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CAREER: Efficient Numerical Solutions in Geophysical Subsurface Sensing

CAREER: Efficient Numerical Solutions in Geophysical Subsurface Sensing
职业:地球物理地下传感的高效数值解决方案
批准号:
9702195
负责人:
Qing Huo Liu
金额:
$20.0万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
1997
资助国家:
美国
项目状态:
已结题
起止时间:
1997-09-15 至 1999-09-08

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中文摘要
翻译
该职业计划的目标是开发有效的正演和反演技术来解决地球物理地下传感中的电磁和弹性动力学问题,并培养有效的跨学科教育计划。在地球物理地下传感中,电磁和声波传感器被广泛用于探测井内复杂的地质构造。然而,由于地下介质的复杂性和井筒的存在,这些重要测量数据的解释仍然是一个具有挑战性的问题。如果使用传统方法,模拟这些问题中遇到的真实三维模型很容易超出任何现代超级计算机的能力。因此,迫切需要更有效的数值技术来模拟大规模的电磁和声学测量。这些模拟在处理收集的数据和新的测量系统的计算机辅助设计中也至关重要。在本研究中,将为三维非均匀介质中的电极、感应和声波测井工具开发有效的正解和反解。在正解中,根据介质的物理性质对测量数据进行模拟。反问题则是根据测量数据确定介质的物理性质,这是地球物理地下传感的最终目的。作为研究的重点,将开发一系列高效的正演模型,作为三维电磁和弹动力问题非线性反演的支柱。所提出的技术将允许人们在超级计算机上解决比传统有限差分和有限元方法大得多的问题。正解将与逆算法有效耦合。在教育计划方面,首席研究员(PI)建议通过开发跨学科课程和合作,加强电气工程,地球物理和机械工程部门教师和学生之间的互动。开设3门跨系新课程,将计算机和网络纳入电磁学教学,提高教学效果。本研究计划将与电气工程本科及研究生教育充分整合。这个综合的职业计划将大大提高模拟地球物理地下传感中大规模正、逆电磁和弹性动力学问题的能力。石油工业将从这个研究项目中受益,通过知识的出版和开发的软件。该计划还将有利于地下掩埋废物的地下测绘和医疗成像行业。参与这项研究的学生将有独特的机会获得关于电气工程在地球物理勘探中的应用的跨学科知识。
英文摘要
The goals of this career program are to develop efficient forward and inverse techniques to solve electromagnetic and elastodynamic problems in geophysical subsurface sensing, and to foster an effective, interdisciplinary educational program. In geophysical subsurface sensing, electromagnetic and acoustic sensors are widely used to probe the complex geological structures from within a borehole. The interpretation of these important measurements, however, remains a challenging problem because of the complexity of the underground medium and of the presence of the wellbore. Simulating realistic three-dimensional models encountered in these problems can easily exceed the capacity of any modern supercomputer if conventional methods are used. Therefore, there is a pressing demand for more efficient numerical techniques to simulate large-scale electromagnetic and acoustic measurements. These simulations are also critical in processing the collected data and in computer-aided design of new measurement systems. In this research, efficient forward and inverse solutions will be developed for electrodetype, induction, and sonic well logging tools in three-dimensional inhomogeneous media. In forward solutions, the measurement data are simulated given the physical properties of the medium. In inverse problems, on the other hand, the physical properties of the medium are determined from the measurement data, which is the ultimate goal of geophysical subsurface sensing. As the focus of research, a series of efficient forward models will be developed as a backbone of nonlinear inversion for 3-D electromagnetic and elastodynamic problems. The techniques proposed will allow one to solve much larger problems than conventional finite-difference and finite-element methods on a supercomputer. The forward solutions will be effectively coupled with the inverse algorithms. In the educational program, the principal investigator (PI) proposes to strengthen the interactions among faculty members and students in electrical engineering, geophysics, and mechanical engineering departments by developing interdisciplinary courses and by collaboration. Three new cross-department courses will be developed, and the use of computers and network in electromagnetic education will be incorporated to improve the teaching effectiveness. The research program will be fully integrated with the undergraduate and graduate electrical engineering education. This integrated career program Will significantly advance the capability of simulating large-scale forward and inverse electromagnetic and elastodynamic problems in geophysical subsurface sensing. The petroleum industry will benefit from this research program through the publication of knowledge and software developed. This program will also benefit subsurface mapping of underground buried waste and the medical imaging industry. The students involved in this research will have the unique opportunity to acquire interdisciplinary knowledge on the applications of electrical engineering in geophysical exploration.
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海外基金