针对油气勘探中普遍使用的脆性因子的缺点，构建了两个新的相对脆性因子（弹性参数脆性因子和矿物脆性因子），以准确预测脆性泥页岩的空间展布。弹性参数脆性因子利用测井、地震得到的弹性参数（弹性模量和泊松比）评价储集层脆性，这些参数能够反映储集层原位物理性质；根据弹性参数脆性因子确定泥页岩中主要矿物的脆性系数，构建与每种矿物脆性系数及体积分数相关的矿物脆性因子。所构建的两个脆性因子有一定的理论优势并能够较合理地对测井、叠前地震资料反演结果进行解释。根据富有机质泥页岩岩石物理模型，建立矿物-弹性参数-脆性因子的岩石物理量版，对测井资料进行分析以得到优质脆性泥页岩的弹性参数特征，并将其应用于解释叠前地震资料反演结果，得到优质含气脆性泥页岩的空间分布范围，所预测的优质含气脆性泥页岩分布与测井资料对应较好。图12表2参18

Aiming at the disadvantages of the brittleness index commonly used in oil/gas exploration, this article proposed two new brittleness indexes (elastic brittleness and mineral brittleness) in order to predict brittle shale distribution accurately: the former index, based on elastic parameters (Young’s modulus and Poisson’s ratio), characterizes the original physical properties of reservoirs, the other takes the volume content of minerals in the shale and brittle factor of each kind of mineral into consideration. The two proposed brittleness indexes have theoretical advantages and can explain the brittleness of reservoir rocks from logging and prestack seismic inversion reasonably. According to the rock physics model of organic-enriched shale, a rock physics template for mineral-elastic parameter-brittle factor was established to find out the elastic parameter features of high quality brittle shale from logging data. The spatial distribution of high-quality gas-bearing brittle shale was predicted utilizing pre-stacked seismic inversion results, and the predicted results match well with the well-logging data.

页岩的脆性指数是页岩气水平井体积压裂设计中应考虑的重要因素之一。为了更全面地表征页岩的可压性，探索适用性更好的页岩脆性指数预测方法，以四川盆地涪陵焦石坝地区奥陶系五峰组—志留系龙马溪组页岩为例，在对当前常用的脆性预测方法进行对比分析的基础上，结合该区页岩地质特点及工程地质力学特征，建立了矿物脆性指数与弹性参数（杨氏模量、泊松比、拉梅系数×密度、剪切模量×密度）之间的多元回归计算模型，形成了基于4个参数计算模型的叠前脆性预测技术。利用叠前弹性参数反演可以完成脆性指数数据体的预测，进而实现页岩层段纵向上优质压裂层与平面上甜点压裂区的综合评价。通过已知井检验，该方法预测的脆性指数与矿物脆性指数相关性好，并与工程压裂时的破裂压力具有良好的一致性，说明该方法具有较高的可信度和现场实用性，具有较高的推广价值。

<p>The brittleness index of shale is an important factor that should be considered seriously when designing volume fracturing scenario of horizontal well.In order to fully characterize the fracability of shale and search for a better method to predict the brittleness index of shale,taking shale of Wufeng Formation of Ordovicain and Longmaxi Formation of Silurian as examples,a multivariate regression model for calculating shale rock brittleness index is proposed in this paper after comparing different methods of depicting rock brittleness.The multivariate model is built up by analyzing the relationship between brittleness index of minerals and rock geomechanical parameters (Young&rsquo;s modulus,Poission's ratio,the product of Lam&eacute;&rsquo;s coefficient and density,the product of shear modulus and density).Combined with pre-stack seismic inversion technique,the brittleness index volume can be got to evaluate shale fracability vertically and horizontally.The predicted brittleness index coincides well with the fracturing pressure during engineering reservoir stimulation,which gives a strong evidence for the validation and application value of the new brittleness index calculation method.</p>

Due to the huge differences between the unconventional shale and conventional sand reservoirs in many aspects such as the types and the characteristics of minerals, matrix pores and fluids, the construction of shale rock physics model is significant for the exploration and development of shale reservoirs. To make a better characterization of shale gas-bearing reservoirs, we first propose a new but more suitable rock physics model to characterize the reservoirs. We then use a well A to demonstrate the feasibility and reliability of the proposed rock physics model of shale gas-bearing reservoirs. Moreover, we propose a new brittleness indicator for the high-porosity and organic-rich shale gas-bearing reservoirs. Based on the parameter analysis using the constructed rock physics model, we finally compare the new brittleness indicator with the commonly used Young's modulus in the content of quartz and organic matter, the matrix porosity, and the types of filled fluids. We also propose a new shale brittleness index by integrating the proposed new brittleness indicator and the Poisson's ratio. Tests on real data sets demonstrate that the new brittleness indicator and index are more sensitive than the commonly used Young's modulus and brittleness index for the high-porosity and high-brittleness shale gas-bearing reservoirs.

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。

Shale brittleness index is a key parameter in the design of shale gas fracturing.Commonly used elastic brittleness prediction methods have poor adaptability in block L of the Southern Sichuan shale gas field owing to regional differences in tectonic setting and sedimentary characteristics.Although both Rickman brittleness index and minimum closure stress coefficient have a certain correlation with mineral brittleness index,their correlation is not sufficient to accurately predict mineral brittleness index; therefore,a new model of multivariate nonlinear regression brittleness index prediction is proposed in this study.The model establishes the relationship between mineral brittleness index,Rickman brittleness index,and minimum closure stress coefficient and then uses 3D seismic data to obtain the required elastic parameters through pre-stack seismic inversion method to realize the longitudinal and lateral quantitative brittleness prediction of the shale interval in the study area.The application in Block L of the Southern Sichuan Shale Gas Field proves that the new prediction method of brittleness index is more applicable under the constraints of the existing mineral brittleness index of drilled well.The brittleness index of the Wufeng Formation-Longmaxi Formation first sub-member is distributed stably in the horizontal direction,and this is in line with geological understanding.In the vertical direction,the shale brittleness index tends to increase gradually from top to bottom,and the vertical stratification is obvious.This study revealed that drilling data and predicted brittleness index have a good correlation with mineral brittleness index,which has application and promotion value.

页岩岩石物理建模旨在建立页岩矿物组分、微观结构、流体填充与岩石弹性参数的关系.对四川盆地龙马溪组页岩进行岩石物理建模研究，针对页岩黏土含量高、层间微裂缝发育等特点，利用Backus平均理论描述页岩黏土矿物弹性参数，利用Chapman理论计算与水平微裂缝有关的VTI各向异性，并利用Bond变换考虑地层倾角的影响.提出以黏土矿物纵、横波速度和孔隙纵横比为拟合参数进行岩石物理反演的方法，并引入贝叶斯框架减小反演的多解性.由已知的黏土矿物纵、横波速度和孔隙纵横比作为先验信息，并以测井纵、横波速度作为约束条件建立反演的目标函数，同时利用粒子群算法进行最优化搜索.计算结果表明，基于先验约束和粒子群算法的反演方法能够较准确地反演黏土矿物的弹性参数、孔隙形态参数以及裂缝密度等参数.计算得到的黏土纵、横波速度较高，并且在一定范围内变化，这可能与龙马溪组页岩的黏土矿物组分中具有较高弹性模量的伊利石含量较高有关，同时也与黏土定向排列等微观物性特征有关.反演得到的裂缝密度与纵波各向异性参数ε呈明显的正相关，而与横波各向异性参数γ相关性较小.另外，页岩各向异性参数与黏土垂向的纵横波速度有较强的相关性.

在各向同性背景地层中发育有垂直裂缝的地层, 其可以表征为具有水平对称轴的横向各向同性介质(HTI介质), 而裂缝弱度参数可用来表征岩石裂缝密度和识别流体。为了提升基于HTI介质裂缝弱度参数反演的稳定性和准确性, 提出了一种稳定、可靠的储层裂缝弱度参数反演方法。该方法以褶积模型和HTI介质反射系数近似公式为基础, 通过不同方位地震数据相减的方式, 求取地震振幅差异, 以减少待反演模型参数的数量, 进一步基于贝叶斯反演理论, 通过线性化反演算法求取裂缝弱度参数的最大后验期望和协方差, 实现裂缝弱度参数反演。合成数据和实际资料的测试结果表明, 裂缝弱度参数反演结果和测井数据具有良好的一致性, 可有效表征储层裂缝发育特征, 该方法在裂缝型储层预测和表征方面具有广泛的应用前景。

Formations with vertical fractures developed in isotropic background formations can be characterized as transversely isotropic media with a horizontal symmetry axis(HTI media).Fracture weaknesses can be effectively used for seismic fracture density characterizations and fluid identifications.To achieve stability and accuracy of fracture weaknesses in HTI media, a reliable reservoir fracture weakness inversion method is proposed herein.This method is based on the convolution model and the HTI media reflection coefficient approximation formula, and it reduces the number of model parameters to be inverted by taking the differences in azimuthal seismic amplitudes.Reliable fracture weakness inversion is then realized by employing the Bayesian theory using the maximum a posteriori estimation and covariance.Finally, test results obtained using synthetic and real data reveal that the inversion results are in good agreement with the logging data and that the inversion results of fracture weakness parameters can characterize the real reservoir fracture development characteristics effectively.These results demonstrate that the method has wide application prospects in the prediction and characterization of fracture reservoirs.

提出了各向异性页岩储层统计岩石物理反演方法.通过统计岩石物理模型建立储层物性参数与弹性参数的定量关系，使用测井数据及井中岩石物理反演结果作为先验信息，将地震阻抗数据定量解释为储层物性参数、各向异性参数的空间分布.反演过程在贝叶斯框架下求得储层参数的后验概率密度函数，并从中得到参数的最优估计值及其不确定性的定量描述.在此过程中综合考虑了岩石物理模型对复杂地下介质的描述偏差和地震数据中噪声对反演不确定性的影响.在求取最大后验概率过程中使用模拟退火优化粒子群算法以提高收敛速度和计算准确性.将统计岩石物理技术应用于龙马溪组页岩气储层，得到储层泥质含量、压实指数、孔隙度、裂缝密度等物性，以及各向异性参数的空间分布及相应的不确定性估计，为页岩气储层的定量描述提供依据.

针对确定性叠前三参数反演存在的精度低、稳定性差、抗噪性差以及过度依赖初始模型的问题,虽然利用随机反演方法实现叠前三参数同步反演有助于解决这些问题,但此类方法反演效率较低。为此,提出了利用自适应粒子群优化马尔科夫链蒙特卡洛(APSO-MCMC)算法以提高叠前三参数反演的计算效率。结合纵波速度、横波速度以及密度的变化统计扰动关系,建立模型扰动的高斯分布,根据三参数扰动先验分布抽样获取初始粒子群。在每一步迭代过程中,利用跃迁矩阵改变粒子的演化,根据粒子之间的距离计算演化因子,判定粒子群的收敛状态。此外,利用精英策略,帮助粒子实现跳出局部极小值的困境。由于传统叠前近似公式在宽角度区域与非近似公式误差较大,故利用Zoeppritz公式来保证叠前三参数反演在各个角度的精度。NS地区二维海洋实际数据应用表明,该方法估算纵波速度、横波速度和密度有效,稳定收敛,计算效率高于传统的随机方法,具有较好的精度和抗噪性。

Deterministic inversion of prestack data has problems concerning inaccuracy,instability,poor noise resistance,and excessive dependence on the initial model.Therefore,a stochastic inversion method was previously proposed to determine the prestack three-parameter simultaneous inversion;however,the efficiency of conventional stochastic inversion is low.In this study,the APSO-MCMC method was developed to improve the computational efficiency of the prestack simultaneous inversion.According to the statistical perturbation relationship of the P-wave velocity,S-wave velocity,and density,the Gaussian distribution of the model perturbation is constructed.Based on the acceptance-rejection method,an initial swarm is generated as an input for the inversion process.During the iteration,a transition matrix is employed to change the evolution of the particles.Additionally,the evolution factor was calculated based on the distance between the particles to determine the convergence state of the particle swarm.In each iteration,an elite learning strategy was employed to determine the jump-out of the local minimum.Because the conventional forward modeling algorithm is not accurate in wide-angle regions,this study employed the Zoeppritz equations to ensure the accuracy of the prestack three-parameter inversion.The field data test of the NS area shows that the method correctly estimates the P-wave velocity,S-wave velocity,and density,and has a stability of convergence,high resistance to noise,and better efficiency than conventional stochastic approaches.