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Blended acquisition along with efficient spatial sampling is capable of providing high-quality seismic data in a cost-effective and productive manner. While deblending and data reconstruction conventionally accompany this way of data acquisition, the recorded data can be processed directly to estimate subsurface properties. We establish a workflow to design survey parameters that account for the source blending as well as the spatial sampling of sources and detectors. The proposed method involves an iterative scheme to derive the survey design leading to optimum reflectivity and velocity estimation via joint migration inversion. In the workflow, we extend the standard implementation of joint migration inversion to cope with the data acquired in a blended fashion along with irregular detector and source geometries. This makes a direct estimation of reflectivity and velocity models feasible without the need of deblending or data reconstruction. During the iterations, the errors in reflectivity and velocity estimates are used to update the survey parameters by integrating a genetic algorithm and a convolutional neural network. Bio-inspired operators enable the simultaneous update of the blending and sampling operators. To relate the choice of survey parameters to the performance of joint migration inversion, we utilize a convolutional neural network. The applied network architecture discards suboptimal solutions among newly generated ones. Conversely, it carries optimal ones to the subsequent step, which improves the efficiency of the proposed approach. The resultant acquisition scenario yields a notable enhancement in both reflectivity and velocity estimation attributable to the choice of survey parameters. 相似文献
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Time-lapse monitoring is a powerful tool for observing dynamic changes in the subsurface. In particular it offers the potential for achieving inversion results with increased fidelity through the inclusion of complementary information from multiple time-steps. This inclusion of complementary information can reduce the need for spatial smoothing, without adding inversion artifacts to the resulting images. Commonly used time-lapse inversion methods include the ratio method, cascaded time-lapse inversion, difference inversion and differencing independent inversions. We introduce two additional methods in which both time-lapse data sets are inverted simultaneously. In the first, called temporally constrained time-lapse inversion, inversion of both datasets is done under a single optimization procedure and constraints are added to the regularization to ensure that the changes from one time to another are smooth. In the second method, called simultaneous time-lapse inversion, the inversions at time 1 and time 2 are performed simultaneously and constraints of smoothness and closeness to a reference model are applied to the difference image produced at each iteration, and subsequently, the constraints are updated at each iteration. Through both a numerical and a field example we compare the results of common time-lapse inversion methods as well as the introduced approaches. We found that of the commonly used time-lapse inversion methods the difference inversion method produced the best resolution of time-lapse changes and was the most robust in the presence of noise. However, we found that the alternative approach of simultaneous time-lapse inversion produced the best reconstruction of modeled EC changes in the numerical example and easily interpretable high resolution difference images in the field example. Moreover, there was less tailoring of regularization parameters with our simultaneous time-lapse approach, suggesting that it will lend itself well to an automated inversion code. 相似文献
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Considering Zoeppritz equations, reflections of PP and PS are only the function of ratios of density and velocity. So the inversion results will be the same if the ratios are the same but values of density, velocities of P-wave and S-wave are different without strict constraint. This paper makes efforts to explore nonlinear simultaneous PP and PS inversion with expectation to reduce the ambiguity of AVO analysis by utilizing the redundancy of multi-component AVO measurements. Accurate estimation of ratio parameters depends on independence of input data. There are only two independent AVO attributes for PP reflectivity (i.e. intercept and gradient) and two for PS reflectivity (i.e. pseudo-intercept and pseudo-gradient or extreme amplitude), respectively. For individual PP and PS inversion, the values of least-squares objective function do not converge around a large neighborhood of chosen true model parameters. Fortunately for joint PP and PS inversion the values of the least-squares objective function show closed contours with single minima. Finally the power function fitting is used to provide a higher precision AVO attributes than traditional polynomial fitting. By using the four independent fitting attributes (two independent attributes for PP and PS respectively), the inversion of four ratio parameters (velocities and densities) would be estimated with less errors than that in traditional method. 相似文献
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The added value of the joint pre-stack inversion of PP (incident P-wave and reflected P-wave) and PS (incident P-wave and reflected S-wave) seismic data for the time-lapse application is shown. We focus on the application of this technique to the time-lapse (four-dimensional) multicomponent Jubarte field permanent reservoir monitoring seismic data. The joint inversion results are less sensitive to noise in the input data and show a better match with the rock physics models calibrated for the field. Further, joint inversion improves S-impedance estimates and provides a more robust quantitative interpretation, allowing enhanced differentiation between pore pressure and fluid saturation changes, which will be extremely useful for reservoir management. Small changes in reservoir properties are expected in the short time between the time-lapse seismic acquisitions used in the Jubarte project (only 1 year apart). The attempt to recover subtle fourth-dimensional effects via elastic inversion is recurrent in reservoir characterization projects, either due to the small sensitivity of the reservoirs to fluid and pressure changes or the short interval between the acquisitions. Therefore, looking for methodologies that minimize the uncertainty of fourth-dimensional inversion outputs is of fundamental importance. Here, we also show the differences between PP only and joint PP–PS inversion workflows and parameterizations that can be applied in other projects. We show the impact of using multicomponent data as input for elastic seismic inversions in the analysis of the time-lapse differences of the elastic properties. The larger investment in the acquisition and processing of multicomponent seismic data is shown to be justified by the improved results from the fourth-dimensional joint inversion. 相似文献
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通过地震海洋学联合调查航次,获得了同时采集的高分辨率多道地震数据与水文数据（XBT）联合调查数据.通过针对性处理获得了清晰的海洋水体反射地震剖面,捕捉到南海东北部次表层涡旋,证明了该调查方法的有效性.利用背景场约束反演方法得到海水的波阻抗、声速、密度、温度和盐度剖面,揭示了涡旋具有相对低速、高密、低温与高盐特征.处理和反演结果表明,在浅部和部分噪声较强和无约束反演区域,结果误差较大,可靠性较低.调查结果说明,获得较高信噪比的原始高分辨率地震资料采集技术方法、联合约束数据的获取、针对性的特殊处理方法和有效的反演方法是地震海洋学资料有效分析利用的重要保证. 相似文献
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在VTI介质中,由于引入了各向异性参数使得多分量多参数地震反演问题的非线性程度显著增加,因此采用传统的权重加权法构建单目标函数进行反演得到的反演结果往往并不理想.本文以反射率法为基础,结合快速非支配排序遗传算法研究了一种VTI介质的多分量叠前联合反演方法.该方法以反射率法为正演方程,应用互相关原理构建PP波和PSV波的多目标函数,进而采用快速非支配排序遗传算法全局寻优获得VTI介质的厚度、纵横波速度、密度和各向异性参数等多个参数.在正演的过程中,反射率法可以考虑几何扩散、吸收衰减、透射损失、多次波以及纵横波旅行时不匹配等地震波传播效应,更能精确地描述地震波在地下地层中的真实传播情况;在反演的过程中,快速非支配排序遗传算法可以在不引入权重系数的条件下同时优化多个目标函数,获得联合反演问题的Pareto最优解,既不添加权重系数影响又充分利用多分量地震数据.模型测试结果验证了该反演方法的有效性和可行性. 相似文献
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本文针对蒸汽辅助重力泄油(SAGD)生产中开发监测问题,发展了综合应用地震及重力数据反演储层密度的联合反演算法.通过测井数据建立纵波阻抗与密度的直接关系,并推导出这种关系下重力与纵波阻抗数据联合反演的计算方法,从而计算出蒸汽腔体密度分布规律.文中应用密度反演后验约束正则化方法,采用Tikhonov正则化模型,通过波阻抗数据作为约束进行联合反演,在算法上提高了稳定性,同时得到较高的反演精度.文中对SAGD生产中的理论模型进行了方法试算,并分析了算法的误差,最终应用于SAGD生产的实际数据中,通过最终反演结果分析,该方法取得了很好的应用效果. 相似文献
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Traditional least-squares reverse time migration (LSRTM) often aims to improve the quality of seismic imaging, such as removing the acquisition footprint, suppressing migration artifacts and enhancing resolution. In this paper, we find that the conventional reflectivity defined in the LSRTM is related to the normal-incident reflection coefficient and the background velocity. Compared with the defined reflectivity, our inverted result is relatively “true”. With reflected data, LSRTM is mainly sensitive to impedance perturbations. According to an approximate relationship between them, we reformulate the perturbation related system into a reflection-coefficient related one. Then, we seek the inverted image through linearized iteration. Moreover, with the assumption that the density varies more gradually than the migration velocity, only the knowledge of the latter is required, although the reflected waves are produced at impedance discontinuities. We test our method using the 2D Marmousi synthetic dataset. 相似文献
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逆时偏移(RTM)是复杂介质条件下地震成像的重要手段.因受观测系统限制、上覆地层影响以及波场带宽有限等因素的影响,现行的常规RTM所采用的互相关成像条件通常对地下构造进行模糊成像.最小二乘逆时偏移(LSRTM)通过最小化线性Born近似正演数据和采集数据之间的波形差异,采用梯度类反演算法优化反射系数模型,获得的成像结果具有更高的分辨率和更可靠的振幅保真度.然而,基于波形拟合的LSRTM对背景速度模型的依赖性很强.误差太大的速度模型容易产生周波跳跃现象,导致LSRTM难以获得全局最优解.为了克服这一问题,本文基于扩展模型的思想,在线性Born近似下,推导得到RTM扩展成像条件.并基于最小二乘反演理论,提出扩展成像条件下的LSRTM方法.理论模型试算表明,本文方法不仅可以提供分辨率更高、振幅属性更为可靠的成像结果,而且能够在一定程度上消除速度误差对反演成像的影响. 相似文献
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Cross double‐difference inversion for simultaneous velocity model update and microseismic event location 
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下载免费PDF全文 Microseismic monitoring is an approach for mapping hydraulic fracturing. Detecting the accurate locations of microseismic events relies on an accurate velocity model. The one‐dimensional layered velocity model is generally obtained by model calibration from inverting perforation data. However, perforation shots may only illuminate the layers between the perforation shots and the recording receivers with limited raypath coverage in a downhole monitoring problem. Some of the microseismic events may occur outside of the depth range of these layers. To derive an accurate velocity model covering all of the microseismic events and locating events at the same time, we apply the cross double‐difference method for the simultaneous inversion of a velocity model and event locations using both perforation shots and microseismic data. The cross double‐difference method could provide accurate locations in both the relative and absolute sense, utilizing cross traveltime differences between P and S phases over different events. At the downhole monitoring scale, the number of cross traveltime differences is sufficiently large to constrain events locations and velocity model as well. In this study, we assume that the layer thickness is known, and velocities of P‐ and S‐wave are inverted. Different simultaneous inversion methods based on the Geiger's, double‐difference, and cross double‐difference algorithms have been compared with the same input data. Synthetic and field data experiments suggest that combining both perforation shots and microseismic data for the simultaneous cross double‐difference inversion of the velocity model and event locations is available for overcoming the trade‐offs in solutions and producing reliable results. 相似文献
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4-D inversion of DC resistivity monitoring data acquired over a dynamically changing earth model 总被引：2，自引：0，他引：2
Jung-Ho Kim Myeong-Jong Yi Sam-Gyu Park Jae Gon Kim 《Journal of Applied Geophysics》2009,68(4):522-532
Geophysical monitoring is used principally to interpret the locations and amounts of ground condition changes. To achieve these objectives, differences are computed and examined using time-lapse images calculated under the time-invariant static assumption, that any material property changes during the data measurement can be practically ignored. These monitored data, however, can be contaminated with noise and frequently generate false anomalies of ground condition changes. Furthermore, the assumption of the static model can be invalid if the material property changes significantly during data acquisition. To alleviate these problems, we developed a new least-squares inversion algorithm that allows for the subsurface properties to continuously change in time. We define the subsurface structure and the entire monitoring data in the space–time domain, allowing us to obtain a four-dimensional space–time model using just one inversion process. We introduce the regularizations not only in the space domain but also in time, resulting in reduced inversion artifacts and improved stability of the inverse problem. We demonstrated the performance of the proposed algorithm through numerical experiments that assumed several scenarios of ground condition changes and data acquisition sequences. Finally, the applicability to field data was proven by applying the developed algorithm to the monitoring data of crosshole resistivity tomography jointly performed with a dye tracer flooding experiment. This experiment had a small enough scale that we could not ignore the change of material properties during the data measurement. 相似文献
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总结了牛顿类地震反演方法中Hessian算子的作用,对其在地震反演成像中的数学物理含义进行了分析.Hessian算子是误差泛函对模型参数的二阶导数,反映了误差泛函对模型变化的二次型特征.分析声波方程下的Hessian算子的格林函数表达形式,发现其表达了整个观测系统和子波频带等因素对地震数据空间到模型空间投影过程的影响.提出了两种分别适用于最小二乘偏移和全波形反演的Hessian算子简化格式.平面波Hessian算子应用于最小二乘偏移能够得到相对保真的成像结果,改善了地震偏移成像的精度.地下偏移距Hessian算子应用于全波形反演能够加快反演迭代的计算效率.最后,对Hessian算子在地震反演成像中的价值进行了讨论和评价. 相似文献
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全波形反演可以为叠前深度偏移成像提供更高精度的速度模型,但该方法具有较强的非线性,对初始速度模型的依赖性较强,尤其是在实际应用中,地质条件复杂多变,速度变化不连续,增加了反演非线性程度,常常使反演陷入局部极小值,影响反演的精度.全变差约束在图像去噪领域应用广泛,属于非光滑约束,在去噪过程中能有效的保留图像的不连续界面和边缘信息.本文提出基于Hinge损失函数的垂向全变差约束全波形反演方法,在全变差约束的基础上,利用Hinge损失函数控制模型的更新方向,并使用原-对偶混合梯度算法进行求解,给出这一优化问题的迭代格式,有效提高了对地下不连续界面的重构精度,同时也降低反演对初始速度模型的依赖程度.数值算例证明：与常规全波形反演方法相比,基于全变差约束的全波形反演方法可以有效的重构速度模型中的不连续界面,尤其对高速体边缘的重构效果更明显,但该方法对初始速度模型的依赖性仍然较强;基于Hinge损失函数的垂向全变差约束全波形反演方法降低了对初始速度模型的依赖程度,可以从一个较差的初始模型通过循环迭代的方式最终得到同样精确的速度模型,较好的重构了高速体边缘和不连续界面. 相似文献
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叠前同时反演是油气探测的一种有效工具.其理论基础是平面P波Zoeppritz方程计算的反射系数的近似,是入射角的函数.叠前同时反演可以利用三项或两项Fatti方程进行反演分析.本文针对实际油田的测井数据,利用反射率法模拟了仅包含P波一次反射记录,包含P波一次反射和P波层间多次波记录以及全波场地震记录,再利用叠前同时反演对合成地震记录进行反演研究.研究结果表明,在大偏移距处P波主要反射受到其它模式波的污染,从而影响了叠前同时反演结果的精度.对于薄互层介质当转换波影响严重时,使用小角度数据的两项AVO反演比使用大角度数据的三项AVO反演更合理可靠. 相似文献
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随着地震勘探目标从构造型油气藏向岩性油气藏的转变,地震勘探难度日益增大,这就要求从地震数据中获得更多可靠且具有明确地质含义的属性信息,并充分利用这些属性信息来对储层的岩性、岩相进行分析.AVO三参数反演能够从振幅随炮检距的变化信息中直接提取纵波速度、横波速度以及密度来估计岩石和流体的性质,进而对储层进行预测.然而,AVO反演本身是一个不适定的问题,加上地震纵波反射系数对横波速度和密度的不敏感,会造成单纯利用纵波地震数据进行反演的结果误差大.随着地震接收和数据处理技术的发展,越来越多的学者对PP-PS联合反演方法进行了研究并在实际资料中得以运用.融合转换横波地震数据的联合反演在一定程度上提高了反演的精度,降低了解的不稳定性.但是在信噪比较低的情况下,联合反演的效果受到了限制.本文从优化理论出发,提出了基于粒子滤波提供先验知识的l1范数约束极小化问题的稀疏解算法.并将上述方法运用到了不同的模型中,通过比较分析,证实了该方法在不同信噪比资料中的有效性和在信噪比较低情况下的优势. 相似文献
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Pre-stack depth migration velocity analysis is one of the key techniques influencing image quality. As for areas with a rugged surface and complex subsurface, conventional prestack depth migration velocity analysis corrects the rugged surface to a known datum or designed surface velocity model on which to perform migration and update the velocity. We propose a rugged surface tomographic velocity inversion method based on angle-domain common image gathers by which the velocity field can be updated directly from the rugged surface without static correction for pre-stack data and improve inversion precision and efficiency. First, we introduce a method to acquire angle-domain common image gathers (ADCIGs) in rugged surface areas and then perform rugged surface tomographic velocity inversion. Tests with model and field data prove the method to be correct and effective. 相似文献
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地震反演是储层定量描述和地震油气识别的关键技术,反演结果在复杂构造区域的横向连续性和保真性是影响地震资料定量解释精度的重要因素.基于此,本文发展了地震数据互相关驱动的多道反演方法.考虑地层反射系数与地震数据在结构上具有相似性的特点,基于地震数据互相关描述地层反射系数的结构特征,并将其作为多道地震反演的横向约束条件;此外,为改善地震数据本身横向连续性差对反演结果的影响,在目标泛函的惩罚项中引入局部优化算子,构建了一个易于求解的多道地震反演目标泛函.与常规多道地震反演方法相比,本文方法能够设计更合理、更符合实际情况的横向约束算子,提高反演结果的横向连续性,并且能有效降低地震资料质量对反演结果的影响.模型测试和实际应用验证了本方法的可靠性和稳定性. 相似文献
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针对时移地震差异数据,给出了一种基于贝叶斯理论的AVO波形反演方法.该方法可以利用时移地震差异数据同时反演出纵波阻抗、横波阻抗和密度的变化.利用时移地震资料进行反演,由于采集和处理过程中存在一定的差异,不同年份地震资料在非注采过程影响区域也会存在一定的变化,而该变化会导致反演结果在非注采区域有较大的变化.针对这一问题,本文采用贝叶斯理论框架,将待求的纵横波阻抗、密度变化的先验信息和包含在地震数据中的信息结合起来,对于纵横波阻抗和密度变化,假设其服从Gauss分布,并以时移地震分别反演的结果作为其期望,同时,为了更好地表征储层属性变化,提高分辨率和抑制非注采区域弹性参数的变化,假设弹性参数变化的导数服从改进的Cauchy分布.数值模拟试验和实际资料处理结果皆表明,本文提出的反演方法能够有效地抑制假象,突出储层性质的变化,得到高分辨率的弹性参数变化信息,为研究储层属性的变化和优化开采方案提供更多的有效的信息. 相似文献