scholarly journals Research on 3D SIP Conjugate Gradient Inversion Algorithm with Parameter Range Constraints

2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Jianjun Xi ◽  
Yongliang Liu ◽  
Dandan Cui
Keyword(s):  
Electromagnetic Field ◽  
Conjugate Gradient ◽  
High Speed ◽  
Forward Modeling ◽  
Parameter Range ◽  
Analytic Approximation ◽  
Primary Field ◽  
Inversion Algorithm ◽  
Multiple Parameters ◽  
Speed And Accuracy

3D SIP inversion algorithm involves multiple parameters, and the key is the calculating speed and memory. A whole set of quasi-linear (QL) theories has taken shape in recent years, including the QL approximation method proposed by Zhdanov, quasi-analytic approximation, and localized quasi-linear (LQL) approximation. They are characterized by high speed and accuracy in electromagnetic field numerical modeling. The above-based 3D QL inversion algorithm, boasting quicker calculating speed plus more stable and favorable inversion effect, has been adopted profoundly in electromagnetic prospecting, whereas its frequent source conversion requires recalculating the dyadic Green’s function and primary field each time, thus delaying the 3D SIP modeling speed. This study makes use of the spatial symmetry in the primary field and Green function to propose an effective and quicker QL forward modeling method, which has the hallmark of higher calculating speed owing to less calculating times, and makes feasible the 3D SIP conjugate gradient inversion algorithm with Cole–Cole parameter range constraints.

scholarly journals A New Method to Verify the Measurement Speed and Accuracy of Frequency Modulated Interferometers

2021 ◽  
Vol 11 (13) ◽  
pp. 5787
Author(s):  
Toan-Thang Vu ◽  
Thanh-Tung Vu ◽  
Van-Doanh Tran ◽  
Thanh-Dong Nguyen ◽  
Ngoc-Tam Bui
Keyword(s):  
Phase Change ◽  
High Speed ◽  
Measurement Accuracy ◽  
Slow Motion ◽  
New Method ◽  
Virtual Displacement ◽  
Electro Optic ◽  
Lock In ◽  
Speed And Accuracy ◽  
Electro Optic Modulator

The measurement speed and measurement accuracy of a displacement measuring interferometer are key parameters. To verify these parameters, a fast and high-accuracy motion is required. However, the displacement induced by a mechanical actuator generates disadvantageous features, such as slow motion, hysteresis, distortion, and vibration. This paper proposes a new method for a nonmechanical high-speed motion using an electro-optic modulator (EOM). The method is based on the principle that all displacement measuring interferometers measure the phase change to calculate the displacement. This means that the EOM can be used to accurately generate phase change rather than a mechanical actuator. The proposed method is then validated by placing the EOM into an arm of a frequency modulation interferometer. By using two lock-in amplifiers, the phase change in an EOM and, hence, the corresponding virtual displacement could be measured by the interferometer. The measurement showed that the system could achieve a displacement at 20 kHz, a speed of 6.08 mm/s, and a displacement noise level < 100 pm//√Hz above 2 kHz. The proposed virtual displacement can be applied to determine both the measurement speed and accuracy of displacement measuring interferometers, such as homodyne interferometers, heterodyne interferometers, and frequency modulated interferometers.

Fast 3D magnetic inversion of a surface relief in the space domain

Geophysics ◽  
2019 ◽  
Vol 84 (5) ◽  
pp. J57-J67 ◽  
Author(s):  
Marlon C. Hidalgo-Gato ◽  
Valéria C. F. Barbosa
Keyword(s):  
Hessian Matrix ◽  
Computational Cost ◽  
Magnetization Vector ◽  
Forward Modeling ◽  
Magnetic Data ◽  
Total Field ◽  
Inversion Algorithm ◽  
Sensitivity Matrix ◽  
Magnetic Inversion ◽  
Magnetic Basement

We have developed a fast 3D regularized magnetic inversion algorithm for depth-to-basement estimation based on an efficient way to compute the total-field anomaly produced by an arbitrary interface separating nonmagnetic sediments from a magnetic basement. We approximate the basement layer by a grid of 3D vertical prisms juxtaposed in the horizontal directions, in which the prisms’ tops represent the depths to the magnetic basement. To compute the total-field anomaly produced by the basement relief, the 3D integral of the total-field anomaly of a prism is simplified by a 1D integral along the prism thickness, which in turn is multiplied by the horizontal area of the prism. The 1D integral is calculated numerically using the Gauss-Legendre quadrature produced by dipoles located along the vertical axis passing through the prism center. This new magnetic forward modeling overcomes one of the main drawbacks of the nonlinear inverse problem for estimating the basement depths from magnetic data: the intense computational cost to calculate the total-field anomaly of prisms. The new sensitivity matrix is simpler and computationally faster than the one using classic magnetic forward modeling based on the 3D integrals of a set of prisms that parameterize the earth’s subsurface. To speed up the inversion at each iteration, we used the Gauss-Newton approximation for the Hessian matrix keeping the main diagonal only and adding the first-order Tikhonov regularization function. The large sparseness of the Hessian matrix allows us to construct and solve a linear system iteratively that is faster and demands less memory than the classic nonlinear inversion with prism-based modeling using 3D integrals. We successfully inverted the total-field anomaly of a simulated smoothing basement relief with a constant magnetization vector. Tests on field data from a portion of the Pará-Maranhão Basin, Brazil, retrieved a first depth-to-basement estimate that was geologically plausible.

Frequency‐domain acoustic‐wave modeling and inversion of crosshole data: Part II—Inversion method, synthetic experiments and real‐data results

Geophysics ◽  
1995 ◽  
Vol 60 (3) ◽  
pp. 796-809 ◽  
Author(s):  
Zhong‐Min Song ◽  
Paul R. Williamson ◽  
R. Gerhard Pratt
Keyword(s):  
Frequency Domain ◽  
Real Data ◽  
Forward Modeling ◽  
Two Dimensions ◽  
Inversion Method ◽  
Inversion Algorithm ◽  
Data Set ◽  
Wave Inversion ◽  
Full Wave ◽  
And Inversion

In full‐wave inversion of seismic data in complex media it is desirable to use finite differences or finite elements for the forward modeling, but such methods are still prohibitively expensive when implemented in 3-D. Full‐wave 2-D inversion schemes are of limited utility even in 2-D media because they do not model 3-D dynamics correctly. Many seismic experiments effectively assume that the geology varies in two dimensions only but generate 3-D (point source) wavefields; that is, they are “two‐and‐one‐half‐dimensional” (2.5-D), and this configuration can be exploited to model 3-D propagation efficiently in such media. We propose a frequency domain full‐wave inversion algorithm which uses a 2.5-D finite difference forward modeling method. The calculated seismogram can be compared directly with real data, which allows the inversion to be iterated. We use a descents‐related method to minimize a least‐squares measure of the wavefield mismatch at the receivers. The acute nonlinearity caused by phase‐wrapping, which corresponds to time‐domain cycle‐skipping, is avoided by the strategy of either starting the inversion using a low frequency component of the data or constructing a starting model using traveltime tomography. The inversion proceeds by stages at successively higher frequencies across the observed bandwidth. The frequency domain is particularly efficient for crosshole configurations and also allows easy incorporation of attenuation, via complex velocities, in both forward modeling and inversion. This also requires the introduction of complex source amplitudes into the inversion as additional unknowns. Synthetic studies show that the iterative scheme enables us to achieve the theoretical maximum resolution for the velocity reconstruction and that strongly attenuative zones can be recovered with reasonable accuracy. Preliminary results from the application of the method to a real data set are also encouraging.

Nonlinear Vibration and Bifurcation Analysis for Rotor-Seal-Bearing Systems of Centrifugal Compressors

2007 ◽  
Author(s):  
Yuefang Wang ◽  
Yong Li ◽  
Yong Zhang ◽  
Xiaoyan Wang
Keyword(s):  
High Speed ◽  
Labyrinth Seal ◽  
Journal Bearings ◽  
Coupling Vibration ◽  
Oil Film ◽  
Disc Center ◽  
Multiple Parameters ◽  
Jeffcott Rotor ◽  
Vibration Responses ◽  
The One

This paper presents the nonlinear coupling vibration and bifurcation of a high-speed centrifugal compressor with a labyrinth seal and two journal bearings. The rotor system is modeled as a Jeffcott rotor. The Muszynska’s model is used to express the seal force with multiple parameters. For the journal bearings, the model proposed by Zhang is adopted to express the excitation of unsteady oil-film force. The Runge-Kutta method is used to determine the vibration responses at the disc center and the two bearings. With parameters of rotation speed and pressure difference of the seal, bifurcation diagrams are presented to demonstrate the complexity in the rotor motions. Multiple periodic bifurcations are pointed out using two seal pressure differences. The intricate bifurcation behavior shows inherent interactions between forces of oil-film and seal, which reflect much more complicated rotor dynamics than the one with either of the excitations alone.

Real time quasi–2-D inversion of array resistivity logging data using neural network

Geophysics ◽  
2002 ◽  
Vol 67 (2) ◽  
pp. 517-524 ◽  
Author(s):  
Zhiyi Zhang ◽  
Zhiqiang Zhou
Keyword(s):  
Neural Network ◽  
Real Time ◽  
Forward Modeling ◽  
Time Inversion ◽  
Resistivity Structure ◽  
Inversion Algorithm ◽  
Neural Network Simulation ◽  
Formation Resistivity ◽  
Resistivity Logging ◽  
Fast Inversion

We present a quasi-2-D real-time inversion algorithm for a modern galvanic array tool via dimensional reduction and neural network simulation. Using reciprocity and superposition, we apply a numerical focusing technique to the unfocused data. The numerically focused data are much less subject to 2-D and layering effects and can be approximated as from a cylindrical 1-D earth. We then perform 1-D inversion on the focused data to provide approximate information about the 2-D resistivity structure. A neural network is used to perform forward modeling in the 1-D inversion, which is several hundred times faster than conventional numerical forward solutions. Testing our inversion algorithm on both synthetic and field data shows that this fast inversion algorithm is useful for providing formation resistivity information at a well site.

Normal Voice Production: Computation of Driving Parameters from Endoscopic Digital High Speed Images

2003 ◽  
Vol 42 (03) ◽  
pp. 271-276 ◽  
Author(s):  
T. Braunschweig ◽  
J. Lohscheller ◽  
U. Eysholdt ◽  
U. Hoppe ◽  
M. Döllinger
Keyword(s):  
Vocal Fold ◽  
High Speed ◽  
Biomechanical Model ◽  
Vocal Folds ◽  
Inversion Algorithm ◽  
Knowledge Based ◽  
Normal Voice ◽  
Inversion Procedure ◽  
High Speed Glottography

Summary Objectives: A central point for quantitative evaluation of pathological and healthy voices is the analysis of vocal fold oscillations. By means of digital High Speed Glottography (HGG), vocal fold oscillations can be recorded in real time. Recently, a numerical inversion procedure was developed that allows the extraction of physiological parameters from digital high speed videos and a classification of voice disorders. The aim of this work was to validate the inversion procedure and to investigate the applicability to normal voices. Methods: High speed recordings were performed during phonation within a group of five female and five male persons with normal voices. By using knowledge based image processing algorithms, motion curves of the vocal folds were extracted at three different positions (dorsal, medial, ventral). These curves were used to obtain physiological voice parameters, and in particular the degree of symmetry of the vocal folds based upon a biomechanical model of the vocal folds. Results: The highest degree of symmetry was observed for the medial motion curves. While the dor-sally and ventrally extracted motion curves exhibited similar results concerning the degree of symmetry the performance of the algorithm was less stable. Conclusions: The inversion algorithm provides reasonable results for all subjects when applied to the medial motion curves. However, for dorsal and ventral motion curves, correct performance is reduced to 85 %.

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