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    METRICS MONITORING AND FINANCIAL VALIDATION SYSTEM (M2FVS) FOR TRACKING PERFORMANCE OF CAPITAL, OPERATIONS, AND MAINTENANCE INVESTMENTS TO AN INFRASTRUCTURE
    2.
    发明申请
    METRICS MONITORING AND FINANCIAL VALIDATION SYSTEM (M2FVS) FOR TRACKING PERFORMANCE OF CAPITAL, OPERATIONS, AND MAINTENANCE INVESTMENTS TO AN INFRASTRUCTURE 有权
    用于跟踪资本，运营和维护对基础设施投资绩效的衡量监测和金融确认系统（M2FVS）

    公开(公告)号：US20130073488A1

    公开(公告)日：2013-03-21

    申请号：US13589737

    申请日：2012-08-20

    申请人： Roger N. Anderson ,  Albert Boulanger ,  Leon L. Wu

    发明人： Roger N. Anderson ,  Albert Boulanger ,  Leon L. Wu

    IPC分类号： G06F15/18

    CPC分类号： G06Q10/04

    摘要： Techniques for evaluating the accuracy of a predicted effectiveness of an improvement to an infrastructure include collecting data, representative of at least one pre-defined metric, from the infrastructure during first and second time periods corresponding to before and after a change has been implemented, respectively. A machine learning system can receive compiled data representative of the first time period and generate corresponding machine learning data. A machine learning results evaluator can empirically analyze the generated machine learning data. An implementer can implement the change to the infrastructure based at least in part on the data from a machine learning data outputer. A system performance improvement evaluator can compare the compiled data representative of the first time period to that of the second time period to determine a difference, if any, and compare the difference, if any, to a prediction based on the generated machine learning data.

    摘要翻译： 用于评估对基础设施改进的预测有效性的准确性的技术包括分别在对应于改变之前和之后的第一和第二时间段期间从基础设施收集表示至少一个预定义度量的数据 。 机器学习系统可以接收代表第一时间段的编译数据并产生相应的机器学习数据。 机器学习结果评估器可以经验性地分析生成的机器学习数据。 至少部分地基于来自机器学习数据输出器的数据，实现者可以实现对基础设施的改变。 系统性能改进评估器可以将表示第一时间段的编译数据与第二时间周期的编译数据进行比较，以确定差异（如果有的话），并根据所生成的机器学习数据将差值（如果有的话）与预测进行比较。

    METHODS AND SYSTEMS OF DETERMINING THE EFFECTIVENESS OF CAPITAL IMPROVEMENT PROJECTS
    3.
    发明申请
    METHODS AND SYSTEMS OF DETERMINING THE EFFECTIVENESS OF CAPITAL IMPROVEMENT PROJECTS 审中-公开
    确定资本改进项目效率的方法与制度

    公开(公告)号：US20110231213A1

    公开(公告)日：2011-09-22

    申请号：US12885800

    申请日：2010-09-20

    申请人： Roger N. Anderson ,  Albert Boulanger ,  Samantha Cook ,  John Johnson

    发明人： Roger N. Anderson ,  Albert Boulanger ,  Samantha Cook ,  John Johnson

    IPC分类号： G06Q10/00

    CPC分类号： G06Q40/06 ,  G06Q10/063

    摘要： The present application provides methods and systems for quantitatively predicting an effectiveness of a proposed capital improvement project based on one or more previous capital improvement projects representative of one or more physical assets and including one or more attributes that includes defining a first sample pool from the previous capital improvement project data in which said previous capital improvement project has been performed, defining a second sample in which the previous capital improvement project has not been performed, the second sample pool including one or more attribute values that are the same as, or similar to, the attribute values for the first sample pool, generating a performance metric for each of the first and second sample pools, comparing the performance metric from the first sample pool with the performance metric from the second sample pool to determine a net performance metric, and, generating a prediction of effectiveness of the proposed capital improvement project concerning based on said net performance metric.

    摘要翻译： 本申请提供方法和系统，用于基于一个或多个代表一个或多个物理资产的以前的资本改进项目定量地预测所提出的资本改进项目的有效性，并且包括一个或多个属性，所述一个或多个属性包括从先前的 已经执行了所述先前资本改进项目的资本改进项目数据，定义了尚未执行先前资本改进项目的第二个样本，第二样本池包括一个或多个与之相同或相似的属性值 ，所述第一样本池的属性值，为每个第一和第二样本池生成性能度量，将来自第一样本池的性能度量与来自第二样本池的性能度量进行比较以确定净性能度量，以及 ，产生建议资本的有效性的预测i 基于所述净性能指标的改进项目。

    Method for identifying subsurface fluid migration and drainage pathways in and among oil and gas reservoirs using 3-D and 4-D seismic imaging
    5.
    发明授权
    Method for identifying subsurface fluid migration and drainage pathways in and among oil and gas reservoirs using 3-D and 4-D seismic imaging 失效
    使用三维和四维地震成像识别油气藏及其中的地下流体迁移和排水路径的方法

    公开(公告)号：US5586082A

    公开(公告)日：1996-12-17

    申请号：US398371

    申请日：1995-03-02

    申请人： Roger N. Anderson ,  Albert Boulanger ,  Edward P. Bagdonas ,  Liqing Xu ,  Wei He

    发明人： Roger N. Anderson ,  Albert Boulanger ,  Edward P. Bagdonas ,  Liqing Xu ,  Wei He

    IPC分类号： G01V1/30 ,  G01V1/13 ,  G01V1/28

    CPC分类号： G01V1/30

    摘要： The invention utilizes 3-D and 4-D seismic surveys as a means of deriving information useful in petroleum exploration and reservoir management. The methods use both single seismic surveys (3-D) and multiple seismic surveys separated in time (4-D) of a region of interest to determine large scale migration pathways within sedimentary basins, and fine scale drainage structure and oil-water-gas regions within individual petroleum producing reservoirs. Such structure is identified using pattern recognition tools which define the regions of interest. The 4-D seismic data sets may be used for data completion for large scale structure where time intervals between surveys do not allow for dynamic evolution. The 4-D seismic data sets also may be used to find variations over time of small scale structure within individual reservoirs which may be used to identify petroleum drainage pathways, oil-water-gas regions and, hence, attractive drilling targets. After spatial orientation, and amplitude and frequency matching of the multiple seismic data sets, High Amplitude Event (HAE) regions consistent with the presence of petroleum are identified using seismic attribute analysis. High Amplitude Regions are grown and interconnected to establish plumbing networks on the large scale and reservoir structure on the small scale. Small scale variations over time between seismic surveys within individual reservoirs are identified and used to identify drainage patterns and bypassed petroleum to be recovered. The location of such drainage patterns and bypassed petroleum may be used to site wells.

    摘要翻译： 本发明利用三维和四维地震勘测作为推导石油勘探和油藏管理有用信息的手段。 该方法采用单独的地震勘测（3-D）和多个地震勘探，在时间上分离（4-D），以确定沉积盆地内的大规模迁移路径，精细规模排水结构和油水气 个别石油生产水库的区域。 使用定义感兴趣区域的模式识别工具识别这种结构。 4-D地震数据集可用于大规模结构的数据完成，其中调查之间的时间间隔不允许动态演化。 4-D地震数据集还可用于发现各个储层内的小尺度结构随时间推移的变化，可用于识别石油排放通道，油水 - 气体区域，从而识别有吸引力的钻井目标。 在空间取向和多个地震数据集的幅度和频率匹配之后，使用地震属性分析来确定与石油存在一致的高幅度事件（HAE）区域。 高幅度地区生长和相互连接，在小规模的大规模和储层结构上建立管道网络。 确定各个储层之间的地震勘测之间随时间的小规模变化，并用于确定要回收的排水模式和旁路石油。 这种排水模式和旁路石油的位置可用于现场井。

    Metrics monitoring and financial validation system (M2FVS) for tracking performance of capital, operations, and maintenance investments to an infrastructure
    6.
    发明授权
    Metrics monitoring and financial validation system (M2FVS) for tracking performance of capital, operations, and maintenance investments to an infrastructure 有权
    衡量基础设施资本，运营和维护投资绩效的指标监测和财务确认系统（M2FVS）

    公开(公告)号：US08725665B2

    公开(公告)日：2014-05-13

    申请号：US13589737

    申请日：2012-08-20

    申请人： Roger N. Anderson ,  Albert Boulanger ,  Leon Wu ,  Serena Lee

    发明人： Roger N. Anderson ,  Albert Boulanger ,  Leon Wu ,  Serena Lee

    IPC分类号： G06F15/18

    CPC分类号： G06Q10/04

    摘要： Techniques for evaluating the accuracy of a predicted effectiveness of an improvement to an infrastructure include collecting data, representative of at least one pre-defined metric, from the infrastructure during first and second time periods corresponding to before and after a change has been implemented, respectively. A machine learning system can receive compiled data representative of the first time period and generate corresponding machine learning data. A machine learning results evaluator can empirically analyze the generated machine learning data. An implementer can implement the change to the infrastructure based at least in part on the data from a machine learning data outputer. A system performance improvement evaluator can compare the compiled data representative of the first time period to that of the second time period to determine a difference, if any, and compare the difference, if any, to a prediction based on the generated machine learning data.

    摘要翻译： 用于评估对基础设施改进的预测有效性的准确性的技术包括分别在对应于改变之前和之后的第一和第二时间段期间从基础设施收集表示至少一个预定义度量的数据 。 机器学习系统可以接收代表第一时间段的编译数据并产生相应的机器学习数据。 机器学习结果评估器可以经验性地分析生成的机器学习数据。 至少部分地基于来自机器学习数据输出器的数据，实现者可以实现对基础设施的改变。 系统性能改进评估器可以将表示第一时间段的编译数据与第二时间周期的编译数据进行比较，以确定差异（如果有的话），并根据生成的机器学习数据将差值（如果有的话）与预测进行比较。

    Martingale control of production for optimal profitability of oil and gas fields
    7.
    发明授权
    Martingale control of production for optimal profitability of oil and gas fields 有权
    控制生产以控制油气田的最佳利润

    公开(公告)号：US08560476B2

    公开(公告)日：2013-10-15

    申请号：US12019347

    申请日：2008-01-24

    申请人： Roger N. Anderson ,  Albert Boulanger ,  Wei He ,  Ulisses Mello ,  Liqing Xu

    发明人： Roger N. Anderson ,  Albert Boulanger ,  Wei He ,  Ulisses Mello ,  Liqing Xu

    IPC分类号： G06F17/00 ,  G06N5/00 ,  G06G7/48

    CPC分类号： G01V11/00 ,  G01V2210/612 ,  G06Q10/04

    摘要： A computer-aided lean management (CALM) controller system recommends actions and manages production in an oil and gas reservoir/field as its properties and conditions change with time. The reservoir/field is characterized and represented as an electronic-field (“e-field”). A plurality of system applications describe dynamic and static e-field properties and conditions. The application workflows are integrated and combined in a feedback loop between actions taken in the field and metrics that score the success or failure of those actions. A controller/optimizer operates on the combination of the application workflows to compute production strategies and actions. The controller/optimizer is configured to generate a best action sequence for production, which is economically “always-in-the-money.”

    摘要翻译： 计算机辅助精简管理（CALM）控制器系统建议在油气藏/油田中的生产进行动作和管理，因为其属性和条件随时间而变化。 水库/油田被表征为电子场（“电场”）。 多个系统应用程序描述动态和静态电场特性和条件。 应用程序工作流程被集成在一起，并结合在现场采取的动作和衡量这些操作的成功或失败的指标之间的反馈循环中。 一个控制器/优化器运行在应用程序工作流的组合上来计算生产策略和动作。 控制器/优化器被配置为生成最佳的动作序列，这是经济上“永远在金钱”。

    MARTINGALE CONTROL OF PRODUCTION FOR OPTIMAL PROFITABILITY OF OIL AND GAS FIELDS
    9.
    发明申请
    MARTINGALE CONTROL OF PRODUCTION FOR OPTIMAL PROFITABILITY OF OIL AND GAS FIELDS 有权
    MARTINGALE控制生产油和油田的最佳利润

    公开(公告)号：US20080294387A1

    公开(公告)日：2008-11-27

    申请号：US12019347

    申请日：2008-01-24

    申请人： Roger N. Anderson ,  Albert Boulanger ,  Wei He ,  Ulisses Mello ,  Liqing Xu

    发明人： Roger N. Anderson ,  Albert Boulanger ,  Wei He ,  Ulisses Mello ,  Liqing Xu

    IPC分类号： G06F17/50 ,  G06G7/50

    CPC分类号： G01V11/00 ,  G01V2210/612 ,  G06Q10/04

    摘要： A computer-aided lean management (CALM) controller system recommends actions and manages production in an oil and gas reservoir/field as its properties and conditions change with time. The reservoir/field is characterized and represented as an electronic-field (“e-field”). A plurality of system applications describe dynamic and static e-field properties and conditions. The application workflows are integrated and combined in a feedback loop between actions taken in the field and metrics that score the success or failure of those actions. A controller/optimizer operates on the combination of the application workflows to compute production strategies and actions. The controller/optimizer is configured to generate a best action sequence for production, which is economically “always-in-the-money.”

    摘要翻译： 计算机辅助精简管理（CALM）控制器系统建议在油气藏/油田中的生产进行动作和管理，因为其属性和条件随时间而变化。 水库/油田被表征为电子场（“电场”）。 多个系统应用程序描述动态和静态电场特性和条件。 应用程序工作流程被集成在一起，并结合在现场采取的动作和衡量这些操作的成功或失败的指标之间的反馈循环中。 一个控制器/优化器运行在应用程序工作流的组合上来计算生产策略和动作。 控制器/优化器被配置为生成最佳的动作序列，这是经济上“永远在金钱”。

    Dynamic contingency avoidance and mitigation system
    10.
    发明授权
    Dynamic contingency avoidance and mitigation system 有权
    动态应急避免和减轻系统

    公开(公告)号：US09395707B2

    公开(公告)日：2016-07-19

    申请号：US13214057

    申请日：2011-08-19

    申请人： Roger N. Anderson ,  Albert Boulanger ,  John A. Johnson

    发明人： Roger N. Anderson ,  Albert Boulanger ,  John A. Johnson

    IPC分类号： G06F1/28 ,  G06F17/00 ,  G05B13/02 ,  G06Q10/04 ,  G06Q10/06 ,  G05B23/02 ,  G05B15/02 ,  H02J3/00

    CPC分类号： G06Q10/06315 ,  G05B13/0265 ,  G05B15/02 ,  G05B23/0283 ,  G06F17/5009 ,  G06Q10/04 ,  G06Q10/06375 ,  G06Q50/06 ,  H02J2003/007 ,  Y04S10/54

    摘要： The disclosed subject matter provides systems and methods for allocating resources within an infrastructure, such as an electrical grid, in response to changes to inputs and output demands on the infrastructure, such as energy sources and sinks. A disclosed system includes one or more processors, each having respective communication interfaces to receive data from the infrastructure, the data including infrastructure network data, one or more software applications, operatively coupled to and at least partially controlling the one or more processors, to process and characterize the infrastructure network data; and a display, coupled to the one or more processors, for visually presenting a depiction of at least a portion of the infrastructure including any changes in condition thereof, and one or more controllers in communication with the one or more processors, to manage processing of the resource, wherein the resource is obtained and/or distributed based on the characterization of the real time infrastructure data.

    摘要翻译： 所公开的主题提供了用于在诸如电网之类的基础设施（例如电网）内分配资源的系统和方法，以响应对基础设施（例如能量源和汇）的输入和输出需求的改变。 所公开的系统包括一个或多个处理器，每个处理器具有各自的通信接口以从基础设施接收数据，数据包括基础设施网络数据，一个或多个软件应用，可操作地耦合到并且至少部分地控制一个或多个处理器，以处理 并表征基础设施网络数据; 以及耦合到所述一个或多个处理器的显示器，用于可视地呈现所述基础设施的至少一部分的描绘，包括其条件的任何改变，以及与所述一个或多个处理器通信的一个或多个控制器，以管理 资源，其中基于实时基础设施数据的表征来获得和/或分发资源。