测井资料岩石物理分析在苏西地区储层预测研究中的应用

苏里格地区天然气资源量丰富,勘探前景广阔,是我国油气增储上产的重要区域.研究区位于苏里格气田的西侧,该区储层段砂岩与泥岩的纵波速度、密度和纵波阻抗等常规参数相互叠置,叠后波阻抗反演难以解决该区储层预测和流体识别问题.为此,利用测井资料,开展了以地震岩石物理参数分析、弹性阻抗分析、流体替换及AVO特征分析为基础的叠前储层预测可行性研究.研究结果表明:岩石的弹性参数能够很好地区分岩性,并优选出反映储层或含气性的敏感参数,如纵横波速度比、泊松比、拉梅系数和拉梅系数/剪切模量对含气性具有良好的识别能力;不同角度的弹性阻抗既可以识别岩性,也可以区分气层和非气层;利用AVO属性可以预测盒8砂岩是否含气,但不能预测其是否具有工业价值.上述研究为该区开展地震叠前储层预测和流体识别研究提供了依据,使得该区的储层预测更具针对性.     

应用叠前反演弹性参数进行储层预测(英文)

本文是利用叠前弹性参数反演结果进行致密性含气砂岩储层预测的一个实例研究。随着油气勘探开发的发展,叠前地震数据及其反演结果的应用研究已经广泛用于实际生产中。叠前地震数据的特有属性研究,不仅包括简单的AVO特性,还包括其他的弹性属性的变化特性。本文通过对含气砂岩岩芯弹性属性参数响应特征的分析,发现特定弹性属性参数或其组合可以作为流体检测因子。因此,可以利用叠前地震反演得到不同的弹性属性参数结果,进行储层解释和储层描述。该叠前反演方法是基于Zoeppritz方程的Aki—Richard简化公式建立起来的,根据测井数据和地质解释结果建立初始反演模型,反演的地震数据为叠前时间或深度偏移的共反射点道集数据,反演结果可以是不同的弹性属性参数及其组合。通过对一实际的致密性含气砂岩储层进行叠前弹性属性参数反演,并将反演结果与其它预测结果进行对比分析发现弹性属性参数λ和λρ, λ/μ,以及K／μ能够很好地预测含气储层,而且反演结果很好展现出储层中的含气特性。     

含气饱和度半定量预测方法探讨与应用

勘探实践中,与水和油相比,地层岩石孔隙中含气引起的地球物理响应特征更加明显,因此利用各种地震弹性参数较容易判定和识别地层中是否含气.然而这种含气性的判别多是定性的,含气饱和度的半定量化预测一直是个挑战.利用岩心分析、测井和测试资料,从岩石物理模拟与诊断出发,结合Gassmann流体替换理论,分别研究含气砂岩和含气饱和度的敏感弹性参数,建立相应的岩石物理解释图版.在此基础上,通过地震叠前弹性反演技术分含气砂岩和高饱和度含气砂岩两步法递进式实现含气饱和度的半定量预测,取得了较好的应用效果.实例研究表明,在一定地质条件下,这种两步法递进式半定量预测砂岩含气饱和度的方法行之有效,实际生产中可操作性强,具有一定借鉴意义.     

非均质碳酸盐岩储层岩石物理建模:孔隙度估算与烃类检测(英文)

在非均质天然气藏中,天然气一般呈细小"斑块状"分布于含水岩石骨架内。这种非均质性,即"斑块状饱和",会引起显著的地震波速度频散和能量衰减现象。为了建立地震响应和流体类型之间的联系,本文进行了碳酸盐岩岩石物理建模。首先利用CT扫描分析部分饱和岩石中的流体分布,然后预测不同频率下波响应与岩性、孔隙流体基本性质之间的定量关系,基于岩石薄片分析孔隙结构和地震反演数据制作岩石物理图板,并将这种方法应用于阿姆河右岸地区的灰岩气藏,基于叠后阻抗反演和叠前弹性参数反演,采用地震数据估算岩石孔隙度与含气饱和度,预测结果与多井试气结果吻合。     

岩石物理驱动的储层物性参数非线性地震反演方法

叠前地震反演和岩石物理反演分别是获取弹性参数和物性参数的重要手段,两者结合有助于实现储层参数预测并精细刻画储层特征.储层物性参数的反演依赖于岩石物理模型,在进行物性参数反演时可以将复杂的岩石物理模型做泰勒展开,进而得到其一阶或高阶的近似表达式,然而这会降低模型的精确性并增加反演的误差.为了提高储层物性参数反演的稳定性和准确性,本文以碎屑岩储层为例,提出了岩石物理驱动的储层物性参数非线性地震反演方法.首先,基于贝叶斯框架和高斯分布约束条件,从叠前地震数据中实现纵、横波速度及密度等弹性参数的反演.其次,通过碎屑岩岩石物理模型建立起弹性参数与物性参数之间的联系.最后,利用粒子群算法进行全局寻优获得较为准确的孔隙度、泥质含量和含水饱和度等物性参数.合成数据和实际资料测试结果验证了所提方法的可行性和准确性,反演结果与测井数据吻合较好,可有效指示含气储层区域,本文方法在储层预测和评价方面具有广泛的应用前景.     

富含煤层气储层的叠前地震反演预测方法研究——以山西晋东南测区为例

叠前地震反演技术能够将地震中振幅、偏移距和入射角等多种有效信息与油气的敏感参数结合起来,在有效识别油气藏"甜点"方面虽发挥了重要的作用,但对于煤层气的有效预测仍需研究.针对煤层气与石油天然气的赋存地质条件不同,本文以山西沁水盆地煤层气地震资料为例,借鉴叠前地震反演技术的多参数预测思想,通过模型正演和实测资料处理,得到纵波、横波速度和密度等不同的数据体,利用数据体和弹性参数关系式,采用AkiRichard近似公式与叠前宽角度反演联合的方法,寻找出富含煤层气储层的敏感参数.从而实现富含煤层气储层的有效预测.经与测井曲线结果对比,吻合率较高,说明了该方法具有可行性与实用性.     

非线性AVO反演方法研究

与叠后地震数据相比,叠前地震数据包含有更多的反映地下地层特征的信息,利用AVO( Amplitude Versus Offset,振幅随偏移距的变化)信息通过求解Zoeppritz方程的近似公式,叠前反演可直接得到反映地下岩石特征的弹性参数——密度、纵波速度和横波速度.从本质上讲,叠前地震反演是非线性的,但目前多采用线...     

基于精确Zoeppritz方程的非线性AVO三参数反演

常规AVO三参数反演通常存在密度反演不准确的问题,而密度参数对常规油气藏中的流体识别、流体饱和度计算、孔隙度计算以及非常规油气藏中TOC含量计算、裂缝预测等都至关重要,因此对于研究如何利用大偏移距振幅信息和富含密度信息的PS波地震资料来提高密度反演结果的稳定性和精度显得尤为重要.研究基于贝叶斯反演理论框架,引入三变量Cauchy分布先验约束,利用精确Zoeppritz方程构建了AVO三参数联合反演的目标函数,对目标函数进行Taylor二阶非线性简化,得到模型参数的迭代更新公式,实现了大偏移距地震振幅信息的利用和PP波、PS波联合反演.合成数据和实际地震数据的方法测试结果表明,新方法不仅可以直接反演纵波速度、横波速度和密度,而且还具有很高的精度,尤其是密度反演结果.基于合成数据的PP波、PS波单独反演结果与PP波和PS波联合反演结果对比显示,联合反演稳定性更好,精度更高,抗噪能力更强,验证了该方法的可行性和有效性.与基于Aki-Richards近似公式的反演结果对比表明,该反演方法具有更高的反演精度和更好的抗噪性.     

基于孔隙度差分频属性反演的高温高压气藏流体检测方法

经过多年的发展,目前对于常规气藏的流体检测方法已趋于成熟,形成了多套较完善的技术体系.但对于莺歌海盆地东方区高温高压气藏,研究区目的层段气层和水层均表现为"亮点"特征,岩石物理分析发现,常规弹性参数均无法区分气层与非气层.因此,针对莺歌海盆地东方区高温高压气藏的流体检测,叠后、叠前反演方法等常规烃检手段均失效.为此,笔者研究提出了一种高温高压气藏流体检测新方法,基于密度孔隙度与中子孔隙度的差值对含气的敏感指示,利用分频属性反演得到密度孔隙度与中子孔隙度的差值剖面.实现了在常规弹性参数无法区分气层和非气层的情况下有效识别和预测高温高压储层中的有效气层,在实际应用中取得了良好的效果.     

非均匀介质孔隙流体参数地震散射波反演

弹性波逆散射是非均匀介质参数反演的有效途径．本文从弹性波逆散射理论出发,利用微扰理论和稳相法,将非均匀介质参数视为背景介质与扰动介质参数的叠加,建立了纵波散射系数和非均匀介质中背景介质与扰动介质孔隙流体参数,剪切模量与密度间的直接关系．进而发展了一种非均匀介质孔隙流体参数叠前地震贝叶斯反演方法．该方法假设模型参数（扰动介质与背景介质孔隙流体参数,剪切模量与密度的比值）服从柯西分布,反演目标似然函数服从高斯分布,并采用平滑初始模型约束提高反演稳定性．模型和实际资料处理表明,该反演方法能够稳定合理的直接从叠前地震资料中获取孔隙流体参数,提供了一种高可靠性的非均匀介质流体描述方法．     

储层弹性与物性参数地震叠前同步反演的确定性优化方法

储层弹性与物性参数可直接应用于储层岩性预测和流体识别,是储层综合评价和油气藏精细描述的基本要素之一.现有的储层弹性与物性参数地震同步反演方法大都基于Gassmann方程,使用地震叠前数据,通过随机优化方法反演储层弹性与物性参数;或基于Wyllie方程,使用地震叠后数据,通过确定性优化方法反演储层弹性与物性参数.本文提出一种基于Gassmann方程、通过确定性优化方法开展储层弹性和物性参数地震叠前反演的方法,该方法利用Gassmann方程建立储层物性参数与叠前地震观测数据之间的联系,在贝叶斯反演框架下以储层弹性与物性参数的联合后验概率为目标函数,通过将目标函数的梯度用泰勒公式展开得到储层弹性与物性参数联合的方程组,其中储层弹性参数对物性参数的梯度用差分形式表示,最后通过共轭梯度算法迭代求解得到储层弹性与物性参数的最优解.理论试算与实际资料反演结果证明了方法的可行性.     

叠前地震描述技术在SLG地区储层预测中的应用

SLG地区天然气资源量丰富,是我国油气增储上产的重要区域,利用叠后地震描述进行储层预测时多解性很强.本文针对SLG地区盒8段储层,充分利用了叠前地震资料信息丰富的特点,以AVO模型正演技术为基础,研究含气砂岩的地球物理响应特征.利用弹性波阻抗反演和叠前同步反演等技术,开展了叠前储层预测和含气性检测,形成了叠前地震描述技术系列.实际钻探结果表明,预测结果的精度较高,表明利用叠前地震描述技术进行SLG地区盒8段储层预测是可行的.     

基于弹性参数加权统计的地震岩相预测方法

岩相信息能够反映储层岩性及流体特征,在地震储层预测中具有重要作用.常规方法主要利用与岩相信息关系密切的弹性参数定性或定量地转化为岩相信息.在实际应用中,弹性参数的获取主要基于叠前地震反演技术.而不同弹性参数的叠前地震反演精度间存在着差异,势必影响岩相的整体预测精度.本文提出对弹性参数进行加权统计来预测岩相.首先,基于贝叶斯理论,引入权重系数来调节弹性参数信息的采用量,构建出最终的目标反演函数;其次,考虑到勘探初期缺少明确的测井岩相信息,提出利用高斯混合分布函数来自动估算岩相先验概率;最后,根据输入弹性参数的取值,计算每类岩相对应的后验概率密度,将目标反演函数取最大后验概率密度时对应的岩相类别作为最终预测的岩相.新方法旨在减少弹性参数精度间的精度差异对岩相预测结果的影响,以期提高地震岩相的预测精度.模型与实际资料测试均表明该方法可行、有效且预测精度较高.     

Cauchy prior distribution-based AVO elastic parameter estimation via weakly nonlinear waveform inversion

Cauchy priori distribution-based Bayesian AVO reflectivity inversion may lead to sparse estimates that are sensitive to large reflectivities. For the inversion, the computation of the covariance matrix and regularized terms requires prior estimation of model parameters, which makes the iterative inversion weakly nonlinear. At the same time, the relations among the model parameters are assumed linear. Furthermore, the reflectivities, the results of the inversion, or the elastic parameters with cumulative error recovered by integrating reflectivities are not well suited for detecting hydrocarbons and fuids. In contrast, in Bayesian linear AVO inversion, the elastic parameters can be directly extracted from prestack seismic data without linear assumptions for the model parameters. Considering the advantages of the abovementioned methods, the Bayesian AVO reflectivity inversion process is modified and Cauchy distribution is explored as a prior probability distribution and the time-variant covariance is also considered. Finally, we propose a new method for the weakly nonlinear AVO waveform inversion. Furthermore, the linear assumptions are abandoned and elastic parameters, such as P-wave velocity, S-wave velocity, and density, can be directly recovered from seismic data especially for interfaces with large reflectivities. Numerical analysis demonstrates that all the elastic parameters can be estimated from prestack seismic data even when the signal-to-noise ratio of the seismic data is low.     

Prestack amplitude versus angle inversion for Young's modulus and Poisson's ratio based on the exact Zoeppritz equations

Elastic parameters such as Young's modulus, Poisson's ratio, and density are very important characteristic parameters that are required to properly characterise shale gas reservoir rock brittleness, evaluate gas characteristics of reservoirs, and directly interpret lithology and oil‐bearing properties. Therefore, it is significant to obtain accurate information of these elastic parameters. Conventionally, they are indirectly calculated by the rock physics method or estimated by approximate formula inversion. The cumulative errors caused by the indirect calculation and low calculation accuracy of the approximate Zoeppritz equations make accurate estimation of Young's modulus, Poisson's ratio, and density difficult in the conventional method. In this paper, based on the assumption of isotropy, we perform several substitutions to convert the Zoeppritz equations from the classical form to a new form containing the chosen elastic constants of Young's modulus, Poisson's ratio, and density. The inversion objective function is then constructed by utilising Bayesian theory. Meanwhile, the Cauchy distribution is introduced as a priori information. We then combine the idea of generalised linear inversion with an iterative reweighed least squares algorithm in order to solve the problem. Finally, we obtain the iterative updating formula of the three elastic parameters and achieve the direct inversion of these elastic parameters based on the exact Zoeppritz equations. Both synthetic and field data examples show that the new method is not only able to obtain the two elastic parameters of Young's modulus and Poisson's ratio stably and reasonably from prestack seismic data but also able to provide an accurate estimation of density information, which demonstrates the feasibility and effectiveness of the proposed method. The proposed method offers an efficient seismic method to identify a “sweet spot” within a shale gas reservoir.     

Reservoir parameter inversion based on weighted statistics

Variation of reservoir physical properties can cause changes in its elastic parameters. However, this is not a simple linear relation. Furthermore, the lack of observations, data overlap, noise interference, and idealized models increases the uncertainties of the inversion result. Thus, we propose an inversion method that is different from traditional statistical rock physics modeling. First, we use deterministic and stochastic rock physics models considering the uncertainties of elastic parameters obtained by prestack seismic inversion and introduce weighting coefficients to establish a weighted statistical relation between reservoir and elastic parameters. Second, based on the weighted statistical relation, we use Markov chain Monte Carlo simulations to generate the random joint distribution space of reservoir and elastic parameters that serves as a sample solution space of an objective function. Finally, we propose a fast solution criterion to maximize the posterior probability density and obtain reservoir parameters. The method has high efficiency and application potential.     

Quantitative gas saturation estimation by frequency‐dependent amplitude‐versus‐offset analysis

Seismic amplitudes contain important information that can be related to fluid saturation. The amplitude‐versus‐offset analysis of seismic data based on Gassmann's theory and the approximation of the Zoeppritz equations has played a central role in reservoir characterization. However, this standard technique faces a long‐standing problem: its inability to distinguish between partial gas and “fizz‐water” with little gas saturation. In this paper, we studied seismic dispersion and attenuation in partially saturated poroelastic media by using frequency‐dependent rock physics model, through which the frequency‐dependent amplitude‐versus‐offset response is calculated as a function of porosity and water saturation. We propose a cross‐plotting of two attributes derived from the frequency‐dependent amplitude‐versus‐offset response to differentiate partial gas saturation and “fizz‐water” saturation. One of the attributes is a measure of “low frequency”, or Gassmann, of reflectivity, whereas the other is a measure of the “frequency dependence” of reflectivity. This is in contrast to standard amplitude‐versus‐offset attributes, where there is typically no such separation. A pragmatic frequency‐dependent amplitude‐versus‐offset inversion for rock and fluid properties is also established based on Bayesian theorem. A synthetic study is performed to explore the potential of the method to estimate gas saturation and porosity variations. An advantage of our work is that the method is in principle predictive, opening the way to further testing and calibration with field data. We believe that such work should guide and augment more theoretical studies of frequency‐dependent amplitude‐versus‐offset analysis.     

基于双相介质理论的储层参数反演方法

传统基于单相介质理论的储层参数反演方法将孔隙流体与固体骨架等效为单一固体,弱化了孔隙流体的影响,反演结果精度不高.本文提出根据双相介质理论反演储层参数的方法.首先,在前人研究的基础上,利用岩石物理模型建立弹性参数与孔隙度、饱和度、泥质含量等储层参数间的关系,进而将双相介质反射系数推导为储层参数的函数;其次,根据贝叶斯反演理论,在高斯噪声假设的基础上,采用更加符合实际情况的修正柯西分布函数描述反射系数的稀疏性,推导出储层物性参数目标反演函数;最后,应用差分进化非线性全局寻优算法来求解目标反演函数,使得反演结果与实际资料间误差最小.新方法旨在突出流体对介质反射系数的影响,以期得到较高的储层参数反演精度.模型与实际资料测试均表明该方法可行、有效且反演精度较高.