Download or read book Uncertainty Quantification for Prestack Time lapse Seismic Tomography written by Valentin Tschannen and published by . This book was released on 2014 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Time lapse Seismic Imaging and Uncertainty Quantification written by Maria Kotsi and published by . This book was released on 2020 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Time-lapse (4D) seismic monitoring is to date the most commonly used technique for estimating changes of a reservoir under production. Full-Waveform Inversion (FWI) is a high resolution technique that delivers Earth models by iteratively trying to match synthetic prestack seismic data with the observed data. Over the past decade the application of FWI on 4D data has been extensively studied, with a variety of strategies being currently available. However, 4D FWI still has challenges unsolved. In addition, the standard outcome of a 4D FWI scheme is a single image, without any measurement of the associated uncertainty. These issues beg the following questions: (1) Can we go beyond the current FWI limitations and deliver more accurate 4D imaging?, and (2) How well do we know what we think we know? In this thesis, I take steps to answer both questions. I first compare the performances of three common 4D FWI approaches in the presence of model uncertainties. These results provide a preliminary understanding of the underlying uncertainty, but also highlight some of the limitations of pixel by pixel uncertainty quantification. I then introduce a hybrid inversion technique that I call Dual-Domain Waveform Inversion (DDWI), whose objective function joins traditional FWI with Image Domain Wavefield Tomography (IDWT). The new objective function combines diving wave information in the data-domain FWI term with reflected wave information in the image-domain IDWT term, resulting in more accurate 4D model reconstructions. Working with 4D data provides an ideal situation for testing and developing new algorithms. Since there are repeated surveys at the same location, not only is the surrounding geology well-known and the results of interest are localized in small regions, but also they allow for better error analysis. Uncertainty quantification is very valuable for building knowledge but is not commonly done due to the computational challenge of exploring the range of all possible models that could fit the data. I exploit the structure of the 4D problem and propose the use of a focused modeling technique for a fast Metropolis-Hastings inversion. The proposed framework calculates time-lapse uncertainty quantification in a targeted way that is computationally feasible. Having the ground truth 4D probability distributions, I propose a local 4D Hamiltonian Monte Carlo (HMC) - a more advanced uncertainty quantification technique - that can handle higher dimensionalities while offering faster convergence.
Download or read book Uncertainty Quantification in Seismic Imaging written by Iga Pawelec and published by . This book was released on 2018 with total page 73 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Computationally Efficient Methods for Uncertainty Quantification in Seismic Inversion written by Georgia K. Stuart and published by . This book was released on 2020 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Full waveform inversion is an iterative optimization technique used to estimate subsurface physical parameters in the earth. A seismic energy source is generated in a borehole or on the surface of the earth which causes a seismic wave to propagate into the underground material. The transmitted wave then reflects off of material interfaces (rocks and fluids) and the returning wave is recorded at geophones. The inverse problem involves estimating parameters that describe this wave propagation (such as velocity) to minimize the misfit between the measured data and data we simulate from our mathematical model. The seismic velocity inversion problem is difficult because it contains sources of uncertainty, due to the instruments used to record the data and our mathematical model for seismic wave propagation. Using uncertainty quantification (UQ), we construct distributions of earth velocity models. Distributions give information about how probable an Earth model is, given the recorded seismic data. This rich information impacts real-world decision making, such as where to drill a well to produce oil and gas. UQ methods based on repeated sampling to construct estimates of the distribution, such as Markov chain Monte Carlo (MCMC), are desirable because they do not impose restrictions on the shape of the distribution. How ever, MCMC methods are computationally expensive because they require solving the wave equation repeatedly to generate simulated seismic wave data. This dissertation focuses on techniques to reduce the computational expense of MCMC methods for the seismic velocity inversion problem. Two-stage MCMC uses an inexpensive filter to cheaply reject unacceptable velocity models. The operator upscaling method, an inexpensive surrogate for the wave equation, is one such filter. We find that two-stage MCMC with the operator upscaling filter is effective at producing the same uncertainty information as traditional one-stage MCMC, but reduces the computational cost by between 20% and 45%. A neural network, in conjunction with operator upscaling, is another choice of filter. We find that the neural network filter reduces the computational cost of MCMC by 65% for our experiment, which includes the time needed to generate the training set and the neural network. The size of the problem we can solve using two-stage MCMC is limited by the random walk sampler. Hamiltonian Monte Carlo (HMC) and the No-U-Turn sampler (NUTS) use gradient information and Hamiltonian dynamics to steer the sampler, thereby eliminating the inefficient random walk behavior. Discretizing Hamiltonian dynamics requires two user specified parameters: trajectory length and step size. The NUTS algorithm avoids setting the trajectory length in advance by constructing variable-length paths. We find that the NUTS algorithm for seismic inversion results in superior decrease in the residual over traditional HMC while removing the need for costly tuning runs. However, constructing the gradient for the seismic inverse problem is computationally expensive. In two-stage, neural network-enhanced HMC we replace the costly gradient computation with a neural network. Additionally, we use the neural network to reject unacceptable samples as in two-stage MCMC. We find that the two-stage neural network HMC scheme reduces the computational cost by over 80% when compared to traditional HMC for a 100-unknown layered problem.
Download or read book Uncertainty Quantification and Model Calibration written by Jan Peter Hessling and published by BoD – Books on Demand. This book was released on 2017-07-05 with total page 228 pages. Available in PDF, EPUB and Kindle. Book excerpt: Uncertainty quantification may appear daunting for practitioners due to its inherent complexity but can be intriguing and rewarding for anyone with mathematical ambitions and genuine concern for modeling quality. Uncertainty quantification is what remains to be done when too much credibility has been invested in deterministic analyses and unwarranted assumptions. Model calibration describes the inverse operation targeting optimal prediction and refers to inference of best uncertain model estimates from experimental calibration data. The limited applicability of most state-of-the-art approaches to many of the large and complex calculations made today makes uncertainty quantification and model calibration major topics open for debate, with rapidly growing interest from both science and technology, addressing subtle questions such as credible predictions of climate heating.
Download or read book Uncertainty Quantification in Seismic Interferometry written by Daniella Ayala-Garcia and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Geophysics and Geosequestration written by Thomas L. Davis and published by Cambridge University Press. This book was released on 2019-05-09 with total page 391 pages. Available in PDF, EPUB and Kindle. Book excerpt: An overview of the geophysical techniques and analysis methods for monitoring subsurface carbon dioxide storage for researchers and industry practitioners.
Download or read book Introduction to uncertainty quantification written by T. J. Sullivan and published by . This book was released on 2015 with total page 342 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Handbook of Uncertainty Quantification written by Roger Ghanem and published by . This book was released on 2017 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Quantitative Detection of Fluid Distribution Using Time lapse Seismic written by Futoshi Tsuneyama and published by . This book was released on 2005 with total page 332 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Quantitative Analysis of Geopressure for Geoscientists and Engineers written by Nader C. Dutta and published by Cambridge University Press. This book was released on 2021-03-11 with total page 582 pages. Available in PDF, EPUB and Kindle. Book excerpt: Geopressure, or pore pressure in subsurface rock formations impacts hydrocarbon resource estimation, drilling, and drilling safety in operations. This book provides a comprehensive overview of geopressure analysis bringing together rock physics, seismic technology, quantitative basin modeling and geomechanics. It provides a fundamental physical and geological basis for understanding geopressure by explaining the coupled mechanical and thermal processes. It also brings together state-of-the-art tools and technologies for analysis and detection of geopressure, along with the associated uncertainty. Prediction and detection of shallow geohazards and gas hydrates is also discussed and field examples are used to illustrate how models can be practically applied. With supplementary MATLAB® codes and exercises available online, this is an ideal resource for students, researchers and industry professionals in geoscience and petroleum engineering looking to understand and analyse subsurface formation pressure.
Download or read book Methods and Applications in Reservoir Geophysics written by David H. Johnston and published by SEG Books. This book was released on 2010 with total page 669 pages. Available in PDF, EPUB and Kindle. Book excerpt: The reservoir-engineering tutorial discusses issues and data critically important engineers. The geophysics tutorial has explanations of the tools and data in case studies. Then each chapter focuses on a phase of field life: exploration appraisal, development planning, and production optimization. The last chapter explores emerging technologies.
Download or read book Interpreting Subsurface Seismic Data written by Rebecca Bell and published by Elsevier. This book was released on 2022-05-27 with total page 384 pages. Available in PDF, EPUB and Kindle. Book excerpt: Interpreting Subsurface Seismic Data presents recent advances in methodologies for seismic imaging and interpretation across multiple applications in geophysics including exploration, marine geology, and hazards. It provides foundational information for context, as well as focussing on recent advances and future challenges. It offers detailed methodologies for interpreting the increasingly vast quantity of data extracted from seismic volumes. Organized into three parts covering foundational context, case studies, and future considerations, Interpreting Subsurface Seismic Data offers a holistic view of seismic data interpretation to ensure understanding while also applying cutting-edge technologies. This view makes the book valuable to researchers and students in a variety of geoscience disciplines, including geophysics, hydrocarbon exploration, applied geology, and hazards. - Presents advanced seismic detection workflows utilized cutting-edge technologies - Integrates geophysics and geology for a variety of applications, using detailed examples - Provides an overview of recent advances in methodologies related to seismic imaging and interpretation
Download or read book Quantitative Seismic Interpretation written by Per Avseth and published by Cambridge University Press. This book was released on 2010-06-10 with total page 524 pages. Available in PDF, EPUB and Kindle. Book excerpt: Quantitative Seismic Interpretation demonstrates how rock physics can be applied to predict reservoir parameters, such as lithologies and pore fluids, from seismically derived attributes. The authors provide an integrated methodology and practical tools for quantitative interpretation, uncertainty assessment, and characterization of subsurface reservoirs using well-log and seismic data. They illustrate the advantages of these new methodologies, while providing advice about limitations of the methods and traditional pitfalls. This book is aimed at graduate students, academics and industry professionals working in the areas of petroleum geoscience and exploration seismology. It will also interest environmental geophysicists seeking a quantitative subsurface characterization from shallow seismic data. The book includes problem sets and a case-study, for which seismic and well-log data, and MATLAB® codes are provided on a website (http://www.cambridge.org/9780521151351). These resources will allow readers to gain a hands-on understanding of the methodologies.
Download or read book Practical Applications of Time lapse Seismic Data written by David H. Johnston and published by . This book was released on 2013 with total page 270 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Seismic Diffraction written by Tijmen Jan Moser and published by SEG Books. This book was released on 2016-06-30 with total page 823 pages. Available in PDF, EPUB and Kindle. Book excerpt: The use of diffraction imaging to complement the seismic reflection method is rapidly gaining momentum in the oil and gas industry. As the industry moves toward exploiting smaller and more complex conventional reservoirs and extensive new unconventional resource plays, the application of the seismic diffraction method to image sub-wavelength features such as small-scale faults, fractures and stratigraphic pinchouts is expected to increase dramatically over the next few years. “Seismic Diffraction” covers seismic diffraction theory, modeling, observation, and imaging. Papers and discussion include an overview of seismic diffractions, including classic papers which introduced the potential of diffraction phenomena in seismic processing; papers on the forward modeling of seismic diffractions, with an emphasis on the theoretical principles; papers which describe techniques for diffraction mathematical modeling as well as laboratory experiments for the physical modeling of diffractions; key papers dealing with the observation of seismic diffractions, in near-surface-, reservoir-, as well as crustal studies; and key papers on diffraction imaging.
Download or read book A First Course in Applied Mathematics written by Jorge Rebaza and published by John Wiley & Sons. This book was released on 2012-04-24 with total page 458 pages. Available in PDF, EPUB and Kindle. Book excerpt: Explore real-world applications of selected mathematical theory, concepts, and methods Exploring related methods that can be utilized in various fields of practice from science and engineering to business, A First Course in Applied Mathematics details how applied mathematics involves predictions, interpretations, analysis, and mathematical modeling to solve real-world problems. Written at a level that is accessible to readers from a wide range of scientific and engineering fields, the book masterfully blends standard topics with modern areas of application and provides the needed foundation for transitioning to more advanced subjects. The author utilizes MATLAB® to showcase the presented theory and illustrate interesting real-world applications to Google's web page ranking algorithm, image compression, cryptography, chaos, and waste management systems. Additional topics covered include: Linear algebra Ranking web pages Matrix factorizations Least squares Image compression Ordinary differential equations Dynamical systems Mathematical models Throughout the book, theoretical and applications-oriented problems and exercises allow readers to test their comprehension of the presented material. An accompanying website features related MATLAB® code and additional resources. A First Course in Applied Mathematics is an ideal book for mathematics, computer science, and engineering courses at the upper-undergraduate level. The book also serves as a valuable reference for practitioners working with mathematical modeling, computational methods, and the applications of mathematics in their everyday work.
