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    INTEGRATED ASSET MODELING FOR ENERGY CONSUMPTION AND EMISSION
    1.
    发明申请
    INTEGRATED ASSET MODELING FOR ENERGY CONSUMPTION AND EMISSION 有权

    公开(公告)号：US20250077734A1

    公开(公告)日：2025-03-06

    申请号：US18724939

    申请日：2023-02-09

    Applicant: Schlumberger Technology Corporation

    Inventor： David Rowan ,  Syed Abdul Samad Ali ,  Stephen Freeman

    IPC: G06F30/20 ,  G01V20/00 ,  G06F30/13

    Abstract: A method for quantifying and managing energy consumption and emissions equivalents of a subsurface development plan includes generating a plurality of digital representations of the subsurface development plan. The subsurface development plan includes a plurality of wellbores. The method also includes determining fluid production rates from the wellbores, fluid injection rates into the wellbores, or both based upon the digital representations. The method also includes determining that the fluid production rates, the fluid injection rates, or both are within operational constraints, achieve predetermined objectives, or both. The method also includes determining the energy consumption and the emissions equivalents based upon the digital representations. The emissions equivalents correspond to the energy consumption. The method also includes generating a plurality of different subsurface development plans based upon the energy consumption, the emissions equivalents, or both.

    Integrated Oilfield Asset Modeling Using Multiple Resolutions Of Reservoir Detail
    3.
    发明申请
    Integrated Oilfield Asset Modeling Using Multiple Resolutions Of Reservoir Detail 审中-公开
    综合油田资产建模利用多个分辨率的油藏细节

    公开(公告)号：US20160222766A1

    公开(公告)日：2016-08-04

    申请号：US14915674

    申请日：2014-09-05

    Applicant: SCHLUMBERGER TECHNOLOGY CORPORATION

    Inventor： David Rowan ,  Mark Wakefield ,  Simon D. Bulman

    IPC: E21B43/00 ,  E21B49/00

    CPC classification number: E21B43/00 ,  E21B41/00 ,  E21B49/00 ,  G01V11/00 ,  G01V99/005 ,  G01V2210/66

    Abstract: A method, apparatus, and program product model an oilfield asset by selecting, for each of multiple sectors of the oilfield asset, a sector model from among a collection of sector models, building a multi-resolution integrated asset model of the oilfield asset using the selected sector model for each of the sectors, and performing a computer simulation using the multi-resolution integrated asset model. The collection of sector models for each sector includes multiple sector models modeled at varying resolutions. In addition, the multi-resolution integrated asset model includes a surface network model that couples the selected sector models to one another. As such, different sectors of an oilfield asset may be modeled at varying resolutions to balance accuracy and turnaround time when performing integrated oilfield asset modeling.

    Abstract translation: 一种油田资产的方法，装置和程序产品模型，通过从油田资产的多个部门中选择一个部门模型集合中的一个部门模型，使用该油田资产构建油田资产的多分辨率综合资产模型 为每个扇区选择扇区模型，并使用多分辨率集成资产模型执行计算机模拟。 每个部门的部门模型的收集包括以不同分辨率建模的多个部门模型。 此外，多分辨率集成资产模型包括将所选择的扇区模型彼此耦合的表面网络模型。 因此，油田资产的不同部门可以以不同的决议建模，以平衡执行综合油田资产建模时的准确性和周转时间。

    Runtime Parameter Selection in Simulations
    5.
    发明申请
    Runtime Parameter Selection in Simulations 有权

    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

    IPC: G01V99/00 ,  G06F30/27 ,  G06F30/28 ,  G06N20/00

    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.

    Runtime parameter selection in simulations
    6.
    发明授权
    Runtime parameter selection in simulations 有权

    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

    IPC: G06N20/00 ,  G06F30/20 ,  G06F30/28 ,  G01V99/00 ,  G06F30/27 ,  G06F113/08

    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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