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DHI evaluation by combining rock physics simulation and statistical techniques for fluid identification of Cambrian-to-Cretaceous clastic reservoirs in Pakistan

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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
The use of seismic direct hydrocarbon indicators is very common in exploration and reservoir development to minimise exploration risk and to optimise the location of production wells. DHIs can be enhanced using AVO methods to calculate seismic attributes that approximate relative elastic properties. In this study, we analyse the sensitivity to pore fluid changes of a range of elastic properties by combining rock physics studies and statistical techniques and determine which provide the best basis for DHIs. Gassmann fluid substitution is applied to the well log data and various elastic properties are evaluated by measuring the degree of separation that they achieve between gas sands and wet sands. The method has been applied successfully to well log data from proven reservoirs in three different siliciclastic environments of Cambrian, Jurassic, and Cretaceous ages. We have quantified the sensitivity of various elastic properties such as acoustic and extended elastic (EEI) impedances, elastic moduli (Ksat and Ksat – μ), lambda–murho method (λρ and μρ), P-to-S-wave velocity ratio (VP/VS), and Poisson’s ratio (σ) at fully gas/water saturation scenarios. The results are strongly dependent on the local geo-logical settings and our modeling demonstrates that for Cambrian and Cretaceous reservoirs, Ksat – μ, EEI, VP/VS, and σ are more sensitive to pore fluids (gas/water). For the Jurassic reservoir, the sensitivity of all elastic and seismic properties to pore fluid reduces due to high overburden pressure and the resultant low porosity. Fluid indicators are evaluated using two metrics: a fluid indicator coefficient based on a Gaussian model and an overlap coefficient which makes no assumptions about a distribution model. This study will provide a potential way to identify gas sand zones in future exploration.
Czasopismo
Rocznik
Strony
991--1007
Opis fizyczny
Bibliogr. 44 poz.
Twórcy
autor
  • Institute of Geology, University of the Punjab, Lahore, Pakistan
autor
  • Institute of Geology, University of the Punjab, Lahore, Pakistan
  • Institute of Geology, University of the Punjab, Lahore, Pakistan
autor
  • Patrick Connolly Associates Ltd., Berkshire, UK
Bibliografia
  • 1. Ahmed N, Khalid P, Ghazi S, Anwar AW (2015) AVO forward modeling and attributes analysis for fluid’s identification: a case study. Acta Geod Geophys 50(4):377–390. doi: 10.1007/s40328-014-0097-x
  • 2. Ahmed N, Khalid P, Ali T, Ahmad SR, Akhtar S (2016) Differentiation of pore fluids using amplitude versus offset attributes in clastic reservoirs, Middle Indus Basin, Pakistan. Arab J Sci Eng 41(6):2315–2323. doi: 10.1007/s13369-015-1992-3
  • 3. Aki K, Richards PG (1980) Quantitative seismology: theory and methods. W. H. Freeman, San Francisco
  • 4. Archie GE (1942) The electrical resistivity log as an aid in determining some reservoir characteristics. Trans Am Inst Mech Eng 146(1):54–62
  • 5. Avseth P, Mukerji T, Mavko G (2005) Quantitative seismic interpretation. Cambridge University Press, Cambridge
  • 6. Baddari K, Bellalem F, Baddari I, Makdeche S (2016) Some probabilistic and statistical properties of the seismic regime of Zemmouri (Algeria) seismoactive zone. Acta Geophys 64(5):1275–1310. doi: 10.1515/acgeo-2016-0049
  • 7. Baig MO, Harris NB, Ahmed H, Baig MOA (2016) Controls on reservoir diagenesis in the Lower Goru Sandstone Formation, Lower Indus Basin, Pakistan. J Petrol Geol 39(1):29–48. doi: 10.1111/jpg.12626
  • 8. Baqri SRH, Baloch MQ (1991) Sedimentological studies and palaeo environments of Khewra Sandstone with reference to its hydrocarbon potential. Pak J Pet Technol Altern Fuels 1:23–38
  • 9. Batzle ML, Wang Z (1992) Seismic properties of pore fluids. Geophysics 57(11):1396–1408. doi: 10.1190/1.1443207
  • 10. Batzle ML, Han DH, Hofmann R (2001) Optimal hydrocarbon indicators. In: 71th SEG international exposition and annual meeting 2001, September 9–14, 2001, San Antonio. doi: 10.1190/1.1816446
  • 11. Castagna JP, BatzleML Eastwood RL (1985) Relationships between compressional and shear-wave velocities in clastic silicate rocks. Geophysics 50(4):551–570. doi: 10.1190/1.1441933
  • 12. Castagna JP, Smith SW (1994) Comparison of AVO indicators: a modeling study. Geophysics 59(12):1849–1855. doi: 10.1190/1.1443572
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  • 14. Connolly P (1999) Elastic impedance. Lead Edge 18(4):438–452. doi: 10.1190/1.1438307
  • 15. Connolly P, Hughes M (2014) The application of very large numbers of pseudo-wells for reservoir characterization. Society of Petroleum Engineers 2014, SPE-171879-MS, November 10–13, 2014, Abu Dhabi. doi: 10.2118/171879-MS
  • 16. Dillon L, Schwedersky G, Vasquez G, Velloso R, Nunes C (2003) A multiscale DHI elastic attributes evaluation. Lead Edge 22(10):1024–1029. doi: 10.1190/1.1623644
  • 17. Doyen P (2007) Seismic reservoir characterization. EAGE, Netherlands
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  • 19. Gholami R, Moradzadeh A, Rasouli V, Hanachi J (2014) Shear wave velocity prediction using seismic attributes and well log data. Acta Geophys 62(4):818–848. doi: 10.2478/s11600-013-0200-7
  • 20. Goodway W, Chen T, Downton J (1997) Improved AVO fluid detection and lithology discrimination using Lamé petrophysical Parameters; “Lambda–Rho”, “Mu–Rho”, and “Lambda/Mu fluid stack”, from P and S inversions. In: 67th SEG annual international meeting 1997, November 2–7, 1997, Dallas. doi: 10.1190/1.1885795
  • 21. Grana D (2014) Probabilistic approach to rock physics modeling. Geophysics 79(2):D123–D143. doi: 10.1190/GEO2013-0333.1
  • 22. Grana D, Rossa ED (2010) Probabilistic petrophysical-properties estimation integrating statistical rock physics with seismic inversion. Geophysics 75(3):O21–O37. doi: 10.1190/1.3386676
  • 23. Grana D, Schlanser K, Campbell-Stone E (2015) Petroelastic and geomechanical classification of lithologic facies in the Marcellus Shale. Interpretation 3(1):SA51–SA63. doi: 10.1190/INT-2014-0047.1
  • 24. Hedlin K (2000) Pore space modulus and extraction using AVO. In: 70th SEG annual international meeting 2000, August 6–1, 2000, Calgary. doi: 10.1190/1.1815749
  • 25. Hussain M, Ahmed N, Chun WY, Khalid P, Mahmood A, Ahmad SR, Rasool U (2017) Reservoir characterization of basal sand zone of lower Goru formation by petrophysical studies of geophysical logs. J Geol Soc India 89(3):331–338. doi: 10.1007/s12594-017-0614-y
  • 26. Hydrocarbon Development Institute of Pakistan (2008) Energy Year Book, 2008. Ministry of Petroleum and Natural Resources, Pakistan
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  • 28. Kadri IB (1995) Petroleum geology of Pakistan. Pakistan Petroleum Ltd, Karachi
  • 29. Khalid P, Ahmed N (2016) Modulus defect, velocity dispersion and attenuation in partially-saturated reservoirs of Jurassic sandstone, Indus Basin, Pakistan. Stud Geophys Geod 60(1):112–129. doi: 10.1007/s11200-015-0804-2
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  • 31. Kumar D (2006) A Tutorial on Gassmann fluid substitution: formulation, algorithm and matlab code. Geohorizons 11(1):4–12
  • 32. Malureanu I, Boaca T, Daniela-Doina N (2016) New relations of water saturation’s Calculus from well logs. Acta Geophys 64(5):1542–1562. doi: 10.1515/acgeo-2016-0063
  • 33. Pakistan Petroleum Information Service (2009) Upstream Petroleum activities. Ministry of Petroleum and Natural Resources
  • 34. Poupon A, Levaux J (1971) Evaluation of water saturation in shaly formations. Society of Professional Well Log Analysts 12th annual logging symposium transactions, Paper O
  • 35. Quakenbush M, Shangn B, Tuttle C (2006) Poisson impedance. Lead Edge 25(2):128–138. doi: 10.1190/1.2172301
  • 36. Raza HA, Ahmad W, Ali SM, Mujtaba M, Alam S, Shafeeq M, Iqbal M, Noor I, Riaz N (2008) Hydrocarbon prospects of Punjab Platform Pakistan, with special reference to Bikaner-Nagaur Basin of India, Pakistan. J Hydrocarbon Res 18(6):1–33
  • 37. Rider MH (2002) The geological interpretation of well logs. Rider French Consulting Ltd, Sutherland
  • 38. Russell B, Hedlin K, Hilterman F, Lines L (2003) Fluid-property discrimination with AVO: a Biot–Gassmann perspective. Geophysics 68(1):29–39. doi: 10.1190/1.1543192
  • 39. Schlumberger (1997) Log interpretation charts. Schlumberger well services, Houston
  • 40. Shams O, Qureshi AW, Abbasi IA (2005) Lithofacies, sand-bodies geometry and depositional setting of the Datta Formation in Surghar Range, North Pakistan. In: Annual technical conference 2005, November 21–23, 2005, Islamabad
  • 41. Tarantola A (2005) Inverse problem theory. SIAM, Paris, France
  • 42. Whitcombe DN (2002) Elastic impedance normalization. Geophysics 67(1):60–62. doi: 10.1190/1.1451331
  • 43. Whitcombe DN, Connolly PA, Reagan RL, Redshaw TC (2002) Extended elastic impedance for fluid and lithology prediction. Geophysics 67(1):63–67. doi: 10.1190/1.1451337
  • 44. Zaidi SNA, Brohi IA, Ramzan K, Ahmed N, Mehmood F, Brohi AU (2013) Distribution and hydrocarbon potential of Datta Sands in Upper Indus Basin, Pakistan. Sindh Univ Res J 45(2):325–332
Uwagi
Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2018)
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-43147954-a8b1-4e85-b1e6-5831ef9af1b2
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