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1. 发明申请

WO2012015516A8 METHODS AND SYSTEMS FOR MACHINE-LEARNING BASED SIMULATION OF FLOW 审中-公开
公开(公告)号：WO2012015516A8
公开(公告)日：2012-02-02
申请号：PCT/US2011/037174
申请日：2011-05-19
申请人： EXXONMOBIL UPSTREAM RESEARCH COMPANY , USADI, Adam , LI, Dachang , PARASHKEVOV, Rossen , TEREKHOV, Sergey, A. , WU, Xiao-hui , YANG, Yahan
发明人： USADI, Adam , LI, Dachang , PARASHKEVOV, Rossen , TEREKHOV, Sergey, A. , WU, Xiao-hui , YANG, Yahan
IPC分类号： G06G7/48
摘要： There is provided a method for modeling a hydrocarbon reservoir that includes generating a reservoir model comprising a plurality of coarse grid cells. The method includes generating a fine grid model corresponding to one of the coarse grid cells and simulating the fine grid model using a training simulation to generate a set of training parameters comprising boundary conditions of the coarse grid cell. A machine learning algorithm may be used to generate, based on the set of training parameters, a coarse scale approximation of a phase permeability of the coarse grid cell. The hydrocarbon reservoir can be simulated using the coarse scale approximation of the effective phase permeability generated for the coarse grid cell. The method also includes generating a data representation of a physical hydrocarbon reservoir in a non- transitory, computer-readable, medium based at least in part on the results of the simulation.

2. 发明申请

WO2012015515A1 METHODS AND SYSTEMS FOR MACHINE-LEARNING BASED SIMULATION OF FLOW 审中-公开
标题翻译：基于机器学习的流程模拟方法与系统
公开(公告)号：WO2012015515A1
公开(公告)日：2012-02-02
申请号：PCT/US2011/037168
申请日：2011-05-19
申请人： EXXONMOBIL UPSTREAM RESEARCH COMPANY , USADI, Adam , LI, Dachang , PARASHKEVOV, Rossen , TEREKHOV, Sergey, A. , WU, Xiao-Hui , YANG, Yahan
发明人： USADI, Adam , LI, Dachang , PARASHKEVOV, Rossen , TEREKHOV, Sergey, A. , WU, Xiao-Hui , YANG, Yahan
IPC分类号： G06G7/48
CPC分类号： E21B43/00 , G01V1/282 , G01V99/005 , G01V2210/66 , G06F17/5018 , G06F2217/16 , G06N3/0427 , G06N99/005
摘要： There is provided a method for modeling a hydrocarbon reservoir that includes generating a reservoir model that has a plurality of sub regions. A solution surrogate is obtained for a sub region by searching a database of existing solution surrogates to obtain an approximate solution surrogate based on a comparison of physical, geometrical, or numerical parameters of the sub region with physical, geometrical, or numerical parameters associated with the existing surrogate solutions in the database. If an approximate solution surrogate does not exist in the database, the sub region is simulated using a training simulation to obtain a set of training parameters comprising state variables and boundary conditions of the sub region. A machine learning algorithm is used to obtain a new solution surrogate based on the set of training parameters. The hydrocarbon reservoir can be simulated using the solution surrogate obtained for the at least one sub region.
摘要翻译：提供了一种用于对烃储层进行建模的方法，其包括产生具有多个子区域的储层模型。通过搜索现有解决方案代理的数据库来获得一个解决方案代用品，以便通过将子区域的物理，几何或数值参数与物理，几何或数值参数与现有的代理解决方案在数据库中。如果数据库中不存在近似的解决方案代用品，则使用训练模拟来模拟子区域，以获得包括状态变量和子区域的边界条件的训练参数的集合。基于训练参数的集合，使用机器学习算法获得新的解决方案代理。可以使用为至少一个子区域获得的溶液替代物来模拟烃储存器。

3. 发明申请

WO2012015518A3 METHODS AND SYSTEMS FOR MACHINE-LEARNING BASED SIMULATION OF FLOW 审中-公开
公开(公告)号：WO2012015518A3
公开(公告)日：2012-02-02
申请号：PCT/US2011/037178
申请日：2011-05-19
申请人： EXXONMOBIL UPSTREAM RESEARCH COMPANY , USADI, Adam , LI, Dachang , PARASHKEVOV, Rossen , TEREKHOV, Sergey, A. , WU, Xiao-hui , YANG, Yahan
发明人： USADI, Adam , LI, Dachang , PARASHKEVOV, Rossen , TEREKHOV, Sergey, A. , WU, Xiao-hui , YANG, Yahan
IPC分类号： G06G7/48
摘要： There is provided a method for modeling a hydrocarbon reservoir that includes generating a reservoir model that has a plurality of coarse grid cells. A plurality of fine grid models is generated, wherein each fine grid model corresponds to one of the plurality of coarse grid cells that surround a flux interface. The method also includes simulating the plurality of fine grid models using a training simulation to obtain a set of training parameters, including a potential at each coarse grid cell surrounding the flux interface and a flux across the flux interface. A machine learning algorithm is used to generate a constitutive relationship that provides a solution to fluid flow through the flux interface. The method also includes simulating the hydrocarbon reservoir using the constitutive relationship and generating a data representation of a physical hydrocarbon reservoir in a non-transitory, computer-readable medium based on the results of the simulation.

4. 发明申请

WO2012015517A1 METHODS AND SYSTEMS FOR MACHINE-LEARNING BASED SIMULATION OF FLOW 审中-公开
标题翻译：基于机器学习的流程模拟方法与系统
公开(公告)号：WO2012015517A1
公开(公告)日：2012-02-02
申请号：PCT/US2011/037177
申请日：2011-05-19
申请人： EXXONMOBIL UPSTREAM RESEARCH COMPANY , USADI, Adam , LI, Dachang , PARASHKEVOV, Rossen , TEREKHOV, Sergey, A. , WU, Xiao-hui , YANG, Yahan
发明人： USADI, Adam , LI, Dachang , PARASHKEVOV, Rossen , TEREKHOV, Sergey, A. , WU, Xiao-hui , YANG, Yahan
IPC分类号： G06G7/48
CPC分类号： G06F17/5009 , G06F17/5018 , G06N3/0427
摘要： There is provided a method for modeling a hydrocarbon reservoir that includes generating a reservoir model comprising a plurality of sub regions. At least one of the sub regions is simulated using a training simulation to obtain a set of training parameters comprising state variables and boundary conditions of the at least one sub region. A machine learning algorithm is used to approximate, based on the set of training parameters, an inverse operator of a matrix equation that provides a solution to fluid flow through a porous media. The hydrocarbon reservoir can be simulated using the inverse operator approximated for the at least one sub region. The method also includes generating a data representation of a physical hydrocarbon reservoir can be generated in a non-transitory, computer-readable, medium based, at least in part, on the results of the simulation.
摘要翻译：提供了一种用于对烃储层进行建模的方法，其包括产生包括多个子区域的储层模型。使用训练模拟来模拟至少一个子区域，以获得包括所述至少一个子区域的状态变量和边界条件的训练参数集合。机器学习算法用于基于训练参数集来近似矩阵方程的逆算子，其提供通过多孔介质的流体流动的解决方案。可以使用对于至少一个子区域近似的逆算子来模拟烃储层。该方法还包括生成物理碳氢化合物储层的数据表示可以至少部分地基于模拟的结果以非暂时的，计算机可读的，基于媒体的方式产生。

5. 发明申请

WO2012015521A1 METHOD AND SYSTEM FOR RESERVOIR MODELING 审中-公开
标题翻译：储层建模方法与系统
公开(公告)号：WO2012015521A1
公开(公告)日：2012-02-02
申请号：PCT/US2011/037594
申请日：2011-05-23
申请人： EXXONMOBIL UPSTREAM RESEARCH COMPANY , USADI, Adam , LI, Dachang , PARASHKEVOV, Rossen , WU, Xiao-hui , YANG, Yahan
发明人： USADI, Adam , LI, Dachang , PARASHKEVOV, Rossen , WU, Xiao-hui , YANG, Yahan
IPC分类号： G06G7/48
CPC分类号： G06F17/5009 , G06F2217/16
摘要： A method is presented for modeling reservoir properties. The method includes constructing a coarse computational mesh for the reservoir. The coarse computational mesh comprises a plurality of cells. The method further includes determining a plurality of flows for each of the plurality of cells based on Dirichlet boundary conditions. Additionally, the method includes determining a solution to a coarse pressure equation for the reservoir based on the plurality of flows.
摘要翻译：提出了一种用于建模储层性质的方法。该方法包括为储层构建粗计算网格。粗计算网格包括多个单元。该方法还包括基于Dirichlet边界条件来确定多个小区中的每一个的多个流。另外，该方法包括基于多个流量确定储层的粗压方程的解。

6. 发明申请

WO2011059537A1 METHOD AND SYSTEM FOR RAPID MODEL EVALUATION USING MULTILEVEL SURROGATES 审中-公开
标题翻译：使用多种语言的快速模型评估的方法和系统
公开(公告)号：WO2011059537A1
公开(公告)日：2011-05-19
申请号：PCT/US2010/043499
申请日：2010-07-28
申请人： EXXONMOBIL UPSTREAM RESEARCH COMPANY , WU, Xiao-hui , LI, Dachang , PARASHKEVOV, Rossen , USADI, Adam, K. , YANG, Yahan
发明人： WU, Xiao-hui , LI, Dachang , PARASHKEVOV, Rossen , USADI, Adam, K. , YANG, Yahan
IPC分类号： G06E1/00
CPC分类号： G06F17/5009 , G06F19/704
摘要： The present techniques disclose methods and systems for rapidly evaluating multiple models using multilevel surrogates (for example, in two or more levels). These surrogates form a hierarchy in which surrogate accuracy increases with its level. At the highest level, the surrogate becomes an accurate model, which may be referred to as a full-physics model (FPM). The higher level surrogates may be used to efficiently train the low level surrogates (more specifically, the lowest level surrogate in most applications), reducing the amount of computing resources used. The low level surrogates are then used to evaluate the entire parameter space for various purposes, such as history matching, evaluating the performance of a hydrocarbon reservoir, and the like.
摘要翻译：本技术公开了使用多级代理（例如，在两个或更多个级别）中快速评估多个模型的方法和系统。这些代理形成了代理精度随着其水平而增加的等级。在最高级别，代理成为一个准确的模型，可以被称为全物理模型（FPM）。可以使用较高级别的代理来有效地训练低级别代理（更具体地说，在大多数应用中是最低级替代），减少了所使用的计算资源的数量。然后，使用低级替代物来评估用于各种目的的整个参数空间，例如历史匹配，评估烃储层的性能等。

7. 发明申请

WO2012071090A1 VARIABLE DISCRETIZATION METHOD FOR FLOW SIMULATION ON COMPLEX GEOLOGICAL MODELS 审中-公开
标题翻译：用于复杂地质模型流变模拟的可变分离方法
公开(公告)号：WO2012071090A1
公开(公告)日：2012-05-31
申请号：PCT/US2011/047612
申请日：2011-08-12
申请人： EXXONMOBIL UPSTREAM RESEARCH COMPANY , YANG, Yahan , BI, Linfeng , GUO, Weidong , PARASHKEVOV, Rossen , WU, Xiao-Hui
发明人： YANG, Yahan , BI, Linfeng , GUO, Weidong , PARASHKEVOV, Rossen , WU, Xiao-Hui
IPC分类号： G06G7/58
CPC分类号： G06F17/5018 , G01V99/005 , G06F2217/16
摘要： A variable discretization method for general multiphase flow simulation in a producing hydrocarbon reservoir. For subsurface regions for which a regular or Voronoi computational mesh is suitable, a finite difference/finite volume method ("FDM") is used to discretize numerical solution of the differential equations governing fluid flow (101). For subsurface regions with more complex geometries, a finite element method ("FEM") is used. The invention combines FDM and FEM in a single computational framework (102). Mathematical coupling at interfaces between different discretization regions is accomplished by decomposing individual phase velocity into an averaged component and a correction term. The averaged velocity component may be determined from pressure and averaged capillary pressure and other properties based on the discretization method employed, while the velocity correction term may be computed using a multipoint flux approximation type method, which may be reduced to two-point flux approximation for simple grid and permeability fields.
摘要翻译：一种用于生产油气藏的一般多相流模拟的可变离散化方法。对于常规或Voronoi计算网格适合的地下区域，使用有限差分/有限体积法（“FDM”）来离散控制流体流动的微分方程（101）的数值解。对于具有更复杂几何的地下区域，使用有限元法（“FEM”）。本发明将FDM和FEM组合在一个单一的计算框架中（102）。通过将各个相速度分解成平均分量和校正项来实现不同离散区域之间的界面处的数学耦合。平均速度分量可以基于所采用的离散化方法从压力和平均毛细管压力和其他性质确定，而速度校正项可以使用多点通量近似方法来计算，该方法可以减少到两点通量近似简单网格和渗透性领域。

8. 发明申请

WO2009120409A1 COMPUTING A CONSISTENT VELOCITY VECTOR FIELD FROM A SET OF FLUXES 审中-公开
标题翻译：从一组通道计算一致速度矢量场
公开(公告)号：WO2009120409A1
公开(公告)日：2009-10-01
申请号：PCT/US2009/033434
申请日：2009-02-06
申请人： EXXONMOBIL UPSTREAM RESEARCH COMPANY , PARASHKEVOV, Rossen
发明人： PARASHKEVOV, Rossen
IPC分类号： G06G7/50
CPC分类号： G06F17/5018 , G06F2217/16
摘要： A method for constructing a velocity vector field from a grid and a set of fluxes for each face of the grid cells. The cells are first subdivided and internal fluxes are calculated for each cell subject to the constraints of the flux for each cell and to achieve the minimum energy state for the each cell. The minimum energy state is computed efficiently using a divergence-free correction method without introducing a pressure variable. Then, the velocity vector field is constructed from the subcell fluxes using mixed finite element interpolation.
摘要翻译：一种用于从网格构建速度矢量场的方法和用于网格单元的每个面的一组通量。先对细胞进行细分，然后根据每个细胞的通量约束计算每个细胞的内部通量，并实现每个细胞的最小能量状态。使用无差分校正方法有效地计算最小能量状态，而不引入压力变量。然后，使用混合有限元插值从子电池通量构建速度矢量场。

9. 发明公开

EP2599031A1 METHODS AND SYSTEMS FOR MACHINE-LEARNING BASED SIMULATION OF FLOW 审中-公开
标题翻译：基于机器学习的流动模拟方法和系统
公开(公告)号：EP2599031A1
公开(公告)日：2013-06-05
申请号：EP11812892.5
申请日：2011-05-19
申请人： ExxonMobil Upstream Research Company , Yang, Yahan
发明人： YANG, Yahan , USADI, Adam , LI, Dachang , PARASHKEVOV, Rossen , TEREKHOV, Sergey, A. , WU, Xiao-hui
IPC分类号： G06G7/48
CPC分类号： G06F17/5009 , G06F17/5018 , G06N3/0427
摘要： There is provided a method for modeling a hydrocarbon reservoir that includes generating a reservoir model comprising a plurality of sub regions. At least one of the sub regions is simulated using a training simulation to obtain a set of training parameters comprising state variables and boundary conditions of the at least one sub region. A machine learning algorithm is used to approximate, based on the set of training parameters, an inverse operator of a matrix equation that provides a solution to fluid flow through a porous media. The hydrocarbon reservoir can be simulated using the inverse operator approximated for the at least one sub region. The method also includes generating a data representation of a physical hydrocarbon reservoir can be generated in a non-transitory, computer-readable, medium based, at least in part, on the results of the simulation.
摘要翻译：提供了一种用于建模碳氢化合物储层的方法，其包括生成包括多个子区域的储层模型。使用训练模拟模拟至少一个子区域以获得包括至少一个子区域的状态变量和边界条件的一组训练参数。机器学习算法用于基于该组训练参数来近似矩阵方程的逆运算符，该矩阵方程为通过多孔介质的流体流提供解决方案。可以使用近似于至少一个子区域的逆算子来模拟碳氢化合物储层。该方法还包括可以至少部分地基于模拟结果在非暂时性计算机可读介质中生成物理碳氢化合物储层的数据表示。

10. 发明公开

EP2599030A1 METHODS AND SYSTEMS FOR MACHINE-LEARNING BASED SIMULATION OF FLOW 审中-公开
标题翻译：基于机器学习的流动模拟方法和系统
公开(公告)号：EP2599030A1
公开(公告)日：2013-06-05
申请号：EP11812891.7
申请日：2011-05-19
申请人： ExxonMobil Upstream Research Company
发明人： USADI, Adam , LI, Dachang , PARASHKEVOV, Rossen , TEREKHOV, Sergey, A. , WU, Xiao-hui , YANG, Yahan
IPC分类号： G06G7/48
CPC分类号： E21B43/00 , G01V99/005 , G06F17/5018 , G06F2217/16 , G06N3/0427 , G06N99/005
摘要： There is provided a method for modeling a hydrocarbon reservoir that includes generating a reservoir model comprising a plurality of coarse grid cells. The method includes generating a fine grid model corresponding to one of the coarse grid cells and simulating the fine grid model using a training simulation to generate a set of training parameters comprising boundary conditions of the coarse grid cell. A machine learning algorithm may be used to generate, based on the set of training parameters, a coarse scale approximation of a phase permeability of the coarse grid cell. The hydrocarbon reservoir can be simulated using the coarse scale approximation of the effective phase permeability generated for the coarse grid cell. The method also includes generating a data representation of a physical hydrocarbon reservoir in a non-transitory, computer-readable, medium based at least in part on the results of the simulation.
摘要翻译：提供了一种用于建模碳氢化合物储层的方法，其包括生成包括多个粗栅格单元的储层模型。该方法包括生成与粗糙网格单元中的一个对应的精细网格模型并且使用训练模拟来模拟精细网格模型以生成包括粗网格单元的边界条件的一组训练参数。机器学习算法可以用于基于该组训练参数生成粗网格单元的相位导磁率的粗略近似。可以使用为粗网格单元生成的有效相位渗透率的粗尺度近似来模拟碳氢化合物储层。该方法还包括至少部分地基于模拟结果在非暂时性计算机可读介质中生成物理碳氢化合物储层的数据表示。

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