scholarly journals FORWARD MODELLING METODE GAYABERAT DENGAN MODEL INTRUSI DAN PATAHAN MENGGUNAKAN OCTAVE

2020 ◽  
Vol 4 (2) ◽  
pp. 111-117
Author(s):  
Muhammad Nurul ◽  
Syamsurijal Rasimeng ◽  
Ida Bagus Suananda Yogi ◽  
Aprillia Yulianata ◽  
Aisah Yuliantina
Keyword(s):  
Synthetic Data ◽  
Vertical Component ◽  
Model Parameters ◽  
Attraction Force ◽  
Distance Curve ◽  
Rock Density ◽  
The Earth ◽  
Fracture Modeling ◽  
Fracture Models ◽  
Acceleration Of Gravity

The gravity method is a geophysical exploration method to measure variations in the acceleration of gravity on the surface of the earth in response to variations in rocks that exist beneath the surface. In gravity exploration requires a preliminary picture as a reference for measurement. This study aims to make forward modeling synthetic OCTAVE based using synthetic data on subsurface rock structures, so as to produce intrusion and fracture models based on differences in the value of the acceleration of gravity from one point to another on the surface of the earth. Synthetic modeling with the geological parameter approach of the study area is based on variations in the price of rock density. The model parameters used in intrusion modeling are the density value of 2.7 g/cm3 and the depth of 850 meters while the fracture modeling uses a density value of 2.7 g/cm3 with a depth of 350 meters and 360 meters and a thickness of 500 meters. From intrusion modeling, the gravity vertical component of attraction force is 0.03 mGal and in the fracture modeling the gravity vertical component of attraction force is 0.0565 mGal. Based on the results of this modeling, distance curve vs. gravity anomaly response is obtained for both cases. In the intrusion rock model obtained by the profile model with an open type down. While the fracture modeling is obtained anomalous profile curve variation which states that in the fracture area with a significant change in the direction of the curve.

scholarly journals A flexible framework for sequential estimation of model parameters in computational hemodynamics

2020 ◽  
Vol 7 (1) ◽  
Author(s):  
Christopher J. Arthurs ◽  
Nan Xiao ◽  
Philippe Moireau ◽  
Tobias Schaeffter ◽  
C. Alberto Figueroa
Keyword(s):  
Unscented Kalman Filter ◽  
Three Dimensional ◽  
Synthetic Data ◽  
Sequential Estimation ◽  
Wall Material ◽  
Patient Specific ◽  
Model Parameters ◽  
Computational Framework ◽  
Lumped Parameter ◽  
Estimation Of Model Parameters

AbstractA major challenge in constructing three dimensional patient specific hemodynamic models is the calibration of model parameters to match patient data on flow, pressure, wall motion, etc. acquired in the clinic. Current workflows are manual and time-consuming. This work presents a flexible computational framework for model parameter estimation in cardiovascular flows that relies on the following fundamental contributions. (i) A Reduced-Order Unscented Kalman Filter (ROUKF) model for data assimilation for wall material and simple lumped parameter network (LPN) boundary condition model parameters. (ii) A constrained least squares augmentation (ROUKF-CLS) for more complex LPNs. (iii) A “Netlist” implementation, supporting easy filtering of parameters in such complex LPNs. The ROUKF algorithm is demonstrated using non-invasive patient-specific data on anatomy, flow and pressure from a healthy volunteer. The ROUKF-CLS algorithm is demonstrated using synthetic data on a coronary LPN. The methods described in this paper have been implemented as part of the CRIMSON hemodynamics software package.

scholarly journals Sequential modelling of the Earth’s core magnetic field

2020 ◽  
Vol 72 (1) ◽  
Author(s):  
Guillaume Ropp ◽  
Vincent Lesur ◽  
Julien Baerenzung ◽  
Matthias Holschneider
Keyword(s):  
Magnetic Field ◽  
Prior Information ◽  
Spatial Scales ◽  
Model Parameters ◽  
International Geomagnetic Reference Field ◽  
The Earth ◽  
Temporal And Spatial ◽  
Different Sources ◽  
Original Approach ◽  
Modelling Approach

Abstract We describe a new, original approach to the modelling of the Earth’s magnetic field. The overall objective of this study is to reliably render fast variations of the core field and its secular variation. This method combines a sequential modelling approach, a Kalman filter, and a correlation-based modelling step. Sources that most significantly contribute to the field measured at the surface of the Earth are modelled. Their separation is based on strong prior information on their spatial and temporal behaviours. We obtain a time series of model distributions which display behaviours similar to those of recent models based on more classic approaches, particularly at large temporal and spatial scales. Interesting new features and periodicities are visible in our models at smaller time and spatial scales. An important aspect of our method is to yield reliable error bars for all model parameters. These errors, however, are only as reliable as the description of the different sources and the prior information used are realistic. Finally, we used a slightly different version of our method to produce candidate models for the thirteenth edition of the International Geomagnetic Reference Field.

Single-station SVD-based polarization filtering of ground roll: Perfection and investigation of limitations and pitfalls

Geophysics ◽  
2012 ◽  
Vol 77 (2) ◽  
pp. V41-V59 ◽  
Author(s):  
Olena Tiapkina ◽  
Martin Landrø ◽  
Yuriy Tyapkin ◽  
Brian Link
Keyword(s):  
Time Window ◽  
Synthetic Data ◽  
Vertical Component ◽  
Horizontal Component ◽  
Frequency Bandwidth ◽  
Polarization Filter ◽  
Data Set ◽  
Single Station ◽  
Ground Roll ◽  
Polarization Filtering

The advent of single receiver point, multi-component geophones has necessitated that ground roll be removed in the processing flow rather than through acquisition design. A wide class of processing methods for ground-roll elimination is polarization filtering. A number of these methods use singular value decomposition (SVD) or some related transformations. We focus on a single-station SVD-based polarization filter that we consider to be one of the best in the industry. The method is comprised of two stages: (1) ground-roll detection and (2) ground-roll estimation and filtering. To detect the ground roll, a special attribute dependent on the singular values of a three-column matrix formed by a sliding time window is used. The ground roll is approximated and subtracted using the first two eigenimages of this matrix. To limit the possible damage to the signal, the filter operates within the record intervals where the ground roll is detected and within the ground-roll frequency bandwidth only. We improve the ground-roll detector to make it theoretically insensitive to ambient noise and more sensitive to the presence of ground roll. The advantage of the new detector is demonstrated on synthetic and field data sets. We estimate theoretically and with synthetic data the attenuation of the underlying reflections that can be caused by the polarization filter. We show that the underlying signal always loses almost all the energy on the vertical component and on the horizontal component in the ground-roll propagation plane and within the ground-roll frequency bandwidth. The only signal component, if it exists, that can retain a significant part of its energy is the horizontal component orthogonal to the above plane. When 2D 3C field operations are conducted, the signal particle motion can deviate from the ground-roll propagation plane and can therefore retain some of its energy due to a set of offline reflections. In the case of 3D 3C seismic surveys, the reflected signal always deviates from the ground-roll propagation plane on the receiver lines that do not contain the source. This is confirmed with a 2.5D 3C synthetic data set. We discuss when the ability of the filter to effectively subtract the ground roll may, or may not, allow us to ignore the inevitable harm that is done to the underlying reflected waves.

A search for constraints on lithospheric net rotation in 2D convection simulations

2021 ◽  
Author(s):  
Suzanne Atkins ◽  
Nicolas Coltice
Keyword(s):  
Reference Frames ◽  
Plate Motion ◽  
Model Parameters ◽  
Motion Model ◽  
Motion Models ◽  
The Third ◽  
The Earth ◽  
Geological Past ◽  
Wide Range ◽  
Third Dimension

<p>Net rotation is the process whereby the entire lithosphere can rotate with respect to the Earth’s mantle. The plates and continents retain their location with respect to each other, but they change their position with respect to global reference frames such as the Earth’s magnetic dipole, and structures in the Earth’s mantle such as plumes and hotspots. Constraining lithospheric net rotation is therefore one factor in building an absolute plate motion model. However, the amount of net rotation occurring at present day is poorly contained, and the drivers of net rotation are very poorly understood. Many absolute plate motion models therefore attempt to minimise net rotation, because there is no way to constrain rotation in the geological past. </p><p> </p><p>In previous geodynamical studies, the presence of thick continents and large viscosity contrasts were found to be controlling factors in the development of net rotation. We investigate the effects of different convection parameters and tectonic states on the magnitude and evolution of net rotation in 2D simulations. The use of 2D simulations allows us to run enough simulations to study a wide range of model parameters. We intend to compare our 2D conclusions with 3D simulations, to investigate how much of a difference the third dimension makes.</p><p> </p><p>We find that net rotation varies on much shorter timescales than any other geodynamic feature. Net rotation is not cleanly correlated with any tectonic behaviours or settings, and that the magnitude and duration is unpredictable. We do however find that the distribution of net rotation within the lifetime of a particular simulation is Gaussian, with standard deviation dependent on the viscosity structure and contrasts of the simulation, in agreement with previous studies. However, in contrast to previous studies, the presence and thickness of continents makes very little difference to the speed of lithospheric rotation, although this may be because we are working in 2D. If the 2D results are also relevant in 3D, net rotation is a continuously varying and unpredictable value, but with a predictable statistical range. This may provide a way to better constrain net rotation for plate motion models.</p>

Modeling the crashes count using finite mixture models

2019 ◽  
Vol 7 (1) ◽  
pp. 13-27
Author(s):  
Safaa K. Kadhem ◽  
Sadeq A. Kadhim
Keyword(s):  
Bayesian Inference ◽  
Mixture Models ◽  
Gibbs Sampler ◽  
Simulation Study ◽  
Finite Mixture Models ◽  
Synthetic Data ◽  
Finite Mixture Model ◽  
Finite Mixture ◽  
Model Parameters ◽  
Mcmc Method

"This paper aims at the modeling the crashes count in Al Muthanna governance using finite mixture model. We use one of the most common MCMC method which is called the Gibbs sampler to implement the Bayesian inference for estimating the model parameters. We perform a simulation study, based on synthetic data, to check the ability of the sampler to find the best estimates of the model. We use the two well-known criteria, which are the AIC and BIC, to determine the best model fitted to the data. Finally, we apply our sampler to model the crashes count in Al Muthanna governance.

A new method for absolute underground positioning based on transient electromagnetics

2019 ◽  
Vol 221 (1) ◽  
pp. 87-96
Author(s):  
S Malecki ◽  
R-U Börner ◽  
K Spitzer
Keyword(s):  
Field Data ◽  
Synthetic Data ◽  
Trust Region ◽  
Trust Region Algorithm ◽  
Location Data ◽  
The Earth ◽  
Time Regime ◽  
Em Method ◽  
Em Field ◽  
Confidence Ellipses

SUMMARY We present a procedure for localizing underground positions using a time-domain inductive electromagnetic (EM) method. The position to be localized is associated with an EM receiver placed inside the Earth. An EM field is generated by one or more transmitters located at known positions at the Earth’s surface. We then invert the EM field data for the receiver positions using a trust-region algorithm. For any given time regime and source–receiver geometry, the propagation of the electromagnetic fields is determined by the electrical conductivity distribution within the Earth. We show that it is sufficient to use a simple 1-D model to recover the receiver positions with reasonable accuracy. Generally, we demonstrate the robustness of the presented approach. Using confidence ellipses and confidence intervals we assess the accuracy of the recovered location data. The proposed method has been extensively tested against synthetic data obtained by numerical experiments. Furthermore, we have successfully carried out a location recovery using field data. The field data were recorded within a borehole in Alberta (Canada) at 101.4 m depth. The recovered location of the borehole receiver differs from the actual location by 0.70 m in the horizontal plane and by 0.82 m in depth.

Robust Empirical Time–Frequency Relations for Seismic Spectral Amplitudes, Part 1: Application to Regional S Waves in Southeastern Iran

2020 ◽  
Author(s):  
Maryam Safarshahi ◽  
Igor B. Morozov
Keyword(s):  
Seismic Waves ◽  
Joint Inversion ◽  
Vertical Component ◽  
Transverse Component ◽  
Model Parameters ◽  
S Wave ◽  
Near Surface ◽  
S Waves ◽  
Time Frequency ◽  
Frequency Independent

ABSTRACT Empirical models of geometrical-, Q-, t-star, and kappa-type attenuation of seismic waves and ground-motion prediction equations (GMPEs) are viewed as cases of a common empirical standard model describing variation of wave amplitudes with time and frequency. Compared with existing parametric and nonparametric approaches, several new features are included in this model: (1) flexible empirical parameterization with possible nonmonotonous time or distance dependencies; (2) joint inversion for time or distance and frequency dependencies, source spectra, site responses, kappas, and Q; (3) additional constraints removing spurious correlations of model parameters and data residuals with source–receiver distances and frequencies; (4) possible kappa terms for sources as well as for receivers; (5) orientation-independent horizontal- and three-component amplitudes; and (6) adaptive filtering to reduce noise effects. The approach is applied to local and regional S-wave amplitudes in southeastern Iran. Comparisons with previous studies show that conventional attenuation models often contain method-specific biases caused by limited parameterizations of frequency-independent amplitude decays and assumptions about the models, such as smoothness of amplitude variations. Without such assumptions, the frequency-independent spreading of S waves is much faster than inferred by conventional modeling. For example, transverse-component amplitudes decrease with travel time t as about t−1.8 at distances closer than 90 km and as t−2.5 beyond 115 km. The rapid amplitude decay at larger distances could be caused by scattering within the near surface. From about 90 to 115 km distances, the amplitude increases by a factor of about 3, which could be due to reflections from the Moho and within the crust. With more accurate geometrical-spreading and kappa models, the Q factor for the study area is frequency independent and exceeds 2000. The frequency-independent and Q-type attenuation for vertical-component and multicomponent amplitudes is somewhat weaker than for the horizontal components. These observations appear to be general and likely apply to other areas.

scholarly journals Spatial and Seasonal Variations and Inter-Relationship in Fitted Model Parameters for Rainfall Totals across Australia at Various Timescales

Climate ◽  
2019 ◽  
Vol 7 (1) ◽  
pp. 4 ◽  
Author(s):  
Md Masud Hasan ◽  
Barry F. W. Croke ◽  
Fazlul Karim
Keyword(s):  
Probabilistic Models ◽  
Dispersion Model ◽  
Synthetic Data ◽  
Daily Rainfall ◽  
Seasonal Rainfall ◽  
Model Parameters ◽  
Exponential Dispersion Model ◽  
Gamma Distributions ◽  
Using Data ◽  
Combined Data

Probabilistic models are useful tools in understanding rainfall characteristics, generating synthetic data and predicting future events. This study describes the results from an analysis on comparing the probabilistic nature of daily, monthly and seasonal rainfall totals using data from 1327 rainfall stations across Australia. The main objective of this research is to develop a relationship between parameters obtained from models fitted to daily, monthly and seasonal rainfall totals. The study also examined the possibility of estimating the parameters for daily data using fitted parameters to monthly rainfall. Three distributions within the Exponential Dispersion Model (EDM) family (Normal, Gamma and Poisson-Gamma) were found to be optimal for modelling the daily, monthly and seasonal rainfall total. Within the EDM family, Poisson-Gamma distributions were found optimal in most cases, whereas the normal distribution was rarely optimal except for the stations from the wet region. Results showed large differences between regional and seasonal ϕ-index values (dispersion parameter), indicating the necessity of fitting separate models for each season. However, strong correlations were found between the parameters of combined data and those derived from individual seasons (0.70–0.81). This indicates the possibility of estimating parameters of individual season from the parameters of combined data. Such relationship has also been noticed for the parameters obtained through monthly and daily models. Findings of this research could be useful in understanding the probabilistic features of daily, monthly and seasonal rainfall and generating daily rainfall from monthly data for rainfall stations elsewhere.

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