1887
  1. Home
  2. A-Z Publications
  3. First Break
  4. Volume 39, Issue 1
  5. Article
Volume 39 Number 1
  • ISSN: 0263-5046
  • E-ISSN: 1365-2397

Abstract

Abstract

Brittleness is a key property for horizontal well placement, fracture development, and production sustainability assessments of unconventional shale and gas plays. Conventionally, brittleness is estimated from Young’s modulus and Poisson’s ratio, and averaged. As Young’s modulus is a function of density, field wide brittleness estimation from Young’s modulus after seismic inversion may be compromised because density is the least accurate estimate compared to acoustic impedance and shear impedance. A simple quantitatively equivalent brittleness computation can be made from using Young’s modulus × density rather than directly from Young’s modulus. Further, it is preferable to use the average brittleness estimation from Young’s modulus × density and shear modulus × density rather than the conventional average, because Poisson’s ratio is an indicator of lithology rather than brittleness. Examples of brittleness and total organic carbon estimation first from well logs, then from rock parameters inverted from 3D land seismic data successfully mapped a brittle shale zone in a Silurian hot shale, a known source rock onshore Turkey and now targeted as oil shale play. The estimated brittleness and total organic carbon showed agreement with the core analysis made at another well on the same prospect.

EAGE Publications BV
Loading

Article metrics loading...

/content/journals/10.3997/1365-2397.fb2021001
2021-01-01
2024-04-25

  • From This Site

    /content/journals/10.3997/1365-2397.fb2021001
    dcterms_title,dcterms_subject,pub_keyword
    -contentType:Journal -contentType:Contributor -contentType:Concept -contentType:Institution
    10
    5
Loading full text...

Full text loading...

References

  1. Altamar, R.P.
    [2013] Brittleness Estimation from Seismic Measurements in Unconventional Reservoirs: Application to the Barnett Shale: PhD theses, University of Oklahoma.
     [Google Scholar]
  2. Altındağ, R.
    [2003] Correlation of specific energy with rock E concepts on rock cutting:The Journal of South African Institute of Mining and Metallurgy, April, 163–171.
     [Google Scholar]
  3. Altındağ, R. and Güney, A.
    [2010] Predicting the relationships between E and mechanical properties (UCS, TS and SH) of rocks:Scientific Research Essays, 5, 2107–2118.
     [Google Scholar]
  4. Archie, G.E.
    [1942] The electrical resistivity log as an aid in determining some reservoir characteristics:Petroleum Technology, 1, 55–67.
     [Google Scholar]
  5. Arpacı, T. and Özdemir, H.
    [2020] Step-out well positioning using hydrocarbon indicators from seismic inversion: a case study:First Break, 38(1), 43–51.
     [Google Scholar]
  6. Bai, M.
    [2016] Why are brittleness and fracability not equivalent in designing hydraulic fracturing in tight shale gas reservoirs:Petroleum, 2, 1–19.
     [Google Scholar]
  7. Beckwith, R.
    [2012] The tantalizing promise of shale:Journal of Petroleum Technology, 64(1), 30–36. http://www.spe.org/jpt/print/archives/2012/01/10OilShales.pdf
     [Google Scholar]
  8. Bowman, T.D.
    [2010] Direct method for determining organic shale potential from porosity and R logs to identify possible resource plays:http://www.searchanddiscovery.net/documents/2010/110128bowman/ndx_bowman.pdf
     [Google Scholar]
  9. [2011] Hydrocarbon potential of Upper Cretaceous shale sections, including the Eagle Ford, Woodbine and Maness Shale, Central Texas:AAPG Annual Convention and Exhibition, Search and Discovery Article10328.
     [Google Scholar]
  10. Broadhead, M.K., Cheshire, S.G. and Hayton, S.
    [2016] The effect of TOC on acoustic impedance for a Middle Eastern source rock:The Leading Edge, 35(3), 258–264.
     [Google Scholar]
  11. Buller, D., Suparman, F.N.U., Kwong, S., Spain, D. and Miller, M.
    [2010] A Novel Approach to Shale-Gas Evaluation Using a Cased-Hole Pulsed Neutron Tool:51st SPWLA Annual Logging Symposium, Paper 87257.
     [Google Scholar]
  12. Bustin, R.M., Bustin, A., Ross, D., Chalmers, G., Murthy, V., Laxmi, C. and Cui, X.
    [2009] Shale Gas Opportunities and Challenges:AAPG Search and Discovery Article 40382. http://www.searchanddiscovery.com/documents/2009/40382bustin/ndx_bustin.pdf
     [Google Scholar]
  13. Carcione, J.M., Ursin, B. and Nordskag, J.I.
    [2007] Cross-property relations between electrical conductivity and the seismic velocity of rocks:Geophysics, 72(5), E193–E204.
     [Google Scholar]
  14. Cho, D. and Perez, M.
    [2014] Brittleness revisited: GeoConvention2014: FOCUS, Extended Abstract.
     [Google Scholar]
  15. Close, D., Perez, M., Goodway, W. and Purdue, G.
    [2012] Integrated workflows for shale gas and case study results for the Horn River Basin, British Columbia, Canada:The Leading Edge, 31(5), 493–612.
     [Google Scholar]
  16. Convers, C., Davis, T., Tura, A., Curia, D. and Hanitzsch, C.
    [2019] Elastic parameter estimation for sweet spot identification in unconventional shale plays, Vaca Muerta Formation, Neuquén Basin, Argentina:89th SEG Annual Meeting and International Exposition, Expanded Abstracts, 3730–3734.
     [Google Scholar]
  17. Convers, C., Hanitzsch, C., Curia, D., Davis, T. and Tura, A.
    [2017] Elastic parameter estimation for the identification of sweet spots, Vaca Muerta Formation, Neuquén Basin, Argentina:The Leading Edge, 36(11), 948a1–948a10.
     [Google Scholar]
  18. Dębski, W. and Tarantola, A.
    [1995] Information on elastic parameters obtained from the amplitudes of reflected waves:Geophysics, 60(5), 1426–1436.
     [Google Scholar]
  19. Delaplanche, J., Hagemann, R.F. and Bollard, P.G.C.
    [1963] An example of the use of synthetic seismograms:Geophysics, 28(5), 842–854.
     [Google Scholar]
  20. EIA Report
    EIA Report [2012] Technically Recoverable Shale Oil and Shale Gas Resources: An Assessment of 137 Shale Formations in 41 Countries Outside the United States:US Department of Energy, Energy Information Administration (EIA). https://www.eia.gov/analysis/studies/worldshalegas/pdf/fullreport.pdf
     [Google Scholar]
  21. Engelmark, F.
    [2010] Velocity to R transform via porosity:80th SEG Annual Meeting, Expanded Abstract, 2501–2505.
     [Google Scholar]
  22. Faust, L.Y.
    [1953] A velocity function including lithologic variation:Geophysics, 18, 271–288.
     [Google Scholar]
  23. Flower, J.G.
    [1983] Use of sonic-shear-wave/resistivity overlay as a quick-look method for identifying pay zone in the Ohio (Devonian) Shale:Journal of Petroleum Technology, 35(3), 638–642.
     [Google Scholar]
  24. Gonzalez, J., Lewis, R., Hemingway, J., Gray, J., Rylander, E. and Schmitt, R.
    [2013] Determination of formation organic carbon content using a new neutron-induced gamma ray spectroscopy service that directly measures carbon:54th SPWLA Annual Logging Symposium.
     [Google Scholar]
  25. Goodway, W.
    [2007] A tutorial on AV O and Lamé constants for rock parameterization and fluid detection: Geophysical Society of Alaska, http://gsa.seg.org/pdf_forms/RecorderJune2001LMRAVO_new-2007july.pdf.
     [Google Scholar]
  26. [2009] The Magic of Lamé: SEG North American Honorary Lecture.http://www.seg.org/education/online-education/online-presentations/dl-presentations/goodwaypresentation
     [Google Scholar]
  27. Goodway, W., Perez, M., Varsek, J. and Abaco, C.
    [2010] Seismic petro-physics and isotropic-anisotropic AVO methods for unconventional gas exploration:The Leading Edge, 29(12), 1500–1508.
     [Google Scholar]
  28. Goodway, W., Varsek, J. and Abaco, C.
    [2007] Isotropic AVO methods to detect fracture prone zones in tight gas resource plays: CSPG CSEG Convention, Expanded Abstracts, 585–589.
     [Google Scholar]
  29. Gray, D., Anderson, P., Logel, J., Delbecq, F., Schmidt, D. and Schmid, R.
    [2012] Estimation of stress and geomechanical properties using 3D seismic data:First Break, 30(3), 59–68.
     [Google Scholar]
  30. Hacıköylü, P., Dvorkin, J. and Mavko, G.
    [2006] R-velocity transform revisited:The Leading Edge, 25(8), 1006–1009.
     [Google Scholar]
  31. Hall, M.
    [2013] Which E index? http://www.agilegeoscience.com/journal/2013/12/3/which-E-index.html
  32. Han, T., Best, A., MacGregor, L.M., Sothcott, J. and Minshull, T.
    [2010] Joint velocity- R effective medium models:72nd EAGE Conference and Exhibition, Extended Abstract I007.
     [Google Scholar]
  33. Harris, N. B.
    [2015] Shale Velocity and Density as Functions of TOC and Thermal Maturity. Upper Devonian Woodford Shale, Permian Basin, Texas:AAPG, Search and Discovery Article51124.
     [Google Scholar]
  34. Harris, N.B., Miskimins, L.L. and Mnich, C.A.
    [2011] Mechanical anisotropy in the Woodford Shale, Permian Basin. Origin, magnitude, and scale:The Leading Edge, 30 (3), 284–291.
     [Google Scholar]
  35. Heath-Clarke, M., Taylor, K., Harrison, D., Fogg, A., Hughes, F., Haarhoff, M. and Mortimer, A.
    [2016] The characterization of unconventional reservoirs in the Bowland sequence using onshore 3D seismic data, Cleveland Basin, UK:First Break, 34 (3), 45–52.
     [Google Scholar]
  36. Herwanger, J.V., Bottrill, A.D. and Mildren, S.D.
    [2015] Uses and abuses of the E index with applications to hydraulic stimulation:Unconventional Resources Technology Conference, URTeC 2172545, Expanded Abstracts, 1215–1223.
     [Google Scholar]
  37. Hu, Y., Perdomo, G., Wu, K., Chen, Z., Zhang, K., Ji, D. and Zhong, H.
    [2015a] A novel model of brittleness index for shale gas reservoirs: Confining pressure effect:SPE Asia Pacific Unconventional Resources Conference and Exhibition, Paper 176886.
     [Google Scholar]
  38. Hu, Y., Perdomo, G., Wu, K., Chen, Z., Zhang, K.
    [2015b] New models of Brittleness Index for shale gas reservoir: weights of brittle minerals and rock mechanics parameters.SPE Asia Pacific Unconventional Resources Conference and Exhibition, Paper 177010.
     [Google Scholar]
  39. Issler, D. R., Hu, K., Bloch, J.D. and Katsube, J.T.
    [2002] Organic carbon content determined from well logs. Examples from Cretaceous sediments of Western Canada: Geological Survey of Canada, Open File 4362. http://ftp.geogratis.gc.ca/pub/nrcan_rncan/publications/ess_sst/213/213654/gscof_4362_e_2002_pr01.pdf
     [Google Scholar]
  40. Jarvie, D.M.
    [1991] Total Organic Carbon (TOC) analysis, in Source and migration processes and evaluation techniques,
     [Google Scholar]
  41. Merrill, R.K.
    (Ed.), Treatise of Petroleum Geology:AAPG Bulletin, 113–118. http://www.sciepub.com/reference/1617055 and https://www.researchgate.net/publication/309758283_Interpreting_Total_Organic_Carbon_TOC_in_Source_Rock_Oil_Plays
     [Google Scholar]
  42. Jarvie, D.M., Hill, R.J., Ruble, T.E. and Pollastro, R.M.
    [2007] Unconventional shale-gas systems. the Mississippian Barnett Shale of North-Central Texas as one model for thermogenic shale-gas assessment:AAPG Bulletin, 91(4), 475–499.
     [Google Scholar]
  43. Jenkins, C., Ouenes, A., Zellou, A. and Wingard, J.
    [2009] Quantifying and predicting naturally fractured reservoir behavior with continuous fracture models:AAPG Bulletin93(11), 1597–1608.
     [Google Scholar]
  44. Løseth, H., Wensaas, L., Gading, M., Duffaut, K. and Springer, M.
    [2011] Can hydrocarbon source rocks be identified on seismic data?Geology, 39(12), 1167–1170.
     [Google Scholar]
  45. Lüning, S. and Kolonic, S.
    [2003] Uranium spectral Gamma-ray response as a proxy for organic richness in black shales:Journal of Petroleum Geology, 26(2), 153–174.
     [Google Scholar]
  46. Mathia, E., Ratcliffe, K. and Wright, M.
    [2016] Brittleness index – A parameter to embrace or avoid?Unconventional Resources Technology Conference, URTeC, 2448745, 1156–1165.
     [Google Scholar]
  47. Mavko, G. and Mukerji, T.
    [1998] A rock physics strategy for quantifying uncertainty in common hydrocarbon indicators:Geophysics, 63(6), 1997–2008.
     [Google Scholar]
  48. Mendelson, J.D. and Toksöz, M.N.
    [1985] Source rock characterizations using multivariate analysis of log data:26th SPWLA Annual Logging Symposium, 1–21.
     [Google Scholar]
  49. Meyer, B.L. and Nederlof, M.H.
    [1984] Identification of source rocks on wireline logs by density/R and sonic transit/R crossplots:AAPG Bulletin, 68, 121–129.
     [Google Scholar]
  50. Miskimins, J.L.
    [2009] The importance of geophysical and petrophysical data integration for the hydraulic fracturing of unconventional reservoirs:The Leading Edge, 28(7), 844–849.
     [Google Scholar]
  51. [2012] The impact of mechanical stratigraphy on hydraulic fracture growth and design considerations for horizontal wells:AAPG Search and Discovery Article 41102.
     [Google Scholar]
  52. Nash, S.S.
    [2013] A Compilation of articles on shale plays and unconventional resources. The role of access and the making of normative standards: AAPG Annual Convention and Exhibition, Search and Discovery Article 70135.
     [Google Scholar]
  53. Özdemir, H., Flanagan, K. and Tyler, E.
    [2010] Lithology and hydrocarbon mapping from multicomponent seismic data:Geophysical Prospecting, 58(2), 297–306.
     [Google Scholar]
  54. Özdemir, H., Hansen, J.W. and Tyler, E.
    [2006] Rock and reservoir parameters from pre-stack inversion of surface seismic data:First Break, 24(10), 83–87.
     [Google Scholar]
  55. Passey, Q.R., Creaney, S., Kulla, J.B., Moretti, F.J. and Stroud, J.D.
    [1990] A practical model for organic richness from porosity and R logs:AAPG Bulletin, 74, 1777–1794.
     [Google Scholar]
  56. Passey, Q.R., Bohaces, K.M., Esch, W.L., Klimentidis, R. and Sinha, S.
    [2010] From oil-prone source rock to gas-producing shale reservoir, geologic and petrophysical characterization of unconventional shale gas reservoirs: SPE Paper 131350.
     [Google Scholar]
  57. [2012] My source rock is now my reservoir – geologic and petrophysical characterization of shale-gas reservoirs: Search and Discovery Article 80231.
     [Google Scholar]
  58. Perez, R.A.
    [2010] Application of LMR inversion and clustering analysis in the Barnett Shale:80th SEG Technical Program, Expanded Abstracts, 2236–2239.
     [Google Scholar]
  59. [2013] E Estimation from Seismic Measurements in Unconventional Reservoirs. Application to the Barnett Shale: PhD thesis, University of Oklahoma.
     [Google Scholar]
  60. [2014] Seismic E index volume estimation from well logs in unconventional reservoirs: AAPG Annual Convention and Exhibition, Search and Discovery Article 80381.
     [Google Scholar]
  61. Perez, M., Close, D., Goodway, W. and Purdue, G.
    [2011] Developing templates for integrating quantitative geophysics and hydraulic fracture completions data. Part I- Principles and theory:81st SEG Technical Program Expanded Abstracts, 1794–1798.
     [Google Scholar]
  62. Perez, R.A. and Marfurt, K.
    [2013a] E estimation from seismic measurements in unconventional reservoirs. Application to the Barnett Shale:83rd SEG Technical Program Expanded Abstracts, 2258–2263.
     [Google Scholar]
  63. [2013b] Calibration of brittleness to elastic rock properties via mineralogy logs in unconventional reservoirs:AAPG International Conference and Exhibition, Paper 41237.
     [Google Scholar]
  64. [2014] Mineralogy-based brittleness prediction from surface seismic data: Application to the Barnett Shale:Interpretation, 2(4), T255–T271.
     [Google Scholar]
  65. [2015] Identification of brittle/ductile areas in unconventional reservoirs using seismic and microseismic data. Application to the Barnett Shale:Interpretation, 3(4), T233–T243.
     [Google Scholar]
  66. Pitcher, J. and Buller, D.
    [2012] Shale Assets. Applying the Right Technology for Improving Results:AAPG Search and Discovery Article 40883.
     [Google Scholar]
  67. Rickman, R., Mullen, M., Petre, E., Grieser, B. and Kundert, D.
    [2008] A practical use of shale petrophysics for stimulation design optimization. All shale plays are not clones of the Barnett Shale:SPE Annual Technical Conference and Exhibition, SPE Paper 115258.
     [Google Scholar]
  68. Rudman, A.J., Whaley, J.F., Blakely, R.F. and Biggs, M.E.
    [1975] Transformation of R to pseudovelocity logs:The American Association of Petroleum Geologists Bulletin, 59(7), 1151–1165.
     [Google Scholar]
  69. Sayers, C.M.
    [2002] The effect of anisotropy on the Young’s moduli and Poisson’s ratios of shales:72nd SEG Annual Meeting, Expanded Abstract, 2606–2611.
     [Google Scholar]
  70. [2010] Geophysics under stress. Geomechanical applications of seismic and borehole acoustic waves: DISC, SEG/EAGE publication.
     [Google Scholar]
  71. Sayers, C.M., Johnson, G.M. and Denyer, G.
    [2002] Predrill pore-pressure prediction using seismic data:Geophysics, 67(4), 1286–1292.
     [Google Scholar]
  72. Sharma, R. K. and Chopra, S.
    [2015] Determination of lithology and brittleness of rocks with a new attribute:The Leading Edge, 34(5), 936–941.
     [Google Scholar]
  73. [2016] Identification of sweet spots in shale reservoir formations:First Break, 34(9), 43–51.
     [Google Scholar]
  74. Tarantola, A.
    [1986] A strategy for nonlinear elastic inversion for seismic reflection data:Geophysics, 51(10), 1983–1903.
     [Google Scholar]
  75. Thomsen, L.
    [1986] Weak elastic anisotropy:Geophysics, 51, 10, 1954–1966.
     [Google Scholar]
  76. Tütüncü, A. N., Krohn, C., Gelinsky, S., Leveille, J., Esmersoy, C. and Mese, A. I.
    [2012] Environmental challenges in fracturing unconventional resources:The Leading Edge, 31(10), 898–906.
     [Google Scholar]
  77. Ursin, B. and Carcione, J.M.
    [2007] Seismic-Velocity/Electrical-Conductivity relations: EGM International Workshop, Extended Abstract.http://www.eageseg.org/data/egm2007/Sessione%20D/Oral%20papers/D_OP_01.pdf
     [Google Scholar]
  78. Venedik, G. and Özdemir, H.
    [2017] Brittleness computation without density for unconventional resource development:79th EAGE Conference and Exhibition, Extended Abstract Th D1 14.
     [Google Scholar]
  79. Verma, S., Roy, A., Perez, R. and Marfurt, K
    [2012] Finding high frackability and TOC zones in Barnett shale with supervised probabilistic neural network and unsupervised multi-attribute Kohonen SOM:82nd SEG Technical Program, Expanded Abstracts.
     [Google Scholar]
  80. VernikL., NurA.
    [1992] Ultrasonic velocity and anisotropy of hydrocarbon source rock:Geophysics, 57(5), 727–735.
     [Google Scholar]
  81. Waldo, D.
    [2012] A review of three North American shale plays: learnings from shale gas exploration in the Americas:AAPG Search and Discovery Article 80214. http://www.searchanddiscovery.com/documents/2012/80214waldo/ndx_waldo.pdf
     [Google Scholar]
  82. Wang, H.Q.
    [2016] Brittleness prediction of tight reservoir with product of Young modulus and density:78th EAGE Conference and Exhibition, Extended Abstract Th LHR3 15.
     [Google Scholar]
  83. Wang, F.P. and Gale, J.F.W.
    [2009] Screening criteria for shale-gas systems:GCAGS Transactions, 59, 779–793.
     [Google Scholar]
  84. Wang, L. and Zhang, F.
    [2016] A new lithology-E evaluation method based on statistical rock physics - Combine mineralogy and elastic modulus:78th EAGE Conference and Exhibition, Extended Abstract We SBT3 01.
     [Google Scholar]
  85. Yang, Y., Sone, H., Hows, A., and Zoback, M.D.
    [2013] Comparison of brittleness indices in organic-rich shale formations: US Rock Mechanics and Geomechanics Symposium, Paper ARMA 13-403.
     [Google Scholar]
  86. Yasin, Q., Ismail, A., Du, Q. and Abid, M.
    [2016] Brittleness prediction based on rock’s properties – Application to Sembar shale.SEG Technical Conference.At Kanagawa, Japan.
     [Google Scholar]
  87. Yasin, Q., Du, Q., Sohail, G. and Ismail, A.
    [2017] Impact of organic contents and brittleness indices to differentiate the brittle-ductile transitional zone in shale gas reservoir:Geosciences Journal, June, 1–11.
     [Google Scholar]
  88. Zhang, D., Ranjith, P.G. and Perera, M.S.A.
    [2016] The brittleness indices used in rock mechanics and their application in shale hydraulic fracturing: A review:Journal of Petroleum Science and Engineering, 143, 158–170.
     [Google Scholar]
  89. Zhu, Y. Liu, E., Martinez, A., Payne, M.A. and Harris, C.E.
    [2011] Understanding geophysical responses of shale-gas plays:The Leading Edge, 30(3), 332–338.
     [Google Scholar]
http://instance.metastore.ingenta.com/content/journals/10.3997/1365-2397.fb2021001
Loading
Brittleness computation from rock moduli without density
First Break 39, 39 (2021); https://doi.org/10.3997/1365-2397.fb2021001
/content/journals/10.3997/1365-2397.fb2021001
/content/journals/10.3997/1365-2397.fb2021001
Loading

Data & Media loading...

  • Article Type: Research Article

Most Cited This Month Most Cited RSS feed

This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error