Facies Modeling Using a Markov Mesh Model Specification

The spatial continuity of facies is one of the key factors controlling flow in reservoir models. Traditional pixel-based methods such as truncated Gaussian random fields and indicator simulation are based on only two-point statistics, which is insufficient to capture complex facies structures. Current methods for multi-point statistics either lack a consistent statistical model specification or are too computer intensive to be applicable. We propose a Markov mesh model based on generalized linear models for geological facies modeling. The approach defines a consistent statistical model that is facilitated by efficient estimation of model parameters and generation of realizations. Our presentation includes a formulation of the general framework, model specifications in two and three dimensions, and details on how the parameters can be estimated from a training image. We illustrate the method using multiple training images, including binary and trinary images and simulations in two and three dimensions. We also do a thorough comparison to the snesim approach. We find that the current model formulation is applicable for multiple training images and compares favorably to the snesim approach in our test examples. The method is highly memory efficient.     

Modeling Conditional Distributions of Facies from Seismic Using Neural Nets

We present a general, flexible, and fast neural network approach to the modeling of a conditional distribution of a discrete random variable, given a continuous or discrete random vector. Although many more applications of the neural net technique could be envisioned, the aim is to apply the developed methodology to the integration of seismic data into reservoir models. Many geostatistical methods for integrating seismic data rely on a screening assumption of further away seismic events by the colocated seismic datum. Such assumption makes the task of modeling cross-covariances and local conditional distributions much easier. In many cases, however, the seismic data exhibit distinct and locally varying spatial patterns of continuity related to geological events such as channels, shale bodies, or fractures. The previous screening assumption prevents recognizing and hence utilizing these patterns of seismic data. In this paper we propose to relate seismic data to facies or petrophysical properties through a colocated window of seismic information instead of the single colocated seismic datum. The variation of seismic data from one window to another is accounted for. Several examples demonstrate that using such a window improves the predictive power of seismic data.     

岩相识别的神经网络计算

模式识别在定量研究岩相模式中是一种有效的方法，神经网络是模式识别的一种新方法，和其它模式识别方法不同之处在于它能模拟人脑并行处理信息的模式和神经系统的可塑性。经传统岩相分析，鄂中拗陷二叠系碳酸盐岩确认为碳酸盐岩台坪相，它包含五个亚相，即局限台洼、台坡Ｂ、台洼、台坡Ａ和台滩相。它们在岩石的颜色、矿物组分、古生物种属、结构等特征上都有不同的差异。应用ＢＰ神经网络，特别是与模糊模式识别的结合，对拗陷区的岩相识别是成功的，令人鼓舞，两种方法各自的正确判对率约为７５%，而综合两种方法的判对结果，则岩相全部判对。     

Application of Bayesian Generative Adversarial Networks to Geological Facies Modeling

Mathematical Geosciences - Geological facies modeling is a key component in exploration and characterization of subsurface reservoirs. While traditional geostatistical approaches are still commonly...     

A Finite-Volume Method with Hexahedral Multiblock Grids for Modeling Flow in Porous Media

This paper presents a finite-volume method for hexahedral multiblock grids to calculate multiphase flow in geologically complex reservoirs. Accommodating complex geologic and geometric features in a reservoir model (e.g., faults) entails non-orthogonal and/or unstructured grids in place of conventional (globally structured) Cartesian grids. To obtain flexibility in gridding as well as efficient flow computation, we use hexahedral multiblock grids. These grids are locally structured, but globally unstructured. One major advantage of these grids over fully unstructured tetrahedral grids is that most numerical methods developed for structured grids can be directly used for dealing with the local problems. We present several challenging examples, generated via a commercially available tool, that demonstrate the capabilities of hexahedral multiblock gridding. Grid quality is discussed in terms of uniformity and orthogonality. The presence of non-orthogonal grid and full permeability tensors requires the use of multi-point discretization methods. A flux-continuous finite-difference (FCFD) scheme, previously developed for stratigraphic hexahedral grid with full-tensor permeability, is employed for numerical flow computation. We extend the FCFD scheme to handle exceptional configurations (i.e. three- or five-cell connections as opposed to the regular four), which result from employing multiblock gridding of certain complex objects. In order to perform flow simulation efficiently, we employ a two-level preconditioner for solving the linear equations that results from the wide stencil of the FCFD scheme. The individual block, composed of cells that form a structured grid, serves as the local level; the higher level operates on the global block configuration (i.e. unstructured component). The implementation uses an efficient data structure where each block is wrapped with a layer of neighboring cells. We also examine splitting techniques [14] for the linear systems associated with the wide stencils of our FCFD operator. We present three numerical examples that demonstrate the method: (1) a pinchout, (2) a faulted reservoir model with internal surfaces and (3) a real reservoir model with multiple faults and internal surfaces.     

变质火山岩、火山碎屑岩的绿片岩相成岩格子和成岩格子的若干特征

变质火山岩、火山碎屑岩的绿片岩相成岩格子可用阳起石—黑云母—方解石—绿泥石—绿帘石—白云母六相三元系和钠长石—阳起石—黑云母—方解石—绿泥石—绿帘石六相三元系成岩格子来表示,石英往往为过剩组分。在只讨论两个强度相同的变量前提下,每个六相三元系的成岩格子都只可能有一对成对的成岩格子,且这对成岩格子的非封闭双变区的分区相同、分区之间的边界斜率相同、相应的单变线的排列顺序也相同,因此,六相三元系的每个成岩格子中的不变点数、单变线数、和双变区数之间的关系可用数学式来表示。     

下寺湾油田长8段储层相控建模研究

运用Petrel储层建模软件,对下寺湾油田长8段砂组进行储层相控建模研究。首先利用序贯指示模拟方法建立能够表征储层较大规模非均质性的沉积微相模型;在沉积微相模型建立之后,采取相控物性参数建模方法,分小层分微相统计各种物性参数分布特征;然后利用序贯高斯模拟方法分别进行模拟,建立了研究区的孔隙度模型、渗透率模型和含油饱和度模型。结果证明按此方法建立的模型效果较好,客观反映了地质实际,为该区下一步滚动勘探开发提供了地质依据。     

Facies Recognition Using Multifractal Hurst Analysis: Applications to Well-Log Data

Well-log (radioactivity, density and resistivity) analysis constitutes a standard approach for inferring lithology from wells. However, due to inherent complexity of the signals (such as highly heterogeneous deep-water sedimentary sequences) lithology recognition is not straightforward. We used a rescaled range analysis, calibrated with cores, to recognize lithological patterns from signal recorded along wireline logs. The detected intervals coincide with zones of visual electro-facies associations proposed by geologist well-log interpreters. In addition, we propose a rescaled range multifractal analysis to identify ranges of well-log signal complexities, which could be related to sedimentary process variations at specific stratigraphic order cycles.     

Modeling Spatial Variability with One and Multidimensional Continuous-Lag Markov Chains

The continuous-lag Markov chain provides a conceptually simple, mathematically compact, and theoretically powerful model of spatial variability for categorical variables. Markov chains have a long-standing record of applicability to one-dimensional (1-D) geologic data, but 2- and 3-D applications are rare. Theoretically, a multidimensional Markov chain may assume that 1-D Markov chains characterize spatial variability in all directions. Given that a 1-D continuous Markov chain can be described concisely by a transition rate matrix, this paper develops 3-D continuous-lag Markov chain models by interpolating transition rate matrices established for three principal directions, say strike, dip, and vertical. The transition rate matrix for each principal direction can be developed directly from data or indirectly by conceptual approaches. Application of Sylvester's theorem facilitates establishment of the transition rate matrix, as well as calculation of transition probabilities. The resulting 3-D continuous-lag Markov chain models then can be applied to geo-statistical estimation and simulation techniques, such as indicator cokriging, disjunctive kriging, sequential indicator simulation, and simulated annealing.     

基于贴体全交错网格的起伏地表正演模拟影响因素

贴体网格有限差分正演模拟算法不仅能够精确模拟任意起伏地形下的波场特征,且计算效率较高,是一种很有应用前景的处理西部复杂地表问题的方法;然而,目前求解波动方程时常用的同位网格和标准交错网格,在处理贴体网格起伏地表正演模拟时存在诸多问题。为此,将全交错网格引入到曲线坐标系下,避免了标准交错网格的插值误差和同位网格中奇偶失联引起的高频振荡现象,提高了模拟精度,减小了算法实现的复杂度。在自由边界条件实施时,采用牵引力镜像法计算速度分量,速度自由边界条件配合紧致交错差分格式更新应力分量,得到了较好的效果。随后,重点研究了贴体全交错网格正演模拟算法的影响因素,考虑了网格正交性、网格间距和网格拼接等的影响,并取得了如下认识：算法对网格的正交性没有过分要求;网格间距的突变会引起虚假反射的产生;不同类型的网格拼接对模拟结果不会造成明显的影响。     

Implicit Tetrahedral and Surface Mesh Generation for 3D Reservoir Structural Modeling

Mathematical Geosciences - This paper presents a method for tetrahedral mesh generation for subsurface reservoir structural modeling based on sequentially cutting an input tetrahedral grid with...     

Continuous Facies Updating Using the Ensemble Kalman Filter and the Level Set Method

We present a methodology based on the ensemble Kalman filter (EnKF) and the level set method for the continuous model updating of geological facies with respect to production data. Geological facies are modeled using an implicit surface representation and conditioned to production data using the ensemble Kalman filter. The methodology is based on Gaussian random fields used to deform the facies boundaries. The Gaussian random fields are used as the model parameter vector to be updated sequentially within the EnKF when new measurements are available. We show the successful application of the methodology to two synthetic reservoir models.     

Thematic Map Analysis Using Multiple Regression

Thematic maps can be analyzed by multiple regression for (1) forward prediction where a younger geological structural map is written as a least-squares function of older maps for information on historical perspectives or (2) by backward prediction where an older map is regressed stepwise on a series of younger ones to aid in prospecting. The technique was evaluated by a series of structure maps on different geological horizons from the U.S. Midcontinent (Kansas) where the forward prediction proved more effective than backward. In forward prediction, the first map entered into a multiple regression is invariably the immediately underlying one as expected. On the other hand, the first map in a backward prediction is not necessarily related to stratigraphy which limits the utility of the technique for prospecting.     

两淮地区奥陶系沉积相及相模式

安徽两淮地区，奥陶系发育良好，以浅水碳酸盐岩为主，根据岩石类型、结构、构造、生物和剖面结构特征，可划分潮坪、局限潮下、浅滩、开阔潮下４个相带及２２个主要碳酸盐微相类型。碳酸盐相模式为均斜缓坡类型。     

马尔柯夫链分析在甘肃礼县地区上石炭统东扎口组沉积相研究中的应用

采用马尔柯夫链分析方法研究了甘肃礼县地区晚石炭世东扎口组的陆架三角洲平原分支流河道微相演化特征。应用马尔柯夫链分析方法得到的结果是,本区石炭统上段砾石质三角洲平原分支流河道的微岩相旋回的向上演化,是重复而迅速的,每次都是由粗到细的正旋回,最后演化为沼泽沉积。