公开(公告)号：US20130110484A1

公开(公告)日：2013-05-02

申请号：US13551801

申请日：2012-07-18

Applicant: Lin Ying Hu ,  Yongshe Liu

Inventor： Lin Ying Hu ,  Yongshe Liu

IPC: G06G7/48 ,  G06F17/10

CPC classification number: E21B49/00 ,  G01V99/005 ,  G06T17/05

Abstract: A multiple point simulation technique for generating a model realization of a subterranean formation having different facies is described which uses a non-stationary training image which reflects facies spatial trends across the formation. The realization is formed by sequentially populating each cell; a facies pattern of neighboring cells is identified for each cell in the model grid, and then corresponding facies patterns identified in the training image. The probability of a target cell in the model grid having a given facies is calculated based on the proportion of occurrences of the corresponding facies pattern where the central cell has that facies. The contribution of each corresponding facies pattern occurrence in the training image to this proportion or probability is weighted according to the distance between its central cell and the training image cell corresponding in location to the target cell in the model grid.

Abstract translation: 描述了一种用于产生具有不同相的地下地层的模型实现的多点模拟技术，其使用反映整个地层的相空间趋势的非平稳训练图像。 通过依次填充每个单元格来形成实现; 为模型网格中的每个单元识别相邻单元的相图，然后在训练图像中识别相应的相图。 基于具有该相的相应相图的出现比例来计算具有给定相的模型网格中的目标单元的概率。 将训练图像中的每个对应的相图发生在该比例或概率上的贡献根据其在中心单元与在模型网格中的目标单元的位置对应的训练图像单元之间的距离进行加权。

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：US10519766B2

公开(公告)日：2019-12-31

申请号：US13551801

申请日：2012-07-18

Applicant: Lin Ying Hu ,  Yongshe Liu

Inventor： Lin Ying Hu ,  Yongshe Liu

IPC: E21B49/00 ,  G01V99/00 ,  G06T17/05

Abstract: A multiple point simulation technique for generating a model realization of a subterranean formation having different facies is described which uses a non-stationary training image which reflects facies spatial trends across the formation. The realization is formed by sequentially populating each cell; a facies pattern of neighboring cells is identified for each cell in the model grid, and then corresponding facies patterns identified in the training image. The probability of a target cell in the model grid having a given facies is calculated based on the proportion of occurrences of the corresponding facies pattern where the central cell has that facies. The contribution of each corresponding facies pattern occurrence in the training image to this proportion or probability is weighted according to the distance between its central cell and the training image cell corresponding in location to the target cell in the model grid.

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。

公开(公告)号：US07363163B2

公开(公告)日：2008-04-22

申请号：US11514925

申请日：2006-09-05

Applicant: Mickaële Le Ra Valec-Dupin ,  Lin-Ying Hu

Inventor： Mickaële Le Ra Valec-Dupin ,  Lin-Ying Hu

IPC: G01V9/00

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：US07274993B2

公开(公告)日：2007-09-25

申请号：US10992793

申请日：2004-11-22

Applicant: Lin-Ying Hu ,  Darryl Fenwick

Inventor： Lin-Ying Hu ,  Darryl Fenwick

IPC: G01V1/28 ,  G06F19/00

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

Abstract: A computer implemented 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, based upon measured dynamic data, representative of fluid displacements in a medium, using a continuous distribution parameterization technique is disclosed. The method has application for elaboration of an underground reservoir model by simulating the configuration of various heterogeneities: permeability, porosity, fractures, channels, etc.

Abstract translation: 一种计算机实现的方法，用于基于测量的动态数据（代表介质中的流体位移），使用连续分布参数化来形成代表异质地下区域中物理量（例如渗透率和孔隙率）的空间分布的最优随机模型 技术被公开。 该方法通过模拟各种不均匀性的构造，渗透率，孔隙度，裂缝，通道等，对地下储层模型进行了阐述。

公开(公告)号：US07151845B2

公开(公告)日：2006-12-19

申请号：US10091454

申请日：2002-03-07

Applicant: Lin-Ying Hu

Inventor： Lin-Ying Hu

IPC: G06K9/00 ,  G06K9/40 ,  G06K9/38

CPC classification number: G01V11/00

Abstract: A geostatistical method for gradually deforming an initial distribution of objects, of geologic type for example, from measurements or observations, so as to best adapt it to imposed physical constraints of, for example, a hydrodynamic type having applications of geostatistical modelling of heterogeneous reservoirs of various objects: fracture, channels, vesicles, etc., for example. The objects are distributed in a zone of a heterogeneous medium according to a Poisson point process in form of figurative points with a point density λ(x) that varies according to their position (x) in the zone, a realization of a uniform random vector according to which the position of each object is defined while respecting density λ(x) is formed, and the uniform random vector is gradually modified according to a gradual deformation process so as to obtain gradual migration of each object until a final realization best adjusted to parameters relative to the structure of the medium, such as hydrodynamic parameters, is obtained.

Abstract translation: 一种地质统计学方法，用于逐渐变形例如来自测量或观测的地质类型的物体的初始分布，以便最佳地适应其施加的物理约束，例如具有应用了异质储层的地统计建模的流体动力学类型 各种物体：例如骨折，通道，囊泡等。 根据泊松点过程，物体按照泊位点过程的形式分布在异质介质区域中，形象点的点密度λ（x）根据区域的位置（x）而变化，实现均匀的随机向量 根据该方法，在形成密度λ（x）的同时定义每个对象的位置，并且根据逐渐变形过程逐渐修改均匀随机向量，以便获得每个对象的逐渐迁移，直到最终实现最佳地调整为 获得了相对于介质结构的参数，如流体力学参数。

公开(公告)号：US08942966B2

公开(公告)日：2015-01-27

申请号：US13271727

申请日：2011-10-12

Applicant: Lin Ying Hu ,  Yongshe Liu

Inventor： Lin Ying Hu ,  Yongshe Liu

IPC: G01V99/00 ,  G06F17/18 ,  G06F19/00

CPC classification number: G01V99/005 ,  G01V2210/665

Abstract: A method for creating a modified realization of a geostatistical model of a subterranean hydrocarbon reservoir is described, which may be used in a history matching process. The modified realization is based on a current realization which is a function of a first uniform random number field. At least one further uniform random number field Ui is created and a linear combination made of the first uniform random number field and the further uniform random number field or fields Ui, together with combination coefficients ri, to derive a modified non-uniform random number field V. A uniform score transformation procedure is then performed, e.g. using an empirical cumulative distribution function, on the modified non-uniform number field V, to derive a modified uniform random number field Umod. A modified realization of the model can then be derived from the uniform random number field Umod.

Abstract translation: 描述了用于创建地下油气藏的地统计模型的修改实现的方法，其可以用于历史匹配过程。 修改后的实现基于作为第一均匀随机数字段的函数的当前实现。 创建至少一个进一步的均匀随机数字段U i，并且由第一均匀随机数字段和进一步的均匀随机数字段或场Ui以及组合系数ri组合的线性组合，以导出修改的非均匀随机数字段 然后执行统一的分数变换过程，例如 使用经验累积分布函数，对经修改的非均匀数字字段V，导出修正的均匀随机数字段Umod。 然后可以从均匀随机数字段Umod导出修改后的模型实现。

公开(公告)号：US20120265512A1

公开(公告)日：2012-10-18

申请号：US13422070

申请日：2012-03-16

Applicant: Lin Ying Hu ,  Yong Zhao ,  Yongshe Liu

Inventor： Lin Ying Hu ,  Yong Zhao ,  Yongshe Liu

IPC: G06G7/48

CPC classification number: G01V99/005 ,  G01V2210/663 ,  G01V2210/665 ,  G06F17/5009 ,  G06F2217/16

Abstract: The invention relates to a method for history matching a facies geostatistical model using the ensemble Kalman filter (EnKF) technique. The EnKF is not normally appropriate for discontinuous facies models such as multiple point simulation (MPS). In the method of the invention, an ensemble of realizations are generated and then uniform vectors on which those realizations are based are transformed to Gaussian vectors before applying the EnKF to the Gaussian vectors directly. The updated Gaussian vectors are then transformed back to uniform vectors which are used to update the realizations. The uniform vectors may be vectors on which the realizations are based directly; alternatively each realization may be based on a plurality of uniform vectors linearly combined with combination coefficients. In this case each realization is associated with a uniform vector made up from the combination coefficients, and the combination coefficient vector is then transformed to Gaussian and updated using EnKF.

Abstract translation: 本发明涉及一种使用综合卡尔曼滤波（EnKF）技术对相位地统计模型进行历史匹配的方法。 EnKF通常不适用于不连续相模型，如多点模拟（MPS）。 在本发明的方法中，生成实现集合，然后将这些实现所基于的均匀向量在将EnKF直接应用于高斯向量之前被变换为高斯向量。 然后将更新的高斯向量转换回用于更新实现的均匀向量。 均匀向量可以是实现基础的向量直接; 或者每个实现可以基于与组合系数线性组合的多个均匀向量。 在这种情况下，每个实现与由组合系数组成的均匀向量相关联，然后将组合系数向量转换为高斯并使用EnKF更新。

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。