PL EN


Preferencje help
Widoczny [Schowaj] Abstrakt
Liczba wyników
Powiadomienia systemowe
  • Sesja wygasła!
Tytuł artykułu

Seismic inversion based prediction of the elastic parameters of rocks surrounding roadways: a case study from the Shijiazhuang mining area of North China

Wybrane pełne teksty z tego czasopisma
Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Increasing mining depths and intensities have resulted in frequent accidents during roadway excavation, thus increasing the necessity of preemptively determining the geological conditions of rock formations along roadways. Identifying the spatial distributions of lithotypes and the mechanical properties of non-marker bed intervals in coal measure strata are crucial for roadway horizon design, roof management, and efficient excavation. Therefore, based on petrophysical tests, well logging, and seismic data, a comprehensive method is proposed, which uses post-stack wave impedance inversion, petrophysical statistical analyses, and pre-stack simultaneous inversion to predict the lithology and elastic parameters of rocks surrounding roadways. The lithology of the target layer is first divided according to the wave impedances of the inversion body, and the sand lenses within the mudstone interval are described. Based on petrophysical test data, the shear-wave conversion equations of the sand lenses in this target interval and background mudstone are then obtained via marginal limit extrapolation. Finally, pre-stack simultaneous inversion, based on the seismic data and shear-wave conversion curves of different lithologies, is performed to obtain the elastic parameter profile of the target interval in the cross-section of the roadway, laying the foundation for further prediction of the mechanical properties of the surrounding rocks. The results agree with roadway drilling data by>90%.
Czasopismo
Rocznik
Strony
2219--2230
Opis fizyczny
Bibliogr. 50 poz.
Twórcy
autor
  • State Key Laboratory of Coal Resources and Safety Mining, China University of Mining and Technology, Beijing 100083, China
autor
  • College of Geoscience and Surveying Engineering, China University of Mining and Technology, Beijing 100083, China
autor
  • Yangquan Coal Industry (Group) Co., Ltd, Yangquan 045000, China
autor
  • College of Geoscience and Surveying Engineering, China University of Mining and Technology, Beijing 100083, China
autor
  • College of Geoscience and Surveying Engineering, China University of Mining and Technology, Beijing 100083, China
autor
  • College of Geoscience and Surveying Engineering, China University of Mining and Technology, Beijing 100083, China
autor
  • School of Mechanics and Civil Engineering, China University of Mining and Technology, Beijing 100083, China
Bibliografia
  • 1. Ao YL, Li HQ, Zhu LP et al (2019) Logging lithology discrimination in the prototype similarity space with random forest [J]. IEEE Geosci Remote Sens Lett 16(5):687–691
  • 2. Bagheripour P, Gholami A, Asoodeh M et al (2015) Support vector regression based determination of shear wave velocity[J]. J Petrol Sci Eng 125:95–99
  • 3. Bing P, Cao S, Lu J (2012) Non-linear AVO inversion based on support vector machine[J]. Chinese J Geophys- Chinese Edition 55(3):1025–1032
  • 4. Breitzke M (2000) Acoustic and elastic characterization of marine sediments by analysis, modeling, and inversion of ultrasonic P wave transmission seismograms[J]. J Geophys Res: Solid Earth 105(B9):21411–21430
  • 5. Buland A, Omre H (2003) Bayesian linearized AVO inversion[J]. Geophysics 68(1):185–198
  • 6. Castagna JP et al (1985) Relationships between compressional-wave and shear-wave velocities in clastic silicate rocks. Geophysics 50(4):571–581
  • 7. Chuong H D, Yen N, Le N, et al. Determining the density of liquid using gamma scattering method[J]. Applied Radiation and Isotopes, 2020, 163:109197.
  • 8. Connolly P (1999) Elastic impedance[J]. Leading Edge 18(4):438–438
  • 9. Das B, Chatterjee R (2018) Well log data analysis for lithology and fluid identification in Krishna-Godavari Basin, India[J]. Arab J Geosci 11(10):231
  • 10. Delfiner PC, Peyret O, Serra O (1984) Automatic Determination of Lithology from Well Logs[J]. Spe Formation Eval 2(3):303–310
  • 11. Esmaeili-Sani V, Moussavi-Zarandi A, Boghrati B et al (2012) Gamma–gamma density and lithology tools simulation based on GEANT4 advanced low energy Compton scattering (GALECS) package[J]. Nucl Instrum Methods Phys Res 664(1):6–10
  • 12. Fatti JL, Smith GC, Vail PG et al (1994) Detection of gas in sandstone reservoirs using AVO analysis; a 3-D seismic case history using the Geostack technique[J]. Geophysics 59(9):1362–1376
  • 13. Gholami R, Moradzadeh A, Rasouli V et al (2016) Shear wave splitting analysis to estimate fracture orientation and frequency dependent anisotropy[J]. Acta Geophys 64(1):76–100
  • 14. Goodway B, Chen T, Downton J (1997) Improved AVO fluid detection and lithology discrimination using Lamé petrophysical parameters; “λρ”, “μρ”,&“λ/μ fluid stack”, from P and S inversions[J]. SEG Tech Program Exp Abstracts 16(1):2067
  • 15. Hampson DP, Russell BH, Bankhead B (2005) Simultaneous inversion of pre-stack seismic data: 75th annual international meeting[C]. SEG, Exp Abstracts, pp 1633–1637.
  • 16. Han D-h, Nur A, Morgan D (1986) Effects of porosity and clay content on wave velocities in sandstones[J]. Geophysics 51(11):2093–2107
  • 17. Hariri Naghadeh D et al (2018) Stochastic Gabor reflectivity and acoustic impedance inversion[J]. J Geophys Eng 15(1):179–191
  • 18. Harris NB (2011) Mechanical anisotropy in the Woodford Shale. Permian Basin. Lead Edge 30(3):284–291
  • 19. Hatherly P, Zhou B, Peters T, Urosevic M (2008) 2008, Acoustic impedance inversion for geotechnical evaluation in underground coal mining: 78th SEG 2008 annual meeting, Las Vegas, 9–14thNovember, 2008. SEG Exp Abstracts 27:3600. https://doi.org/10.1190/1.3064076
  • 20. He W, Hao J, Yang J et al (2019) Application of pre-stack simultaneous inversion to predict gas-bearing dolomite reservoir: a case study from Sichuan Basin, China[J]. Carbonates Evaporites 34(3):1191–1201
  • 21. Horrocks T, Holden EJ, Wedge D (2015) Evaluation of automated lithology classification architectures using highly-sampled wireline logs for coal exploration[J]. Comput Geosci 83:209–218
  • 22. Hsieh BZ, Lewis C, Lin ZS (2005) Lithology identification of aquifers from geophysical well logs and fuzzy logic analysis: Shui-Lin Area, Taiwan[J]. Comput Geosci 31(3):267–275
  • 23. Hu Y, Zhou Y, Guo B et al (2018) Characteristics of the impedance variation in clastic rock reservoirs and lithology interpretation method for the threshold volume[J]. Mar Pet Geol 97:277–287
  • 24. Jiang J, Sun JZ (2011) Comparative study of static and dynamic parameters of rock for the Xishan Rock Cliff Statue[J]. J Zhejiang Univ, Sci, A 12(10):771–781
  • 25. Kalashnikova V, Meisingset I, Overas R et al (2020) High-resolution seismic velocity field estimation techniques and their application to geohazard, lithology and porosity prediction [J]. Near Surf Geophys 18(1):61–76
  • 26. Keys RG, Xu S (2002) An approximation for the Xu-white velocity model[J]. Geophysics 67(5):1406–1414
  • 27. Lee MW (2006) A simple method of predicting S-wave velocity[J]. Geophysics 71(6):F161–F164
  • 28. Li S, Peng Z, Wu H (2017) Prestack multi-gather simultaneous inversion of elastic parameters using multiple regularization constraints[J]. J Earth Sci 4:1–13
  • 29. Liu C, Pei SJ, Guo ZQ et al (2017) The application of seismic amplitude inversion for the characterization of interbedded sand-shale reservoirs[J]. Chin J Geophys 60(05):1893–1902
  • 30. Liu C, Ghosh DP, Salim AMA et al (2019) A new fluid factor and its application using a deep learning approach[J]. Geophys Prospect 67(1):140–149
  • 31. Lukumon A, Adesanya OY, Oyedele KF et al (2018) Lithology and fluid prediction from simultaneous seismic inversion over Sandfish field, Niger Delta, Nigeria[J]. Geosci J 22(1):155–169
  • 32. Mehrgini B, Izadi H, Memarian H (2017) Shear wave velocity prediction using Elman artificial neural network[J]. Carbonates Evaporites 6:1–11
  • 33. Oloruntob O, Onalo D, Adedigba S et al (2019) Data-driven shear wave velocity prediction model for siliciclastic rocks. J Petroleum Sci Eng 183:106293
  • 34. Ostrander WJ (1984) Plane-wave reflection coefficients for gas sands at nonnormal angles of incidence[J]. Explor Geophys 15(3):193
  • 35. Qian Minggao Xu, Jialin WJ (2018) Further on the sustainable mining of coal [J]. J China Coal Soc 43(01):1–13
  • 36. Riedel M, Dosso SE, Beran L (2003) Uncertainty estimation for amplitude variation with offset (AVO) inversion[J]. Geophysics 68(5):1485–1496
  • 37. Russell BH, Gray D, Hampson DP (2011) Linearized AVO and poroelasticity[J]. Geophysics 76(3):C19–C29
  • 38. Santos LK, De Figueiredo JJS, Omoboya B et al (2015) On the source-frequency dependence of fracture-orientation estimates from shear-wave transmission experiments[J]. J Appl Geophys 114:81–100
  • 39. Shuey RT (1985) A simplification of the Zoeppritz equations[J]. Geophysics 50(4):609–614
  • 40. Simmons JL (1996) Waveform-based AVO inversion and AVO prediction-error[J]. Geophysics 61(6):1575
  • 41. Sone H, Zoback MD (2013) Mechanical properties of shale-gas reservoir rocks — Part 2: Ductile creep, brittle strength, and their relation to the elastic modulus[J]. Geophysics 78(5):D393–D402
  • 42. Sousa MC, De Figueiredo JJS, Silva CB et al (2019) Prediction of S-wave velocity by a hybrid model based on the Greenberg-Castagna equation[J]. J Petroleum Sci Eng 172:303–313
  • 43. Tang J, Jiang C, Chen Y et al (2016) Line prediction technology for forecasting coal and gas outbursts during coal roadway tunneling[J]. J Natural Gas Sci Eng 34:412–418
  • 44. Teng JW, Qiao YH, Song PH (2016) Analysis of exploration, potential reserves and high efficient utilization of coal in China[J]. Chin J Geophys 59(12):4633–4653
  • 45. Tong L, Che H, Pan H et al (2019) Comparison of shear wave velocity prediction models to Yangtze river deltaic sediments based on piezocone test data[J]. Int J Civil Eng 17(12):1845–1858
  • 46. Whitcombe DN, Connolly PA, Reagan RL et al (2002) Extended elastic impedance for fluid and lithology prediction[J]. Geophysics 67(1):63–67
  • 47. Yan W (2017) Study on the sequence stratigraphy and the gas enrichment regularity of Taiyuan Formation in Yangquan Sijiazhuang Mining Area [D]. China University of Mining and Technology.
  • 48. Zhang Q, Chen Y, Guan H et al (2016) Well-log constrained inversion for lithology characterization: a case study at the JZ25-1 oil fileld, CHINA[J]. J Seism Explor 25(2):121–129
  • 49. Zong Z, Yin X, Wu G (2013b) Elastic impedance parameterization and inversion with Young’s modulus and Poisson’s ratio[J]. Geophysics 78(6):N35–N42
  • 50. Zong Z, Yin X, Wu G (2013) Model parameterization and EVA-DSVD inversion with Young's modulus and Poisson's ratio[C]. SEG Tech Prog Exp Abstracts.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-85310312-4ef0-4cff-b802-984978a82c09
JavaScript jest wyłączony w Twojej przeglądarce internetowej. Włącz go, a następnie odśwież stronę, aby móc w pełni z niej korzystać.