Direct extraction of fractured reservoirs' parameters based on five-dimensional data
ZHANG Hongxue1,2, YIN Xingyao2, LI Kun2, XU Xiaokai1
1. SINOPEC Matrix Corporation, Qingdao, Shandong 266071, China; 2. School of Geosciences, China University of Petroleum (East China), Qingdao, Shandong 266580, China
Abstract：The existing fluid identification methods for fractured reservoirs do not consider the influence of rock skeleton, fractures, pores, and oil-gas coupling in determining sensitive parameters of the fluid and fail to fully excavate fluid information contained in a wealth of azimuth information in five-dimensional (5D) data. In addition, oil and gas identification of fractured reservoirs is mainly based on indirectly calculated parameters. The inversion of wide-azimuth 5D seismic data has problems of ill-conditioned solution and uncertainty, and simulta-neous inversion of multiple fracture parameters is more likely to make the inversion accuracy of reservoirs' parameters decrease. Therefore, the fluid factors based on indirect algebraic combination inevitably accumulate calculation errors during calculation, which thus affects the effect of oil and gas identification. In view of the above problems, by combining the anisotropic Gassmann theory of pore elasticity and linear sliding theory, a new P-wave reflection coefficient equation directly characterized by the fluid factor decoupled by solid-fluid-fractures is derived. Moreover, the applicable condition and the sensitivity of the equation are analyzed. On this basis, the seismic inversion objective function with Bayesian framework is constructed, and the fluid identification method by 5D data is studied based on the time-frequency data, which thus directly obtains the fluid factor decoupled by solid-fluid-fractures in fractured reservoirs, eliminates the influence of cumulative errors, and improves the prediction accuracy. Research on models and actual data show that the proposed method can reasonably and reliably predict the distribution of oil and gas in fractured reservoirs.
印兴耀,张洪学,宗兆云.OVT数据域五维地震资料解释技术研究现状与进展[J].石油物探,2018,57(2):155-178.YIN Xingyao,ZHANG Hongxue,ZONG Zhaoyun.Research status and progress of 5D seismic data interpretation in OVT domain[J].Geophysical Prospecting for Petroleum,2018,57(2):155-178.
[2]
CARCIONE J M,GUREVICH B,SANTOS J E,et al.Angular and frequency-dependent wave velocity and attenuation in fractured porous media[J].Pure Applied Geophysics,2013,170(11):1673-1683.
[3]
ZONG Z,SUN Q,LI C,et al.Young's modulus variation with azimuth for fracture orientation estimation[J].Interpretation,2018,6(4):T809-T818.
[4]
CHEN H.Seismic frequency component inversion for elastic parameters and maximum inverse quality factor driven by attenuating rock physics models[J].Surveys in Geophysics,2020,41(4):835-857.
[5]
SMITH G C,GIDLOW P M.Weighted stacking for rock property estimation and detection of gas[J].Geophysical Prospecting,1987,35(9):993-1014.
[6]
SMITH G C,GIDLOW P M.The fluid factor angle and the crossplot angle[C].SEG Technical Program Expanded Abstracts,2003,22:185-188.
[7]
GOODWAY B,CHEN T,DOWNTON J.Improved AVO fluid detection and lithology discrimination using Lamé petrophysical parameters;"λρ","μρ",& "λ/μ fluid stack",from P and S inversions[C].SEG Technical Program Expanded Abstracts,1997,16:183-186.
[8]
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.
[9]
QUAKENBUSH M,SHANG B,TUTTLE C.Poisson impedance[J].The Leading Edge,2006,25(2):128-138.
[10]
HUDSON J A.Wave speeds and attenuation of elastic waves in material containing cracks[J].Geophysical Journal International,1981,64(1):133-150.
[11]
SCHOENBERG M,SAYERS C M.Seismic anisotropy of fractured rock[J].Geophysics,1995,60(1):204-211.
[12]
CHEN H,JI Y,INNANEN K A.Estimation of modified fluid factor and dry fracture weaknesses using azimuthal elastic impedance[J].Geophysics,2018,83(1):WA73-WA88.
[13]
CHAPMAN M,LIU E,LI X.The influence of fluid-sensitive dispersion and attenuation on AVO analysis[J].Geophysical Journal International,2006,167(1):89-105.
[14]
PAN X,ZHANG G,LIU J,et al.Estimating fluid term and anisotropic parameters in saturated transversely isotropic media with aligned fractures[J].Journal of Seismic Exploration,2021,30(1):65-84.
[15]
王迪,张益明,牛聪,等.储层敏感流体因子反演及烃类检测[J].石油地球物理勘探,2021,56(1):146-154.WANG Di,ZHANG Yiming,NIU Cong,et al.Reservoir sensitive fluid factor inversion and its application in hydrocarbon detection[J].Oil Geophysical Prospecting,2021,56(1):146-154.
[16]
ZHANG S,HUANG H,DONG Y,et al.Direct estimation of the fluid properties and brittleness via elastic impedance inversion for predicting sweet spots and the fracturing area in the unconventional reservoir[J].Journal of Natural Gas Science and Engineering,2017,doi:10.1016/j.jngse.2017.04.028.
[17]
RUSSELL B H,HEDLIN K J.Extended poroelastic impedance[J].Geophysics,2019,84(2):N1-N14.
[18]
PAN X,DU X,ZHAO X,et al.Seismic characterization of decoupled orthorhombic fractures based on observed surface azimuthal amplitude data[J].IEEE Transactions on Geoscience and Remote Sensing,2021,doi:10.1109/TGRS.2021.3105724.
[19]
CHEN H,MORADI S,INNANEN K A.Joint inversion of frequency components of PP-and PSV-wave amplitudes for attenuation factors using second-order derivatives of anelastic impedance[J].Surveys in Geophysics,2021,42(4):961-987.
[20]
印兴耀,张洪学,宗兆云.五维地震油气识别方法[J].应用声学,2020,39(1):63-70.YIN Xingyao,ZHANG Hongxue,ZONG Zhaoyun.Seismic fluid identification based on 5D seismic data[J].Journal of Applied Acoustics,2020,39(1):63-70.
[21]
SHAW R K,SEN M K.Use of AVOA data to estimate fluid indicator in a vertically fractured medium[J].Geophysics,2006,71(3):C15-C24.
[22]
YIN X,ZHANG S.Bayesian inversion for effective pore-fluid bulk modulus based on fluid-matrix decoupled amplitude variation with offset approximation[J].Geophysics,2014,79(5):R221-R232.
[23]
YIN X,ZONG Z,WU G.Research on seismic fluid identification driven by rock physics[J].Science China Earth Sciences,2015,58(2):159-171.
[24]
LI K,YIN X,ZONG Z,et al.Estimation of porosity,fluid bulk modulus,and stiff-pore volume fraction using a multitrace Bayesian amplitude-variation-with-offset petrophysics inversion in multiporosity reservoirs[J].Geophysics,2022,87(1):M25-M41.
[25]
印兴耀,张世鑫,张峰.针对深层流体识别的两项弹性阻抗反演与 Russell 流体因子直接估算方法研究[J].地球物理学报,2013,56(7):2378-2390.YIN Xingyao,ZHANG Shixin,ZHANG Feng.Two-term elastic impedance inversion and Russell fluid factor direct estimation method for deep reservoir fluid identification[J].Chinese Journal of Geophysics,2013,56(7):2378-2390,
陈超,印兴耀,陈祖庆,等.基于页岩岩石物理等效模型的地层压力系数预测方法[J].石油地球物理勘探,2022,57(2):367-376,394.CHEN Chao,YIN Xingyao,CHEN Zuqing,et al.Prediction for formation pressure coefficients based on an equivalent petrophysical model of shale[J].Oil Geophysical Prospecting,2022,57(2):367-376,394.
[28]
刘晓晶,陈祖庆,陈超,等.方位弹性阻抗傅里叶级数裂缝预测方法[J].石油地球物理勘探,2022,57(2):423-433.LIU Xiaojing,CHEN Zuqing,CHEN Chao,et al.Fracture prediction method based on Fourier series of azimuthal elastic impedance[J].Oil Geophysical Prospecting,2022,57(2):423-433.
[29]
顾雯,印兴耀,巫芙蓉,等.波形驱动下多参数约束高分辨率反演方法——以四川盆地渝西地区龙马溪组页岩气为例[J].石油地球物理勘探,2021,56(6):1311-1321.GU Wen,YIN Xingyao,WU Furong,et al.Multi-parameter constrained high-resolution inversion method driven by waveform:A case study of Longmaxi Formation shale gas in western Chongqing,Sichuan Basin[J].Oil Geophysical Prospecting,2021,56(6):1311-1321.
[30]
ZONG Z,JI L.Model parameterization and amplitude variation with angle and azimuthal inversion in orthotropic media[J].Geophysics,2021,86(1):R1-R14.
[31]
GUREVICH B.Elastic properties of saturated porous rocks with aligned fractures[J].Journal of Applied Geophysics,2003,54(3-4):203-218.
