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公开(公告)号：US11536873B2
公开(公告)日：2022-12-27
申请号：US16328270
申请日：2017-09-28
Applicant: Schlumberger Technology Corporation
Inventor： Tom Jonsthovel , Terry Wayne Stone
Abstract: A method for performing a modified two point flux approximation scheme is disclosed. The method includes: obtaining a first pressure value for a first neighbor cell and a second pressure value for a second neighbor cell, where the first neighbor cell has a first value of a reservoir property and the second neighbor cell as a second value of the reservoir property; determining a first weight using the first pressure value and a second weight using the second pressure value; calculating a third value of the reservoir property as a weighted average of the first value and the second value; and applying the third value to the first neighbor cell.
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Patent Agency Ranking
公开(公告)号：US11782184B2
公开(公告)日：2023-10-10
申请号：US18145561
申请日：2022-12-22
Applicant: Schlumberger Technology Corporation
Inventor： Tom Jonsthovel , Terry Wayne Stone
CPC classification number: G01V99/005 , G01V3/18 , G01V11/00 , G06F17/13 , G06F30/20
Abstract: A method for performing a modified two point flux approximation scheme is disclosed. The method includes: obtaining a first pressure value for a first neighbor cell and a second pressure value for a second neighbor cell, where the first neighbor cell has a first value of a reservoir property and the second neighbor cell as a second value of the reservoir property; determining a first weight using the first pressure value and a second weight using the second pressure value; calculating a third value of the reservoir property as a weighted average of the first value and the second value; and applying the third value to the first neighbor cell.
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公开(公告)号：US20210033748A1
公开(公告)日：2021-02-04
申请号：US16306891
申请日：2016-06-13
Applicant: Schlumberger Technology Corporation
Inventor： David Rowan , Tom Jonsthovel
Abstract: A method for performing a field operation of a field. The method includes obtaining historical parameter values of a runtime parameter and historical core datasets, where the historical parameter values and the historical core datasets are used for a first simulation of the field, and where each historical parameter value results in a simulation convergence during the first simulation, generating a machine learning model based at least on the historical core datasets and the historical parameter values, obtaining, during a second simulation of the field, a current core dataset, generating, using the machine learning model and based on the current core dataset, a predicted parameter value of the runtime parameter for achieving the simulation convergence during the second simulation, and completing, using at least the predicted parameter value, the second simulation to generate a modeling result of the field.
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公开(公告)号：US20150160371A1
公开(公告)日：2015-06-11
申请号：US14535459
申请日：2014-11-07
Applicant: SCHLUMBERGER TECHNOLOGY CORPORATION
Inventor： Tom Jonsthovel , Paul Woodhams
CPC classification number: G06F17/16 , G01V2210/624 , G01V2210/64 , G06F17/12 , G06F17/5009 , G06F17/5018 , G06F2217/16
Abstract: Using a CPU and at least one GPU to simulate geomechanical reservoir deformation due to a change in force on the reservoir is presented. An example method includes obtaining a stiffness matrix representing a finite element mesh for a grid of the reservoir, obtaining a load vector representing the change in force, determining a displacement vector representing the deformation of the reservoir, by computing, as a setup process apart from a conjugate gradient solver iteration, and by the CPU and the at least one GPU, at least a portion of a deflation operator and iterating, by the CPU and the at least one GPU, a conjugate gradient solver applied to a system of linear equations defined by at least the deflation operator, the stiffness matrix, the load vector, and the displacement vector, such that a deflated solution corresponding to the displacement vector is produced.
Abstract translation: 提出了使用CPU和至少一个GPU来模拟由于储层上的力的变化引起的地质力学储层变形。 一个示例性方法包括获得表示储层网格的有限元网格的刚度矩阵，通过计算作为设计过程的计算，获得表示力变化的载荷矢量，确定表示储层变形的位移矢量 共轭梯度求解器迭代，以及由CPU和至少一个GPU，至少一部分放气算子，并由CPU和至少一个GPU迭代应用于定义的线性方程组的系统的共轭梯度求解器 通过至少缩放算子，刚度矩阵，载荷矢量和位移矢量，使得产生与位移矢量对应的放气解。
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公开(公告)号：US20250061422A1
公开(公告)日：2025-02-20
申请号：US18723554
申请日：2022-02-17
Applicant: Schlumberger Technology Corporation
Inventor： Wiebke Athmer , Aicha Bounaim , Tom Jonsthovel
IPC: G06Q10/10
Abstract: A digital platform is provided that is accessed by a plurality of users that represent entities that provide services or facilities related to carbon capture and storage projects. The platform executes at least one process configured to enable collaboration between users for carbon capture and sequestration projects. Additionally or alternatively. the platform can be configured for access by users that represent entities that provide services or facilities related to other energy-related projects, such as hydrogen projects and geothermal projects. The platform can be configured to execute at least one process configured to enable collaboration between users for energy-related projects.
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公开(公告)号：US11775858B2
公开(公告)日：2023-10-03
申请号：US16306891
申请日：2016-06-13
Applicant: Schlumberger Technology Corporation
Inventor： David Rowan , Tom Jonsthovel
CPC classification number: G06N20/00 , G01V99/005 , G06F30/20 , G06F30/27 , G06F30/28 , G06F2113/08
Abstract: A method for performing a field operation of a field. The method includes obtaining historical parameter values of a runtime parameter and historical core datasets, where the historical parameter values and the historical core datasets are used for a first simulation of the field, and where each historical parameter value results in a simulation convergence during the first simulation, generating a machine learning model based at least on the historical core datasets and the historical parameter values, obtaining, during a second simulation of the field, a current core dataset, generating, using the machine learning model and based on the current core dataset, a predicted parameter value of the runtime parameter for achieving the simulation convergence during the second simulation, and completing, using at least the predicted parameter value, the second simulation to generate a modeling result of the field.
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