Acoustic impedance logs computed from seismic traces

Geophysics ◽  
1979 ◽  
Vol 44 (9) ◽  
pp. 1485-1501 ◽  
Author(s):  
M. Becquey ◽  
M. Lavergne ◽  
C. Willm
Keyword(s):  
Time Series ◽  
Acoustic Impedance ◽  
Seismic Velocity ◽  
Physical Property ◽  
Well Logs ◽  
Accurate Estimation ◽  
Low Frequencies ◽  
Short Period ◽  
And Migration ◽  
Initial Processing

Acoustic impedance, the product of seismic velocity and density, is a basic physical property of rocks. Seismic traces are converted into pseudoreflection‐coefficient time series by appropriate initial processing, then into acoustic impedance by the inversion of the time series. Such pseudologs are roughly equivalent to logs recorded in wells drilled at every seismic trace location. They yield important information concerning the nature of the rock and variations in lithology. To obtain the best quality pseudologs, careful initial processing is necessary: true‐amplitude recovery, appropriate deconvolution, common‐depth‐point (CDP) stack, wave‐shaping, wave‐equation migration, and amplitude scaling. The low frequencies from moveout velocity information are inserted. Both the short‐period information computed from reflection amplitudes and the long‐period trend computed from reflection moveout are displayed on acoustic impedance logs. Possible causes of pseudolog distortions are inaccuracies of amplitude recovery and scaling, imperfection of deconvolution and migration, and difficulties of calibrating the pseudolog to an acoustic log derived from well logs. Such calibration increases the precision; facies variations observed in well logs can be extrapoled to large distances from the wells, leading to a more accurate estimation of hydrocarbon reserves.

Prediction of Atmospheric Turbulence Characteristics for Surface Boundary Layer using Empirical Spectral Methods

2020 ◽  
Author(s):  
Yagya Dutta Dwivedi ◽  
Vasishta Bhargava Nukala ◽  
Satya Prasad Maddula ◽  
Kiran Nair
Keyword(s):  
Boundary Layer ◽  
Time Series ◽  
Surface Roughness ◽  
Wind Speed ◽  
Atmospheric Turbulence ◽  
Surface Boundary ◽  
Low Frequencies ◽  
Surface Boundary Layer ◽  
Power Spectral ◽  
Mean Wind Speed

Abstract Atmospheric turbulence is an unsteady phenomenon found in nature and plays significance role in predicting natural events and life prediction of structures. In this work, turbulence in surface boundary layer has been studied through empirical methods. Computer simulation of Von Karman, Kaimal methods were evaluated for different surface roughness and for low (1%), medium (10%) and high (50%) turbulence intensities. Instantaneous values of one minute time series for longitudinal turbulent wind at mean wind speed of 12 m/s using both spectra showed strong correlation in validation trends. Influence of integral length scales on turbulence kinetic energy production at different heights is illustrated. Time series for mean wind speed of 12 m/s with surface roughness value of 0.05 m have shown that variance for longitudinal, lateral and vertical velocity components were different and found to be anisotropic. Wind speed power spectral density from Davenport and Simiu profiles have also been calculated at surface roughness of 0.05 m and compared with k−1 and k−3 slopes for Kolmogorov k−5/3 law in inertial sub-range and k−7 in viscous dissipation range. At high frequencies, logarithmic slope of Kolmogorov −5/3rd law agreed well with Davenport, Harris, Simiu and Solari spectra than at low frequencies.

Acoustic Neuromas and the Acoustic Impedance of the Ear

1973 ◽  
Vol 38 (3) ◽  
pp. 345-353 ◽  
Author(s):  
J. H. Macrae
Keyword(s):  
Tympanic Membrane ◽  
Acoustic Neuroma ◽  
Acoustic Impedance ◽  
Theoretical Calculations ◽  
Low Frequencies ◽  
Cochlear Duct ◽  
Acoustic Neuromas ◽  
Affected Side ◽  
Contralateral Ear ◽  
Conductive System

The acoustic impedance at the tympanic membrane was measured at frequencies in the range 100–1000 Hz and found to be abnormal on the affected side in four patients with acoustic neuroma. In all four the resistance was abnormally high at low frequencies on the affected side, and in three the reactance of the affected ear was raised relative to that of the contralateral ear, particularly at low frequencies. The abnormality is attributed to an increase in the input acoustic impedance of the cochlea produced by the increase in protein content of the cochlear fluids and dilatation of the cochlear duct known to occur in acoustic neuroma. This explanation is supported by theoretical calculations carried out on an electric analogue of the conductive system, and it is suggested that similar abnormalities in the acoustic impedance at the tympanic membrane might occur in other pathologies which produce abnormal mechanical conditions in the cochlea.

DYNAMICAL ESTIMATION OF CALENDAR EFFECTS

2006 ◽  
Vol 06 (01) ◽  
pp. L7-L15
Author(s):  
ALEXANDROS LEONTITSIS
Keyword(s):  
Dynamical System ◽  
Time Series ◽  
Noise Level ◽  
Nonlinear Dynamical System ◽  
Main Tool ◽  
Experimental Results ◽  
Accurate Estimation ◽  
Nonlinear Dynamical ◽  
Correlation Integral ◽  
Calendar Effects

The paper introduces a method for estimation and reduction of calendar effects from time series, which their fluctuations are governed by a nonlinear dynamical system and additive normal noise. Calendar effects can be considered deviations of the distribution(s) of particular group(s) of observations that have a common characteristic related to the calendar. The concept of this method is the following: since the calendar effects are not related to the dynamics of the time series, the accurate estimation and reduction will result a time series with a smaller amount of noise level (i.e. more accurate dynamics). The main tool of this method is the correlation integral, due to its inherit capability of modeling both the dynamics and the additive normal noise. Experimental results are presented on the Nasdaq Cmp. index.

Estimating contribution of high-frequency sea-level oscillations to the extreme sea levels in the Adriatic Sea

2021 ◽  
Author(s):  
Krešimir Ruić ◽  
Jadranka Šepić ◽  
Maja Karlović ◽  
Iva Međugorac
Keyword(s):  
Time Series ◽  
Sea Level ◽  
High Frequency ◽  
Adriatic Sea ◽  
Tide Gauge ◽  
Data Series ◽  
Sea Levels ◽  
Short Period ◽  
Extreme Sea Levels ◽  
Sea Level Oscillations

<p>Extreme sea levels are known to hit the Adriatic Sea and to occasionally cause floods that produce severe material damage. Whereas the contribution of longer-period (T > 2 h) sea-level oscillations to the phenomena has been well researched, the contribution of the shorter period (T < 2 h) oscillations is yet to be determined. With this aim, data of 1-min sampling resolution were collected for 20 tide gauges, 10 located at the Italian (north and west) and 10 at the Croatian (east) Adriatic coast. Analyses were done on time series of 3 to 15 years length, with the latest data coming from 2020, and with longer data series available for the Croatian coast. Sea level data were thoroughly checked, and spurious data were removed. </p><p>For each station, extreme sea levels were defined as events during which sea level surpasses its 99.9 percentile value. The contribution of short-period oscillations to extremes was then estimated from corresponding high-frequency (T < 2 h) series. Additionally, for four Croatian tide gauge stations (Rovinj, Bakar, Split, and Dubrovnik), for period of 1956-2004, extreme sea levels were also determined from the hourly sea level time series, with the contribution of short-period oscillations visually estimated from the original tide gauge charts.  </p><p>Spatial and temporal distribution of contribution of short-period sea-level oscillations to the extreme sea level in the Adriatic were estimated. It was shown that short-period sea-level oscillation can significantly contribute to the overall extremes and should be considered when estimating flooding levels. </p>

Deepwater reservoir prediction using broadband seismic-driven impedance inversion and seismic sedimentology in the South China Sea

2018 ◽  
Vol 6 (4) ◽  
pp. SO17-SO29 ◽  
Author(s):  
Yaneng Luo ◽  
Handong Huang ◽  
Yadi Yang ◽  
Qixin Li ◽  
Sheng Zhang ◽  
...  
Keyword(s):  
South China Sea ◽  
South China ◽  
Seismic Data ◽  
Seismic Velocity ◽  
The South China Sea ◽  
Hydrocarbon Exploration ◽  
The South ◽  
Low Frequencies ◽  
China Sea ◽  
Impedance Inversion

In recent years, many important discoveries have been made in the marine deepwater hydrocarbon exploration in the South China Sea, which indicates the huge exploration potential of this area. However, the seismic prediction of deepwater reservoirs is very challenging because of the complex sedimentation, the ghost problem, and the low exploration level with sparse wells in deepwater areas. Conventional impedance inversion methods interpolate the low frequencies from well-log data with the constraints of interpreted horizons to fill in the frequency gap between the seismic velocity and seismic data and thereby recover the absolute impedance values that may be inaccurate and cause biased inversion results if wells are sparse and geology is complex. The variable-depth streamer seismic data contain the missing low frequencies and provide a new opportunity to remove the need to estimate the low-frequency components from well-log data. Therefore, we first developed a broadband seismic-driven impedance inversion approach using the seismic velocity as initial low-frequency model based on the Bayesian framework. The synthetic data example demonstrates that our broadband impedance inversion approach is of high resolution and it can automatically balance between the inversion resolution and stability. Then, we perform seismic sedimentology stratal slices on the broadband seismic data to analyze the depositional evolution history of the deepwater reservoirs. Finally, we combine the broadband amplitude stratal slices with the impedance inversion results to comprehensively predict the distribution of deepwater reservoirs. Real data application results in the South China Sea verify the feasibility and effectiveness of our method, which can provide a guidance for the future deepwater hydrocarbon exploration in this area.

NDVI dynamics as reflected in climatic variables: spatial and temporal trends – a case study of Hungary

2019 ◽  
Vol 56 (4) ◽  
pp. 624-644 ◽  
Author(s):  
Szabó ◽  
Elemér ◽  
Kovács ◽  
Püspöki ◽  
Kertész ◽  
...  
Keyword(s):  
Climate Change ◽  
Time Series ◽  
Local Level ◽  
Temporal Trends ◽  
Maximum Temperature ◽  
Time Range ◽  
Climatic Data ◽  
Spatial Pattern Analysis ◽  
Short Period ◽  
Temporal Variance

Understanding climate change and revealing its future paths on a local level is a great challenge for the future. Beside the expanding sets of available climatic data, satellite images provide a valuable source of information. In our study we aimed to reveal whether satellite data are an appropriate way to identify global trends, given their shorter available time range. We used the CARPATCLIM (CC) database (1961–2010) and the MODIS NDVI images (2000–2016) and evaluated the time period covered by both (2000–2010). We performed a regression analysis between the NDVI and CC variables, and a time series analysis for the 1961–2008 and 2000–2008 periods at all data points. The results justified the belief that maximum temperature (TMAX), potential evapotranspiration and aridity all have a strong correlation with the NDVI; furthermore, the short period trend of TMAX can be described with a functional connection with its long period trend. Consequently, TMAX is an appropriate tool as an explanatory variable for NDVI spatial and temporal variance. Spatial pattern analysis revealed that with regression coefficients, macro-regions reflected topography (plains, hills and mountains), while in the case of time series regression slopes, it justified a decreasing trend from western areas (Transdanubia) to eastern ones (The Great Hungarian Plain). This is an important consideration for future agricultural and land use planning; i.e. that western areas have to allow for greater effects of climate change.

scholarly journals Observatory crustal magnetic biases during CHAMP satellite mission

2015 ◽  
Vol 7 (1) ◽  
pp. 495-508
Author(s):  
G. Verbanac ◽  
M. Mandea ◽  
M. Bandić ◽  
S. Subašić
Keyword(s):  
Time Series ◽  
External Field ◽  
Personal Communication ◽  
Field Pattern ◽  
Monthly Means ◽  
Satellite Mission ◽  
Champ Satellite ◽  
Annual Variations ◽  
Oscillatory Pattern ◽  
Short Period

Abstract. Taking advantage of nine years of CHAMP satellite mission (June 2000–August 2009), we investigate the temporal evolution of the observatory monthly crustal magnetic biases. To determine biases we compute X (northward), Y (eastward) and Z (vertically downward) monthly means from 42 observatory one-minute or hourly values, and compare them to synthetic monthly means obtained from a GRIMM3 core field model (V. Lesur, personal communication, 2014). Both short period variations and long term trends in the monthly bias time series are analyzed. A comparison with biases based on MAGSAT and Ørsted satellite data, related to the 1979.92 and 1992.92 epochs is performed. Generally, the larger biases averaged over nine years and the larger differences between biases based on different models are found in Z component. This can be the signature of the induced magnetic fields. Although annual trends in most bias series are observed, no clear evidence that the constant crustal field changed significantly over the studied period is found. Time series of monthly biases exhibit distinct oscillatory pattern in the whole time span, which we assign to the external field contributions. The amplitudes of these variations are linked with the phase of the solar cycle, being significantly larger in the period 2000–2005 than in the period 2006–2009. Clear semi-annual variations are evident in all components, with extremes in spring and fall months of each year. Common external field pattern is found for European monthly biases. A dependence of the bias monthly variations on geomagnetic latitudes is not found for the non-European observatories. The results from this study represent a base to further exploit the observatory and repeat stations magnetic biases together with the data from the new satellite mission SWARM.

scholarly journals Preliminaries on the Accurate Estimation of the Hurst Exponent Using Time Series

2021 ◽  
Author(s):  
Ginno Millán ◽  
Román Osorio-Comparán ◽  
Gastón Lefranc
Keyword(s):  
Time Series ◽  
Hurst Exponent ◽  
High Speed ◽  
Mean Squared Error ◽  
Computer Network ◽  
Accurate Estimation ◽  
Minimum Length ◽  
Squared Error ◽  
In Series ◽  
Speed Computer

<div>This article explores the required amount of time series points from a high-speed computer network to accurately estimate the Hurst exponent. The methodology consists in designing an experiment using estimators that are applied to time series addresses resulting from the capture of high-speed network traffic, followed by addressing the minimum amount of point required to obtain in accurate estimates of the Hurst exponent. The methodology addresses the exhaustive analysis of the Hurst exponent considering bias behaviour, standard deviation, and Mean Squared Error using fractional Gaussian noise signals with stationary increases. Our results show that the Whittle estimator successfully estimates the Hurst exponent in series with few</div><div>points. Based on the results obtained, a minimum length for the time series is empirically proposed. Finally, to validate the results, the methodology is applied to real traffic captures in a high-speed computer network.</div>

scholarly journals TIME SERIES PROCESSING USING WAVELET-TRANSFORMATIONS FOR ACCURACY INCREASE IN INFORMATION PRESENTATION

2018 ◽  
Vol 2018 (8) ◽  
pp. 67-75
Author(s):  
Юрий Кропотов ◽  
Yuriy Kropotov ◽  
Алексей Белов ◽  
Aleksey Belov ◽  
Александр Проскуряков ◽  
...  
Keyword(s):  
Time Series ◽  
Wavelet Decomposition ◽  
Statistical Processing ◽  
Threshold Level ◽  
Information Presentation ◽  
Statistical Parameters ◽  
Noise Component ◽  
Low Frequencies ◽  
Accuracy Increase ◽  
Approximation Coefficients

The purpose of this work is development of the method for error decrease in information presentation in telecommunication systems of monitoring by means of filtering noise and fluctuations of levels in time series counts. To solve this problem there is used a method of wavelet processing. In particular, the decrease of time series fluctuation impact is carried out by means of the computation of approximating coefficients of the n-th level which corresponds to the fulfillment of multi-level statistical processing the values of time series counts and equivalent to a signal passage through a filter of low frequencies. There was developed and investigated a simulator and its statistical parameters of processing with a wavelet transformation of time series counts. It is shown that time series wavelet processing and the application of approximation coefficients of waveletdecomposition increase the accuracy of data presentation. It is also ensured at the expense of noise component suppression through a method of thresholding upon detailing coefficients of decomposition. In the paper there are shown investigations of the dependence of approximation coefficient correlation time upon a wavelet decomposition level. There was also investigated a depression dependence of noise components of time series count fluctuations of emission at the processing with the wavelet decomposition with obtaining approximation coefficients of different levels. The fulfilled analysis of the results of different criteria application and approaches to smoothing on the basis of threshold processing the detail coefficients of wavelet decomposition has shown that at smoothing time series there will be an optimum choice of an adaptive penalty threshold level. The presented results of smoothing with an adaptive penalty threshold have shown that the signal-noise ratio increased for more than 2.53dB in comparison with the initial one.

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