Realistic weather conditions and removal of time-varying sea-surface effects: Application on ocean-bottom-cable data

Geophysics ◽  
2020 ◽  
Vol 85 (3) ◽  
pp. V297-V315
Author(s):  
Elsa Cecconello ◽  
Walter Söllner
Keyword(s):  
Weather Conditions ◽  
Surface Effects ◽  
Sea Surface ◽  
Ocean Bottom ◽  
Time Varying ◽  
Theoretical Derivation ◽  
Data Set ◽  
Wave Heights ◽  
Sea Surface Effects ◽  
The Impact

In marine seismic acquisition, seismic reflections at the sea surface, such as sea-surface ghosts and multiples, affect the accuracy of the retrieved subsurface reflections and reduce the usable frequency bandwidth. These sea-surface effects tend to increase with the increasing roughness of the weather conditions. Consequently, processing techniques that neglect the roughness and time variation of the sea surface induce errors in the data that could compromise the validity of the final images and interpretations. We study the impact of time-varying rough sea surfaces using a modeling method derived from the Rayleigh reciprocity theorem for time-varying surfaces, and we analyze errors in the source-deghosting operation. We show that the source-deghosting limitations are weather dependent for data including sea-surface multiples: For calm sea states (wave heights below 1.25 m), the error made by the source-deghosting process is negligible; however, for rough seas (wave heights above 1.5 m), it becomes significant and blurs the deghosted image at the sea-surface multiple signals. To accurately remove all sea-surface effects from the seismic data, we simultaneously apply source-deghosting and multiple-removal operations to the same up-going wavefield. This procedure is shown to be weather independent based on our theoretical derivation and the synthetic results. Finally, this is tested on a 2D OBC data set. Comparing the proposed inversion to up-down deconvolution, we observe similar features in both wavefields: Source ghosts and sea-surface multiples seem to have been correctly removed from the data, and the inverted result indicates a slightly better resolution for deeper reflections.

Modeling scattering effects from time-varying sea surface based on acoustic reciprocity

Geophysics ◽  
2018 ◽  
Vol 83 (2) ◽  
pp. T49-T68 ◽  
Author(s):  
Elsa Cecconello ◽  
Endrias G. Asgedom ◽  
Okwudili C. Orji ◽  
Morten W. Pedersen ◽  
Walter Söllner
Keyword(s):  
Weather Conditions ◽  
Sea Surface ◽  
Time Varying ◽  
Flat Mirror ◽  
Sea Surface Effects ◽  
Marine Seismic ◽  
Rough Sea Surface ◽  
Frequency Domain Approach ◽  
The Impact ◽  
Rough Sea

In marine seismic processing, the sea surface is often considered a flat mirror; hence, the effects of different weather conditions during the acquisition are largely ignored. However, studies have shown that rough sea-surface ghosts can severely damage the 4D signal, if not handled properly in data processing. To account for realistic sea-surface effects in processing, the impact of time-varying rough sea surfaces needs to be studied. We derive a method for modeling source and receiver ghosts from the time-varying rough sea surface and their interaction with subsurface reflections. This method is based on acoustic reciprocity and leads to integral equations of nonstationary wavefields. These modeling equations can also serve as a basis for investigating source and receiver deghosting methods for time-varying rough sea surfaces. Our developed modeling algorithm is validated against a frequency-domain approach for a “frozen” rough sea surface. For a moving simple sea surface, the Doppler shift produced by our method is in very good agreement with the analytical solution. Using a Pierson-Moskowitz spectrum, we derive a time-varying rough sea surface and model the receiver ghost, the source ghost, and the source-receiver ghost for the subsurface primary reflections of a heterogeneous geologic model. The results highlight that the source and receiver ghost interactions with a time-varying sea surface differently affect the subsurface reflections, and these effects can significantly impact the seismic repeatability of 4D studies.

Removal of all time-varying sea-surface effects by source deghosting and demultiple

Geophysics ◽  
2019 ◽  
Vol 84 (6) ◽  
pp. T347-T362 ◽  
Author(s):  
Elsa Cecconello ◽  
Endrias G. Asgedom ◽  
Walter Söllner
Keyword(s):  
Seismic Data ◽  
Surface Condition ◽  
Seismic Source ◽  
Sea Surface ◽  
Normal Velocity ◽  
Time Varying ◽  
Data Set ◽  
Marine Seismic ◽  
Rough Sea Surface ◽  
The Impact

Seismic source deghosting and sea-surface-related demultiple have been long-standing problems in marine seismic data processing. Although the receiver ghost problem may be considered as solved by using collocated measurement of pressure and normal velocity wavefields, the source deghosting and demultiple algorithms are still limited by assumptions related to the sea-surface condition. We have investigated the impact of a time-varying rough sea surface on source deghosting and demultiple. Starting from Rayleigh’s reciprocity theorem for time-varying sea surfaces, we uncover a fundamental limitation for source deghosting of time-dependent wavefields, such as marine seismic data that contain a receiver ghost or sea-surface-related multiples. We use simple synthetic examples to study the impact of source deghosting on sea-surface-related multiples. To resolve this limitation, we derive a method for simultaneous source deghosting and sea-surface-related demultiple for time-variant wavefields. Finally, we use the complex geologic model Sigsbee 2B first to illustrate that the source deghosting operation brings significant errors when applied to a data set containing sea-surface multiples. Second, we find that this problem can be resolved by simultaneously performing source deghosting and demultiple operations even in the presence of time-varying sea surfaces.

Has tourism driven house prices in Germany? Time-varying evidence since 1870

2021 ◽  
pp. 135481662110088
Author(s):  
Sefa Awaworyi Churchill ◽  
John Inekwe ◽  
Kris Ivanovski
Keyword(s):  
World War Ii ◽  
Historical Data ◽  
House Prices ◽  
Housing Prices ◽  
Time Varying ◽  
Data Set ◽  
Time Series Modelling ◽  
The Impact ◽  
Tourism Flows ◽  
Non Parametric

Using a historical data set and recent advances in non-parametric time series modelling, we investigate the nexus between tourism flows and house prices in Germany over nearly 150 years. We use time-varying non-parametric techniques given that historical data tend to exhibit abrupt changes and other forms of non-linearities. Our findings show evidence of a time-varying effect of tourism flows on house prices, although with mixed effects. The pre-World War II time-varying estimates of tourism show both positive and negative effects on house prices. While changes in tourism flows contribute to increasing housing prices over the post-1950 period, this is short-lived, and the effect declines until the mid-1990s. However, we find a positive and significant relationship after 2000, where the impact of tourism on house prices becomes more pronounced in recent years.

The Impact of US Monetary Growth on Bitcoin Trading Volume in the Current Economic Uncertainty

2020 ◽  
pp. 493-509
Author(s):  
İsmail Canöz
Keyword(s):  
Causal Relationship ◽  
Trading Volume ◽  
Causal Effect ◽  
Study Data ◽  
Time Interval ◽  
Time Varying ◽  
Economic Uncertainty ◽  
Causality Test ◽  
Data Set ◽  
The Impact

This study examines the effect of US monetary growth on Bitcoin trading volume. To achieve this purpose, firstly, the symmetric causality test is used. Following this test, another symmetric causality test is used to reveal a time-varying causal effect between variables. The data set covers the period from July 2010 to July 2019. The results of the first symmetric causality test, which considers the time interval of the study data as a whole, show that there is no causal relationship between variables. According to the results of the second causality test, these support the previous results substantially. However, an interesting detail is the causal relationship between variables for the period between April 2019 and July 2019. The reason for this relationship could be that investors who are indecisive during the current economic uncertainty add Bitcoin to their portfolios in response to the Federal Reserve's decisions.

scholarly journals Weather Impact on Airport Performance

Aerospace ◽  
2018 ◽  
Vol 5 (4) ◽  
pp. 109 ◽  
Author(s):  
Michael Schultz ◽  
Sandro Lorenz ◽  
Reinhard Schmitz ◽  
Luis Delgado
Keyword(s):  
Traffic Management ◽  
Probability Distributions ◽  
Weather Conditions ◽  
Air Traffic ◽  
Weather Data ◽  
Data Set ◽  
Airport Capacity ◽  
Weather Events ◽  
The Individual ◽  
The Impact

Weather events have a significant impact on airport performance and cause delayed operations if the airport capacity is constrained. We provide quantification of the individual airport performance with regards to an aggregated weather-performance metric. Specific weather phenomena are categorized by the air traffic management airport performance weather algorithm, which aims to quantify weather conditions at airports based on aviation routine meteorological reports. Our results are computed from a data set of 20.5 million European flights of 2013 and local weather data. A methodology is presented to evaluate the impact of weather events on the airport performance and to select the appropriate threshold for significant weather conditions. To provide an efficient method to capture the impact of weather, we modelled departing and arrival delays with probability distributions, which depend on airport size and meteorological impacts. These derived airport performance scores could be used in comprehensive air traffic network simulations to evaluate the network impact caused by weather induced local performance deterioration.

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