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Complex-valued adaptive-coefficient finite-difference frequency-domain method for wavefield modeling based on the diffusive-viscous wave equation
Zhao, Haixia (Xi’an Jiaotong University, National Engineering Research Center of Offshore Oil and Gas Exploration) | Wang, Shaoru (Xi’an Jiaotong University) | Xu, Wenhao (Hohai University) | Gao, Jinghuai (Xi’an Jiaotong University, National Engineering Research Center of Offshore Oil and Gas Exploration)
ABSTRACT The diffusive-viscous wave (DVW) equation is an effective model for analyzing seismic low-frequency anomalies and attenuation in porous media. To effectively simulate DVW wavefields, the finite-difference or finite-element method in the time domain is favored, but the time-domain approach proves less efficient with multiple shots or a few frequency components. The finite-difference frequency-domain (FDFD) method featuring optimal or adaptive coefficients is favored in seismic simulations due to its high efficiency. Initially, we develop a real-valued adaptive-coefficient (RVAC) FDFD method for the DVW equation, which ignores the numerical attenuation error and is a generalization of the acoustic adaptive-coefficient FDFD method. To reduce the numerical attenuation error of the RVAC FDFD method, we introduce a complex-valued adaptive-coefficient (CVAC) FDFD method for the DVW equation. The CVAC FDFD method is constructed by incorporating correction terms into the conventional second-order FDFD method. The adaptive coefficients are related to the spatial sampling ratio, number of spatial grid points per wavelength, and diffusive and viscous attenuation coefficients in the DVW equation. Numerical dispersion and attenuation analysis confirm that, with a maximum dispersion error of 1% and a maximum attenuation error of 10%, the CVAC FDFD method only necessitates 2.5 spatial grid points per wavelength. Compared with the RVAC FDFD method, the CVAC FDFD method exhibits enhanced capability in suppressing the numerical attenuation during anelastic wavefield modeling. To validate the accuracy of our method, we develop an analytical solution for the DVW equation in a homogeneous medium. Three numerical examples substantiate the high accuracy of the CVAC FDFD method when using a small number of spatial grid points per wavelength, and this method demands computational time and computer memory similar to those required by the conventional second-order FDFD method. A fluid-saturated model featuring various layer thicknesses is used to characterize the propagation characteristics of DVW.
- Geophysics > Seismic Surveying > Seismic Processing (1.00)
- Geophysics > Seismic Surveying > Seismic Modeling > Velocity Modeling > Seismic Inversion (0.93)
- Geophysics > Seismic Surveying > Seismic Interpretation (0.93)
- Information Technology > Artificial Intelligence > Machine Learning (0.46)
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Complex-valued adaptive-coefficient finite-difference frequency-domain method for wavefield modeling based on the diffusive-viscous wave equation
Zhao, Haixia (Xi’an Jiaotong University, National Engineering Research Center of Offshore Oil and Gas Exploration) | Wang, Shaoru (Xi’an Jiaotong University) | Xu, Wenhao (Hohai University) | Gao, Jinghuai (Xi’an Jiaotong University, National Engineering Research Center of Offshore Oil and Gas Exploration)
ABSTRACT The diffusive-viscous wave (DVW) equation is an effective model for analyzing seismic low-frequency anomalies and attenuation in porous media. To effectively simulate DVW wavefields, the finite-difference or finite-element method in the time domain is favored, but the time-domain approach proves less efficient with multiple shots or a few frequency components. The finite-difference frequency-domain (FDFD) method featuring optimal or adaptive coefficients is favored in seismic simulations due to its high efficiency. Initially, we develop a real-valued adaptive-coefficient (RVAC) FDFD method for the DVW equation, which ignores the numerical attenuation error and is a generalization of the acoustic adaptive-coefficient FDFD method. To reduce the numerical attenuation error of the RVAC FDFD method, we introduce a complex-valued adaptive-coefficient (CVAC) FDFD method for the DVW equation. The CVAC FDFD method is constructed by incorporating correction terms into the conventional second-order FDFD method. The adaptive coefficients are related to the spatial sampling ratio, number of spatial grid points per wavelength, and diffusive and viscous attenuation coefficients in the DVW equation. Numerical dispersion and attenuation analysis confirm that, with a maximum dispersion error of 1% and a maximum attenuation error of 10%, the CVAC FDFD method only necessitates 2.5 spatial grid points per wavelength. Compared with the RVAC FDFD method, the CVAC FDFD method exhibits enhanced capability in suppressing the numerical attenuation during anelastic wavefield modeling. To validate the accuracy of our method, we develop an analytical solution for the DVW equation in a homogeneous medium. Three numerical examples substantiate the high accuracy of the CVAC FDFD method when using a small number of spatial grid points per wavelength, and this method demands computational time and computer memory similar to those required by the conventional second-order FDFD method. A fluid-saturated model featuring various layer thicknesses is used to characterize the propagation characteristics of DVW.
- Geophysics > Seismic Surveying > Seismic Processing (1.00)
- Geophysics > Seismic Surveying > Seismic Modeling > Velocity Modeling > Seismic Inversion (0.93)
- Geophysics > Seismic Surveying > Seismic Interpretation (0.93)
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We are on the verge of a second quantum revolution, building on the one that occurred in the last century. The first revolution involved manipulating groups of quantum particles like electrons and photons, which led to the development of technologies such as transistors and lasers that completely transformed the world. The second revolution, which began in the 1980s and has gained momentum in recent years, is expected to be even more transformative. It involves manipulating individual quantum particles and utilizing the quantum phenomena of superposition, entanglement, and interference. This leads to the development of three new technologies: quantum computing, quantum communications, and quantum sensing.
Quantum computing involves specialized computers that solve mathematical problems and run quantum models that are quantum theory principles. This powerful technology allows data scientists to build models related to complex processes such as molecular formations, photosynthesis, and superconductivity. Information is processed differently from regular computers, transferring data using qubits (quantum bits) rather than in binary form. Qubits are vital in terms of delivering exponential computational power in quantum computing as they can remain in superposition, explained in the full article. Using a wide range of algorithms, quantum computers can measure and observe vast amounts of data.
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The CO2 Storage Resources Management System (SRMS) provides a classification and categorization system that reflects geologic certainty and project maturity of storable quantities. This short course explains the classes used to indicate the level of project maturity, which is indicative of data available for the assessment. The Storage Capacity indicates the highest level of project maturity, while Prospective Storage Resources is the class for undiscovered storage resources, with the lowest level of project maturity. The categories indicate geologic certainty, e.g. The course includes discussions of commercial evaluation of storage projects and estimating CO2 storable quantities, with examples.
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- North America > United States > Texas > Permian Basin > Yates Formation (0.99)
- North America > United States > Texas > Permian Basin > Wolfcamp Formation (0.99)
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In July 2017, the SPE Board approved the CO2 Storage Resources Management System (SRMS). The document, written by a subcommittee of the Carbon Dioxide Capture, Utilization and Storage Technical Section (CCUS), establishes technically-based capacity and resources evaluation standards. The new SRMS Guidelines, released in July 2022, is now available and includes suggestions for the application of the SRMS with the intent of including details of the processes of quantification, categorization, and classification of storable quantities so that the subjective nature of subsurface assessments can be consistent between storage resource assessors. Purchase SRMS Guidelines for Applications of the CO2 Storage (for individual use only) Purchase Corporate or Institutional annual license to the SRMS and SRMS Guidelines (This license grants license to use the SRMS and SRMS Guidelines for commercial purposes which enables employees of the Licensee globally to lawfully reproduce and distribute content, in print or electronic format, as needed within Licensee's company.) Would you like to be kept informed about new publications and activities related to this topic?
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- Facilities Design, Construction and Operation > Unconventional Production Facilities > CO2 capture and management (1.00)
Sven Treitel is a German born Argentinan American geophysicist, who, with Enders Robinson was instrumental in the transition of exploration geophysics from analog to digital recording and data processing. Early in the technological timetable of their profession, geophysicists laboriously tracked peaks and valleys on photographic paper - data processing vis-à-vis interpretation. Today, such operations minus digital computers would appear self-contradictory.[3] The turning point occurred in the mid-1960s, when geophysical companies began the gradual conversion from analog to digital systems, thus becoming, in fact, the first industry to successfully make widespread use of digital technology in its infancy and now one of the most computer-intensive of all. It was in academia, however, at the Massachusetts Institute of Technology, that a need for digitization of analog signals first arose in exploring the possible application of statistical methods of time series analysis to seismic data processing.
Computer software, or simply software, is a collection of data or computer instructions that tell the computer how to work. This is in contrast to physical hardware, from which the system is built and actually performs the work. In computer science and software engineering, computer software is all information processed by computer systems, programs and data. Computer software includes computer programs, libraries and related non-executable data, such as online documentation or digital media. Computer hardware and software require each other and neither can be realistically used on its own.
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- Information Technology > Software > Programming Languages (0.36)
S. Rutt Bridges is the founder of Advance Geophysics, the developer of the popular seismic data processing software packages MicroMAX and ProMAX, for which the SEG honored him with the Cecil Green Enterprise Award in 1991. Rutt was the 1997-1998 SEG President. Rutt Bridges is receiving Honorary Membership for his distinguished contributions to the advancement of the profession through service to the Society and for his distinguished contributions to exploration geophysics. Rutt has served as SEG President, Denver Geophysical Society president, and in a significant capacity on other SEG committees. He organized the 1989 symposium "The Future of Desktop Computers in Geophysics" and was Technical Program Chairman for SEG's 1989 Midwest Meeting.
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