Joint inversion of gravity and gravity gradient data: A systematic evaluation

Geophysics ◽  
2021 ◽  
pp. 1-93
Author(s):  
Joseph Capriotti ◽  
Yaoguo Li
Keyword(s):  
Noise Level ◽  
Joint Inversion ◽  
Low Noise ◽  
Systematic Evaluation ◽  
Gravity Gradient ◽  
Gravity Inversion ◽  
Data Sets ◽  
Noise Levels ◽  
Data Set ◽  
Test Range

Gravity and gravity gradiometry measurements are commonly used to map density variations in the subsurface. Gravity measurements can characterize gravitational anomalies at both long and short wavelengths effectively, but the cost of collecting a sufficiently spatially dense survey to characterize the short wavelengths can be prohibitive. Gravity gradient data can be quickly collected with short wavelength information at a low noise level, but have decreasing sensitivity to longer wavelengths. We describe a method to jointly invert gravity and gravity gradient data that takes advantage of the differing frequency contents and noise levels of the two methods to create an improved image of the subsurface. Previous work simply treated the inversion as a multiple component gravity inversion, however this can cause unintended errors in the recovered models because each data set is not guaranteed to be fit within its noise level. Our joint inversion methodology ensures that both the gravity and gravity gradient data sets are fit to within their individual noise levels by incorporating a relative weighting parameter, and we describe how to find that parameter. This method can also be used to create an improved broadband gravity anomaly map that has a reduced noise level at long wavelengths using a joint equivalent source reconstruction. We first build a synthetic model using a Minecraft world editor, that has different wavelength anomalies, and show the improvement with joint inversion. These results are also confirmed using a real world example at the R. J. Smith test range in Kauring, Australia.

A Bayesian approach to modeling 2D gravity data using polygons

Geophysics ◽  
2017 ◽  
Vol 82 (1) ◽  
pp. G1-G21 ◽  
Author(s):  
William J. Titus ◽  
Sarah J. Titus ◽  
Joshua R. Davis
Keyword(s):  
Gravity Data ◽  
Synthetic Data ◽  
Gravity Inversion ◽  
Limiting Factor ◽  
Data Sets ◽  
Data Set ◽  
Local Optima ◽  
Occupancy Probability ◽  
Compute Model ◽  
Parameter Values

We apply a Bayesian Markov chain Monte Carlo formalism to the gravity inversion of a single localized 2D subsurface object. The object is modeled as a polygon described by five parameters: the number of vertices, a density contrast, a shape-limiting factor, and the width and depth of an encompassing container. We first constrain these parameters with an interactive forward model and explicit geologic information. Then, we generate an approximate probability distribution of polygons for a given set of parameter values. From these, we determine statistical distributions such as the variance between the observed and model fields, the area, the center of area, and the occupancy probability (the probability that a spatial point lies within the subsurface object). We introduce replica exchange to mitigate trapping in local optima and to compute model probabilities and their uncertainties. We apply our techniques to synthetic data sets and a natural data set collected across the Rio Grande Gorge Bridge in New Mexico. On the basis of our examples, we find that the occupancy probability is useful in visualizing the results, giving a “hazy” cross section of the object. We also find that the role of the container is important in making predictions about the subsurface object.

scholarly journals Analysis of Skid Resistance and Noise Characteristics for Varieties of Concrete Pavement

2020 ◽  
Vol 2020 ◽  
pp. 1-8
Author(s):  
Jinmiao Fang ◽  
Jinsong Tu ◽  
Kunming Wu
Keyword(s):  
Noise Level ◽  
Evaluation Criteria ◽  
Sound Intensity ◽  
Low Noise ◽  
Concrete Pavement ◽  
Skid Resistance ◽  
Concrete Pavements ◽  
Noise Levels ◽  
Cement Concrete ◽  
Noise Characteristics

To establish evaluation criteria for the pavement skid resistance and noise level in tunnels pavements, the zoning and control standards for skid resistance and concrete pavement noise were examined. Transverse friction coefficient (TFC) test equipment and the on-board sound intensity (OBSI) method were used to evaluate the antisliding characteristics and noise levels of several tunnel pavements. The results indicated poor antisliding characteristics and noise levels in ordinary grooved cement concrete pavement, whereas new types of cement concrete pavements, such as exposed concrete pavements and polymer-modified cement concrete pavements, had good antisliding characteristics and achieved low noise levels. Combined with the cluster analysis method, a zoning method for the antisliding and noise level in concrete pavement is proposed. The antisliding characteristics and noise levels of the pavement are divided into three zones. To ensure safety and comfort during driving, the antisliding value (SFC) of the tunnel pavement should be more than 50, and the noise level should not exceed 105 dB. Finally, the correlation between the antisliding and noise levels for pavement was analyzed. The results indicated that the antiskiding value of pavement has a strong correlation to the noise level.

scholarly journals Application of Artificial Neural Network for Image Noise Level Estimation in the SVD domain

Electronics ◽  
2019 ◽  
Vol 8 (2) ◽  
pp. 163 ◽  
Author(s):  
Emir Turajlic ◽  
Alen Begović ◽  
Namir Škaljo
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Noise Level ◽  
Low Noise ◽  
Singular Value ◽  
Fine Tuning ◽  
Noise Levels ◽  
Noise Level Estimation ◽  
Artificial Neural ◽  
Block Based

The blind additive white Gaussian noise level estimation is an important and a challenging area of digital image processing with numerous applications including image denoising and image segmentation. In this paper, a novel block-based noise level estimation algorithm is proposed. The algorithm relies on the artificial neural network to perform a complex image patch analysis in the singular value decomposition (SVD) domain and to evaluate noise level estimates. The algorithm exhibits the capacity to adjust the effective singular value tail length with respect to the observed noise levels. The results of comparative analysis show that the proposed ANN-based algorithm outperforms the alternative single stage block-based noise level estimating algorithm in the SVD domain in terms of mean square error (MSE) and average error for all considered choices of block size. The most significant improvements in MSE levels are obtained at low noise levels. For some test images, such as “Car” and “Girlface”, at σ = 1 , these improvements can be as high as 99% and 98.5%, respectively. In addition, the proposed algorithm eliminates the error-prone manual parameter fine-tuning and automates the entire noise level estimation process.

Paper 16: A Study of Tractor Noise Control

1969 ◽  
Vol 184 (17) ◽  
pp. 149-169
Author(s):  
J. Matthews ◽  
J. D. C. Talamo
Keyword(s):  
Hearing Loss ◽  
Diesel Engine ◽  
Noise Reduction ◽  
Noise Level ◽  
Exhaust System ◽  
Low Noise ◽  
Acoustic Features ◽  
Noise Levels ◽  
Engine Design ◽  
High Incidence

A high incidence of hearing loss has been encountered among tractor drivers, and noise levels are shown to be further increased by the addition of cabs, particularly those which are structurally strong to resist crushing if the vehicle overturns. Some reductions in the noise level of the operator's environment can be obtained by covering the engine or by exhaust system modifications, while possible future improvements to diesel engine design may effect a significant improvement. However, it is proposed that noise reduction is likely to be achieved by attention to acoustic features of the operator's cab. The inclusion of resilient mounts, substantial floors and bulkheads, and acoustically absorbent linings are all shown to provide worthwhile improvements and, in combination, these measures can reduce noise levels from more than 100 dBA to 90 dBA or less. Where the tractor is fitted with a safety frame only, a low noise fabric cladding is shown to be feasible.

Enhancement of first arrivals using the τ-p transform on energy-ratio seismic shot records

Geophysics ◽  
2012 ◽  
Vol 77 (3) ◽  
pp. V101-V111 ◽  
Author(s):  
Wail A. Mousa ◽  
Abdullatif A. Al-Shuhail
Keyword(s):  
Conventional Method ◽  
Noise Level ◽  
Energy Ratio ◽  
Data Sets ◽  
Robust Method ◽  
Noise Levels ◽  
High Noise ◽  
Seismic Records ◽  
Better Than

We propose a robust method of first-break picking for data sets with high noise levels through the use of the [Formula: see text] transform on energy-ratio seismic records. Using synthetic shot records with various noise levels, we showed that the performance of this proposed method enhances first arrivals, which helps in picking them. This was particularly true when the noise level was high where picking on raw amplitudes completely fails. We also applied the method on two published real shot records, for which first-break picking was difficult. We showed that for one of the shot records our method succeeds in determining first breaks that are consistent with manual picks and better than those obtained from a conventional method. The method can be used to guide better the subsequent careful picking of first arrivals and requires one forward and one inverse [Formula: see text] transform operations. In contrast to methods based on trace-by-trace picking that often fail to pick some traces, the proposed method automatically interpolates missing picks.

On the Use of the Inverted Abel Integral for Evaluating Spectroscopic Sources

1981 ◽  
Vol 35 (1) ◽  
pp. 35-42 ◽  
Author(s):  
J. D. Algeo ◽  
M. B. Denton
Keyword(s):  
Noisy Data ◽  
Large Data ◽  
Cubic Spline ◽  
Low Noise ◽  
Large Data Sets ◽  
Small Data ◽  
Data Sets ◽  
Spline Method ◽  
Noise Levels ◽  
Small Data Sets

A numerical method for evaluating the inverted Abel integral employing cubic spline approximations is described along with a modification of the procedure of Cremers and Birkebak, and an extension of the Barr method. The accuracy of the computations is evaluated at several noise levels and with varying resolution of the input data. The cubic spline method is found to be useful only at very low noise levels, but capable of providing good results with small data sets. The Barr method is computationally the simplest, and is adequate when large data sets are available. For noisy data, the method of Cremers and Birkebak gave the best results.

Reservoir-parameter identification using minimum relative entropy-based Bayesian inversion of seismic AVA and marine CSEM data

Geophysics ◽  
2006 ◽  
Vol 71 (6) ◽  
pp. O77-O88 ◽  
Author(s):  
Zhangshuan Hou ◽  
Yoram Rubin ◽  
G. Michael Hoversten ◽  
Don Vasco ◽  
Jinsong Chen
Keyword(s):  
Relative Entropy ◽  
Joint Inversion ◽  
Parameter Estimates ◽  
Data Sets ◽  
Data Set ◽  
Mean Values ◽  
Prior Probabilities ◽  
Reservoir Fluid ◽  
Minimum Relative Entropy ◽  
Reservoir Parameter

A stochastic joint-inversion approach for estimating reservoir-fluid saturations and porosity is proposed. The approach couples seismic amplitude variation with angle (AVA) and marine controlled-source electromagnetic (CSEM) forward models into a Bayesian framework, which allows for integration of complementary information. To obtain minimally subjective prior probabilities required for the Bayesian approach, the principle of minimum relative entropy (MRE) is employed. Instead of single-value estimates provided by deterministic methods, the approach gives a probability distribution for any unknown parameter of interest, such as reservoir-fluid saturations or porosity at various locations. The distribution means, modes, and confidence intervals can be calculated, providing a more complete understanding of the uncertainty in the parameter estimates. The approach is demonstrated using synthetic and field data sets. Results show that joint inversion using seismic and EM data gives better estimates of reservoir parameters than estimates from either geophysical data set used in isolation. Moreover, a more informative prior leads to much narrower predictive intervals of the target parameters, with mean values of the posterior distributions closer to logged values.

Noise Prediction and Control of Floating, Production, Storage and Offloading (FPSO)

2013 ◽  
Author(s):  
Keun Bok Song ◽  
Hyung Taek Kim ◽  
Sung Hoon Kim ◽  
Won Ho Joo
Keyword(s):  
Noise Level ◽  
Large Scale ◽  
Noise Analysis ◽  
Offshore Structures ◽  
Low Noise ◽  
Acoustic Properties ◽  
Noise Levels ◽  
Airborne Noise ◽  
Control Procedures ◽  
Indoor And Outdoor

Recently, the noise regulations are being reinforced to restrict the noise levels in the workplace and to protect the operator on the offshore structures. So, the noise levels of indoor and outdoor are one of the crucial barometers for determining the quality of offshore structures. In this paper, an efficient and accurate noise analysis method, which is used to calculate the indoor and outdoor noise levels for Floating, Production, Storage and Offloading (FPSO) vessel, is introduced. The indoor noise level is calculated through summing up structure-borne noise, airborne noise from machinery, HVAC noise and transmitted noise from topside. Each noise level is predicted using appropriate methods by HHI’s procedures, which consider room acoustic theories, numerical methods like SEA and measured database at various ships and offshore structures. The outdoor noise level is predicted by using ray tracing method. Noise control procedures to improve acoustic properties of cabin/machinery room and to reduce the indoor/outdoor noise levels of offshore structures are also introduced: these procedures are produced by numerous experiments at the large scale acoustic test facilities like reverberant rooms and cabin mock-up. The established method has been applied to various types of real projects for FPSOs. The predicted results are confirmed to agree well with measurements results. It is expected to be very helpful to design the low noise FPSO.

scholarly journals The first pan-Alpine surface-gravity database, a modern compilation that crosses frontiers

2021 ◽  
Vol 13 (5) ◽  
pp. 2165-2209
Author(s):  
Pavol Zahorec ◽  
Juraj Papčo ◽  
Roman Pašteka ◽  
Miroslav Bielik ◽  
Sylvain Bonvalot ◽  
...  
Keyword(s):  
Reference Frames ◽  
Joint Inversion ◽  
Gravity Data ◽  
Bouguer Anomaly ◽  
Interdisciplinary Studies ◽  
Water Masses ◽  
Data Sets ◽  
Data Set ◽  
Homogeneous Surface ◽  
Gravity Database

Abstract. The AlpArray Gravity Research Group (AAGRG), as part of the European AlpArray program, focuses on the compilation of a homogeneous surface-based gravity data set across the Alpine area. In 2017 10 European countries in the Alpine realm agreed to contribute with gravity data for a new compilation of the Alpine gravity field in an area spanning from 2 to 23∘ E and from 41 to 51∘ N. This compilation relies on existing national gravity databases and, for the Ligurian and the Adriatic seas, on shipborne data of the Service Hydrographique et Océanographique de la Marine and of the Bureau Gravimétrique International. Furthermore, for the Ivrea zone in the Western Alps, recently acquired data were added to the database. This first pan-Alpine gravity data map is homogeneous regarding input data sets, applied methods and all corrections, as well as reference frames. Here, the AAGRG presents the data set of the recalculated gravity fields on a 4 km × 4 km grid for public release and a 2 km × 2 km grid for special request. The final products also include calculated values for mass and bathymetry corrections of the measured gravity at each grid point, as well as height. This allows users to use later customized densities for their own calculations of mass corrections. Correction densities used are 2670 kg m−3 for landmasses, 1030 kg m−3 for water masses above the ellipsoid and −1640 kg m−3 for those below the ellipsoid and 1000 kg m−3 for lake water masses. The correction radius was set to the Hayford zone O2 (167 km). The new Bouguer anomaly is station completed (CBA) and compiled according to the most modern criteria and reference frames (both positioning and gravity), including atmospheric corrections. Special emphasis was put on the gravity effect of the numerous lakes in the study area, which can have an effect of up to 5 mGal for gravity stations located at shorelines with steep slopes, e.g., for the rather deep reservoirs in the Alps. The results of an error statistic based on cross validations and/or “interpolation residuals” are provided for the entire database. As an example, the interpolation residuals of the Austrian data set range between about −8 and +8 mGal and the cross-validation residuals between −14 and +10 mGal; standard deviations are well below 1 mGal. The accuracy of the newly compiled gravity database is close to ±5 mGal for most areas. A first interpretation of the new map shows that the resolution of the gravity anomalies is suited for applications ranging from intra-crustal- to crustal-scale modeling to interdisciplinary studies on the regional and continental scales, as well as applications as joint inversion with other data sets. The data are published with the DOI https://doi.org/10.5880/fidgeo.2020.045 (Zahorec et al., 2021) via GFZ Data Services.

scholarly journals Assessment of noise pollution at various locations of Gorakhpur

2021 ◽  
Vol 13 (1) ◽  
pp. 131-137
Author(s):  
Maharshi Yadav ◽  
Ratnesh Kumar Patel ◽  
Abhishek Yadav ◽  
Gaurav Sharma ◽  
Govind Pandey
Keyword(s):  
Human Activities ◽  
Noise Level ◽  
Traffic Noise ◽  
Noise Pollution ◽  
Low Noise ◽  
Educational Institutions ◽  
Noise Levels ◽  
High Noise ◽  
High Noise Level ◽  
Medical College

Noise pollution is one of the major concerns in big cities as well as in the crowded area of small cites, Gorakhpur is fastgrowing city and has many locations with high noise levels. Various crossroads and intersections have traffic issues this causes high noise level. In this study, three locations were selected for noise level assessment, nearby areas of Gorakhnath Temple, BRD medical college and MMMUT. These locations are educational (silent) and low noise level zone but because they situated near traffic roads, which cause high noise levels around them. In this study outside periphery of educational institutions noise level increases due to traffic. Noise level is found to be high due to large number of human activities.  

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