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物探与化探  2025, Vol. 49 Issue (5): 1141-1154    DOI: 10.11720/wtyht.2025.0120
  方法研究信息处理仪器研制 本期目录 | 过刊浏览 | 高级检索 |
基于麻雀搜索算法的致密砂岩储层参数非线性反演方法
曹绍贺1, 黄中群1, 袁春艳1, 马百征1, 王群武2, 张奎2
1.中国石化华北油气分公司,河南 郑州 450006
2.北京普瑞斯安能源科技有限公司,北京 100015
Nonlinear inversion of tight sandstone reservoir parameters using the sparrow search algorithm
CAO Shao-He1, HUANG Zhong-Qun1, YUAN Chun-Yan1, MA Bai-Zheng1, WANG Qun-Wu2, ZHANG Kui2
1. North China Petroleum Bureau,SINOPEC,Zhengzhou 450006,China
2. Beijing Precise Energy Technology Co.,Ltd.,Beijing 100015,China
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摘要 

随着油气储层勘探的日益发展,常规线性反演方法已经无法满足目前致密砂岩储层的勘探精度需要。为此,本文以致密砂岩储层为勘探背景并采用包裹体模型计算了饱和岩石下的纵、横波速度及密度表达式,基于精确Zoeppritz建立非线性精确反射系数方程,以L1范数作为反演目标泛函,采用麻雀搜索算法(sparrow search algorithm,SSA),发展了一种高精度的储层参数AVO反演预测方法,相比于常规最小二乘法求解的L2范数目标函数的反演结果,该方法能够提高反演结果的精度与分辨率,为致密砂岩储层的岩石物理参数预测提供了更为合理、可靠的结果,为致密砂岩储层孔隙发育与含油气性评估提供了更为有效的解决方案。模型测试及鄂尔多斯盆地致密砂岩储层实际资料测试的结果验证了该方法的有效性和实用性。

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曹绍贺
黄中群
袁春艳
马百征
王群武
张奎
关键词 麻雀搜索算法非线性AVO反演高精度含油气储层预测    
Abstract

With the ongoing exploration of hydrocarbon reservoirs, conventional linear inversion methods for conventional hydrocarbon reservoirs fail to meet the accuracy requirements for tight sandstone reservoirs.In response,this study,focusing on tight sandstone reservoirs,calculated expressions for P-wave velocity,S-wave velocity,and density in saturated rocks using inclusion models.A nonlinear reflection coefficient equation was established based on the exact Zoeppritz equations.Using the L1-norm as the inversion objective function,a high-precision amplitude variation with offset(AVO) inversion method for reservoir parameter prediction was developed using the sparrow search algorithm(SSA).Compared to the conventional least-squares inversion results with the L2-norm as the objective function,the proposed method improves the accuracy and resolution of the inversion results.It provides more reasonable and reliable predictions of petrophysical parameters and offers an effective approach for evaluating pore development and hydrocarbon content in tight sandstone reservoirs.The validity and practicality of this method are verified through model tests and application to actual data from tight sandstone reservoirs in the Ordos Basin.

Key wordssparrow search algorithm(SSA)    nonlinear inversion    amplitude versus offset(AVO) inversion    high accuracy    prediction of hydrocarbon-bearing reservoirs
收稿日期: 2025-04-15      修回日期: 2025-07-29      出版日期: 2025-10-20
ZTFLH:  P631.4  
基金资助:中国石化集团华北石油局有限公司“彬长区块太昌目标区石盒子组地震资料目标处理与解释”项目(34550000-23-ZC0611-0064)
作者简介: 曹绍贺(1984-),女,2009年毕业于中国石油大学(北京)地球探测与信息技术专业,获硕士学位;就职于中国石化华北油气分公司,主要从事三维地震储层及含气性预测研究工作。
引用本文:   
曹绍贺, 黄中群, 袁春艳, 马百征, 王群武, 张奎. 基于麻雀搜索算法的致密砂岩储层参数非线性反演方法[J]. 物探与化探, 2025, 49(5): 1141-1154.
CAO Shao-He, HUANG Zhong-Qun, YUAN Chun-Yan, MA Bai-Zheng, WANG Qun-Wu, ZHANG Kui. Nonlinear inversion of tight sandstone reservoir parameters using the sparrow search algorithm. Geophysical and Geochemical Exploration, 2025, 49(5): 1141-1154.
链接本文:  
https://www.wutanyuhuatan.com/CN/10.11720/wtyht.2025.0120      或      https://www.wutanyuhuatan.com/CN/Y2025/V49/I5/1141
Kf/Pa Km/Pa μm/Pa Vp/(km·s-1) Vs/(km·s-1) ρ/(kg·m-3) ?
含气砂岩 1.0×108 3.2×1010 3.4×1010 4.69 3.09 2900 0.10
泥岩 2.40×109 2.0×1010 7×109 3.49 1.60 2500 0.05
Table 1  含气砂岩与泥岩双层模型
Fig.1  反射系数方程精度测试结果
Fig.2  岩石物理模型
Fig.3  正演合成的地震记录
Fig.4  无噪声合成地震记录下的反演结果
Fig.5  合成地震记录信噪比为5情况下的反演结果
Fig.6  无噪声合成地震记录下反演结果与真实模型的误差绝对值
Fig.7  合成地震记录信噪比为5情况下反演结果与真实模型的误差绝对值
Fig.8  部分叠加的实际地震剖面
Fig.9  新非线性方法下的实际地震资料反演结果
Fig.10  常规方法下的实际地震资料反演结果
Fig.11  不同反演方法下实际地震资料井旁道反演结果与滤波后测井曲线对比
Kf/Pa ? ρ/(kg·m-3)
新方法 0.0809 0.0718 0.0747
常规方法 0.1299 0.0815 0.0885
Table 2  实际资料井旁道反演结果与滤波后测井曲线归一化均方根误差统计
Fig.12  新非线性方法下的Kf反演结果沿层切片
Fig.13  新非线性方法下的孔隙度反演结果沿层切片
Fig.B-1  基于SSA算法的叠前非线性反演流程
Fig.C-1  基于梯度下降算法的叠前非线性反演流程
[1] Bosch M, Carvajal C, Rodrigues J, et al. Petrophysical seismic inversion conditioned to well-log data:Methods and application to a gas reservoir[J]. Geophysics, 2009, 74(2):O1-O15.
[2] Ran B. Linearized orthorhombic AVAZ inversion:Theoretical and practical consideration[C]// Denver:SEG Technical Program Expanded Abstracts 2014, Society of Exploration Geophysicists,2014:528-532.
[3] Zong Z Y, Yin X Y, Wu G C. Geofluid discrimination incorporating poroelasticity and seismic reflection inversion[J]. Surveys in Geophysics, 2015, 36(5):659-681.
[4] Pan X P, Zhang G Z. Model parameterization and PP-wave amplitude versus angle and azimuth(AVAZ) direct inversion for fracture quasi-weaknesses in weakly anisotropic elastic media[J]. Surveys in Geophysics, 2018, 39(5):937-964.
[5] Zong Z Y, Zhang J L, Chen F B. Seismic prediction for formation pressure considering diagenesis effect[J]. IEEE Transactions on Geoscience and Remote Sensing, 2024,62:4508813.
[6] Grana D, Della Rossa E. Probabilistic petrophysical-properties estimation integrating statistical rock physics with seismic inversion[J]. Geophysics, 2010, 75(3):O21-O37.
[7] 宗兆云, 印兴耀, 吴国忱. 基于叠前地震纵横波模量直接反演的流体检测方法[J]. 地球物理学报, 2012, 55(1):284-292.
[7] Zong Z Y, Yin X Y, Wu G C. Fluid detection method based on direct inversion of pre-stack seismic P-S wave modulus[J]. Chinese Journal of Geophysics, 2012, 55(1):284-292.
[8] 卢明辉, 巴晶, 晏信飞. 致密砂岩的等效介质理论研究[C]// 中国地球物理学会, 中国石油学会,2011:725-729.
[8] Lu M, Ba J, Yan X F. Theoretical study on equivalent medium of tight sandstone[C]// Chinese Geophysical Society, Chinese Petroleum Society,2011:725-729.
[9] 印兴耀, 刘欣欣, 曹丹平. 基于Biot相洽理论的致密砂岩弹性参数计算方法[J]. 石油物探, 2013, 52(5):445-451,441.
doi: 10.3969/j.issn.1000-1441.2013.05.001
[9] Yin X Y, Liu X X, Cao D P. Elastic parameters calculation for tight sand reservoir based on Biotconsistent theory[J]. Geophysical Prospecting for Petroleum, 2013, 52(5):445-451,441.
[10] 刘倩, 印兴耀, 李超. 含不连通孔隙的致密砂岩储层岩石弹性模量预测方法[J]. 石油物探, 2015, 54(6):635-642.
doi: 10.3969/j.issn.1000-1441.2015.06.001
[10] Liu Q, Yin X Y, Li C. Prediction method of rock elastic modulus of tight sandstone reservoirs with disconnected pores[J]. Geophysical Prospecting for Petroleum, 2015, 54(6):635-642.
[11] Fan X G, Zhang G Z, Zhang J J. Prediction method of pore structure parameters of tight sandstone[C]// San Antonio:SEG Technical Program Expanded Abstracts 2019, Society of Exploration Geophysicists,2019:3678-3682.
[12] Cooke D A, Schneider W A. Generalized linear inversion of reflection seismic data[J]. Geophysics, 1983, 48(6):665-676.
[13] Du B Y, Yang W Y, Zhang J, et al. Matrix-fluid decoupling-based joint PP-PS-wave seismic inversion for fluid identification[J]. Geophysics, 2019, 84(3):R477-R487.
[14] Yin X Y, Cheng G S, Zong Z Y. Non-linear AVO inversion based on a novel exact PP reflection coefficient[J]. Journal of Applied Geophysics, 2018,159:408-417.
[15] Cheng G S, Yin X Y, Zong Z Y. Third-order AVO inversion for lamé parameter based on inverse operator estimation algorithm[J]. Journal of Petroleum Science and Engineering, 2018,164:117-126.
[16] Zhou L, Liu X Y, Li J Y, et al. Robust AVO inversion for the fluid factor and shear modulus[J]. Geophysics, 2021, 86(4):R471-R483.
[17] Kuster G T, Toksöz M N. Velocity and attenuation of seismic waves in two-phase media:Part i.Theoretical formulations[J]. Geophysics, 1974, 39(5):587-606.
[18] Berryman J G. Long-wavelength propagation in composite elastic media II.Ellipsoidal inclusions[J]. Acoustical Society of America Journal, 1980, 68(6):1820-1831.
[19] Zoeppritz K, Erdbebnenwellen V. On the reflection and penetration of seismic waves through unstable layers[J]. Gottinger Nachrichten, 1919, 1(5):66-84.
[20] Xue J K, Shen B. A novel swarm intelligence optimization approach:Sparrow search algorithm[J]. Systems Science & Control Engineering, 2020, 8(1):22-34.
[21] Gassmann F. Elastic waves through a packing of spheres[J]. Geophysics, 1951, 16(4):673-685.
[22] Aki K, Richards P. Quantitative seismology:Theory and methods[M]. W.H. Freeman and Co.,1980.
[23] 印兴耀, 邓炜, 宗兆云. 基于逆算子估计的AVO反演方法研究[J]. 地球物理学报, 2016, 59(4):1457-1468.
doi: 10.6038/cjg20160426
[23] Yin X Y, Deng W, Zong Z Y. AVO inversion based on inverse operator estimation[J]. Chinese J. Geophys., 2016, 59(4):1457-1468.
[24] 邓炜, 印兴耀, 宗兆云, 等. 基于逆算子估计的高阶AVO非线性反演[J]. 石油地球物理勘探, 2016, 51(5):955-964,837.
[24] Deng W, Yin X Y, Zong Z Y, et al. High-order nonlinear AVO inversion based on estimated inverse operator[J]. Oil Geophysical Prospecting, 2016, 51(5):955-964,837.
[25] Cheng G S, Yin X Y, Zong Z Y. Nonlinear amplitude-variation-with-offset inversion for Lamé parameters using a direct inversion method[J]. Interpretation, 2017, 5(3):SL57-SL67.
[26] Luo C, Li X Y, Huang G T. Pre-stack AVA inversion by using propagator matrix forward modeling[J]. Pure and Applied Geophysics, 2019, 176(10):4445-4476.
doi: 10.1007/s00024-019-02157-9
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