Fast pre-stack multi-channel inversion constrained by seismic reflection features

Classical multi-channel technology can significantly reduce the pre-stack seismic inversion uncertainty, especially for complex geology such as high dipping structures. However, due to the consideration of complex structure or reflection features, the existing multi-channel inversion methods have to adopt the highly time-consuming strategy of arranging seismic data trace-by-trace, limiting its wide application in pre-stack inversion. A fast pre-stack multi-channel inversion constrained by seismic reflection features has been proposed to address this issue. The key to our method is to re-characterize the reflection features to directly constrain the pre-stack inversion through a Hadamard product operator without rearranging the seismic data. The seismic reflection features can reflect the distribution of the stratum reflection interface, and we obtained them from the post-stack profile by searching the shortest local Euclidean distance between adjacent seismic traces. Instead of directly constructing a large-size reflection features constraint operator advocated by the conventional methods, through decomposing the reflection features along the vertical and horizontal direction at a particular sampling point, we have constructed a computationally well-behaved constraint operator represented by the vertical and horizontal partial derivatives. Based on the Alternating Direction Method of Multipliers (ADMM) optimization, we have derived a fast algorithm for solving the objective function, including Hadamard product operators. Compared with the conventional reflection features constrained inversion, the proposed method is more efficient and accurate, proved on the Overthrust model and a field data set.

Petrophysical parameters inversion for heavy oil reservoir based on a laboratory-calibrated frequency-variant rock-physics model

Heavy oil has high density and viscosity, and exhibits viscoelasticity. Gassmann's theory is not suitable for materials saturated with viscoelastic fluids. Directly applying such model leads to unreliable results for seismic inversion of heavy oil reservoir. To describe the viscoelastic behavior of heavy oil, we modeled the elastic properties of heavy oil with varying viscosity and frequency using the Cole-Cole-Maxwell (CCM) model. Then, we used a CCoherent Potential Approximation (CPA) instead of the Gassmann equations to account for the fluid effect, by extending the single-phase fluid condition to two-phase fluid (heavy oil and water) condition, so that partial saturation of heavy oil can be considered. This rock physics model establishes the relationship between the elastic modulus of reservoir rock and viscosity, frequency and saturation. The viscosity of the heavy oil and the elastic moduli and porosity of typical reservoir rock samples were measured in laboratory, which were used for calibration of the rock physics model. The well-calibrated frequency-variant CPA model was applied to the prediction of the P- and S-wave velocities in the seismic frequency range (1–100 Hz) and the inversion of petrophysical parameters for a heavy oil reservoir. The pre-stack inversion results of elastic parameters are improved compared with those results using the CPA model in the sonic logging frequency (∼10 kHz), or conventional rock physics model such as the Xu-Payne model. In addition, the inversion of the porosity of the reservoir was conducted with the simulated annealing method, and the result fits reasonably well with the logging curve and depicts the location of the heavy oil reservoir on the time slice. The application of the laboratory-calibrated CPA model provides better results with the velocity dispersion correction, suggesting the important role of accurate frequency dependent rock physics models in the seismic prediction of heavy oil reservoirs.

Pre-stack inversion for caved carbonate reservoir prediction:A case study from Tarim Basin,China

The major storage space types in the carbonate reservoir in the Ordovician in the TZ45 area are secondary dissolution caves.For the prediction of caved carbonate reservoir,post-stack methods are commonly used in the oilfield at present since pre-stack inversion is always limited by poor seismic data quality and insufficient logging data.In this paper,based on amplitude preserved seismic data processing and rock-physics analysis,pre-stack inversion is employed to predict the caved carbonate reservoir in TZ45 area by seriously controlling the quality of inversion procedures.These procedures mainly include angle-gather conversion,partial stack,wavelet estimation,low-frequency model building and inversion residual analysis.The amplitude-preserved data processing method can achieve high quality data based on the principle that they are very consistent with the synthetics.Besides,the foundation of pre-stack inversion and reservoir prediction criterion can be established by the connection between reservoir property and seismic reflection through rock-physics analysis.Finally,the inversion result is consistent with drilling wells in most cases.It is concluded that integrated with amplitude-preserved processing and rock-physics,pre-stack inversion can be effectively applied in the caved carbonate reservoir prediction.

Elastic modulus extraction based on generalized pre-stack PP–PS wave joint linear inversion

Joint PP–PS inversion offers better accuracy and resolution than conventional P-wave inversion. P-and S-wave elastic moduli determined through data inversions are key parameters for reservoir evaluation and fluid characterization. In this paper, starting with the exact Zoeppritz equation that relates P-and S-wave moduli, a coefficient that describes the reflections of P-and converted waves is established. This method effectively avoids error introduced by approximations or indirect calculations, thus improving the accuracy of the inversion results. Considering that the inversion problem is ill-posed and that the forward operator is nonlinear, prior constraints on the model parameters and modified low-frequency constraints are also introduced to the objective function to make the problem more tractable. This modified objective function is solved over many iterations to continuously optimize the background values of the velocity ratio, which increases the stability of the inversion process. Tests of various models show that the method effectively improves the accuracy and stability of extracting P and S-wave moduli from underdetermined data. This method can be applied to provide inferences for reservoir exploration and fluid extraction.

Impedance inversion of pre-stack seismic data in the depth domain

The extensive application of pre-stack depth migration has produced huge volumes of seismic data,which allows for the possibility of developing seismic inversions of reservoir properties from seismic data in the depth domain.It is difficult to estimate seismic wavelets directly from seismic data due to the nonstationarity of the data in the depth domain.We conduct a velocity transformation of seismic data to make the seismic data stationary and then apply the ridge regression method to estimate a constant seismic wavelet.The estimated constant seismic wavelet is constructed as a set of space-variant seismic wavelets dominated by velocities at different spatial locations.Incorporating the weighted superposition principle,a synthetic seismogram is generated by directly employing the space-variant seismic wavelets in the depth domain.An inversion workflow based on the model-driven method is developed in the depth domain by incorporating the nonlinear conjugate gradient algorithm,which avoids additional data conversions between the time and depth domains.The impedance inversions of the synthetic and field seismic data in the depth domain show good results,which demonstrates that seismic inversion in the depth domain is feasible.The approach provides an alternative for forward numerical analyses and elastic property inversions of depth-domain seismic data.It is advantageous for further studies concerning the stability,accuracy,and efficiency of seismic inversions in the depth domain.

Pre-stack AVO inversion with adaptive edge preserving smooth filter regularization based on Aki-Richard approximation

With the development of exploration of oil and gas resources,the requirements for seismic inversion results are getting more accurate.In particular,it is hoped that the distribution patterns of oil and gas reservoirs can be finely characterized,and the seismic inversion results can clearly characterize the location of stratigraphic boundaries and meet the needs of accurate geological description.Specifically,for pre-stack AVO inversion,it is required to be able to distinguish smaller geological targets in the depth or time domain,and clearly depict the vertical boundaries of the geological objects.In response to the above requirements,we introduce the preprocessing regularization of the adaptive edge-preserving smooth filter into the pre-stack AVO elastic parameter inversion to clearly invert the position of layer boundary and improve the accuracy of the inversion results.

Fluid discrimination incorporating amplitude variation with angle inversion and squirt flow of the fluid

Pre-stack seismic inversion is an important method for fluid identification and reservoir characterization in exploration geophysics. In this study, an effective fluid factor is initially established based on Biot poroelastic theory, and a pre-stack seismic inversion method based on Bayesian framework is used to implement the fluid identification. Compared with conventional elastic parameters, fluid factors are more sensitive to oil and gas. However, the coupling effect between rock porosity and fluid content is not considered in conventional fluid factors, which may lead to fuzzy fluid identification results. In addition,existing fluid factors do not adequately consider the physical mechanisms of fluid content, such as squirt flow between cracks and pores. Therefore, we propose a squirt fluid factor(SFF) that minimizes the fluid and pore mixing effects and takes into account the squirt flow. On this basis, a novel P-wave reflection coefficient equation is derived, and the squirt fluid factor is estimated by amplitude variation with offset(AVO) inversion method. The new reflection coefficient equation has sufficient accuracy and can be utilized to estimate the parameters. The effectiveness and superiority of the proposed method in fluid identification are verified by the synthetic and field examples.

A Quadratic precision generalized nonlinear global optimization migration velocity inversion method

An important research topic for prospecting seismology is to provide a fast accurate velocity model from pre-stack depth migration. Aiming at such a problem, we propose a quadratic precision generalized nonlinear global optimization migration velocity inversion. First we discard the assumption that there is a linear relationship between residual depth and residual velocity and propose a velocity model correction equation with quadratic precision which enables the velocity model from each iteration to approach the real model as quickly as possible. Second, we use a generalized nonlinear inversion to get the global optimal velocity perturbation model to all traces. This method can expedite the convergence speed and also can decrease the probability of falling into a local minimum during inversion. The synthetic data and Mamlousi data examples show that our method has a higher precision and needs only a few iterations and consequently enhances the practicability and accuracy of migration velocity analysis （MVA） in complex areas.

准东地区云质岩储层叠前反演及脆性预测

脆性是一种评价致密储层可压裂性的重要指标,对油气勘探与开发有着重要的意义。准东地区勘探程度低、探井少,二叠系中下部云质岩致密储层的精细描述和脆性的准确预测均有着很大的难度。为此,根据岩石物理实验结果,利用叠前地震角度域数据体,开展储层叠前反演及脆性预测。通过AVO反演,获取P(截距)+G(梯度)和P×G属性;通过Y(杨氏模量,E)P(泊松比,σ)D(密度,ρ)和L(拉梅常数,λ)M(μ)R(ρ)反演,获取弹性参数的变化率(反射系数);通过测井约束反演,获取弹性参数的实际值,并用多种表征公式计算脆性,分析其物理含义及应用效果。研究结果表明:①研究区横波速度与纵波速度有较好的拟合关系,杨氏模量、泊松比和密度对泥岩、非泥岩区分度明显;②云质岩具有高速特征,研究区储层呈双“甜点”结构;③用三个小角度数据体直接反演弹性参数反射系数,YPD反演方法相较LMR的储层识别效果更好、分辨率更高,密度反射系数数据体可见比较明显的扇体及河道冲积特征;④脆性表征结果与弹性参数特征有一定的区别,脆性表征的云质岩有利区呈条带状分布,而弹性参数预测的云质岩有利区基本呈连续、成片分布;⑤ρE/σ为研究区最佳的脆性表征公式,可为类似油田云质岩储层脆性预测提供借鉴。

Reservoir prediction using pre-stack inverted elastic parameters

This is a case study of the application of pre-stack inverted elastic parameters to tight-sand reservoir prediction. With the development of oil and gas exploration, pre-stack data and inversion results are increasingly used for production objectives. The pre-stack seismic property studies include not only amplitude verse offset （AVO） but also the characteristics of other elastic property changes. In this paper, we analyze the elastic property parameters characteristics of gas- and wet-sands using data from four gas-sand core types. We found that some special elastic property parameters or combinations can be used to identify gas sands from water saturated sand. Thus, we can do reservoir interpretation and description using different elastic property data from the pre-stack seismic inversion processing. The pre- stack inversion method is based on the simplified Aki-Richard linear equation. The initial model can be generated from well log data and seismic and geologic interpreted horizons in the study area. The input seismic data is angle gathers generated from the common reflection gathers used in pre-stack time or depth migration. The inversion results are elastic property parameters or their combinations. We use a field data example to examine which elastic property parameters or combinations of parameters can most easily discriminate gas sands from background geology and which are most sensitive to pore-fluid content. Comparing the inversion results to well data, we found that it is useful to predict gas reservoirs using λ, λρ, λ/μ, and K/μ properties, which indicate the gas characteristics in the study reservoir.

准北地区侏罗系煤层脆性叠前预测

准噶尔盆地煤层气资源量超6万亿方,中石化探区1.3万亿方,资源潜力大;白家海地区彩探1H井,西山窑组煤层埋深2385 m,通过压裂日产气5.7万方,无水,一年累产气796万方,煤层气勘探取得了重大突破。准北地区石北凹陷煤层主要发育在西山窑组和八道湾组,西山窑组为主力层组.

煤层脆性叠后地震预测方法及应用

煤的脆性是指煤受外力作用而破碎的性质,表现为抗压强度和抗剪强度,强度小者,煤易破碎,脆度大;反之,脆度小(李增学,2009)。煤层脆性是煤层气储层压裂区选择的重要参考依据。影响煤岩脆性的因素较多,包括岩石组分、层理和损伤等先存弱面结构、孔隙流体及其压力、围压、温度、岩体测量尺度以及受力演化过程等(曹东升等,2021)。

致密砂岩储层“双甜点”识别方法在南海东部陆丰地区古近系储层的应用

深层致密砂岩储层是近年来南海东部油气勘探研究的重点目标,然而仅靠常规地质甜点识别方法难以满足现阶段深层勘探评价的需求。地质、工程“双甜点”储层识别方法是客观评价低渗储层产能潜力、寻找具有经济产能有效储层的有效手段。在南海东部陆丰地区,结合古近系致密砂岩储层特点,应用“双甜点”识别方法寻找研究区古近系储层有利区带分布范围,主要包括:①利用机器学习驱动下的反演技术确定优势相带地质甜点砂体分布;②基于岩石力学实验的泊松比、杨氏模量脆性指数构建地震预测模型;③基于叠前弹性阻抗反演技术预测泊松比及杨氏模量进而开展工程甜点识别以及地质甜点与工程甜点融合的致密砂岩储层“双甜点”识别。“双甜点”识别方法有效揭示了研究区古近系致密砂岩储层有利区带分布特征,依据识别结果进行井位部署,最终成功实现了海上压裂求产,证明了“双甜点”识别方法在陆丰地区的适用性。

非常规储层脆性研究进展及展望

简要论述了脆性的国内外研究现状和影响因素,在此基础上总结了7种最主要的脆性指数表达式,阐述了各自的物理含义。将储层脆性的预测方法分为基于传统方法的地震脆性反演方法与基于深度学习技术的脆性预测方法,评价了两种方法的优缺点:传统方法应用广泛、算法相对成熟、稳定可靠但需要大量先验知识,在复杂地质条件下效果受限;深度学习方法可以适应复杂地质条件,无需先验信息,原理和操作简单,但是训练过程需要大量的计算资源和时间。介绍了贝叶斯AVAZ脆性直接反演、基于测井导数和波动率属性的机器学习脆性预测、基于CNN-LSTM模型的混合神经网络脆性预测等新技术。最后,展望了脆性预测技术的发展方向。

川南页岩气田L区块页岩脆性指数叠前地震定量预测

页岩脆性指数是页岩气压裂设计中应考虑的关键参数之一。以川南页岩气田L区块页岩脆性指数研究为例,针对目前常用的弹性脆性预测方法存在地区适应性差的问题,提出了一种多元非线性回归脆性指数预测的改进模型。首先通过模型建立了矿物脆性指数与Rickman脆性指数及最小闭合应力系数之间的关系,然后针对三维地震资料利用叠前地震反演方法获取所需的弹性参数,进而实现研究区页岩层段纵向及横向脆性预测。川南页岩气田L区块的应用结果表明,在已有钻井矿物脆性指数的约束下,利用改进后的脆性指数预测方法得到的改进模型适用性更强,利用该模型预测得到的五峰组-龙马溪组一亚段脆性指数在横向上分布稳定,符合地质认识;通过已知井检验可知,预测得到的脆性指数在纵向上与矿物脆性指数相关性好。

基于机器学习的脆性指数直接反演方法

常规脆性指数预测方法是基于叠前振幅随偏移距的变化(AVO)反演,间接计算过程中会产生累积误差。提出了一种脆性指数直接反演方法,该方法使用BI_Zoeppritz方程来表示地震数据与脆性指数之间的关系,通过机器学习LSSVM算法建立非线性反演模型,直接反演出脆性指数。实际资料测试结果表明:该方法具有更高的精度和更强的抗噪声能力,利用该方法进行脆性指数的直接反演是可行的。

基于叠前地震的脆性预测方法及应用研究

页岩储层的开发主要依赖于水力压裂,因此有必要研究储层的岩石力学性质。利用地球物理方法分析岩石脆性特征、反演杨氏模量和泊松比对于页岩气的开发具有重要意义。基于贝叶斯理论,通过最小二乘构建反演方法对杨氏模量和泊松比进行直接反演,有效避免了常规AVO反演密度项的不稳定和参数转换过程中的误差积累,提高了反演结果精度。同时借助后验协方差矩阵,对反演结果进行了不确定性分析,发现其不确定性有明显的降低。利用反演得到的杨氏模量和泊松比,进一步计算目的层脆性指数(BI),并通过微地震监测数据对预测结果进行验证,为寻找有利压裂区域提供重要的基础数据。应用实际资料预测的脆性结果与测井结果具有较高的一致性,显示了方法具有一定的应用推广前景。

泥页岩脆性地球物理预测技术

本文以四川盆地东部JN地区侏罗系东岳庙段陆相页岩气研究为例,探讨了页岩脆性预测的难点和存在的问题,提出有针对性的页岩脆性地球物理预测技术和方法。在页岩岩石物理建模和脆性特征分析基础上,确定了以叠前弹性参数同时反演为核心的地震预测技术对该区进行页岩脆性预测研究。该方法是基于Zoeppritz近似方程和贝叶斯参数估计理论,用协方差矩阵来描述参数间的相关程度,然后用参数间的岩石物理关系对反演结果进行约束,从而得到页岩层的纵波、横波和密度信息,进而定量描述页岩脆性。通过已知井检验,地震预测的脆性指数与脆性矿物含量有较好的一致性。

岩石脆性预测在吉木萨尔凹陷致密油勘探中的应用

岩石的脆性是非常规油气藏勘探开发中需考虑的关键岩石力学参数之一。岩石脆,压裂过程中易产生缝网,从而有效改造储层,达到提高单井产量的目的。基于岩石弹性参数的归一化杨氏模量和泊松比方法,是当前广泛采用的可用于地震预测的岩石脆性评价技术,但其结果受归一化参数取值的影响较大,适用性受到影响。利用杨氏模量和泊松比的商作为脆性评价指标,并用大量岩石力学实验刻度,大大提高了岩石脆性判别的可信度。利用地震叠前弹性参数反演,开展吉木萨尔凹陷二叠系芦草沟组致密油岩石脆性预测,指导水平井部署。为保证更好的储层改造效果,在水平井轨迹设计过程中不但考虑了储层物性,还充分考虑了岩石脆性。在优选的有利区钻探水平井,并实施了体积压裂,微地震监测结果显示压裂产生了缝状网,储层改造效果理想。该水平井试油获得了稳定高产工业油流。

焦石坝页岩脆性评价与预测

在寻找页岩气有利区域时,页岩的脆性预测是非常重要的一个环节。传统的脆性指数预测方法是叠前三参数反演,即通过反演纵波速度、横波速度和密度等参数计算页岩脆性指数。但受入射角度或偏移距的限制,叠前反演得到的密度误差较大,根据以上参数计算的页岩脆性指数累积误差更大。以四川盆地焦石坝页岩气区块为例,探讨了应用叠后地震波形指示反演预测页岩地层脆性的方法。在页岩脆性矿物定量评价的基础上,依据测井资料计算出单井脆性矿物含量曲线,综合利用测井、地震、地质等资料,通过叠后地震波形指示反演得到脆性矿物含量数据体,进而求取页岩地层脆性的空间分布,提高页岩脆性预测精度。焦石坝工区页岩脆性波形指示反演结果显示,目的层五峰组和龙马溪组的①、③小层脆性指数较高,与岩心测试数据和实钻压裂结果吻合,为该区页岩气田的开发和井位部署提供了依据。