NC40 NC10 NC11 NC9 NC8 NC8 NC7 NC7 NC6 NC6 NC4 NC5 NC9 NC10 NC11 NC12 NC13 NC14 NC15 NC16 NC17 NC18 NC19 NC20 NC21 NC22 NC23 NC24 NC25 NC26 NC27 NC28 NC29 NC30 NC31 NC32 NC33 NC34 NC35 NC36 NC37 NC38 NC39 NC40 NC8 NC7 NC6 Geochemical Allocation Whole-oil gas chromatograms do not differentiate oils produced from the Eagle Ford or the Buda Formation. Austin Chalk oils are slightly different Sample NC4 NC Eagle Ford GC Run # : G Well No.: Burns Ranch A-5H Date: 5/15/11 Field: Brisco Ranch Formation: Eagle Ford Sample ID: Sample BD Austin Chalk GC Run # : G Well No.: Spetell Bendele 1 Date: Field: Pearsall (Austin Chalk) Formation: Austin Chalk Sample ID: BD File: G D\FID1A.CH Date & Time: 01-Jul-11, 22:31:41 Sample NC4 NC Buda GC Run # : G Well No.: Lancaster C 1H Date: 11/30/10 Field: Pearsall (Buda) Formation: Buda Sample ID: File: G D\FID1A.CH Date & Time: 02-Jul-11, 22:40: File: G D\FID1A.CH Date & Time: 03-Jul-11, 03:30:

13 Buda Fm Eagle Ford (LaSalle Co.) Austin Chalk Eagle Ford (Frio Co.)

14 Star Diagram Comparing Absolute Compositional Differences among the Oils Star Diagram Illustrating Differences Between Oils Produced from the Austin Chalk, the Eagle Ford Formation, and the Buda Formation Ratio A/B 2.5 Burns A-1H ( Burns Ranch Ratio R/Q 2.0 Ratio E/F Pan Am B 1H Pedro Morale 1.5 Hilldebrand 4 Shiner Ranch 1.0 Lancaster C 1 Pals 9 (Buda Ratio O/P 0.5 Ratio C/D 0.0 Ratio L/N Ratio H/G Ratio K/M Ratio I/J

15 Five Oil Groups Were Identified Using Hierarchical Clustering Analysis Group 5 Edwards Lime oil from White Kitchen Field, LaSalle Co. Group 4 Austin Chalk oils from Pearsall, Field, Frio Co. Group 3 Eagle Ford oils from Pearsall Field, Frio Co. Group 2 Buda oils from Pearsall Field, Frio Co. Group 1 Eagle Ford oils from Brisco Ranch Field, LaSalle Co.

16 Donovan and Staerker (2010) GCAGS Trans. 60, Lower Eagle Ford SR generates/retains low-maturity oil Eagle Ford expels low-maturity oil into fractured Buda reservoir Lower Eagle Ford Source Rock/Reservoir Lower Eagle Ford Source Rock/Reservoir Lower Eagle Ford Source Rock/Reservoir Buda Reservoir (Fractured Carbonate) Eagle Ford kerogen generates higher-maturity oil -- expelling low-maturity oil it had retained Lower Eagle Ford Source Rock/Reservoir Buda Reservoir Wet Buda Reservoir Eagle Ford expels some highermaturity oil into Buda which mixes with the low-maturity oil Lower Eagle Ford Source Rock/Reservoir (Incremental Charge) Buda Reservoir (Cumulative Charge) Buda Reservoir Shale Reservoir HC Charge Model Proposed by Harris Cander (BP) Oils in Eagle Ford and Buda reservoirs have different fingerprints

17 Buda end-member Modeling Mixing of Oil Produced from Eagle Ford and Buda Reservoirs: Burns Ranch A-4H Well Eagle Ford end-members Duplicate GC analysis analytical precision

18 Assuming the Burns Ranch A-7H oil sample is an end-member oil in the Eagle Ford reservoir and the Pals 9 oil sample is an end-member oil in the Buda reservoir, the Eagle Ford oil sample produced from the Burns Ranch A-4H well actually contains ~11.5% Buda oil.

19 No contribution from Buda end-member Buda end-member Modeling Mixing of Oil Produced from Eagle Ford and Buda Reservoirs: Pan C 1H Well Eagle Ford end-members

20 Observations and Conclusions Oil fingerprinting differentiates oils produced from Austin, Eagle Ford, and Buda reservoirs into distinct groups. Statistical analysis of GC data obtained on a suite of oils produced from a shale reservoir can identify oil samples whose composition represent the oil retained by that reservoir. Fingerprinting can identify oil samples that contain oil produced from a different reservoir than the shale reservoir in which a horizontal well was drilled and completed. Incremental vs. cumulative HC charge models probably explain why the oil a source rock expels into a conventional reservoir is slightly different than the oil retained by that source rock.

21 Recommendations Implement sampling programs to regularly collect high-quality oil samples produced from nearby horizontal wells completed in the Eagle Ford Formation, and in adjacent reservoirs. Apply fingerprinting technology using high-resolution GC data obtained on the oil samples. Use HCA method to identify oil groups, and to identify end-member oil samples within each group. Use allocation software to determine if the least-similar oil samples within a group are mixtures of end-member oils from different groups.

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