POWRE: Seismic Attribute Analysis Using Neural Networks

POWRE：使用神经网络进行地震属性分析

• 批准号: 9973411
• 负责人: Mary Poulton
• 金额: $ 7.48万
• 依托单位: University of Arizona
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 1999
• 资助国家: 美国
• 起止时间: 1999-07-01 至 2002-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9973411&HistoricalAwards=false
• 关键词: POWRE; Seismic; Attribute; Analysis; Using

9973411PoultonThis POWRE research plan is based on laying the groundwork that will lead to more fruitful collaboration in the future with other faculty members and ultimately the creation of a research consortium on computational intelligence for geophysical data processing. The groundwork consists of gaining the necessary background in seismic data processing through reading, coursework, and training, becoming knowledgeable about progress in computational intelligence over the past three years and acquiring the necessary hardware and software to conduct the research. The work will be divided into three phases: study of seismic processing with a particular focus on types of seismic attributes; re-acquiring knowledge of the current state of neural network research and other forms of computational intelligence; and applying neural network processing to seismic data with focus on reservoir property predictions. Because of the PI's extensive involvement in the implementation of a new general education curriculum and administrative responsibilities as the head of the Commission on the Status of Women, she has been removed from active research for the past three years. Her research area is geophysical data. For most of her career she has focused on electrical and electromagnetic geophysical techniques. She will re-establish her research program by moving into a new research area and learning about seismic data processing and how computational intelligence techniques such as neural networks can best be applied in that area.

9973411Poulton 这项 POWRE 研究计划的基础是奠定基础，从而在未来与其他教员进行更富有成效的合作，并最终创建一个地球物理数据处理计算智能研究联盟。 基础工作包括通过阅读、课程作业和培训获得地震数据处理的必要背景，了解过去三年计算智能的进展，并获取进行研究所需的硬件和软件。 这项工作将分为三个阶段：研究地震处理，特别关注地震属性类型；重新获取神经网络研究现状和其他形式的计算智能的知识；将神经网络处理应用于地震数据，重点是储层特性预测。 由于首席研究员广泛参与了新的普通教育课程的实施以及作为妇女地位委员会负责人的行政职责，她在过去三年中已不再参与积极的研究。 她的研究领域是地球物理数据。 在她职业生涯的大部分时间里，她专注于电气和电磁地球物理技术。 她将通过进入新的研究领域并学习地震数据处理以及如何在该领域最好地应用神经网络等计算智能技术来重新建立她的研究计划。