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For more than 80 years, the oil and gas industry has used seismic methods to construct images and determine physical characteristics of rocks that can yield information about oil and gas bearing structures in the earth. This book presents the different seismic data processing methods, also known as seismic "migration," in a unified mathematical way. The book serves as a bridge between the applied math and geophysics communities by presenting geophysicists with a practical introduction to advanced engineering mathematics, while presenting mathematicians with a window into the world of the mathematically sophisticated geophysicist.
With the increasing demand for infrastructure construction as the global economy progresses, the need for exploration and utilization of deep underground space becomes more crucial. Various deep underground projects are planned, are under construction, and have been built to encounter great construction challenges due to the complex geo-environment such as strong tectonic movement, fragile geo-environment and complex thermo-hydro-mechanical-chemical conditions. These deep engineering projects could be endangered by different kinds of geological disasters, such as intense rockburst, large deformation, strong water inrush, and large-scale collapse, which might result in massive loss of life and economic damage during the construction of deep underground projects. It is necessary to take proactive measures to ensure that the development of deep engineering projects is risk-informed and sustainable. Efforts are being called for strengthening science and technology innovation and cooperation in geological disaster mitigation and sustainable development during the construction of deep engineering projects. It is paramount to use new technologies and international cooperation to jointly tackle the geological disasters risks and achieve sustainable development. To mitigate the risk of geological disaster in deep engineering under the complicate geo-environment, the mechanism of the formation and evolution of geological disasters in deep engineering needs to be understood. The testing, monitoring, simulation, risk assessment and early warning methods for geological disaster in deep engineering are also needed urgently. New theories, methods and techniques related to the mechanism, warning and risk mitigation of geological disasters in deep engineering will be extremely helpful for the construction safety of deep engineering.
Acoustic signal is one of the hot topics of research in physics and has been studied by many engineers and scientists in various real-world fields, including underwater acoustics, architectural acoustics, engineering acoustics, physical acoustics, environmental acoustics, psychological acoustics, and so on. Noise reduction is the foundation of acoustic signal pre-processing, and the feature extraction for noise reduction signals can obtain useful information from the acoustic signal, which is the linchpin for pattern recognition, target detection, tracking, and localization.
Current strategies and logistics for seismic data acquisition impose restrictions on the calendar-time temporal resolution obtainable for a given time-lapse monitoring program. One factor that restricts the implementation of a quasi-continuous monitoring program using conventional strategies is the time it takes to acquire a complete survey. Here quasi-continuous monitoring describes the process of reservoir monitoring at short time intervals. This dissertation describes an approach that circumvents the restriction by requiring only a subset of a complete survey data each time an image of the reservoir is needed. Ideally, the time interval between survey subset acquisitions should be short so that changes in the reservoir properties are small. The accumulated data acquired are used to estimate the unavailable data at the monitor survey time, and the combined known and estimated data are used to produce an image of the subsurface for monitoring. Quasi-continuous seismic monitoring can be used to monitor geologic reservoirs during the injection phase of a carbon dioxide sequestration project. It can also be used to monitor reservoir changes between injector and producer wells during the secondary recovery phase in an oil field. The primary advantage of a quasi-continuous monitoring strategy over the conventional strategy is the high temporal resolution of the reservoir changes obtainable. Naturally, the spatial resolution of the image obtained using a subset of the data from a full survey will be worse than the spatial resolution of the image obtained using the complete data from a full survey. However, if the unavailable data are estimated perfectly, the spatial resolution is not lost. The choice of estimation algorithm and the size of the known data play an important role in the success of the approach presented in this dissertation.
For more than 80 years, the oil and gas industry has used seismic methods to construct images and determine physical characteristics of rocks that can yield information about oil and gas bearing structures in the earth. This book presents the different seismic data processing methods, also known as seismic "migration," in a unified mathematical way. The book serves as a bridge between the applied math and geophysics communities by presenting geophysicists with a practical introduction to advanced engineering mathematics, while presenting mathematicians with a window into the world of the mathematically sophisticated geophysicist.
A comprehensive overview of seismic ambient noise, covering observations, physical origins, modelling, processing methods and applications in imaging and monitoring.
​This three-volume set, LNAI 11670, LNAI 11671, and LNAI 11672 constitutes the thoroughly refereed proceedings of the 16th Pacific Rim Conference on Artificial Intelligence, PRICAI 2019, held in Cuvu, Yanuca Island, Fiji, in August 2019. The 111 full papers and 13 short papers presented in these volumes were carefully reviewed and selected from 265 submissions. PRICAI covers a wide range of topics such as AI theories, technologies and their applications in the areas of social and economic importance for countries in the Pacific Rim.
Future remote sensing systems will make extensive use of Compressive Sensing (CS) as it becomes more integrated into the system design with increased high resolution sensor developments and the rising earth observation data generated each year. Written by leading experts in the field Compressive Sensing of Earth Observations provides a comprehensive and balanced coverage of the theory and applications of CS in all aspects of earth observations. This work covers a myriad of practical aspects such as the use of CS in detection of human vital signs in a cluttered environment and the corresponding modeling of rib-cage breathing. Readers are also presented with three different applications of CS to the ISAR imaging problem, which includes image reconstruction from compressed data, resolution enhancement, and image reconstruction from incomplete data.