Characteristic interactions and evaluation of the parameters of the transport equation and formation,including porosity,from data of measurements by some nuclear geophysical methods

An important but problematic component of nuclear geophysical technologies is computer inversion of measurement data based on the equation of particle transport. In this paper, we propose an approach and iterative methods for this inversion that are applicable to many problems of evaluation formation characteristics, including elemental composition, from data of corresponding logging methods. This approach is based on defining characteristic elements, interactions, and trajectories and using the superposition principle for transport processes, and linear a priori constraints on unknowns are used. In comparison with the previous publications of the author, this paper deals with a broader type of measurement data, including the reading ratio of detectors and normalized measurements. The iterative methods are specified for problems of determining the porosity and density from data of neutron-neutron and gamma-gamma logs, respectively. For the first of them, the results of numerical experiments are presented.     

Review of Density Interface Inversion Method in Spatial Domain

Inversion of density interfaces using gravity data has traditionally been an important part of gravity research, and plays an increasingly important role in areas such as regional tectonic research and oil and gas exploration.The density interface inversion methods can be divided into the frequency domain and spatial domain methods according to different computing domains. The frequency domain inversion methods have been considered in previous literature. This paper briefly introduced the rationale and the advance of the direct iterative method, the ridge regression method and the regularization method,which are most studied and used among the spatial domain methods. The performance of the three methods showed that the inversion results of the direct iteration method and the ridge regression method are both the smooth shape density interfaces, while the regularization method can estimate the density interfaces of non-smooth morphology, and is convenient to add prior constraint information. The inversion results of density interface are greatly determined by the precision of potential field separation. The prior information should be used as constraints for gravity field separation as far as possible or the layer-by-layer separation technique could be adopted. The density contrast of the density interface also has noticeable impact on the inversion result. It is necessary to make full use of the rock density data to build a three-dimensional density contrast variation model that conforms to the tectonic features to improve the inversion accuracy.In terms of the theory of inversion method, it is also necessary to combine prior constraint information (which can be obtained through drilling and seismic data, etc.) to improve the accuracy of inversion.More importantly, it is necessary to define the corresponding relationship between the inverted density interface and the geological structure interface in order to evaluate the inversion results correctly.Finally, this paper discussed the developing trend and study emphasis for density interface inversion.The inversion methods that are suitable for large regional or global scale need to be studied with the rapid development of gravity observation technology and the diversification of research objectives. With the increasing difficulty of geological target exploration, it is also urgent to study the optimal single-density interface inversion method conforming to the tectonic features and develop the multi-layer density interface inversion method.     

Ensemble-based conditioning of reservoir models to seismic data

While 3D seismic has been the basis for geological model building for a long time, time-lapse seismic has primarily been used in a qualitative manner to assist in monitoring reservoir behavior. With the growing acceptance of assisted history matching methods has come an equally rising interest in incorporating 3D or time-lapse seismic data into the history matching process in a more quantitative manner. The common approach in recent studies has been to invert the seismic data to elastic or to dynamic reservoir properties, typically acoustic impedance or saturation changes. Here we consider the use of both 3D and time-lapse seismic amplitude data based on a forward modeling approach that does not require any inversion in the traditional sense. Advantages of such an approach may be better estimation and treatment of model and measurement errors, the combination of two inversion steps into one by removing the explicit inversion to state space variables, and more consistent dependence on the validity of assumptions underlying the inversion process. In this paper, we introduce this approach with the use of an assisted history matching method in mind. Two ensemble-based methods, the ensemble Kalman filter and the ensemble randomized maximum likelihood method, are used to investigate issues arising from the use of seismic amplitude data, and possible solutions are presented. Experiments with a 3D synthetic reservoir model show that additional information on the distribution of reservoir fluids, and on rock properties such as porosity and permeability, can be extracted from the seismic data. The role for localization and iterative methods are discussed in detail.     

岩石物理建模技术在致密砂岩储层预测中的应用——以鄂尔多斯盆地北部H区块为例

岩石物理建模是叠前反演前重要的基础工作。以致密砂岩储层为目标,剖析了岩石物理建模涉及的主要过程。将测井评价与岩石物理建模视为迭代过程,测井评价提供岩石物理建模的输入数据,岩石物理建模控制测井评价参数的质量。在测井参数具有较高质量的情况下,优选岩石物理建模方法,优化关键参数,较为准确地预测了横波速度等弹性参数,为叠前弹性参数反演提供了可靠的基础数据。利用岩石物理解释模板对叠前反演纵横波速度体进行了解释,提高了致密砂岩气层的识别精度,在鄂尔多斯盆地取得了较好的应用效果。     

重力异常AlexNet深度神经网络反演

针对传统反演方法存在的初始模型依赖、计算时间较长等问题,提出了一种新的基于AlexNet深度神经网络的重力异常反演方法。该方法首先借鉴经典的深度神经网络AlexNet设计了一种用于重力异常反演的Alex反演网络(AlexInvNet),接着设计大量密度异常体模型并通过正演计算得到带标签的数据集,然后用该数据集训练AlexInvNet网络,最后将重力异常数据输入训练好的AlexInvNet网络直接得到反演结果。理论模型反演结果表明,该方法相较于全连接网络深度学习反演方法,能够更好地反演出异常体的位置和密度,具有较好的泛化能力和抗噪声能力。实测数据反演结果表明,该方法能有效解决重力异常反演问题。     

砂土密实度的成因分析及其评价方法的探讨

砂土的密实程度是影响其工程性质的重要因素,评价砂土密实度的方法很多,但所得结果可能有差异．通常认为这是试验方法不同引起的试验误差。实际上砂土的成因及埋藏条件、地下水也是影响砂土密实度的重要因素。承压水的承压力会改变土中有效自重应力的分布,致使砂土密实度出现反常现象。工程中应注重砂土密实度的成因分析,运用理论知识．分辨各种评价方法的适用条件及其优缺点。     

The Rapid Inversion of 3-D Potential Field and Program Design

The application of three-dimensional inversion of gravity and magnetic fields is very important not only in geophysical researches, but also in the study of geological structures. A formula of potential field in frequency-domain, developed by Parker in 1973, can be used as a rapid and effective algorithm in gravity and magnetic inversion. The technique has been improved then by Oldenburg, Sprenke, Feng and others.In addition to a brief introduction of Parker's algorithm and its applications, this paper includes the following five parts: basic computational techniques, inversion of single layer, convergence and constraints, simultaneous inversion for density and topography as well as inversion of multilayers. The authors present relevant practical iterative formulas and its varieties when density distribution varies with depth in linear or exponential relation. In order to maintain computation stability and speed up iteration convergence, some approaches are taken in the program design, for instance shifting lower interface of the studied layer, inverting corrections of topography, reducing grid boundary effects and utilizing low-pass filter. With the consideration of the nonuniqueness of the inversion, a method of using seismic data to constrain the range ofpossible models is discussed. It is pointed out that the density variation generates less effects than those of topography on the spectrum of gravity anomaly in second order. Therefore density contrast and topography can be inverted simultaneously by an alternative weighting iteration. By analogy, the inversion of multilayer model can be done in the above procedure. An approach of model decomposition is useful in the computation of multilayer model. The techniques discussed in the present paper for gravitational field are also valid for magnetic field.     

磁异常和梯度的频率域三维成像方法

三维反演在磁数据定量解释中具有重要作用。常用的空间域三维反演方法通常需要大量的正演和反演计算,因此对大规模数据的反演效率较低。三维成像是另一种定性和定量解释磁数据的重要方法。文中给出了一种磁异常与梯度三维成像的频率域迭代方法,该方法可以提高成像效率,适用于大规模数据的快速成像。笔者推导了磁总场异常和异常梯度频率域正演公式和成像公式,并将一种深度尺度因子引入成像公式中,提高了深度精度;笔者采用了迭代优化算法,减小了拟合误差,进一步提高了成像精度。通过理论模型数据试验和中国新疆某金属矿床实测数据,验证了本文方法的有效性、可行性。     

Refinement Indicators for Optimal Selection of Geostatistical Realizations Using the Gradual Deformation Method

In the analysis of petroleum reservoirs, one of the most challenging problems is to use inverse theory in the search for an optimal parameterization of the reservoir. Generally, scientists approach this problem by computing a sensitivity matrix and then perform a singular value decomposition in order to determine the number of degrees of freedom i.e. the number of independent parameters necessary to specify the configuration of the system. Here we propose a complementary approach: it uses the concept of refinement indicators to select those degrees which have the greatest sensitivity to an objective function quantifying the mismatch between measured and simulated data. We apply this approach to the problem of data integration for petrophysical reservoir charaterization where geoscientists are currently working with multimillion cell geological models. Data integration may be performed by gradually deforming (by a linear combination) a set of these multimillion grid geostatistical realizations during the optimization process. The inversion parameters are then reduced to the number of coefficients of this linear combination. However, there is an infinity of geostatistical realizations to choose from which may not be efficient regarding operational constraints. Following our new approach, we are able through a single objective function evaluation to compute refinement indicators that indicate which realizations might improve the iterative geological model in a significant way. This computation is extremely fast as it implies a single gradient computation through the adjoint state approach and dot products. Using only the most sensitive realizations from a given set, we are able to resolve quicker the optimization problem case. We applied this methodology to the integration of interference test data into 3D geostatistical models.     

大地电磁测深不同反演方法的应用效果对比--以安徽皖江地区页岩气调查为例

在安徽皖江地区页岩气地质调查中,开展了大地电磁测深(magnetotelluric sounding, MT)剖面研究,通过对比4种不同反演方法和不同极化模式的反演结果,分析各方法的优缺点。4种反演方法各有特点,不同极化模式也具有不同的反演效果。地质与钻孔资料表明,二维带地形共轭梯度反演TM极化模式的电性特征清晰,迭代收敛效果最佳,与地质资料吻合较好,可成功识别二叠纪泥页岩低阻异常。初步推断了皖江地区断裂空间展布特征及页岩气目标层分布,可为其他类似地区大地电磁测深勘探反演方法的选取提供参考。     

评地球物理反演的发展趋向

自 2 0世纪 70年代以来 ,地球物理反演方法已走向成熟 ,这些方法包括地震走时反演与波场反演、层析成像反演、线性化迭代反演、仿真淬火法反演、遗传算法及联合反演方法等。地震反演的目标不仅仅是波速模型 ,而且是地球内部的精细组构和动力学过程 ,并向密度、各向异性及粘度等更多参数成像发展。波动方程线性化迭代反演基于开放物理系统状态发生相变的原理 ,要进一步改善模型参数化的技术和迭代过程的自组织 ;仿真淬火法与遗传算法基于自然过程的指数率或生物演化的优生率 ,可以相互结合以提高解估计的分辨率与置信度 ;联合反演要结合岩石物理性质的统计规律 ,才能取得兼容地质与综合方法的应用效果。地球动力学中的反问题不仅涉及偏微分方程系数项的求解 ,而且涉及初始条件或初始边界的求解 ,对地球动力学作用过程研究特别重要。     

波阻抗反演技术在煤田地震岩性勘探中的应用

在煤田地震勘探中,岩性勘探已成为人们研究的一个热门课题。与其他地震反演技术相比,波阻抗反演技术不仅可提高原始地震资料的垂向分辨率,而且可以将地震波转换为地层信息。介绍了波阻抗反演技术的原理及实现方法,并以平顶山某采区岩性勘探为例,说明波阻抗地震反演方法可以进行岩性勘探,并可用来预测煤层厚度,同时还可以识别煤层中的夹矸。     

频率域位场快速正则化反演界面和物性分布

从理论与模型算例两方面对一种以Ｐａｒｋｅｒ公式为基础的频率域位场反演方法做了进一步深入研究。表明它是一种能够更有效地引入低通滤波因子的迭代方法。与改进的正则化稳定因子相结合，提出新的快速正则化反演方法。除了将其用于反演求解均质界面以外，它也被推广至变物性的界面反演以及物性反演     

Inversion of magnetic anomalies due to isolated thin dike-like sources using artificial neural networks

A new approach is proposed to interpret magnetic anomalies caused by isolated thin dike-like causative targets. The approach is essentially based on utilizing artificial neural network (ANN) inversion for estimating the problem parameters. Particularly, the modular neural network (MNN) is used for the inversion process in order to quantitatively interpret the magnetic anomalies. The MNN inversion has been first tested on a synthetic data with and without random white Gaussian noise. The effect of random noise has been clearly investigated where it showed that the approach provided satisfactory results. Furthermore, three field examples have been inverted in order to investigate the applicability of the proposed approach. The results showed good agreement with the techniques that have been stated in the literatures.     

Gravity anomaly interpretation of 2D fault morphologies by means of nonplanar fault planes and exponential density contrast model: a space domain technique

Boundary faults associated with thick sedimentary basins are more often curved in cross section rather than planar. We develop a space domain-based automatic gravity inversion technique to quantify such listric fault sources from a set of observed gravity anomalies. The density contrast within the hanging wall of fault morphology is presumed to be known according to a prescribed exponential law. Furthermore, the fault plane is described by a polynomial function of arbitrary but specific degree, whose coefficients become the unknown parameters to be estimated from a set of observed gravity anomalies in addition to the thickness of the fault structure. Using a set of characteristic anomalies, the present inversion identifies approximate parameters pertaining to the origin of fault plane and depth to decollement horizon. Based on the errors between the observed and model gravity anomalies of the structure, the algorithm constructs and solves a system of normal equations to estimate the improvements in depth and coefficients of the polynomial in an iterative approach until one of the specified convergence criteria is fulfilled. The efficacy of the algorithm is shown with the analysis of gravity anomalies attributable to a synthetic model of a listric fault source in the presence of pseudorandom noise. Application of the proposed inversion technique on the observed gravity anomalies of the Ahri-Cherla master fault of the Godavari subbasin in India using the derived exponential density contrast model has yielded an interpretation that is consistent with the available/reported information.     

拟神经网络反演在煤田中应用

Parker快速富氏变换反演单一密度界面存在两方面问题：一是求解目标界面重力异常难度较大;二是受正演速度及反演参量维数的限制,不能对界面进行精细划分.拟神经网络BP算法的引入,首先解决了快速三维正演问题,又突破了反演参量维数的限制,实现快速收敛,有效解决两个或多个密度界面的反演问题.在实际应用中,先用密度“补偿法”正演求取剩余生力异常,然后利用拟神经网络BP算法同时反演两个二维密度界面,拟合求得两个界面的深度异常,在此基础上预测煤田.     

Inverse problem theory to chemo-poroelastic parameters estimation: an analytical/experimental investigation

Shale formation swelling is one of the main factors affecting wellbore instability and associated problems in drilling operation. In order to eliminate these problems, it is important to investigate formation characteristics and understand mechanisms of rock-fluid interaction, from chemical/mechanical point of view. Shale membrane efficiency is known as an important parameter affecting wellbore instability. In order to measure this parameter, many mathematical models and experimental efforts have been carried out which consider mechanical-chemical processes for rock-fluid interactions. In this study, the field equations governing the problem have been derived based on the linear chemo-poroelastic theory and solved using analytical/numerical methods. Afterward, a comprehensive workflow to characterize the chemo-poroelastic parameters of illite-rich shale is conducted in the laboratory. In fact, mineralogical and apparent properties of shale sample have been described and some setups were performed such as triaxial test and membrane efficiency. Then genetic algorithm has been applied to solve an inverse problem and get a match between experimental data and modeling results. Ultimately, the three important properties in shale-fluid interactions, i.e., shale membrane efficiency, hydraulic, and chemical diffusivity coefficient have been estimated. Comparing the simulation results with the experimental data indicates that the simulation model can appropriately simulate the pore pressure transmission test. With this approach, the required parameters can be estimated with good accuracy without using time-consuming and costly tests.     

Joint hydrogeophysical inversion: state estimation for seawater intrusion models in 3D

Seawater intrusion (SWI) is a complex process, where 3D modeling is often necessary in order to monitor and manage the affected aquifers. Here, we present a synthetic study to test a joint hydrogeophysical inversion approach aimed at solving the inverse problem of estimating initial and current saltwater distribution. First, we use a 3D groundwater model for variable density flow based on discretized flow and solute mass balance equations. In addition to the groundwater model, a 3D geophysical model was developed for direct current resistivity imaging and inversion. The objective function of the coupled problem consists of data misfit and regularization terms as well as a coupling term that relates groundwater and geophysical states. We present a novel approach to solve the inverse problem using an alternating direction method of multipliers (ADMM) to minimize this coupled objective function. ADMM enables to treat the groundwater and geophysical part separately and thus use the existing software with minor changes. To further reduce the computational cost, the sensitivities are derived analytically for the discretized system of equations, which allows us to efficiently compute the gradients in the minimization procedure. The method was tested on different synthetic scenarios with groundwater and geophysical data represented by solute mass fraction data and direct current resistivity data. With the ADMM approach, we were able to obtain better estimates for the solute distribution compared to just considering each data separately, solving the problem with a simple coupled approach or by a direct substitution of the coupling constraint.     

混沌控制反演系统构造及算法逻辑设计

给出了适用于非线性反演的混沌控制反演系统构造方法及求解控制矩阵的算法逻辑设计。该方法在迭代反演控制参数和迭代反演输出结果之间建立耦合关系，通过时时修改控制参数保证迭代稳定收敛到预期的解空间。在求解过程中，应用数据结构方法分析了混沌控制理论中计算控制矩阵的数据结构，采用树形结构表述出控制矩阵计算过程中下标的取值逻辑，利用可以复读栈中元素的中序遍历来遍历每一棵树，寻找各元素的组合序列，给出的数值算例说明了混沌控制反演方法及其算法的有效性。     

A genetic meta-algorithm-assisted inversion approach: hydrogeological study for the determination of volumetric rock properties and matrix and fluid parameters in unsaturated formations

An evolutionary inversion approach is suggested for the interpretation of nuclear and resistivity logs measured by direct-push tools in shallow unsaturated sediments. The efficiency of formation evaluation is improved by estimating simultaneously (1) the petrophysical properties that vary rapidly along a drill hole with depth and (2) the zone parameters that can be treated as constant, in one inversion procedure. In the workflow, the fractional volumes of water, air, matrix and clay are estimated in adjacent depths by linearized inversion, whereas the clay and matrix properties are updated using a float-encoded genetic meta-algorithm. The proposed inversion method provides an objective estimate of the zone parameters that appear in the tool response equations applied to solve the forward problem, which can significantly increase the reliability of the petrophysical model as opposed to setting these parameters arbitrarily. The global optimization meta-algorithm not only assures the best fit between the measured and calculated data but also gives a reliable solution, practically independent of the initial model, as laboratory data are unnecessary in the inversion procedure. The feasibility test uses engineering geophysical sounding logs observed in an unsaturated loessy-sandy formation in Hungary. The multi-borehole extension of the inversion technique is developed to determine the petrophysical properties and their estimation errors along a profile of drill holes. The genetic meta-algorithmic inversion method is recommended for hydrogeophysical logging applications of various kinds to automatically extract the volumetric ratios of rock and fluid constituents as well as the most important zone parameters in a reliable inversion procedure.