基于偶极地震子波的叠前三参数同时反演方法研究

发布时间：2018-08-26 07:45

【摘要】：针对地震反演受反射系数和低频模型的影响,在分析地震速度和频谱特性的基础上,建立储层地震特征与油藏参数之间的关系,也是储层地震反演研究的重要内容。基于储层顶底总是“成双成对”的特性,从储层的整体性研究入手,构建了偶极子波储层厚度褶积模型,表述了偶极子波地震响应特征和多重积分的数学表达式,推导了偶极子波储层顶底界面反射系数方程,证实了地震奇偶重积分转换的数据具有储层厚度和相对阻抗预测的特性,形成了偶极地震子波储层预测的理论基础。薄互层理论模型证实:能量约束储层厚度谱法实现了储层厚度定量预测,辨识厚度与储、隔层厚度有关;隔层越厚,储层越易分辨,在地质条件相对简单的情况下,预测厚度可达到λ/16(λ波长),对于最难预测的薄互层,辨识厚度仍可达λ/8。在多级沉积微旋回约束下,进一步采用多极子波重构法提高薄互层的预测效果。运用地震多阶微分技术转换的数据突显更高频段的相对阻抗信息,提高辨识薄层的能力。通过井震资料可靠性分析,进一步证实地震多重积分恢复的低频信息与同频段的测井分频阻抗有较好匹配关系,为下一步地震反演的中低频模型构建打下了资料基础。地震反演依赖于初始低频阻抗或速度模型的精度,本文首次提出叠前地震道集逐点连续速度预测法,提高了叠前地震道集波场速度建立的精度。由于地震均方根速度预测层速度对时间变化较为敏感,对地震数据时间重采样真实性和精度有更高的要求,地震波形约束插值法有效改善了时间采样的插值效果,在时空上提高了叠前地震道集连续均方根速度估算的精度,有助于建立精细层速度模型,同时对低频段有较好的预测效果。针对目标函数构建的复杂性,采用逐级分解确定参数的方式。首先解决子波频率和延迟时的时空变化快等预测难题,采用自相关函数、振幅包络、微分特征曲线等约束手段,准确求取子波重要的频率、相位和衰减系数特征参数,明确了地震子波优化的先后顺序:主频、延迟时、衰减系数;再通过弹性参数敏感性分析,指出参数优化先后顺序为储层厚度、纵波速度、横波速度和密度,实现多参数逐级约束偶极子波储层厚度预测到储层特征反演。针对当前叠前全波形反演计算量大、地震道集品质与精度不够等问题,本次在研究地震多重微积分厚度预测和叠前精细低频速度模型建立的基础上,借鉴成熟的叠前波阻抗反演和AVO反演技术和方法,有效结合叠前AVA地震反演波场走时和动力学特征,重构了地震数据多重积分、多阶微分转换相对阻抗储层模型,建立不同角度弹性阻抗模型,提出了一种可实现的偶极子波叠前三参数同时反演的技术方法。编译和调试了叠前地震反演的相关算法程序,在实际缝洞碳酸盐岩、低渗致密砂岩、裂缝性基岩储层预测中取得了较好的应用效果,并申请4项授权发明专利。
[Abstract]:In view of the influence of reflection coefficient and low frequency model on seismic inversion, the relationship between reservoir seismic characteristics and reservoir parameters is established on the basis of analyzing seismic velocity and spectral characteristics, which is also an important content of reservoir seismic inversion research. The thickness convolution model of dipole wavelet reservoir is established, the characteristics of dipole wavelet seismic response and the mathematical expressions of multiple integrals are expressed, the reflection coefficient equation of the top-bottom interface of dipole wavelet reservoir is derived, and the data converted by seismic odd-even multiple integral has the characteristics of reservoir thickness and relative impedance prediction, thus forming the dipole seismic wavelet reservoir. Theoretical basis of layer prediction. The thin interbed theory model confirms that the energy-constrained reservoir thickness spectrum method can realize quantitative prediction of reservoir thickness, and the identification thickness is related to the thickness of reservoir and barrier; the thicker the barrier, the easier the reservoir to distinguish, and the prediction thickness can reach lambda/16 (lambda wavelength) under relatively simple geological conditions. For the most difficult thin interbed to predict, the identification of thickness is made. Under the constraints of multi-stage sedimentary micro-cycles, the multipole wavelet reconstruction method is further used to improve the prediction effect of thin interbeds. The data transformed by seismic multi-stage differential technique is used to highlight the relative impedance information of higher frequency band and improve the ability of identifying thin beds. The low frequency information of integral recovery has a good matching relationship with the frequency division impedance of log in the same frequency band, which lays a foundation for the construction of low frequency model in the next seismic inversion.Seismic inversion depends on the accuracy of the initial low frequency impedance or velocity model. Because the interval velocity of seismic root mean square velocity prediction is sensitive to time variation, it requires higher authenticity and accuracy of seismic data time resampling. The interpolation effect of time sampling is effectively improved by seismic waveform constrained interpolation method, and the continuous root mean square of prestack seismic gather is improved in time and space. The accuracy of velocity estimation is helpful to establish fine layer velocity model and has better prediction effect in low frequency band. Aiming at the complexity of target function construction, the step-by-step decomposition method is adopted to determine the parameters. By means of line and other constraints, the important frequency, phase and attenuation coefficient characteristic parameters of wavelet are accurately obtained, and the order of optimization of seismic wavelet is defined as follows: main frequency, attenuation coefficient when delay occurs; and then through sensitivity analysis of elastic parameters, it is pointed out that the order of optimization of parameters is reservoir thickness, P-wave velocity, S-wave velocity and density, so as to realize multi-parameter step by step. Constrained dipole wave reservoir thickness prediction and reservoir characteristic inversion. Aiming at the problems of large amount of pre-stack full waveform inversion calculation and inadequate quality and accuracy of seismic gathers, this paper studies the multi-calculus thickness prediction and the establishment of pre-stack fine low-frequency velocity model, and draws lessons from mature pre-stack wave impedance inversion and AVO inversion techniques. Combining the travel time and dynamic characteristics of pre-stack AVA seismic inversion wave field effectively, the multi-integral and multi-order differential transformation relative impedance reservoir model of seismic data is reconstructed, and the elastic impedance models with different angles are established. A technique for simultaneous inversion of pre-stack three parameters of dipole wavelet is proposed. The related algorithm program of seismic inversion has achieved good application results in the prediction of carbonate rock, low permeability tight sandstone and fractured bedrock reservoir, and has applied for four patents.
【学位授予单位】：成都理工大学
【学位级别】：博士
【学位授予年份】：2017
【分类号】：P631.4

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