基于沉积过程的数字岩石建模方法研究

本文提出模拟地层沉积及成岩过程的矿物沉积算法,建立数字岩石模型,并通过对比Micro-CT扫描图像和数值模型的局部孔隙度及平均渗流概率函数分布特征,评价建模的准确性.结果表明,由二维扫描提取的粒径信息作为输入参数,模拟矿物沉积过程建模得到的三维数字岩石模型,能够准确重构原始岩心的非均质性及渗流特性,成功应用于泥质砂岩、碳酸盐岩、页岩等存在多矿物或多尺度孔隙的数字岩石建模中.数字岩石物理是正在兴起的重要技术.数字岩石采用超高分辨率先进成像装备,采集和表征微纳尺度岩石结构,在岩石弹性、电性、核磁、渗流特性等数值计算中发挥重要作用.但是,由于三维直接成像在有限视域内难以表征足够的岩石非均质性,提取二维结构统计特征,利用统计或地质过程法重构具有代表性的三维岩石结构成为十分有价值的研究课题,而且,对业界大量存在的岩石薄片及电镜高清二维图像的深度开发应用也具有重要的现实意义.本文发展的新方法,复原沉积过程,较好地解决了孔隙尺度岩石物理定量研究中数值建模与理论计算的技术瓶颈.     

重力和重力梯度数据三维相关成像

本文提出了重力异常三维相关成像方法和重力梯度数据三维相关成像方法,并提出了基于异常分离的三维相关成像方法来提高成像分辨率.通过合成Y型岩脉模型和合成多个直立长方体组合模型的重力异常和重力梯度数据试验分析,验证了本文三维相关成像方法可显示出异常地质体的空间赋存状态和等效剩余质量分布,具有良好的纵向和横向分辨率.     

磁异常△T三维相关成像

本文将重力和重力梯度数据三维相关成像方法推广到磁力勘探领域,推导并建立了磁异常△T的三维相关成像方法,同时提出了基于熵滤波分离异常的三维相关成像算法来提高成像分辨率.组合模型磁异常△T数据和实际磁测资料试验分析表明,本文方法能成像出地下地质体的空间赋存状态和等效磁性分布,具有良好的横向和纵向分辨率.     

利用混合法构建三维数字岩心(英文)

在弹性波有三维数字岩心描述了岩石的微观孔隙结构。X射线CT扫描是获取三维数字岩心最准确和直接的方法,但实验成本高。本文结合沉积过程模拟和模拟退火算法,提出了重建三维数字岩心的混合法,基于岩石二维图像重建三维数字岩心。利用岩石颗粒沉积算法构建初始数字岩心,作为模拟退火算法的初始状态。运用模拟退火算法调整岩石颗粒和孔隙的相对位置,使三维数字岩心与岩心二维图像具有相似的自相关函数,从而建立三维数字岩心。与传统模拟退火算法相比,该方法计算时间明显减小。运用局部孔隙度理论定量比较了重建数字岩心和岩心X射线微CT图像,两种数字岩心具有相似的均质性和孔隙连通性。利用有限元方法和格子玻尔兹曼方法分别模拟了重建三维数字岩心的地层因素和渗透率,数值模拟结果与实验结果相符。相比传统模拟退火算法,混合法重建数字岩心的传导特性更接近真实岩心的传导特性。     

一种改进型C3相干算法

基于特征值结构的相干体算法(C3算法)的核心思想就是用与水平时间切片的相关的相干值压制水平方向上介质连续性,凸显不连续性,因此具有最佳的横向(即水平)分辨率,而对倾角数据效果较差.为了改善倾向分辨率,本文提出一种用测线抽取数据进行计算的方式取代基本算法中面元抽取数据计算的方式.试算结果表明该算法真实有效,精度有较大的提高.     

拉东投影法三维叠前深度偏移

对地下地质构造进行正确成像是地震勘探的最终目的,由于三维地震资料采集不可能都沿垂直构造走向的方向进行,为地震资料的三维处理带来了许多困难. 本文将三维叠后拉东投影偏移思想应用于三维叠前处理中,提出了三维叠前投影偏移算法. 利用拉东投影变换的原理,将整个三维叠前数据体投影到一系列各方向的径向线上,各方位角的构造都包含在其中某条或多条径向剖面上. 投影完成后,形成一系列的独立的二维叠前测线,可采用二维叠前深度偏移成像方法来实现各径向线的叠前偏移,当各径向剖面偏移完成后,在时间切片上进行反投影,从而最终形成三维叠前深度偏移结果. 实际应用表明,用本方法进行三维叠前深度偏移时,深度偏移剖面对横向分辨率有所提高,对陡地层和小断层的成像效果有所改善.     

频谱成像技术研究进展

频谱成像技术是近年来发展起来的一项基于频率谱分解的储层特色解释技术,是地震属性分析中重要组成部分.频谱成像技术具有在空间横向上分辨率高的特点,是一种利用三维地震资料的多尺度信息对储层进行高分辨率成像、检测储层时间厚度变化的工具.地震数据振幅谱可以识别地层的时间厚度变化,相位谱可以检测地质体横向不连续性,在确定油藏边界、计算地层厚度方面比传统地震属性研究方法具有更大的优势.频谱成像技术的核心模块是信号的时频分析,本文回顾了频谱成像技术的基本概念和目前在频谱成像中广泛应用的时频分析方法,简单介绍了几种新的时频分析方法:广义S变换和改进的匹配追踪算法.     

磁异常ΔT三维相关成像

本文将重力和重力梯度数据三维相关成像方法推广到磁力勘探领域,推导并建立了磁异常ΔT的三维相关成像方法,同时提出了基于熵滤波分离异常的三维相关成像算法来提高成像分辨率.组合模型磁异常ΔT数据和实际磁测资料试验分析表明,本文方法能成像出地下地质体的空间赋存状态和等效磁性分布,具有良好的横向和纵向分辨率.     

砂岩和页岩弹性波性质的实验研究进展

砂岩和页岩的弹性波性质是通过地震资料推断储层物性和流体分布的基础.岩石波速测量常用超声波(10⁵～10⁶ Hz)脉冲法,低频岩石物理实验技术的发展为研究弹性波在岩石中的衰减和频散奠定了基础.本文系统总结了前人在高频和低频下测量砂岩和页岩弹性波性质的方法和实验结果,并结合矿物弹性性质和岩石物理模型,分析了压力、温度、矿物组成、孔隙结构、流体、频率等因素对岩石波速和衰减的影响.由于孔隙和微裂隙随压力增加而逐渐关闭,干燥砂岩和页岩的P波和S波速度在低压下随压力非线性增加,高于临界压力呈线性增加.干燥岩石样品的波速随温度增加而缓慢线性降低,频散效应可以忽略.而含流体砂岩和页岩的衰减和频散受温度、压力、流体饱和度、流体黏度、孔隙结构和频率等多种因素的影响,含流体砂岩和页岩的泊松比和逆品质因子Q^-1显著高于干燥样品.低压下砂岩的波速与孔隙度负相关,而影响页岩波速的因素更为复杂,页岩的波速、衰减和频散的各向异性都高于砂岩.将跨频段岩石物理实验与数字岩石物理技术相结合,可为勘探地球物理的方法创新和资料解释提供可靠依据.     

致密砂岩衰减岩石物理图板分析:储层微裂隙预测

致密砂岩储层普遍具有孔隙度低、微裂隙发育的特点,岩石内部常含有强烈的结构非均质性.致密砂岩发育的微裂隙使储层具有良好的连通性,促成高饱和气的天然气成藏.针对川西某探区须家河组高含气饱和度致密砂岩,本文选取致密砂岩岩心样本,进行了不同围压下的超声波实验测量.考虑储层完全饱气情况下的粒间孔隙、微裂隙双重孔隙结构,采用Biot-Rayleigh双重孔隙方程,构建致密砂岩岩石物理模型,进而分析了裂隙含量对纵波频散和衰减的影响.基于地震波衰减,构建了致密砂岩多尺度岩石物理图板.采用谱比法和改进频移法估算致密砂岩样本及储层衰减,对超声和地震频带下的图板进行校正.将校正后的图板应用到研究工区,选取二维测线和三维区块,进行储层孔隙度和裂隙含量的定量预测.对比实际资料进行分析,结果显示,本文预测的孔隙度和裂隙含量与三口测井的孔隙度曲线和实际产气情况基本吻合,基于孔隙-裂隙衰减岩石物理模型有效地预测了优质储层的分布区域.     

3D simultaneous seismic data reconstruction and noise suppression based on the curvelet transform

Seismic data contain random noise interference and are affected by irregular subsampling. Presently, most of the data reconstruction methods are carried out separately from noise suppression. Moreover, most data reconstruction methods are not ideal for noisy data. In this paper, we choose the multiscale and multidirectional 2D curvelet transform to perform simultaneous data reconstruction and noise suppression of 3D seismic data. We introduce the POCS algorithm, the exponentially decreasing square root threshold, and soft threshold operator to interpolate the data at each time slice. A weighing strategy was introduced to reduce the reconstructed data noise. A 3D simultaneous data reconstruction and noise suppression method based on the curvelet transform was proposed. When compared with data reconstruction followed by denoizing and the Fourier transform, the proposed method is more robust and effective. The proposed method has important implications for data acquisition in complex areas and reconstructing missing traces.     

Curvelet reconstruction of non-uniformly sampled seismic data using the linearized Bregman method

Seismic data reconstruction, as a preconditioning process, is critical to the performance of subsequent data and imaging processing tasks. Often, seismic data are sparsely and non-uniformly sampled due to limitations of economic costs and field conditions. However, most reconstruction processing algorithms are designed for the ideal case of uniformly sampled data. In this paper, we propose the non-equispaced fast discrete curvelet transform-based three-dimensional reconstruction method that can handle and interpolate non-uniformly sampled data effectively along two spatial coordinates. In the procedure, the three-dimensional seismic data sets are organized in a sequence of two-dimensional time slices along the source–receiver domain. By introducing the two-dimensional non-equispaced fast Fourier transform in the conventional fast discrete curvelet transform, we formulate an L1 sparsity regularized problem to invert for the uniformly sampled curvelet coefficients from the non-uniformly sampled data. In order to improve the inversion algorithm efficiency, we employ the linearized Bregman method to solve the L1-norm minimization problem. Once the uniform curvelet coefficients are obtained, uniformly sampled three-dimensional seismic data can be reconstructed via the conventional inverse curvelet transform. The reconstructed results using both synthetic and real data demonstrate that the proposed method can reconstruct not only non-uniformly sampled and aliased data with missing traces, but also the subset of observed data on a non-uniform grid to a specified uniform grid along two spatial coordinates. Also, the results show that the simple linearized Bregman method is superior to the complex spectral projected gradient for L1 norm method in terms of reconstruction accuracy.     

基于非均匀曲波变换的高精度地震数据重建

在野外数据采集过程中,空间非均匀采样下的地震道缺失现象经常出现,为了不影响后续资料处理,必须进行高精度数据重建.然而大多数常规方法只能对空间均匀采样下的地震缺失道进行重建,而对于非均匀采样的地震数据则无能为力.为此本文在以往多尺度多方向二维曲波变换的基础上,首先引入非均匀快速傅里叶变换,建立均匀曲波系数与空间非均匀采样下地震缺失道数据之间的规则化反演算子,在L1最小范数约束下,使用线性Bregman方法进行反演计算得到均匀曲波系数,最后再进行均匀快速离散曲波反变换,从而形成基于非均匀曲波变换的高精度地震数据重建方法.该方法不仅可以重建非均匀带假频的缺失数据,而且具有较强的抗噪声能力,同时也可以将非均匀网格数据归为到任意指定的均匀采样网格.理论与实际数据的处理表明了该方法重建效果远优于非均匀傅里叶变换方法,可以有效地指导复杂地区数据采集设计及重建.     

基于jitter采样和曲波变换的三维地震数据重建

传统的地震勘探数据采样必须遵循奈奎斯特采样定理,而野外数据采样可能由于地震道缺失或者勘探成本限制,不一定满足采样定理要求,因此存在数据重建问题.本文基于压缩感知理论,利用随机欠采样方法将传统规则欠采样所带来的互相干假频转化成较低幅度的不相干噪声,从而将数据重建问题转为更简单的去噪问题.在数据重建过程中引入凸集投影算法(POCS),提出采用e^-√x(0≤x≤1)衰减规律的阈值参数,构建基于曲波变换三维地震数据重建技术.同时针对随机采样的不足,引入jitter采样方式,在保持随机采样优点的同时控制采样间隔.数值试验表明,基于曲波变换的重建效果优于傅里叶变换,jitter欠采样的重建效果优于随机欠采样,最后将该技术应用于实际地震勘探资料,获得较好的应用效果.     

基于Curvelet变换的探地雷达资料噪声衰减方法

噪声衰减是探地雷达信号处理中的关键问题之一。当探测目标埋藏深度比较浅时,其反射信号与直耦信号和地面回波信号相互重叠,直接影响目标反射波到达时刻的检测及目标的正确定位。针对这个问题,本文提出了一种基于Curvelet变换的噪声衰减方法。通过对理论数值模拟数据和实测数据的处理,以及与平均消去法和二维连续小波该方法处理结果的对比,验证了该方法的可行性和有效性。处理结果显示,该方法不仅可以去除背景噪声、同时可以衰减倾斜相关的相干干扰和数据中的随机噪声。与二维连续小波变换方法相比有更高的计算效率。     

Computation of elastic properties of 3D digital cores from the Longmaxi shale

The dependence of elastic moduli of shales on the mineralogy and microstructure of shales is important for the prediction of sweet spots and shale gas production. Based on 3D digital images of the microstructure of Longmaxi black shale samples using X-ray CT, we built detailed 3D digital images of cores with porosity properties and mineral contents. Next, we used finite-element (FE) methods to derive the elastic properties of the samples. The FE method can accurately model the shale mineralogy. Particular attention is paid to the derived elastic properties and their dependence on porosity and kerogen. The elastic moduli generally decrease with increasing porosity and kerogen, and there is a critical porosity (0.75) and kerogen content (ca. ≤3%) over which the elastic moduli decrease rapidly and slowly, respectively. The derived elastic moduli of gas- and oil-saturated digital cores differ little probably because of the low porosity (4.5%) of the Longmaxi black shale. Clearly, the numerical experiments demonstrated the feasibility of combining microstructure images of shale samples with elastic moduli calculations to predict shale properties.     

Estimating primaries by sparse inversion of the 3D curvelet transform and the L1-norm constraint

In this paper, we built upon the estimating primaries by sparse inversion (EPSI) method. We use the 3D curvelet transform and modify the EPSI method to the sparse inversion of the biconvex optimization and L1-norm regularization, and use alternating optimization to directly estimate the primary reflection coefficients and source wavelet. The 3D curvelet transform is used as a sparseness constraint when inverting the primary reflection coefficients, which results in avoiding the prediction subtraction process in the surface-related multiples elimination (SRME) method. The proposed method not only reduces the damage to the effective waves but also improves the elimination of multiples. It is also a wave equationbased method for elimination of surface multiple reflections, which effectively removes surface multiples under complex submarine conditions.     

An objective algorithm for reconstructing the three-dimensional ocean temperature field based on Argo profiles and SST data

While global oceanic surface information with large-scale, real-time, high-resolution data is collected by satellite remote sensing instrumentation, three-dimensional (3D) observations are usually obtained from in situ measurements, but with minimal coverage and spatial resolution. To meet the needs of 3D ocean investigations, we have developed a new algorithm to reconstruct the 3D ocean temperature field based on the Array for Real-time Geostrophic Oceanography (Argo) profiles and sea surface temperature (SST) data. The Argo temperature profiles are first optimally fitted to generate a series of temperature functions of depth, with the vertical temperature structure represented continuously. By calculating the derivatives of the fitted functions, the calculation of the vertical temperature gradient of the Argo profiles at an arbitrary depth is accomplished. A gridded 3D temperature gradient field is then found by applying inverse distance weighting interpolation in the horizontal direction. Combined with the processed SST, the 3D temperature field reconstruction is realized below the surface using the gridded temperature gradient. Finally, to confirm the effectiveness of the algorithm, an experiment in the Pacific Ocean south of Japan is conducted, for which a 3D temperature field is generated. Compared with other similar gridded products, the reconstructed 3D temperature field derived by the proposed algorithm achieves satisfactory accuracy, with correlation coefficients of 0.99 obtained, including a higher spatial resolution (0.25° × 0.25°), resulting in the capture of smaller-scale characteristics. Finally, both the accuracy and the superiority of the algorithm are validated.     

Inverse data-space multiple elimination with 3D curvelet sparsity promotion

This paper describes an effective implementation of the inverse data-space multiple elimination method via the three-dimensional (3D) curvelet domain. The method can separate the surface-related operator (A) and primaries (P ₀) through seismic data matrix inversion. A 3D curvelet transform is introduced to sparsely represent the seismic data in the inverse data space. Hence, this approach is suitable for obtaining an accurate solution because of its multiscale and multidirectional analysis properties. The L1 norm is used to promote sparseness in the transform domain. Then, a high-fidelity separation of the operator (A) and the primaries (P ₀) is realized. The proposed method is applied to synthetic data from a model containing a salt structure. We compare the results with that of the traditional inverse data-space multiple elimination method and also with that of two-dimensional surface-related multiple elimination. The findings fully demonstrate the superiority of the proposed method over the traditional inverse method; moreover, the proposed method protects the primary energy more effectively than the SRME method.