The transformation of elastic impedance (EI) from partial-angle-stacked seismic data is a crucial technique in the domains of reservoir modelling. Conventionally, EI inversion is performed on a per-angle basis, leading to significant discrepancies in EI values across different angles, which may not accurately represent actual conditions. When the signal-to-noise ratio (SNR) of seismic data is low, the inverted EI tends to be unstable, resulting in poor-quality inversion outcomes. This research proposes a novel method that allows for enabling the derivation of EI for various angles simultaneously inverted from multiple partial angle-stack seismic datasets in one process. The aim of simultaneous inversion is to potentially ensure consistent EI results. To obtain this aim, we utilize an advanced regularization method called the Gramian constraint. Consequently, the objective function for the simultaneous inversion of multiple EIs is developed. Results from both synthetic and field data demonstrate improved stability in EI inversion, especially for the case of low SNR.

The sparsity-regularized linear inverse problem has been widely used in many fields, such as remote sensing imaging, image processing and analysis, seismic deconvolution, compressed sensing, medical imaging, etc. This method offers greater flexibility in solving real-world problems. There are various sparse regularization method available, such as L0-norm, Lp-norm ( $0\lt {p} \lt 1$ ) regularization, L1-norm, weighted L1-norm regularization, Cauchy regularization, modified Cauchy regularization, t regularization, and so on. L1-norm regularization is the most well-known and widely used due to its convexity and linearity. It can be efficiently solved by the iterative soft thresholding algorithm (ISTA) or its faster variants. The soft thresholding operator works on each element individually and is highly efficient. In contrast, some other efficient sparse regularization methods are nonlinear, making them more challenging to solve. These sparse regularization can address the limitations of L1-norm regularization, such as degeneracy. An effective approach to solving sparse regularization problems is the iterative re-weighting least squares (IRLSs) algorithm. However, IRLS is computationally intensive and may not be suitable for massive data applications. In this letter, we propose a unified algorithmic framework for solving sparse regularization linear inverse problems. Our method combines the principles of ISTA and IRLS to create an element-wise iterative re-weighting algorithm. We have applied this algorithm to the sparse spike deconvolution of real seismic data and demonstrated its effectiveness when solve sparsity-regularized linear inverse problems.

The stress interference in deep shale may lead to shale fracturing and instability and consequently results in engineering risks such as casing deformation in horizontal wells. Therefore, in the early stages of shale gas exploration and development, it is of great significance to evaluate the stability of shale fractures in advance. The stability evaluation of shale reservoir faults can be mainly divided into two categories at present: quantitative evaluation of single faults and qualitative evaluation of wide-range faults. The quantitative evaluation of single faults primarily relies on numerical simulation techniques, while the qualitative evaluation of wide-range faults primarily employs geophysical methods. Both methods are difficult to meet the needs of shale gas exploration and development. The shale fracture stability evaluation method based on 3D discrete fracture model which is developed in this article can quantitatively evaluate the static stability of wide-range shale fractures in the early stage of exploration and development. In this article, seismic geometric attributes were calculated, and fracture seismic facies was established by means of the Bayesian probabilistic cluster analysis method. Then, 3D discrete fracture modeling under the constraint of fracture seismic facies was performed to establish a discrete fracture model. Finally, according to the Mohr-Coulomb criterion, the shear stress and effective normal stress of discrete fracture were calculated by using the formation pressure data in other exploration and development results and the regional in situ stress obtained through seismic prestack inversion. And thus, the stability evaluation of the fractures in shale reservoirs was eventually completed. In addition, this method was verified by using the casing deformation points in some actual shale-gas horizontal wells, the actual small fault points, and microseismic data. It indicates that the method has higher accuracy and is better applicable to the early shale gas exploration and development.

The exploration and development potential of shale gas reservoirs in the Sichuan Basin is enormous; however, it also faces difficulties such as complex structures, strong heterogeneity, and unclear geophysical response characteristics. Fine prediction of geostress is an important part of shale gas exploration and development, which directly affects the implementation effect of reservoir evaluation, well trajectory design, and fracture reconstruction. The existing geostress prediction techniques lack high-precision seismic data constraints, making it difficult to accurately reflect the planar distribution characteristics of geostress in the block with rapid changes in complex tectonic zones. At the same time, the geophysical response characteristics of geostress in the Sichuan Basin are unknown, and the geostress seismic prediction technology lacks theoretical basis. This paper combines numerical simulation and physical experiments and defines the characteristics of the geophysical response of shale gas reservoirs in the Sichuan Basin changing with the stress field, and technical countermeasures for geostress seismic prediction have been established to provide technical means for accurate prediction of the geostress field in the shale gas block. Based on the geostress sensitive parameters obtained from prestack seismic inversion, the geostress field prediction of a shale gas work area in the Sichuan Basin is realized.

Model-based inversion technology has become one of the necessary technologies in the seismic exploration industry. It is frequently used to estimate many subsurface attributes, i.e., velocity, impedance, attenuation, etc. It is important to note that the accuracy of model-based inversion relies on the precision of the initial model, which suffers from insufficiency of low-frequency information in seismic data. Enhancing the high-frequency content and accuracy of low frequencies in the initial model can improve solution accuracy. Conventional initial models fail to adequately represent the high-frequency details of lateral geologic variations and to capture low-frequency components accurately. We develop a wavelet transform solution for this problem. Initially, we demonstrate that seismic records approximate the wavelet transform of logarithmic impedance. Consequently, we use the wavelet inverse transform to reconstruct the mid- and high-frequency information of seismic impedance, highlighting the detailed spatial variations. Furthermore, we apply kriging interpolation, based on subspace interpolation principles, using well impedance and seismic record waveforms to derive the low-frequency impedance from the scale inverse transform. Wavelet transform theory ensures a perfect match between the low- and high-frequency components in the inversion result. The frequency components of the inversion result are balanced, with no deficiencies or redundancies within the seismic data's ' s high cutoff frequency band. Thus, our method of initial model building is a type of inversion method. In addition, this method is simple and efficient because fast convolution processing can be performed. Model experiments and practical data inversions confirm the method's ' s feasibility and its ability to enhance resolution.

河流相储层中由于河道迁移、切削等因素形成的不连续边界常常阻碍了储层内部流体的流动,增大了剩余油气的开采难度.受地震分辨率的限制,这些不连续边界在常规地震剖面上一般难以识别.通过模型试验,提出了一种应用于河流相薄互层砂体的提高频率分辨率的相位谱计算方法,即将一个周期时窗的地震数据末端补零至适当长度,再进行傅里叶变换,求取展开相位谱和积分展开相位,可增加其稳定性;其次,基于典型河流相叠置砂体构型,建立不同纵向高程差的两组砂体叠置模型,分析不同叠置样式的地震相位特征,认为相位异常值与砂体不连续夹层厚度存在定性关系,利用积分展开相位可以较好地识别砂体不连续边界.噪声实验认为信噪比大于 5∶1 时,识别结果可信.将该方法应用于渤海南部海域某工区实际地震数据,识别出两处砂体叠置区域,其结果与测井识别出的叠置情况吻合.应用结果表明,将地震数据周期时窗尾端补零求取的积分展开相位在识别叠置砂体不连续边界稳定且有效.

Sparsity-regularized linear inverse problem has served as the base in many disciplines, such as remote sensing imaging, image processing and analysis, seismic deconvolution, compressed sensing, medical imaging, and so forth. The iterative hard thresholding algorithm (IHTA) and iterative soft thresholding algorithm (ISTA) are two frequently used methods to solve sparsity-regularized linear inverse problems. They are also the basic unit of other more complex methods. IHTA and ISTA are derived under the steepest descent method, i.e., iteratively perform gradient descent and thresholding shrinkage. The steepest descent method is a first-order algorithm, which is a powerful way to solve optimization due to its relatively simple implementation. However, a known issue of the first-order method is the possible poor convergence rate. Fast iterative thresholding-like algorithms have been proposed to overcome this issue in the existing works of literature. In history, another alternative way is second-order algorithms or quasi-second-order algorithms. In this letter, we include a quasi-Newton’s method, i.e., Davidon–Fletcher–Powell (DFP) formulations in the framework of iterative thresholding-like algorithms to replace gradient descent to form a hybrid method to further increase convergence rate. The proposed method has been performed on two numerical examples and a real-life application in sparse-spike seismic deconvolution. The numerical examples and real-life application showed that it provides an effective alternative method to solve sparsity-regularized linear inverse problems.

In exploration geophysics, seismic impedance is a physical characteristic parameter of underground formations. It can mark rock characteristics and help stratigraphic analysis. Hence, seismic data inversion for impedance is a key technology in oil and gas reservoir prediction. To invert impedance from seismic data, one can perform reflectivity series inversion first. Then, under a simple exponential integration transformation, the inverted reflectivity series can give the final inverted impedance. The quality of the inverted reflectivity series directly affects the quality of impedance. Sparse-spike inversion is the most common method to obtain reflectivity series with high resolution. It adopts a sparse regularization to impose sparsity on the inverted reflectivity series. However, the high resolution of sparse-spike-like reflectivity series is obtained at the cost of sacrificing small reflectivity. This is the inherent problem of sparse regularization. In fact, the reflectivity series from the actual impedance well log is not strictly sparse. It contains not only the sparse major large reflectivity, but also small reflectivity between major reflectivity. That is to say, the large reflectivity is sparse, but the small reflectivity is dense. To combat this issue, we adopt elastic-net regularization to replace sparse regularization in seismic impedance inversion. The elastic net is a hybrid regularization that combines sparse regularization and dense regularization. The proposed inversion method was performed on a synthetic seismic trace, which is created from an actual well log. Then, a real seismic data profile was used to test the practice application. The inversion results showed that it provides an effective new alternative method to invert impedance.

High-precision time–frequency (TF) analysis (TFA) can accurately detect anomalies in oil and gas reservoirs. However, conventional TFA methods cannot effectively identify fractured-vuggy carbonate reservoirs, which are deep and strongly heterogeneous. In this letter, a TFA method based on analytical mode decomposition (AMD) and the Hilbert–Huang transform (HHT) is proposed. Specifically, seismic signals are decomposed by empirical mode decomposition (EMD) and then by AMD. Finally, the TF distribution (TFD) of the seismic signals is obtained after Hilbert spectrum analysis (HSA). Synthetic seismic data demonstrate that the AMD-HHT method can effectively eliminate mode mixing and provide higher time and frequency resolutions and energy focus than conventional TFA methods. In addition, model and field seismic data also verify that the AMD-HHT method can effectively detect hydrocarbon-related energy anomalies hidden in broadband seismic data.

利用常规的相干类属性与蚂蚁追踪组合技术所获取的不连续性信息,难以满足油田对于河流相和三角洲相薄砂岩储层精细剖析的需求.为了更好地检测薄砂岩储层内部不连续性,首先利用对薄砂岩储层变化更加敏感的均方根振幅属性计算灰度共生矩阵的均质性统计量,初步得到薄砂岩储层的不连续性特征数据;然后根据其不连续性结构的展布特点,运用路径弯曲度约束人工蚂蚁的移动方向,优化蚁群算法的平面增强效果,达到压制干扰信息、突出不连续性特征的目的;最终形成更适应薄砂岩储层不连续性检测的组合技术.模型和实际工区数据的应用结果表明,采用上述组合技术能较好地识别薄砂岩体的边缘以及其内部的小尺度不连续性结构,说明了该技术对薄砂岩储层内部不连续性检测的有效性,并且其检测结果能用于提升砂岩厚度预测精度,为后续的砂体内部结构精细刻画提供技术支持.

海上油田开发中后期,识别并预测河流相砂体边界是老油田剩余油挖潜中亟待解决的重点问题.由于海上井点少、井距大,砂体尺度小、散度大;密井网条件下的测井方法和常规砂体边界地震识别方法并不适用.基于能反映砂体横向展布的地震属性,使用联合双边滤波、Otsu自适应阈值处理方法及形态学算法改进Canny算子,进行河流相砂体边界的预测,形成了一套自适应、高精度的河流相砂体边界的预测方法.从河流相砂体的沉积特点和演变规律出发,建立了 一组正演模型,验证了方法的有效性.将此方法应用于渤海Q油田,在目标层取得了良好的效果.

In the process of fluvial sedimentary evolution, mudstone interlayer is frequently developed in the interval of sandstone deposition, forming a reservoir of sandstone compartment. Some generally nonpermeable or semipermeable interlayers become discontinuity interfaces of a reservoir, which is one of the causes for the complexity in the distribution of remaining oil. The degree of the impermeability of the discontinuity interface on fluid flow is critical to the development of hydrocarbons. The discontinuity interface, a small-scale reservoir discontinuity comparing with the fault, is generally below the seismic vertical resolution ([Formula: see text]). The key to the study of the discontinuity interface is to characterize the variation of plane characteristics of sediments between isochronous seismic horizons. Therefore, we can extract seismic attributes between isochronous seismic horizons to analyze the subtle changes of seismic data, which reflect the distribution of the discontinuity interfaces. In the experiment of gradient vector to detect discontinuity interface in seismic attribute, the authors find that the width of the discontinuity interface is caused by the “lens” shape of the sandstone itself. This phenomenon is an indicator of the impermeability of the discontinuity interface. Here, we have developed a two-step method. First, we use the erosion operator of mathematical morphology to locate the skeleton of the discontinuity interface with the steering of the gradient direction. Second, we measured the width of the discontinuity interface to indicate its impermeability. The application to a field data set demonstrates that the results of this proposed method are consistent with the production data of the wells. The proposed method characterizes the reservoir heterogeneity refined from sandstone sets to a single sandstone bed, which improves the resolution of seismic geologic interpretation.

The application of seismic sedimentology to the study of reservoir development geology is its development in a new field. It is a small-scale study of reservoir development for the purpose of interpreting the characterization of single genetic sand bodies between wells. Previous interpretation methods of seismic sedimentology focused on depicting the sedimentary facies of sedimentary architecture units, and few directly predicted the discontinuities (architecture boundaries) below the seismic vertical resolution, lambda/4. Therefore, we use the seismic forward modeling method to analyze the seismic recognizable scale of sedimentary architecture units, and reduce the multiplicity of interpretation through geological model constraints. We also use neural network method to predict the architecture seismic facies, and use seismic attributes to predict the internal boundary of the architecture units. The results show that the seismic sedimentology method has a higher accuracy for the internal boundary of sedimentary architecture units comparing with the traditional coherent method below the seismic vertical resolution. Thus, we can use the combined method of seismic architecture facies and boundaries to interpret the internal structure of thin-layer sedimentary units.

在河流相砂体储层中,由于河道凸岸侧向加积,以及河道本身的迁移摆动等,常常使河道砂体产生了叠置沉积界面.这些不连续性沉积界限的存在,会直接影响到砂体内流体的流动,影响河流相砂岩油气藏的开发效果.针对河流相叠置砂体不连续界限检测问题,提出了一种展开相位谱属性识别叠置砂体不连续性界限位置的方法.具体思路是对小时窗内地震数据求得展开相位谱,并将展开相位谱转化为积分相位谱属性,通过这种属性的变化来识别砂体叠置的不连续性界限位置.

地震反射系数的幅值与相位是地震反射波的重要特征,对地震资料反演起着重要作用.利用自由界面上SV波入射的反射系数公式,通过建立9个不同泊松比的介质模型,绘制了反射SV波与转换P波反射系数的振幅、相位随入射角及泊松比的变化曲线,分析了不同泊松比介质的反射系数随入射角变化的规律,特别关注临界角附近的突变特征.通过对比分析发现:在临界角附近,对于P波反射系数的突变值,大泊松比(0.3～0.5)和小泊松比(0～0.3)介质存在较大差异.随着采样点数的增加,能更准确观测到SV波反射系数曲线在临界角前的极小点,进而充分认识SV波的全波型转换.研究结果对于深入认识地震波传播特征以及实施广角地震勘探或多波地震勘探具有较大实际意义.

The ill-posed feature is one basic attribute of geophysical inversion methods. As an example of geophysical inverse problem, AVA (Amplitude variation with incident angle) inversion of pre-stack seismic data is susceptible to noise and uncertainty in the acquisition. To get stable and accurate inversion results, the regularization constraints on model parameter need to be added into the objective function of AVA inversion. In AVA inversion, the most commonly used regularization includes sparsity constraint (e.g. L1-norm regularization, Cauchy regularization) and a priori model parameters constraint, and so forth. However, the existing AVA inversion methods do not consider the structural similarity of different model parameters. All of the different model parameters represent the same underground geological structure, so they should have similar structure. This paper adopts the cross gradient to measure the structural similarity of different model parameters. Next, the cross gradients of different model parameters are added into the objective function of AVA inversion as a regularization term to implement structural similarity constraint. Results of the model numerical tests and real seismic data indicate that the AVA inversion with cross-gradient constraint has higher stability compared to the AVA inversion without structural similarity constraint, especially for the density inversion results.

The prediction of brittleness is an important research field for shale gas exploration and development. Currently, the most common way to evaluate the brittleness is calculating the average of the sum of normalized Young's modulus and Poisson's ratio. But this method needs pre-stack seismic inversion, petrophysics model calculation and normalization which is not an efficient way to obtain brittleness index directly and may introduce iterative error in the process. This paper derives a novel elastic impedance (EI) approximation which establishes a direct relationship with brittleness index. After that, we discussed the accuracy of EI approximation in Goodway's model, the results show the approximation is very close to Zoeppritz matrix when the incident angle is less than 30 degrees. Then we establish a method under Bayesian framework for improving the accuracy of brittleness index prediction. We find the predicted brittleness index fits very well with the real model data even SNR = 3. Finally, we apply our theory to shale gas block in southern Sichuan Basin, it shows that the predicted brittleness index not only fits well with well-logging, but also indicates the highest brittleness layer which is consistent with the rock core experiment results.

By examining field outcrops, drilling cores and seismic data, it is concluded that the Middle and Late Permian “Emeishan basalts” in Western Sichuan Basin were developed in two large eruption cycles, and the two sets of igneous rocks are in unconformable contact. The lower cycle is dominated by overflow volcanic rocks; while the upper cycle made up of pyroclastic flow volcanic breccia and pyroclastic lava is typical explosive facies accumulation. With high-quality micro-dissolution pores and ultra-fine dissolution pores, the upper cycle is a set of high-quality porous reservoir. Based on strong heterogeneity and great differences of pyroclastic flow subfacies from surrounding rocks in lithology and physical properties, the volcanic facies and volcanic edifices in Western Sichuan were effectively predicted and characterized by using seismic attribute analysis method and instantaneous amplitude and instantaneous frequency coherence analysis. The pyroclastic flow volcanic rocks are widely distributed in the Jianyang area. Centering around wells YT1, TF2 and TF8, the volcanic rocks in Jianyang area had 3 edifice groups and an area of about 500 km2 which is the most favorable area for oil and gas exploration in volcanic rocks.

High-resolution multichannel seismic data and multibeam terrain data are used to analyse and identify a focused fluid flow (FFF) system in the central and northern parts of the Zhongjiannan Basin in the western South China Sea. The authors classify and summarise the geophysical characteristics of an FFF system in the study area. It is divided into a fault-related FFF system and a column-related FFF system. In addition, the FFF system in the study area is mainly located within the tectonic activity area, thin slope break belt and land slope area. The rich FFF system in the study area is an important channel for fluid migration, which is conducive to gas hydrate accumulation. The FFF system in the study area is poorly studied, and the distribution research results of the FFF system in this area can be used more widely in hydrocarbon and gas hydrate exploration and must be taken into account when assessing seabed stability.

中国东部油田普遍存在断裂复杂、砂泥岩互层严重以及河道砂体间错落重叠等地质特征.由于地震纵向分辨率的限制,因而无法可靠识别低序级小断层和砂体重叠带,这对于油田开发方案的部署与调整影响很大.针对这一难题,设计了一个包含不同断距的断层和不同叠置范围及落差的重叠河道砂体模型,正演结果表明:小于调谐厚度的砂体重叠带在地震剖面上会形成"伪断层"响应,即与小断层类似的地震同相轴的扭曲或错断.但通过地震多属性的综合分析,发现了地震振幅类属性和地震波形结构类属性对小断层与砂体重叠带有不同的响应特征,结合常规的均方根振幅属性和波形变异系数属性,建立了两条识别准则:①均方根振幅与波形变异系数同时为低值突变可以识别断层存在;②均方根振幅为低值突变而波形变异系数为高值突变则可以识别砂体重叠带.胜利探区W102断块S23储层的地震资料应用结果表明,小断层发育区和薄砂体重叠带的均方根振幅和波形变异系数属性的异常特征与这两条识别准则基本一致,可用于识别与区分薄互层砂岩储层中的小断层与砂体重叠带,为该探区开发方案的调整部署提供了参考依据.