ISSN 1004-4140
CN 11-3017/P
WANG Z T, QU Z P, SHEN G Q. Research and Application of Seismic Inversion Method for Solid-Liquid Decoupling Fluid Factor Based on Frequency Variation Theory of Viscoelastic Media[J]. CT Theory and Applications, 2024, 33(5): 541-550. DOI: 10.15953/j.ctta.2024.003. (in Chinese).
Citation: WANG Z T, QU Z P, SHEN G Q. Research and Application of Seismic Inversion Method for Solid-Liquid Decoupling Fluid Factor Based on Frequency Variation Theory of Viscoelastic Media[J]. CT Theory and Applications, 2024, 33(5): 541-550. DOI: 10.15953/j.ctta.2024.003. (in Chinese).

Research and Application of Seismic Inversion Method for Solid-Liquid Decoupling Fluid Factor Based on Frequency Variation Theory of Viscoelastic Media

More Information
  • Received Date: January 06, 2024
  • Revised Date: January 29, 2024
  • Accepted Date: March 03, 2024
  • Available Online: April 02, 2024
  • Propagation of seismic waves through oil/gas bearing reservoirs will be affected by wave-induced flow, resulting in amplitude attenuation and elastic characteristic dispersion, and making it possible to predict the presence of fluids. However, existing theories are unclear and mathematical expressions lack accuracy, making it difficult to predict the presence of oil and gas. This study examines the attenuation of seismic amplitude and the dispersion of elastic parameters, and uses Chapman's pore-crack attenuation theory, while considering the squirt flow effect, to construct a solid-liquid decoupling fluid factor. Subsequently, the reflection coefficient characteristic equation is constructed by using the new fluid factor, and compared with the Zoeppritz and Aki approximation equations to demonstrate the improved accuracy of the new equation. Finally, a reservoir hydrocarbon-prediction method based on a pre-stack seismic inversion method using solid-liquid decoupling fluid factor is proposed. The reservoir fluid prediction is tested by using the inversion results of the new fluid factor to carry out reservoir oil/gas prediction in the well area A in the down-dropped block of Shengbei fault in China. The results show that the frequency-dependent viscoelastic solid-liquid decoupling fluid factor based on pre-stack seismic data is accurate and reliable, and the identified reservoir fluid distribution results are in good agreement with logging interpretation results. This study provides novel ideas and methods for fluid identification in complex reservoirs.

  • [1]
    LI K, YIN X Y, ZONG Z Y, et al. Estimating frequency-dependent viscoleastic fluid indicator from pre-stack F-AVA inversion[J]. Journal of China University of Petroleum, 2019, 43(1): 23−32.
    [2]
    HUDSON J, LIU E, CRAMPIN S. The mechanical properties of materials with interconnected cracks and pores[J]. Geophysical Journal International, 1996, 124(1): 105−112. DOI: 10.1111/j.1365-246X.1996.tb06355.x.
    [3]
    CHAPMAN M. Frequency-dependent anisotropy due to meso-scale fractures in the presence of equant porosity[J]. Geophysical Prospecting, 2003, 51(5): 369−379. DOI: 10.1046/j.1365-2478.2003.00384.x.
    [4]
    GALVIN R, GUREVICH B. Scattering of a longitudinal wave by a circular crack in a fluid-saturated porous medium[J]. International Journal of Solids and Structures, 2007, 44(22/23): 7389−7398.
    [5]
    唐晓明, 王鹤鸣, 苏远大, 等. 用孔隙、裂隙介质弹性波理论反演岩石孔隙分布特征[J]. 地球物理学报, 2021, 64(8): 2941−2951. DOI: 10.6038/cjg2021O0478.

    TANG X M, WANG H M, SU Y D, et al. Inversion for micro-pore structure distribution characteristics using cracked porous medium elastic wave theory[J]. Chinese Journal of Geophysics, 2021, 64(8): 2941−2951. DOI: 10.6038/cjg2021O0478. (in Chinese).
    [6]
    SMITH G, GIDLOW P. Weighted stacking for rock property estimation and detection of gas[J]. Geophysical Prospecting, 1987, 35(9): 993−1014. DOI: 10.1111/j.1365-2478.1987.tb00856.x.
    [7]
    BIOT M A. General theory of three-dimensional consolidation[J]. Journal of Applied Physics, 1941, 12(2): 155−164. DOI: 10.1063/1.1712886.
    [8]
    GASSMANN F. Uber die elastizitat poroser medien[J]. Vierteljahrsschrift der Naturforschenden Gesellschaft in Zurich, 1951, 96: 1−23.
    [9]
    RUSSELL B H, HEDLIN K, HILTERMAN F J, et al. Fluid-property discrimination with AVO: A Biot-Gassmann perspective[J]. Geophysics, 2003, 68(1): 29−39. DOI: 10.1190/1.1543192.
    [10]
    ZONG Z, YIN X, WU G. Geofluid discrimination incorporating poroelasticity and seismic reflection inversion[J]. Surveys in Geophysics, 2015, 36(5): 659−681. DOI: 10.1007/s10712-015-9330-6.
    [11]
    O'CONNELL R J, BUDIANSKY B. Seismic velocities in dry and saturated cracked solids[J]. Journal of Geophysical Research, 1974, 79(35): 5412−5426. DOI: 10.1029/JB079i035p05412.
    [12]
    O'CONNELL, R J, BUDIANSKY B. Viscoelastic properties of fluid-saturated cracked solids[J]. Journal of Geophysical Research, 1977, 82(36): 5719−5735. DOI: 10.1029/JB082i036p05719.
    [13]
    TANG X M. Unified theory of elastic wave in porous and fractured media — Extension of Biot theory[J]. Scientia Sinica Terrae, 2011, 41(6): 784-795.
    [14]
    TANG X M, CHEN X L, XU X K. A cracked porous medium elastic wave theory and its application to interpreting acoustic data from tight formations[J]. Geophysics, 2012, 77(6): D245−D52. DOI: 10.1190/geo2012-0091.1.
    [15]
    WILSON A, CHAPMAN M, LI X Y. Frequency-dependent AVO inversion[C]//SEG Technical Program Expanded Abstracts 2009. Society of Exploration Geophysicists, 2009: 341-345.
    [16]
    SUN S Z, YUE H L, ZHANG Y Y, et al. An improved frequency-dependent AVO inversion algorithm for fluid detection[J]. SEG Technical Program Expanded Abstracts, 2014: 543-547.
    [17]
    宗兆云, 宋琉璇, 印兴耀. 含流体复杂孔隙介质地震波衰减与频散[J]. 地球物理学报, 2022, 65(10): 659−681. DOI: 10.6038/cjg2022P0322.

    ZONG Z Y, SONG L X, YIN X Y. Seismic wave velocity attenuation and dispersion in the patchy saturated medium with complex pores and cracks[J]. Chinese Journal of Geophysics, 2022, 65(10): 659−681. DOI: 10.6038/cjg2022P0322. (in Chinese).
    [18]
    ZONG Z, YIN X, WU G. Geofluid discrimination incorporating poroelasticity and seismic reflectin inversion[J]. Surveys in Geophysics, 2015, 36(5): 4012−4027.
    [19]
    ZONG Z Y, YIN X Y, LI K. Joint AVO inversion in the time and frequency domain with Bayesian interference[J]. Applied Geophysics, 2016, 13(4): 631−640. DOI: 10.1007/s11770-016-0584-7.
    [20]
    LAN T, ZONG Z, FENG Y. An improved seismic fluid identification method incorporating squirt flow and frequency-dependent fluid-solid inversion[J]. Interpretation, 2022, 11(1): 1−66.
    [21]
    YIN X, ZHANG S, ZHANG F, et al. Utilizing Russell Approximation based elastic wave impedance inversion to conduct reservoir description and fluid identification[J]. Oil Geophysical Prospecting, 2010, 45(3): 373−380.
    [22]
    ZONG Z, YIN X, WU G. Frequency dependent elastic impedance inversion for interstratified dispersive elastic parameters[J]. Journal of Applied Geophysics, 2016, 131: 84−93. DOI: 10.1016/j.jappgeo.2016.05.010.
    [23]
    CONNOLLY P. Elastic impedance[J]. The Leading Edge, 1999, 18(4): 438−452. DOI: 10.1190/1.1438307.
    [24]
    刘道理, 李坤, 杨登锋, 等. 基于频变AVO反演的深层储层含气性识别方法[J]. 天然气工业, 2020, 40(1): 48−54. DOI: 10.3787/j.issn.1000-0976.2020.01.006.

    LIU D L, LI K, YANG D F, et al. A gas-bearing property identification method for deep reservoirs based on frequency-dependent AVO inversion[J]. Narutal Gas Industry, 2020, 40(1): 48−54. DOI: 10.3787/j.issn.1000-0976.2020.01.006. (in Chinese).
    [25]
    BIOT M A. Theory of propagation of elastic waves in a fluid-saturated porous solid. Ⅱ. Higher frequency range[J]. The Journal of the Acoustical Society of America, 1955, 28(2): 179−191. DOI: 10.1121/1.1908241.
    [26]
    FUTTERMAN W I. Dispersive body waves[J]. Journal of Geophysical Research, 1962, 67(13): 5279−5291. DOI: 10.1029/JZ067i013p05279.
    [27]
    RUSSELL B H, GRAY D, HAMPSON D P. Linearized AVO and poroelasticity[J]. Geophysics, 2011, 76(3): C19−C29. DOI: 10.1190/1.3555082.
    [28]
    WATERS K H. Reflection seismology: A tool for energy resource exploration[M]. Wiley New York, 1981.
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