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公开(公告)号：US07966331B2
公开(公告)日：2011-06-21
申请号：US10643191
申请日：2003-08-18
申请人： Martha Gardner , Rajesh Tyagi , Thomas Repoff , Abhinanda Sarkar , Angshuman Saha , Shirley Au , Roy Wilson , Malcolm Craig Winslow , Michael Dion
发明人： Martha Gardner , Rajesh Tyagi , Thomas Repoff , Abhinanda Sarkar , Angshuman Saha , Shirley Au , Roy Wilson , Malcolm Craig Winslow , Michael Dion
摘要： A method and system for assessing and optimizing crude selection are provided. A predictive engine uses data from a database to execute at least one predictive performance model and/or at least one risk assessment model designed to optimize or improve refining operations during a refining process. The predictive engine takes as input key crude information corresponding to a particular crude or crude blend, e.g., at least one crude slate, and refinery operating parameters and/or conditions corresponding to a specific refinery and uses desirability metrics to assess the similarity to data in the database. Based on the resulting output, at least one predictive performance and/or at least one risk assessment model uses the output to predict performance or risk measures of refining the particular crude or crude blend using the specific refinery during the refining process, the probability of problems occurring during the refining process, the distribution of the problems throughout the refining process, etc.
摘要翻译： 提供了评估和优化粗选择的方法和系统。 预测引擎使用来自数据库的数据来执行至少一个预测性能模型和/或至少一个风险评估模型，其被设计为在精炼过程中优化或改进精炼操作。 预测引擎将对应于特定原油或原油混合物的输入关键原油信息，例如至少一个粗钢板，以及对应于特定炼油厂的炼油厂操作参数和/或条件，并且使用可取性度量来评估与数据的相似性 数据库。 基于所得到的产出，至少一个预测性能和/或至少一个风险评估模型使用输出来预测在精炼过程中使用特定炼油厂改进特定原油或粗混合物的性能或风险度量，问题的概率 在精炼过程中发生的问题在整个精炼过程中的分布等
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公开(公告)号：US20050050009A1
公开(公告)日：2005-03-03
申请号：US10643191
申请日：2003-08-18
申请人： Martha Gardner , Rajesh Tyagi , Thomas Repoff , Abhinanda Sarkar , Angshuman Saha , Shirley Au , Roy Wilson , Malcolm Winslow , Michael Dion
发明人： Martha Gardner , Rajesh Tyagi , Thomas Repoff , Abhinanda Sarkar , Angshuman Saha , Shirley Au , Roy Wilson , Malcolm Winslow , Michael Dion
摘要： A method and system for assessing and optimizing crude selection are provided. A predictive engine uses data from a database to execute at least one predictive performance model and/or at least one risk assessment model designed to optimize or improve refining operations during a refining process. The predictive engine takes as input key crude information corresponding to a particular crude or crude blend, e.g., at least one crude slate, and refinery operating parameters and/or conditions corresponding to a specific refinery and uses desirability metrics to assess the similarity to data in the database. Based on the resulting output, at least one predictive performance and/or at least one risk assessment model uses the output to predict performance or risk measures of refining the particular crude or crude blend using the specific refinery during the refining process, the probability of problems occurring during the refining process, the distribution of the problems throughout the refining process, etc.
摘要翻译： 提供了评估和优化粗选择的方法和系统。 预测引擎使用来自数据库的数据来执行至少一个预测性能模型和/或至少一个风险评估模型，其被设计为在精炼过程中优化或改进精炼操作。 预测引擎将对应于特定原油或原油混合物的输入关键原油信息，例如至少一个粗钢板，以及对应于特定炼油厂的炼油厂操作参数和/或条件，并且使用可取性度量来评估与数据的相似性 数据库。 基于所得到的产出，至少一个预测性能和/或至少一个风险评估模型使用输出来预测在精炼过程中使用特定炼油厂改进特定原油或粗混合物的性能或风险度量，问题的概率 在精炼过程中发生的问题在整个精炼过程中的分布等
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