To enhance the signal-Noise ratio different techniques are used to remove the noises.
Types of Seismic Filtering:
1- Frequency Filtering.
2- Inverse Filtering (Deconvolution).
3- Velocity Filtering.
Avo ppt (Amplitude Variation with Offset)Haseeb Ahmed
AVO/AVA can physically explain presence of hydrocarbon in the reservoirs and the thickness, porosity, density, velocity, lithology and fluid content of the reservoir of the rock can be estimated.
Slide1:
Seismic Sources
HOW TO GENERATE SEISMIC WAVES?
Exploration seismology – mostly artificial sources
à active technique
Natural sources can also be used (e.g. earthquakes) – usually
for tectonic studies (passive seismic exploration)
!
What is a good source?
- economical, efficient, convenient
- safe and environmentally acceptable
- sufficient energy over the suitable frequency range
- repeatable
Slide 2:
Land seismic sources
Explosives: - usually detonated in boreholes or buried
PROS
- sharp, impulsive, high amplitude (mostly P-wave)
- reasonably cheap
CONS
- The signal is not repeatable
- slow (borehole drilling)
- can be destructive
Time-Frequency Attenuation of Swell Noise on Seismic Data from Offshore Centr...iosrjce
Diversity of noise types with different characteristics makesseparation of signal and noise a
challenging process.Swell noiseusually contaminates tracesand it is characterized by high amplitude and low
frequencies and affects only a limited band offrequencies.This work presents how FX projection filter (FXEDIT
code) processing approach was used to attenuate swell noise on dataset from a marine seismic survey
offshoreCentral Niger-Delta, Nigeria, which shows as an effective amplitude preserving and robust tool that
gives better results compared to many other conventional filtering algorithms.With this processing approach
and working side-by-side with the shot gather and the RMS windows; the results achieved are reliable and
satisfactory by giving clearer images for reservoir characterization. The level of swell noise attenuation after
this approach greatly increased the confidence to use the data for subsequent processing steps.
Avo ppt (Amplitude Variation with Offset)Haseeb Ahmed
AVO/AVA can physically explain presence of hydrocarbon in the reservoirs and the thickness, porosity, density, velocity, lithology and fluid content of the reservoir of the rock can be estimated.
Slide1:
Seismic Sources
HOW TO GENERATE SEISMIC WAVES?
Exploration seismology – mostly artificial sources
à active technique
Natural sources can also be used (e.g. earthquakes) – usually
for tectonic studies (passive seismic exploration)
!
What is a good source?
- economical, efficient, convenient
- safe and environmentally acceptable
- sufficient energy over the suitable frequency range
- repeatable
Slide 2:
Land seismic sources
Explosives: - usually detonated in boreholes or buried
PROS
- sharp, impulsive, high amplitude (mostly P-wave)
- reasonably cheap
CONS
- The signal is not repeatable
- slow (borehole drilling)
- can be destructive
Time-Frequency Attenuation of Swell Noise on Seismic Data from Offshore Centr...iosrjce
Diversity of noise types with different characteristics makesseparation of signal and noise a
challenging process.Swell noiseusually contaminates tracesand it is characterized by high amplitude and low
frequencies and affects only a limited band offrequencies.This work presents how FX projection filter (FXEDIT
code) processing approach was used to attenuate swell noise on dataset from a marine seismic survey
offshoreCentral Niger-Delta, Nigeria, which shows as an effective amplitude preserving and robust tool that
gives better results compared to many other conventional filtering algorithms.With this processing approach
and working side-by-side with the shot gather and the RMS windows; the results achieved are reliable and
satisfactory by giving clearer images for reservoir characterization. The level of swell noise attenuation after
this approach greatly increased the confidence to use the data for subsequent processing steps.
This presentation will discuss about the introduction, many type of filters, characteristics & causes, and also the spectrum of Vibration Signal Filtering.
UNDER WATER NOISE REDUCTION USING WAVELET AND SAVITZKY-GOLAYcsandit
A precise, linear indication of the depth of water in a specific part of water body is what always
required. Presently there are a wide variety of ways to produce a signal that tracks the depth of
water.The Ultrasonic signal is most commonly used for the depth estimation. This signal is
affected by various underwater noises which results in inaccurate depth estimation. The
objective of this paper is to provide noise reduction methods for underwater acoustic signal.In
present work, the signal processing is done on the data collected using TC2122 dual frequency
transducer along with the Navisound 415 echo sounder. There are two signal processing
techniques which are used: The first method is denoising algorithm based on Stationary wavelet
transform (SWT)and second method is Savitzky-Golay filter. The results are evaluated based on
the criteria of peak signal to noise ratio and 3D Surfer plots of the dam reservoir whose depth
estimation has to be done.
In signal processing, a filter is a device or process that removes some unwanted components or features from a signal. Filtering is a class of signal processing, the defining feature of filters being the complete or partial suppression of some aspect of the signal. Most often, this means removing some frequencies or frequency bands. However, filters do not exclusively act in the frequency domain; especially in the field of image processing many other targets for filtering exist. Correlations can be removed for certain frequency components and not for others without having to act in the frequency domain. Filters are widely used in electronics and telecommunication, in radio, television, audio recording, radar, control systems, music synthesis, image processing, and computer graphics.
TOPICS COVERED:-
How SONAR works
Factors that affect the performance of a sonar unit
Factors that affect underwater acoustic propagation
in the ocean
Principles of sonar
Application of sonar.
Significance of frequency
Conclusion…
In this paper, the performances of adaptive noise cancelling system employing Least Mean Square (LMS) algorithm are studied considering both white Gaussian noise (Case 1) and colored noise (Case 2)
situations. Performance is analysed with varying number of iterations, Signal to Noise Ratio (SNR) and tap size with considering Mean Square Error (MSE) as the performance measurement criteria. Results show that the noise reduction is better as well as convergence speed is faster for Case 2 as compared with Case 1. It is also observed that MSE decreases with increasing SNR with relatively faster decrease of MSE in Case 2 as compared with Case 1, and on average MSE increases linearly with increasing number of filter
coefficients for both type of noise situations. All the experiments have been done using computer
simulations implemented on MATLAB platform.
Observation of Io’s Resurfacing via Plume Deposition Using Ground-based Adapt...Sérgio Sacani
Since volcanic activity was first discovered on Io from Voyager images in 1979, changes
on Io’s surface have been monitored from both spacecraft and ground-based telescopes.
Here, we present the highest spatial resolution images of Io ever obtained from a groundbased telescope. These images, acquired by the SHARK-VIS instrument on the Large
Binocular Telescope, show evidence of a major resurfacing event on Io’s trailing hemisphere. When compared to the most recent spacecraft images, the SHARK-VIS images
show that a plume deposit from a powerful eruption at Pillan Patera has covered part
of the long-lived Pele plume deposit. Although this type of resurfacing event may be common on Io, few have been detected due to the rarity of spacecraft visits and the previously low spatial resolution available from Earth-based telescopes. The SHARK-VIS instrument ushers in a new era of high resolution imaging of Io’s surface using adaptive
optics at visible wavelengths.
Richard's entangled aventures in wonderlandRichard Gill
Since the loophole-free Bell experiments of 2020 and the Nobel prizes in physics of 2022, critics of Bell's work have retreated to the fortress of super-determinism. Now, super-determinism is a derogatory word - it just means "determinism". Palmer, Hance and Hossenfelder argue that quantum mechanics and determinism are not incompatible, using a sophisticated mathematical construction based on a subtle thinning of allowed states and measurements in quantum mechanics, such that what is left appears to make Bell's argument fail, without altering the empirical predictions of quantum mechanics. I think however that it is a smoke screen, and the slogan "lost in math" comes to my mind. I will discuss some other recent disproofs of Bell's theorem using the language of causality based on causal graphs. Causal thinking is also central to law and justice. I will mention surprising connections to my work on serial killer nurse cases, in particular the Dutch case of Lucia de Berk and the current UK case of Lucy Letby.
THE IMPORTANCE OF MARTIAN ATMOSPHERE SAMPLE RETURN.Sérgio Sacani
The return of a sample of near-surface atmosphere from Mars would facilitate answers to several first-order science questions surrounding the formation and evolution of the planet. One of the important aspects of terrestrial planet formation in general is the role that primary atmospheres played in influencing the chemistry and structure of the planets and their antecedents. Studies of the martian atmosphere can be used to investigate the role of a primary atmosphere in its history. Atmosphere samples would also inform our understanding of the near-surface chemistry of the planet, and ultimately the prospects for life. High-precision isotopic analyses of constituent gases are needed to address these questions, requiring that the analyses are made on returned samples rather than in situ.
Earliest Galaxies in the JADES Origins Field: Luminosity Function and Cosmic ...Sérgio Sacani
We characterize the earliest galaxy population in the JADES Origins Field (JOF), the deepest
imaging field observed with JWST. We make use of the ancillary Hubble optical images (5 filters
spanning 0.4−0.9µm) and novel JWST images with 14 filters spanning 0.8−5µm, including 7 mediumband filters, and reaching total exposure times of up to 46 hours per filter. We combine all our data
at > 2.3µm to construct an ultradeep image, reaching as deep as ≈ 31.4 AB mag in the stack and
30.3-31.0 AB mag (5σ, r = 0.1” circular aperture) in individual filters. We measure photometric
redshifts and use robust selection criteria to identify a sample of eight galaxy candidates at redshifts
z = 11.5 − 15. These objects show compact half-light radii of R1/2 ∼ 50 − 200pc, stellar masses of
M⋆ ∼ 107−108M⊙, and star-formation rates of SFR ∼ 0.1−1 M⊙ yr−1
. Our search finds no candidates
at 15 < z < 20, placing upper limits at these redshifts. We develop a forward modeling approach to
infer the properties of the evolving luminosity function without binning in redshift or luminosity that
marginalizes over the photometric redshift uncertainty of our candidate galaxies and incorporates the
impact of non-detections. We find a z = 12 luminosity function in good agreement with prior results,
and that the luminosity function normalization and UV luminosity density decline by a factor of ∼ 2.5
from z = 12 to z = 14. We discuss the possible implications of our results in the context of theoretical
models for evolution of the dark matter halo mass function.
Nutraceutical market, scope and growth: Herbal drug technologyLokesh Patil
As consumer awareness of health and wellness rises, the nutraceutical market—which includes goods like functional meals, drinks, and dietary supplements that provide health advantages beyond basic nutrition—is growing significantly. As healthcare expenses rise, the population ages, and people want natural and preventative health solutions more and more, this industry is increasing quickly. Further driving market expansion are product formulation innovations and the use of cutting-edge technology for customized nutrition. With its worldwide reach, the nutraceutical industry is expected to keep growing and provide significant chances for research and investment in a number of categories, including vitamins, minerals, probiotics, and herbal supplements.
Seminar of U.V. Spectroscopy by SAMIR PANDASAMIR PANDA
Spectroscopy is a branch of science dealing the study of interaction of electromagnetic radiation with matter.
Ultraviolet-visible spectroscopy refers to absorption spectroscopy or reflect spectroscopy in the UV-VIS spectral region.
Ultraviolet-visible spectroscopy is an analytical method that can measure the amount of light received by the analyte.
Filtering in seismic data processing? How filtering help to suppress noises.
1. 1
Filtering in seismic data processing? How filtering help to suppress noises.
The seismic trace is the combination of both signal and noise, the signal (wanted data) is the
representation of the geologic feature but the presence of noise shows it different from real.
Noises are further subdivided into Random (the natural noise with irregular pattern), and
Coherent noise (generated by geophysical equipments and experiments) like surface wave
generation by source. To enhance the signal-Noise ratio different techniques are used to remove
the noises.
Types of Seismic Filtering:
1- Frequency Filtering.
2- Inverse Filtering (Deconvolution).
3- Velocity Filtering.
Frequency Filtering
Basically seismic data processing is done in the frequency domain. The original time domain
data is converted to frequency domain by applying forward Fourier transformation to make
processing easy and filtering easy and cost effective.
The frequency domain data filtering involves the product of amplitude spectrum of input trace
with the filter operator (time-domain representation of wavelet). The processes of seismic
filtering in time and frequency domain are based following concepts in time series. “Convolution
in Time-domain is equivalent to multiplication in the frequency domain, same as convolution in
frequency-domain is equivalent to multiplication in the time domain” (Yalmas, 2001).
Frequency filters are designed in form of Band pass, Band reject, high pass or low cut or Low
pass or high cut. All of them are working on same principle; simply generate the zero phase
wavelet with an amplitude spectrum that satisfies the single specification from four.
2. 2
Original Seismic trace.
Low Pass filtered trace.
High Pass Filtered trace.
Band Pass Filtered trace.
Band Stop Filtered trace.
Frequency filter are usually applied when the frequency of signal and noises are different, it is
therefore can be separated on the function of frequency.
Analogue frequency filter is still commonly used in which simply a range of frequency of
desired signals is set in the filter. And it only passes the specific range of the frequency and
blocks all the high and low frequencies traces.
Band- Pass Filter is also working similar to analogue filter it commonly used and used at
different stages of seismic data processing. It simply pass a certain bandwidth usually 10-70 HZ
and block the lower and higher frequencies, typical seismic trace contains noises like ground
rolls are example of low frequencies mainly of less than 10HZ. Some higher unwanted
frequencies are produced by the ambient noises can be removed using band pass filter.
3. 3
Any other noises random and coherent are removed by frequency filtering in a way wind noise is
removed by high cut filter/low pass filtering, it allow lower frequency to pass and removed
higher frequencies, also known as smoothing filter.
4. 4
High Pass/Low cut filter is only allowed the higher frequencies and cut lower frequencies and it
is widely used for edges detection.
Notch Filter is the removal of removal of noises from electrical lines over geophones during
recording; their frequency is mostly 60 Hz, just remove the effect on signal.
Band Reject; if the range of noises is known then we simply mute or reject their band. It is
totally opposite of band pass filter.
5. 5
Inverse Filtering (Deconvolution):
Earth act as band pass filter for seismic waves that travel through it, higher frequencies are block
and pass lower frequencies. For the better resolution of the seismic data we need to use greater
bandwidth of the frequency so for that reason we apply inverse filtering. In which recover the
higher frequencies, attenuate multiples, equalize amplitude and generate zero phase wavelet.
Some of noises are left and are present with the same character of the reflected signal after
frequency filtering. For this broad range of seismic inverse filters are used to remove the specific
adverse effect of earth filtering (natural) along the transmission path such as absorption and
multiples and (artificial) frequency filtering during the seismic processing.Examples from
inverse filtering to remove the effect of frequency filtering;
Reverberation: The ringing are removed that are associated with the multiple reflection in a
water layers
6. 6
Deconvolution is best way to treat reverberation (reverberations) and multiples (deghostings).
The short duration reverberation is exposed by auto-correlation function with series decaying of
waveform, shown in waveform (a). The long reverberation is also exposed by auto-correlation as
separate side lobes shown in waveform (b). The side lobes present with the time gap through
which it align with the multiple reflection, then this lag of side lobes are periodically matched
with the reverberations.
De ghosting: Short path multiples are removed that directly travel from source to surface and
reflect back to base of weathered layered to receiver.
Whitening: In which amplitude of all the frequencies are equalized within the recorded
frequency band. Below figure is showing the removal of apparent punch-out effect by recovering
its amplitude and equalizing with its lateral extend.
7. 7
Velocity Filtering
The velocity filter is use to remove the coherent noise from the seismic data on the base of angles
at particular angles at which the event dips, this also known as fan filtering and pie slice filtering,
(March & Bailey 1983). The angle of the dip event with it propagates across the spread of
detector is determined by apparent velocity. Apparent velocity is calculated by;
Va= v/sinα
Va= apparent velocity
V= seismic pulse traveling velocity
α= angle with it propagate vertical across spread
Along the direction of spread, every single sinusoidal component of the waveform having a
apparent wave number ᶄa related to its frequency F.
F= Va.ᶄa
Hence plot of F and ᶄa is a straight line along the apparent wave number and apparent velocity.
This filtering will apply to the F-K spectrum to split out a particular seismic event, which is
shown as a sloping linear trend of peaks on the F-K spectrum, as Va = F/ᶄa. though, a typical
8. 8
shot data is in curved hyperbolic form on the original section containing different seismic event
as shown in the below figure.
The seismic event travel across spread way from source will plot in the negative wave number
and the event travel towards the source will plot in the negative wave number like back scattered
noises in the above figure. On the basis of difference in apparent velocity the unwanted noises
are suppressed. The simple way to achieved the same results is by applying the f-k filtering, in f-
k filtering the two dimensional data is converted from t-x to f-k domain then in the wedge shape
model is easily classify the noises and signals.
9. 9
Other important function of the velocity filtering includes the removal of ground rolls from the
short point gather. This will greatly help to better stacking and exact estimation of the stacking
velocity. This is also used to remove the coherent noise from single shot data because of its
anomalous dipping, for example the diffractions are removed by velocity filtering.