公开(公告)号：US07483822B2

公开(公告)日：2009-01-27

申请号：US10893390

申请日：2004-07-19

Applicant: Mickaële Le Ravalec-Dupin ,  Lin-Ying Hu

Inventor： Mickaële Le Ravalec-Dupin ,  Lin-Ying Hu

IPC: G06G7/48 ,  G06F17/10

CPC classification number: G01V99/00 ,  G01V2210/665

Abstract: A method intended for gradual deformation of a Boolean model allowing best simulation of the spatial configuration, in a heterogeneous underground zone, of geologic objects defined by physical quantities. The model is optimized by means of an iterative optimization process from realizations including objects whose number is a random Poisson variable of determined mean, and by minimizing an objective function. In order to impose a continuity in the evolution of the objects in size, number, positions, within the model, a combined realization obtained by combining on the one hand an initial realization comprising a number of objects corresponding to a first mean value and at least another independent realization having another number of objects corresponding to a second mean value is constructed. An application is construction of a Boolean underground reservoir model allowing simulation of the configuration of heterogeneities such as fractures, channels, etc.

Abstract translation: 一种用于布尔模型逐渐变形的方法，允许在异质地下区域中对由物理量定义的地质物体进行空间配置的最佳模拟。 该模型通过来自实现的迭代优化过程进行优化，所述实现包括其数量是确定平均值的随机泊松变量的对象，以及通过最小化目标函数。 为了对模型中的大小，数量，位置的对象的演变施加连续性，通过组合一次包括对应于第一平均值的数量的对象的初始实现和至少 构造具有对应于第二平均值的另一数量对象的另一独立实现。 一个应用是建立一个布尔地下储层模型，允许模拟非均质性的构造，如裂缝，通道等。

公开(公告)号：US07558708B2

公开(公告)日：2009-07-07

申请号：US11114182

申请日：2005-04-26

Applicant: Mickaële Le Ravalec-Dupin ,  Lin-Ying Hu ,  Frédéric Roggero

Inventor： Mickaële Le Ravalec-Dupin ,  Lin-Ying Hu ,  Frédéric Roggero

IPC: G06F17/10

CPC classification number: G01V11/00 ,  G01V2210/665

Abstract: A method of reconstructing a stochastic realization, continuous or discrete, resulting from a random function representing a numerical model, can be representative of a porous heterogeneous medium such as an underground reservoir. It is based on identification, for a given realization, of a random function and of a set of random numbers allowing, from a given geostatistical simulator, to reconstruct the reference realization. The reconstruction techniques proposed are either general or specific to a type of geostatistical simulator. They concern the sphere of optimization, relaxation, filtering and sequential approaches. The reconstruction method allows to estimate a set of random numbers for regenerating the reference realization, this reference realization can then be locally or globally modified, by gradual deformation, so as to better reproduce newly acquired dynamic data (production data for example). The method is applicable notably to oil reservoir development for example.

Abstract translation: 重建由表示数值模型的随机函数产生的连续或离散的随机实现的方法可以代表诸如地下储层的多孔异质介质。 它基于对给定的实现的识别，随机函数和一组随机数的识别，允许从给定的地统计模拟器重建参考实现。 所提出的重建技术对于一种地统计模拟器是一般的或特定的。 它们涉及优化，放松，过滤和顺序方法的领域。 重建方法允许估计用于再生参考实现的一组随机数，然后可以通过逐渐变形来本地或全局地修改该参考实现，以便更好地再现新获取的动态数据（例如生产数据）。 该方法主要适用于油藏开发。

公开(公告)号：US20070055447A1

公开(公告)日：2007-03-08

申请号：US11514925

申请日：2006-09-05

Applicant: Le Ra Mickaele ,  Lin-Ying Hu

Inventor： Le Ra Mickaele ,  Lin-Ying Hu

IPC: G01V5/04

CPC classification number: G01V99/005 ,  G01V2210/66 ,  G01V2210/665

Abstract: A method for updating a geological reservoir model by integration of dynamic data having application, for example, to petroleum reservoir development. An initial map (y) of petrophysical properties is constructed by means of a geostatistical simulator and of static data. Then an initial set of gradual pilot points (PPi) and at least one complementary set of gradual pilot points (PPc) are constructed. A combined set of gradual pilot points (PP(t)) is then constructed by combining these sets of gradual pilot points according to the gradual deformation method wherein at least one deformation parameter is a characteristic parameter of said pilot points (position and/or value). The initial map (y) is then modified, the deformation parameters are modified according to the dynamic data and the procedure is repeated until a stop criterion is reached and the geological reservoir model is updated by associating the map thus optimized with the grid of the model.

Abstract translation: 一种用于通过将例如应用于石油储层开发的动态数据整合来更新地质储层模型的方法。 通过地统计模拟器和静态数据构建岩石物理性质的初始图（y）。 然后，构建一组初始的渐进导频点（PP＆lt; i＆gt;）和至少一个互补的逐渐导频点集合（PP＆lt;＆gt; c＆gt;）。 然后根据逐渐变形方法组合这些渐变导频点集合来构建一组渐进导频点（PP（t）），其中至少一个变形参数是所述导频点的特征参数（位置和/或值 ）。 然后修改初始地图（y），根据动态数据修改变形参数，重复该过程直到达到停止标准，并通过将优化的图与模型的网格相关联来更新地质储层模型 。

公开(公告)号：US07200533B2

公开(公告)日：2007-04-03

申请号：US10695899

申请日：2003-10-30

Applicant: Lin-Ying Hu ,  Mickaële Le Ravalec-Dupin

Inventor： Lin-Ying Hu ,  Mickaële Le Ravalec-Dupin

IPC: G06F17/50 ,  G01V11/00

CPC classification number: G01V1/28 ,  G01V2210/66

Abstract: A method for rapidly forming a stochastic model of Gaussian or related type, representative of a porous heterogeneous medium such as an underground reservoir, constrained by data characteristic of the displacement of fluids. The method comprises construction of a chain of realizations representative of a stochastic model (Y) by gradually combining an initial realization of (Y) and one or more other realization(s) of (Y) referred to as a composite realization, and minimizing an objective function (J) measuring the difference between a set of non-linear data deduced from the combination by means of a simulator simulating the flow in the medium and the data measured in the medium, by adjustment of the coefficients of the combination. The composite realization results from the projection of the direction of descent of the objective function, calculated by the flow simulator for the initial realization, in the vector subspace generated by P realizations of (Y), randomly drawn and independent of one another, and of the initial realization. During optimization, the chain is explored so as to identify a realization that allows minimizing the objective function (J). In order to sufficiently reduce the objective function, sequentially constructed chains are explored by taking as the initial realization the optimum realization determined for the previous chain. The method may be used for development of oil reservoirs.

Abstract translation: 一种用于快速形成高斯或相关类型的随机模型的方法，代表诸如地下储层的多孔异质介质，受到流体位移数据特征的约束。 该方法包括通过逐渐组合（Y）的初始实现和被称为复合实现的（Y）的一个或多个其他实现，并且最小化一个（Y），从而构建代表随机模型（Y）的实现链 目标函数（J）通过调整组合系数，通过模拟介质中的流量的模拟器和在介质中测量的数据来测量从组合推导的一组非线性数据之间的差异。 复合实现是由在（Y）的P实现生成的向量子空间中随机绘制和相互独立的矢量子空间中由目标函数下降的目标函数的下降方向投影出来的，以及 初步实现。 在优化期间，探索链，以便识别允许最小化目标函数（J）的实现。 为了充分减少目标函数，通过以初始实现为先前链确定的最优实现来探索顺序构建的链。 该方法可用于油藏开发。

公开(公告)号：US20060241920A1

公开(公告)日：2006-10-26

申请号：US11114182

申请日：2005-04-26

Applicant: Mickaele Le Ravalec-Dupin ,  Lin-Ying Hu ,  Frederic Roggero

Inventor： Mickaele Le Ravalec-Dupin ,  Lin-Ying Hu ,  Frederic Roggero

IPC: G06F17/10

CPC classification number: G01V11/00 ,  G01V2210/665

Abstract: Method of reconstructing a stochastic realization, continuous or discrete, resulting from a random function representing a numerical model, that can be representative of a porous heterogeneous medium such as an underground reservoir. It is based on identification, for a given realization, of a random function and of a set of random numbers allowing, from a given geostatistical simulator, to reconstruct the reference realization. The reconstruction techniques proposed are either general or specific to a type of geostatistical simulator. They concern the sphere of optimization, relaxation, filtering and sequential approaches. The reconstruction method allows to estimate a set of random numbers for regenerating the reference realization, this reference realization can then be locally or globally modified, by gradual deformation, so as to better reproduce newly acquired dynamic data (production data for example). Application: notably oil reservoir development for example.

Abstract translation: 重建由表示数值模型的随机函数产生的连续或离散的随机实现的方法，其可以代表诸如地下储层的多孔异质介质。 它基于对给定的实现的识别，随机函数和一组随机数的识别，允许从给定的地统计模拟器重建参考实现。 所提出的重建技术对于一种地统计模拟器是一般的或特定的。 它们涉及优化，放松，过滤和顺序方法的领域。 重建方法允许估计用于再生参考实现的一组随机数，然后可以通过逐渐变形来本地或全局地修改该参考实现，以便更好地再现新获取的动态数据（例如生产数据）。 适用范围：特别是油藏开发。

公开(公告)号：US06618695B1

公开(公告)日：2003-09-09

申请号：US09343219

申请日：1999-06-30

Applicant: Lin-Ying Hu ,  André Haas ,  Frédéric Roggero

Inventor： Lin-Ying Hu ,  André Haas ,  Frédéric Roggero

IPC: G06F1710

CPC classification number: G01V11/00 ,  G01V2210/66

Abstract: Method for gradually deforming, totally or locally, a Gaussian or similar type stochastic model of a heterogeneous medium such as an underground zone, constrained by a series of parameters relative to the structure of the medium. The method comprises drawing a number p, at least equal to two, of independent realizations of at least part of the selected medium model from all the possible realizations, and linear combination of these p realizations with p coefficients such that the sum of their squares is equal to 1. This linear combination constitutes a new realization of the stochastic model and it gradually deforms when the p coefficients are gradually modified. More generally, the method can comprise several iterative gradual deformation stages, with combination at each stage of a composite realization obtained at the previous stage with q new independent realizations drawn from all the realizations. The method makes it possible to gradually deform realizations of a model representative of the medium while modifying the statistical parameters relative to the structure of the medium. The method also allows gradual individual deformations of various parts of the model while preserving continuity between these parts. The method can be applied for construction of stochastic reservoir models constrained by non-linear data (data linked with the flow of fluids).

Abstract translation: 一种全面或局部地逐渐变形诸如地下区域的异质介质的高斯或类似类型随机模型的方法，该模型由相对于介质结构的一系列参数约束。 该方法包括从所有可能的实现中绘出所选择的介质模型的至少部分的独立实现的数p，至少等于2，以及这些p个实现与p个系数的线性组合，使得其平方和之和 等于1.该线性组合构成随机模型的新实现，并且当p系数逐渐修改时，其逐渐变形。 更一般地，该方法可以包括几个迭代的逐渐变形阶段，其中在前一阶段获得的复合实现的每个阶段结合，并从所有实现中抽取出新的独立实现。 该方法使得可以在修改相对于介质结构的统计参数的同时逐渐变形代表介质的模型的实现。 该方法还允许模型的各个部分逐渐变形，同时保持这些部件之间的连续性。 该方法可应用于由非线性数据（与流体流动相关的数据）约束的随机储层模型的构建。

公开(公告)号：US20050172699A1

公开(公告)日：2005-08-11

申请号：US10992793

申请日：2004-11-22

Applicant: Lin-Ying Hu ,  Darryl Fenwick

Inventor： Lin-Ying Hu ,  Darryl Fenwick

IPC: E21B41/00 ,  E21B49/00 ,  G01N15/08 ,  G01V1/28 ,  G01V11/00 ,  G06F17/17

CPC classification number: G01V1/282 ,  E21B49/00 ,  G01V2210/665

Abstract: Method for forming an optimum stochastic model representative of the spatial distribution, in a heterogeneous underground zone, of physical quantities such as permeability and porosity, constrained by measured dynamic data, representative of fluid displacements in the medium, using a continuous distribution parametrization technique. The model is calibrated with the dynamic data by means of an iterative process of minimization of an objective function measuring, on each iteration, the difference between the dynamic data measured and dynamic data simulated by means of a flow simulator, obtained from a realization interpolated between a reference realization (initial or obtained at the end of the previous iteration) and another independent realization, by adjustment of a perturbation parameter, the iterative adjustment process being continued until an optimum realization of the stochastic model is obtained. The method applies in particular to Gaussian sequential simulations and, in particular, to Gaussian white noises, from which any type of stochastic models (continuous, facies or object models, etc.) can be constructed. Application: elaboration of an underground reservoir model allowing to simulate the configuration of various heterogeneities: permeability, porosity, fractures, channels, etc.

Abstract translation: 形成代表空间分布的最佳随机模型的方法，在异质地下区域中，通过测量动态数据约束的物理量（如渗透率和孔隙度），代表介质中的流体位移，使用连续分布参数化技术。 该模型利用动态数据进行校准，通过最小化目标函数的迭代过程，在每次迭代中，测量的动态数据和通过流动模拟器模拟的动态数据之间的差异从由 参考实现（初始化或在先前迭代结束时获得）和另一个独立实现，通过调整扰动参数，迭代调整过程继续进行，直到获得随机模型的最佳实现。 该方法特别适用于高斯序列模拟，尤其适用于高斯白噪声，可以构造任何类型的随机模型（连续，相或物体模型等）。 应用：阐述地下储层模型，可以模拟各种异质性的构造：渗透性，孔隙度，裂缝，通道等

公开(公告)号：US20050015226A1

公开(公告)日：2005-01-20

申请号：US10893390

申请日：2004-07-19

Applicant: Mickaele Le Ravalec-Dupin ,  Lin-Ying Hu

Inventor： Mickaele Le Ravalec-Dupin ,  Lin-Ying Hu

IPC: G01V11/00 ,  G06F17/10

CPC classification number: G01V99/00 ,  G01V2210/665

Abstract: Method intended for gradual deformation of a Boolean model allowing to best simulate the spatial configuration, in a heterogeneous underground zone, of geologic objects defined by physical quantities. The model is optimized by means of an iterative optimization process from realizations including each objects whose number is a random Poisson variable of determined mean, and by minimizing an objective function. In order to impose a continuity in the evolution of said objects in size, number, positions, within the model, a combined realization obtained by combining on the one hand an initial realization comprising a certain number of objects corresponding to a first mean value and at least another independent realization having another number of objects corresponding to a second mean value is constructed, this combination being such that the resulting number of objects has a mean value equal to the sum of the first and of the second mean value and that this mean value is also that defined by the model. Furthermore, the size of the objects is associated with the procedure for generating the number of objects so as to make an object appear or disappear progressively. Application: construction of a Boolean underground reservoir model allowing to simulate the configuration of various heterogeneities: fractures, channels, etc.

Abstract translation: 用于布尔模型的逐渐变形的方法，允许最佳地模拟在异质地下区域中由物理量定义的地质物体的空间配置。 该模型通过来自实现的迭代优化过程进行优化，包括每个对象的数量是确定平均值的随机泊松变量，并通过最小化目标函数。 为了对所述对象在模型中的大小，数量，位置的演变施加连续性，通过组合一个包含一定数量的对应于第一平均值的对象的初始实现和 构造具有对应于第二平均值的另一数目的对象的另一独立实现，该组合使得所得到的对象数目具有等于第一和第二平均值之和的平均值，并且该平均值 也是由模型定义的。 此外，对象的大小与用于生成对象数量的过程相关联，以使对象逐渐出现或消失。 应用：建立一个布尔地下储层模型，允许模拟各种异质性的构造：裂缝，通道等

公开(公告)号：US06813565B1

公开(公告)日：2004-11-02

申请号：US09786232

申请日：2001-03-02

Applicant: Lin-Ying Hu ,  Benoît Noetinger

Inventor： Lin-Ying Hu ,  Benoît Noetinger

IPC: G06F1900

CPC classification number: G01V11/00

Abstract: A method of gradual deformation of representations or realizations, generated by sequential simulation, not limited to a Gaussian stochastic model of a physical quantity z in a meshed heterogeneous medium, in order to adjust the model to a set of data relative to the structure or the state of the medium which are collected by previous measurements and observations. The method comprises applying a stochastic model gradual deformation algorithm to a Gaussian vector with N mutually independent variables which is connected to a uniform vector with N mutually independent uniform variables by a Gaussian distribution function so as to define realizations of the uniform vector, and using these realizations to generate representations of the physical quantity z that are adjusted to the data.

Abstract translation: 通过顺序模拟产生的表示或实现的逐渐变形的方法不限于网状非均匀介质中的物理量z的高斯随机模型，以便将模型调整为相对于该结构或 通过以前的测量和观测收集的培养基的状态。 该方法包括对具有N个相互独立变量的高斯向量应用随机模型逐渐变形算法，该变量通过高斯分布函数连接到具有N个相互独立的均匀变量的均匀向量，以便定义均匀向量的实现，并且使用这些变量 用于生成被调整到数据的物理量z的表示的实现。

公开(公告)号：US08422745B2

公开(公告)日：2013-04-16

申请号：US12767852

申请日：2010-04-27

Applicant: Lin-Ying Hu ,  Virginie Patacz

Inventor： Lin-Ying Hu ,  Virginie Patacz

IPC: G06K9/00

CPC classification number: G01V11/00 ,  G01V1/30 ,  G01V2210/665

Abstract: A method of constructing an image representing the distribution of a categorical physical property representative of an underground zone having applications for petroleum reservoir development. A first training image representative of a geometrical structure of the categorical property is constructed. Training images representative of the distributions of several auxiliary properties are then constructed from the first training image. A probability law of the categorical property and a probability law of each auxiliary property are determined, from each training image, for a given pixel according to the values of the neighboring pixels. A probability law of the categorical property is calculated from these laws and from the images representative of the distribution of the auxiliary physical properties in the zone, and for each pixel of the image to be constructed. Finally, the value of the categorical property is determined by carrying out a random selection for the calculated probability law.

Abstract translation: 构建代表具有用于石油储层开发应用的地下区域的分类物理特性的分布的图像的方法。 构建代表分类属性的几何结构的第一训练图像。 然后从第一训练图像构建表示几个辅助属性分布的训练图像。 根据相邻像素的值，从每个训练图像确定给定像素的分类属性的概率定律和每个辅助属性的概率定律。 根据这些定律和表示区域中辅助物理特性分布的图像以及要构建的图像的每个像素计算分类属性的概率定律。 最后，通过对计算出的概率定律进行随机选择来确定分类属性的值。