SOME TECHNICAL ASPECTS OF REFLECTION SEISMIC PROSPECTING IN THE SAHARA

Geophysics ◽  
1958 ◽  
Vol 23 (3) ◽  
pp. 557-573 ◽  
Author(s):  
M. Pieuchot ◽  
H. Richard
Keyword(s):  
Seismic Reflection ◽  
Signal To Noise Ratio ◽  
Small Signal ◽  
Signal To Noise ◽  
Low Frequencies ◽  
Technical Aspects ◽  
Reflection Seismic ◽  
Linear Dimensions ◽  
Single Trace ◽  
Selection Of

The small signal‐to‐noise ratio encountered in the Sahara required the development of special techniques. The gentle dips and low frequencies permitted the use of a pattern of 100 shot holes recorded by an array of 100 or more geophones per trace with the linear dimensions of the arrays of the order of 100 m. The large structural dimensions allowed the compositing of as many as 5 records into a single trace. Seismic reflection exploration was made economically feasible by the use of pneumatic hammers for drilling and the less expensive nitrates for explosives. The experimental procedures leading to the selection of the techniques are described.

Automated phase attribute-based picking applied to reflection seismics

Geophysics ◽  
2016 ◽  
Vol 81 (2) ◽  
pp. V141-V150 ◽  
Author(s):  
Emanuele Forte ◽  
Matteo Dossi ◽  
Michele Pipan ◽  
Anna Del Ben
Keyword(s):  
Signal To Noise Ratio ◽  
Phase Method ◽  
Data Sets ◽  
Reflection Seismic ◽  
Instantaneous Phase ◽  
Whole Process ◽  
Specific Analysis ◽  
Reflection Seismics ◽  
Selection Of ◽  
Energy Package

We have applied an attribute-based autopicking algorithm to reflection seismics with the aim of reducing the influence of the user’s subjectivity on the picking results and making the interpretation faster with respect to manual and semiautomated techniques. Our picking procedure uses the cosine of the instantaneous phase to automatically detect and mark as a horizon any recorded event characterized by lateral phase continuity. A patching procedure, which exploits horizon parallelism, can be used to connect consecutive horizons marking the same event but separated by noise-related gaps. The picking process marks all coherent events regardless of their reflection strength; therefore, a large number of independent horizons can be constructed. To facilitate interpretation, horizons marking different phases of the same reflection can be automatically grouped together and specific horizons from each reflection can be selected using different possible methods. In the phase method, the algorithm reconstructs the reflected wavelets by averaging the cosine of the instantaneous phase along each horizon. The resulting wavelets are then locally analyzed and confronted through crosscorrelation, allowing the recognition and selection of specific reflection phases. In case the reflected wavelets cannot be recovered due to shape-altering processing or a low signal-to-noise ratio, the energy method uses the reflection strength to group together subparallel horizons within the same energy package and to select those satisfying either energy or arrival time criteria. These methods can be applied automatically to all the picked horizons or to horizons individually selected by the interpreter for specific analysis. We show examples of application to 2D reflection seismic data sets in complex geologic and stratigraphic conditions, critically reviewing the performance of the whole process.

scholarly journals Collecting Microplastics in Gardens: Case Study (i) of Soil

2021 ◽  
Vol 9 ◽  
Author(s):  
Zahra Sobhani ◽  
Yunlong Luo ◽  
Christopher T. Gibson ◽  
Youhong Tang ◽  
Ravi Naidu ◽  
...  
Keyword(s):  
Signal To Noise Ratio ◽  
Point Of View ◽  
Signal To Noise ◽  
Statistical Point ◽  
Image Mapping ◽  
Noise Ratio ◽  
In The Beginning ◽  
Raman Image ◽  
Selection Of

As an emerging contaminant, microplastic is receiving increasing attention. However, the contamination source is not fully known, and new sources are still being identified. Herewith, we report that microplastics can be found in our gardens, either due to the wrongdoing of leaving plastic bubble wraps to be mixed with mulches or due to the use of plastic landscape fabrics in the mulch bed. In the beginning, they were of large sizes, such as > 5 mm. However, after 7 years in the garden, owing to natural degradation, weathering, or abrasion, microplastics are released. We categorize the plastic fragments into different groups, 5 mm–0.75 mm, 0.75 mm–100 μm, and 100–0.8 μm, using filters such as kitchenware, meaning we can collect microplastics in our gardens by ourselves. We then characterized the plastics using Raman image mapping and a logic-based algorithm to increase the signal-to-noise ratio and the image certainty. This is because the signal-to-noise ratio from a single Raman spectrum, or even from an individual peak, is significantly less than that from a spectrum matrix of Raman mapping (such as 1 vs. 50 × 50) that contains 2,500 spectra, from the statistical point of view. From the 10 g soil we sampled, we could detect the microplastics, including large (5 mm–100 μm) fragments and small (<100 μm) ones, suggesting the degradation fate of plastics in the gardens. Overall, these results warn us that we must be careful when we do gardening, including selection of plastic items for gardens.

Power spectral analysis of the diaphragm electromyogram

1983 ◽  
Vol 54 (6) ◽  
pp. 1579-1584 ◽  
Author(s):  
T. K. Aldrich ◽  
J. M. Adams ◽  
N. S. Arora ◽  
D. F. Rochester
Keyword(s):  
Power Spectrum ◽  
Signal To Noise Ratio ◽  
Normal Subjects ◽  
Chronic Obstructive ◽  
Signal To Noise ◽  
Low Frequencies ◽  
Mean Values ◽  
The Mean ◽  
Noise Ratio ◽  
Diaphragm Fatigue

We studied the power spectrum of the diaphragm electromyogram (EMG) at frequencies between 31 and 246 Hz in four young normal subjects and five patients with chronic obstructive lung disease (COPD). Diaphragm EMGs were analyzed during spontaneous breathing and maximum inspiratory efforts to determine the effect of signal-to-noise ratio on the power spectrum and if treadmill exercise to dyspnea was associated with diaphragm fatigue. We found that the centroid frequencies of the power spectra (fc) were strongly correlated (r = 0.93) with ratios of power at high frequencies to power at low frequencies (H/L) for all subjects. Of the two indices, H/L had the largest standard deviation expressed as a percentage of the mean. The mean values of both of these decreased significantly after exercise, fc from 100.2 to 97.3 and H/L from 1.07 to 0.97. Signal-to-noise ratios were higher in maximal inspiratory efforts and after exercise in normal subjects and higher in COPD patients. The signal-to-noise ratio was correlated negatively with fc and H/L, indicating that these indices of the shape of the power spectrum are influenced by signal strength and noise levels as well as muscle function. We conclude that the fc and H/L index similar qualities of the power spectrum, that they are partially determined by the signal-to-noise ratio, and that, in some cases, exercise to dyspnea is associated with apparently mild diaphragm fatigue.

scholarly journals The Characteristics of Metaheuristic Method in Selection of Path Pairs on Multicriteria Ad Hoc Networks

2019 ◽  
Vol 2019 ◽  
pp. 1-6 ◽  
Author(s):  
Nyoman Gunantara ◽  
I Dewa Nyoman Nurweda Putra
Keyword(s):  
Power Consumption ◽  
Ad Hoc Network ◽  
Ad Hoc ◽  
Signal To Noise Ratio ◽  
Computing Time ◽  
Signal To Noise ◽  
Swarm Optimization ◽  
Metaheuristic Methods ◽  
Hoc Networks ◽  
Selection Of

This research analyzes the metaheuristic methods, that is, ant colony optimization (ACO), genetic algorithm (GA), and particle swarm optimization (PSO), in the selection of path pairs on multicriteria ad hoc network. Multicriteria used are signal-to-noise ratio (SNR), load variance, and power consumption. Analysis of the simulation result is done as follows: first, in terms of computing time, the ACO method takes the most time compared with GA and PSO methods. Second, in terms of multicriteria performance, i.e., the performance of SNR, load variance, and power consumption, the GA method shows the same value in each repetition. It is different from ACO and PSO that show varying values. Finally, the selection of the path pairs by the GA method indicates the pairs of the path that are always the same as by the ACO and PSO methods indicate those that vary.

Pitfalls in horizon autopicking

2015 ◽  
Vol 3 (1) ◽  
pp. SB1-SB4 ◽  
Author(s):  
Donald A. Herron
Keyword(s):  
Data Quality ◽  
Signal To Noise Ratio ◽  
Signal To Noise ◽  
Tracking Algorithms ◽  
Input Control ◽  
Noise Ratio ◽  
Selection Of

Interpreters use horizon autopicking in many seismic interpretations in the modern workstation environment. When properly used and with data quality permitting this technique enables efficient and accurate tracking of horizons but is not without its pitfalls. Four common pitfalls are improper selection of the input control or seed grid, not accounting for the “directional” behavior of tracking algorithms, attempting autopicking in areas with poor reflection continuity and/or low signal-to-noise ratio, and failing to recognize elements of geology that are not suitable for autopicking.

Magnetoelectric Sensors With Directly Integrated Charge Sensitive Readout Circuit—Improved Field Sensitivity and Signal-to-Noise Ratio

2011 ◽  
Vol 11 (10) ◽  
pp. 2260-2265 ◽  
Author(s):  
Zhao Fang ◽  
Ninad Mokhariwale ◽  
Feng Li ◽  
Suman Datta ◽  
Q. M. Zhang
Keyword(s):  
Room Temperature ◽  
Signal To Noise Ratio ◽  
Low Noise ◽  
Magnetic Sensors ◽  
Readout Circuit ◽  
Signal To Noise ◽  
Low Frequencies ◽  
Field Sensitivity ◽  
Piezoelectric Layers ◽  
Noise Ratio

The large magnetoelectric (ME) coupling in the ME laminates makes them attractive for ultrasensitive room temperature magnetic sensors. Here ,we investigate the field sensitivity and signal-to-noise ratio (SNR) of ME laminates, consisting of magnetostrictive and piezoelectric layers (Metglas and piezopolymer PVDF were used as the model system), which are directly integrated with a low noise readout circuit. Both the theoretical analysis and experimental results show that increasing the number of piezoelectric layers can improve the SNR, especially at low frequencies. We also introduce a figure of merit to measure the overall influence of the piezolayer properties on the SNR and show that the newly developed piezoelectric single crystals of PMN-PT and PZN-PT have the promise to achieve a very high SNR and consequently ultra-high sensitivity room temperature magnetic sensors. The results show that the ME coefficients used in early ME composites development works may not be relevant to the SNR. The results also show that enhancing the magnetostrictive coefficient, for example, by employing the flux concentration effect, can lead to enhanced SNR.

scholarly journals A Temporal Model of Aural Frequency Discrimination

2021 ◽  
Author(s):  
◽  
Kaye McAulay
Keyword(s):  
Signal To Noise Ratio ◽  
Discrimination Performance ◽  
Frequency Discrimination ◽  
Signal To Noise ◽  
Low Frequencies ◽  
Human Data ◽  
Temporal Intervals ◽  
Temporal Model ◽  
Noise Ratio ◽  
Positive Axis

<p>The importance of temporal information versus place information in frequency analysis by the ear is a continuing controversy. This dissertation developes a temporal model which simulates human frequency discrimination. The model gives guantitative measures of performance for the discrimination of sinusoids in white gaussian noise. The model simulates human frequency discrimination performance as a function of frequency and signal-to-noise ratio. The model's predictions are based on the temporal intervals between the positive axis crossings of the stimulus. The histograms of these temporal intervals were used as the underlying distributions from which indices of discriminability were calculated. Human freguency discrimination data was obtained for five observers as a function of frequency and signal-to-noise ratio. The data were analysed using the method of Group-operating-characteristic (GOC) Analysis. This method of analysis statistically removes unique noise from data. The unique noise was removed by summing observers' ratings for identical stimuli. This method of analysis gave human frequency discrimination data with less unigue noise than any existing frequency data. The human data were used for evaluating the model. The GOC Analysis was also used to study the improvement in d' as a function of stimulus replications and signal-to-noise ratio. The model was a good fit to the human data at 250 Hz, for two signal-to-noise ratios. The model did not fit the data at 1000 Hz or 5000 Hz. There was some evidence of a transition occuring at 1000 Hz. This investigation supported the idea that human frequency discrimination relies on a temporal mechanism at low frequencies with a transition to some other mechanism at about lO00 Hz.</p>

scholarly journals Determination of Histamine in Tomatoes by Capillary Electrophoresis

2000 ◽  
Vol 83 (1) ◽  
pp. 89-94 ◽  
Author(s):  
Elek Bolygo ◽  
Paul A Cooper ◽  
K Michael Jessop ◽  
Frank Moffatt
Keyword(s):  
Capillary Electrophoresis ◽  
Signal To Noise Ratio ◽  
High Sensitivity ◽  
Flow Cell ◽  
Voltage Gradient ◽  
Signal To Noise ◽  
Tomato Fruits ◽  
Endogenous Level ◽  
Selection Of

Abstract An improved capillary electrophoresis assay for histamine in crude extracts was developed and used to determine histamine levels in a selection of tomato fruits and pastes. Performance in terms of reproducibility and sensitivity was optimized by use of a high sensitivity detector flow cell, sodium hydroxide rinses, and a voltage gradient. The method was linear down to 0.2 μg/mL (signal-to-noise ratio = 4:1), which was below the endogenous level in all samples.

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