Geostatistical seismic inversion and 3D modelling of metric flow units,porosity and permeability in Brazilian presalt reservoir

Flow units(FU)rock typing is a common technique for characterizing reservoir flow behavior,producing reliable porosity and permeability estimation even in complex geological settings.However,the lateral extrapolation of FU away from the well into the whole reservoir grid is commonly a difficult task and using the seismic data as constraints is rarely a subject of study.This paper proposes a workflow to generate numerous possible 3D volumes of flow units,porosity and permeability below the seismic resolution limit,respecting the available seismic data at larger scales.The methodology is used in the Mero Field,a Brazilian presalt carbonate reservoir located in the Santos Basin,who presents a complex and heterogenic geological setting with different sedimentological processes and diagenetic history.We generated metric flow units using the conventional core analysis and transposed to the well log data.Then,given a Markov chain Monte Carlo algorithm,the seismic data and the well log statistics,we simulated acoustic impedance,decametric flow units(DFU),metric flow units(MFU),porosity and permeability volumes in the metric scale.The aim is to estimate a minimum amount of MFU able to calculate realistic scenarios porosity and permeability scenarios,without losing the seismic lateral control.In other words,every porosity and permeability volume simulated produces a synthetic seismic that match the real seismic of the area,even in the metric scale.The achieved 3D results represent a high-resolution fluid flow reservoir modelling considering the lateral control of the seismic during the process and can be directly incorporated in the dynamic characterization workflow.

Simultaneous inversion of petrophysical parameters based on geostatistical a priori information

The high-resolution nonlinear simultaneous inversion of petrophysical parameters is based on Bayesian statistics and combines petrophysics with geostatistical a priori information. We used the fast Fourier transform–moving average（FFT–MA） and gradual deformation method（GDM） to obtain a reasonable variogram by using structural analysis and geostatistical a priori information of petrophysical parameters. Subsequently, we constructed the likelihood function according to the statistical petrophysical model. Finally, we used the Metropolis algorithm to sample the posteriori probability density and complete the inversion of the petrophysical parameters. We used the proposed method to process data from an oil fi eld in China and found good match between inversion and real data with high-resolution. In addition, the direct inversion of petrophysical parameters avoids the error accumulation and decreases the uncertainty, and increases the computational effi ciency.

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.

Integration of Tracer Test Data to Refine Geostatistical Hydraulic Conductivity Fields Using Sequential Self-Calibration Method

On the basis of local measurements of hydraulic conductivity, geostatistical methods have been found to be useful in heterogeneity characterization of a hydraulic conductivity field on a regional scale. However, the methods are not suited to directly integrate dynamic production data, such as, hydraulic head and solute concentration, into the study of conductivity distribution. These data, which record the flow and transport processes in the medium, are closely related to the spatial distribution of hydraulic conductivity. In this study, a three-dimensional gradient-based inverse method--the sequential self-calibration （SSC） method--is developed to calibrate a hydraulic conductivity field, initially generated by a geostatistical simulation method, conditioned on tracer test results. The SSC method can honor both local hydraulic conductivity measurements and tracer test data. The mismatch between the simulated hydraulic conductivity field and the reference true one, measured by its mean square error （MSE）, is reduced through the SSC conditional study. In comparison with the unconditional results, the SSC conditional study creates the mean breakthrough curve much closer to the reference true curve, and significantly reduces the prediction uncertainty of the solute transport in the observed locations. Further, the reduction of uncertainty is spatially dependent, which indicates that good locations, geological structure, and boundary conditions will affect the efficiency of the SSC study 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.

弱透水层瞬态水力参数的地质统计反演识别研究

弱透水层释水变形伴随着水力参数(渗透系数K和贮水率Ss)的瞬态变化,传统的“移动窗口”式反演方法假定每个反演窗口的初始状态是静态的,这与弱透水层释水变形存在明显滞后效应的实际情况不符。本文提出了在高维参数反演优化情境下,时间域上模型参数的动态变化可与空间域上模型参数的一维非均质性等价,因而可用地质统计反演方法可用于识别弱透水层瞬态K和Ss的新思路,实现了该方法在水文地质领域的创新性应用。以上海越流含水层系统为例,运用似线性地质统计反演算法,高精度地拟合了F16分层标处的长观变形数据,获取了原位透镜体状弱透水层K和Ss的瞬态特征。反演结果显示,观测时段内K的变幅为1.02×10^(-5)~5.89×10^(-4)m/a,平均值为1.38×10^(-4)m/a,Ss的变幅为4.34×10^(-4)~6.02×10^(-3)m^(-1),平均值为2.65×10^(-3)m^(-1)。基于反演所得参数瞬态特征,分析原位弱透水层在1994年前后分别以弹性和塑性变形为主,弱透水层K呈现与含水层水位相反的季节性变化特征,该现象可能与渗流力作用下细粒物质在含水层与弱透水层透镜体交界面附近的对孔隙的阻塞和疏通作用有关。该方法可获取完整观测时段内水文地质参数的动态变化轨迹,在计算评价地表水-地下水交互领域的河床渗透性、原位修复领域的渗透反应墙渗透性等的动态演化特征方面具有潜在的应用价值,并可作为构建水文地质领域、岩土工程等领域有关本构模型的有效辅助手段。

相控地质统计学去硅质反演方法在四川盆地高石梯-磨溪区块灯四段的应用

四川盆地高石梯-磨溪区块震旦系灯影组灯四段因储层埋藏深、厚度薄及硅质层的发育,导致常规反演方法精度低,多解性强。因此提出了一种基于相控地质统计学的去硅质的反演方法:首先结合测井曲线及岩石物理分析来明确各岩性段波阻抗特征;其次将储层波阻抗替换为硅质+基质波阻抗来重构新的波阻抗趋势(Pimp_Trend),并通过统计分析明确Pimp_Trend与样本井硅质含量曲线的共性结构,构建硅质波阻抗初始模型;最后将此模型作为约束条件参与地质统计学反演,求出与反演背景波阻抗相耦合的储层波阻抗,达到“去硅质”储层预测的目的。结果表明:相控地质统计学反演方法成功剔除了硅质层对于储层预测的干扰,凸显出储层波阻抗特征,即通过低波阻抗表征储层;与常规反演相比,相控地质统计学反演方法降低了反演结果的多解性,提高了储层识别精度。研究成果为研究区油气资源的利用与开发提供有力的技术支撑。

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.

基于集合平滑数据同化与直接采样法融合水文地球物理数据刻画裂隙网络分布

刻画裂隙含水层在地下水污染、地热、油气资源开采等研究中起关键作用。由于裂隙介质的强非均质性,其渗透率场一般呈现出显著的非高斯特性,该特性给水文地质参数的推估带来了极大的困难与挑战。为解决裂隙介质参数推估难的问题,本研究利用集合平滑数据同化与直接采样法融合水文地球物理数据推估裂隙介质参数场,设计多个数值算例,探究该数据同化框架刻画裂隙介质参数场的有效性,分析同化3种不同类型的观测数据对参数推估结果的影响,并探讨裂隙密度以及观测井的数量对参数推估效果的影响。研究结果表明:(1)基于集合平滑数据同化与直接采样法融合水文地球物理数据的方法,可有效地推估裂隙介质水文地质参数空间分布;(2)对比3种类型的观测数据推估结果,可知同时融合水头和自然电位观测数据(水文地球物理数据)的参数推估效果最佳;(3)研究区的裂隙密度以及观测井的数量同样对数据同化结果产生影响,因此建议在实际应用中应选择合理的观测井数量从而获得最优的参数推估方案。该研究可为裂隙介质参数场的刻画提供一种有效的方法,进一步为裂隙水资源的开发和管理提供可靠的理论依据。

基于空间协模拟的叠前地震随机反演方法

无论是迭代类随机反演还是线性贝叶斯随机反演,一般采用序贯类随机模拟表征油藏的非均质性。序贯类方法大多依赖变差函数或训练图像描述模型参数的空间相关性,需要逐点计算模拟结果,因此并行实现困难、计算效率低。为此,将一种条件化快速傅里叶变换滑动平均(FFT⁃MA)模拟引入线性反演框架,提出基于空间协模拟的叠前地震随机反演方法。首先,在贝叶斯框架下整合地震数据和测井低频信息,获得弹性参数的后验概率分布。然后,根据FFT⁃MA算法生成概率场,以测井数据为条件数据对贝叶斯后验应用概率场协同模拟,从而获得井震数据约束的叠前弹性参数高分辨率随机反演结果。该方法无需迭代更新模型参数,能极大地提高随机反演的计算效率。最后,由模型试算和实际资料应用测试方法的效果。模型试算表明,所提方法在高分辨率储层预测及计算效率方面均优于常规方法,可稳定、准确地描述小尺度储层特征。实际资料应用表明,所提方法得到的高分辨反演结果与测井数据契合良好,提高了随机反演在薄储层定量表征方面的实用性。

相控叠前地质统计学反演在储层预测中的应用——以四川盆地川西坳陷须家河组二段致密砂岩储层为例

四川盆地川西坳陷新场构造带高庙子气田须家河组二段致密砂岩气藏多套砂体叠置,相变明显,表现为“整体富砂、局部含气”的特征,但有效储层发育段与泥岩的阻抗相当,常规叠后反演方法难以准确预测砂体边界及优质储层分布。在须二段地质特征研究基础上,首先开展有利相带边界识别及预测研究,并结合岩石物理敏感参数分析,开展相控约束下叠前地质统计学反演研究,实现对有效储层与泥岩层劈分,进而完成了相控有效储层预测。预测结果不仅提高了砂体识别精度,同时也提高了有效储层预测的可靠性,预测结果与实际钻井吻合度较高。该预测技术有效支撑了合兴场气田储量提交和探井井位部署,已产生了一定的油气效益。

薄储层综合预测技术在新疆塔里木盆地WS凸起的应用

塔里木盆地WS地区新近系储层单层厚度小,横向变化大,单砂体厚度在2~10 m,储层岩性复杂,厚度变化快,传统地震预测技术维度和方法单一,预测精度低。为落实WS地区吉迪克组储层分布及内部油组展布,根据储层的测井敏感参数结合研究区内井位分布,优选在稀疏脉冲反演控制本区吉迪克组一、二、三段砂层组横向全貌的基础上,在研究区西南部——赛克地区针对吉迪克组三段纵向较薄的单个砂组或单砂体,进一步应用相控地质统计学反演和自然伽马协模拟反演。在多资料、多反演方法结合下,准确分辨出吉迪克组Ⅲ油组最薄砂体厚度为2 m的砂体储层分布范围,并进行了油气检测。储层预测技术的综合应用对塔里木盆地WS地区薄储层的精细刻画及岩性圈闭的圈定奠定了坚实基础,该结果有效支撑了井位优选,实际钻井的油气显示证实了该技术的合理性。

南堡凹陷火山岩喷发模式及火山碎屑岩分布

渤海湾盆地南堡凹陷中深层火山岩纵向多期次发育,厚度大,分布广泛,是油气富集有利区带,但火山岩储层薄,横向变化快,地震资料无法直接识别及刻画,影响着有利目标落实。为了有效刻画火山岩优势储层甜点发育区,针对火山碎屑岩有利储层预测问题,开展了火山岩区域分布规律研究、火山喷发模式建立、火山机构精细解剖、正演模型分析、融合属性及地质统计学反演工作。研究结果表明:1)火山喷发具有多期次性,单一期次火山岩喷发形成多个独立火山岩体;2)基性喷发岩之上发育火山碎屑岩,是火山岩岩性组合有利储层发育段;3)火山碎屑岩储层越发育,上覆地层地震波振幅变弱特征越明显;4)火山碎屑岩测井曲线表现为中声波时差和中伽玛特点。以上成果认识,详细描述了不同期次下火山岩顶面构造形态及火山碎屑岩有利储层分布,对南堡凹陷中深层火山岩进一步勘探具有一定指导意义。

基于岩性数据重构的叠前快速反演技术研究及应用

四川盆地中部地区是致密气核心建产区,其中侏罗系沙溪庙组是近几年致密气藏勘探开发的重要层系。由于沙溪庙组河道砂体横向变化快、纵向叠置关系复杂、储层非均质性强,导致叠后波阻抗岩性反演方法的精度低,而叠前岩性反演计算流程繁杂、耗时长,无法满足快速增储上产的需求。为此,提出了基于岩性数据重构的叠前快速反演技术。首先,利用纵、横波阻抗结合地质先验信息,重构岩性阻抗测井曲线,明确岩性识别门槛值,并建立岩性阻抗解析式;其次,开展AVO属性分析,推导出以截距P与梯度G表征的岩性阻抗反射数据表达式,并重构地震响应特征明显的目标岩性阻抗反射数据;最后,利用叠后反演快速获取高精度三维岩相体,作为后续相控叠前地质统计学反演的三维空间约束项。在川中金秋区块1.3×10^(4) km^(2)连片三维的应用表明,该技术在减少耗时的同时有效提升了反演流程的平稳性和可靠性,反演结果具有更高的精度和分辨率,储层刻画与实钻井吻合率达90%以上,探井实施成功率达100%,推动了沙溪庙组致密气藏的高效勘探开发。