Offshore field trial application of low-frequency passive microseismic technology in the North Sea for exploration, appraisal and development of hydrocarbon deposits

First Break ◽  
2021 ◽  
Vol 39 (4) ◽  
pp. 45-50
Author(s):  
Vasilii Ryzhov ◽  
Dmitrii Ryzhov ◽  
Ilshat Sharapov ◽  
Sergey Feofilov ◽  
Evgeny Smirnov ◽  
...  
Keyword(s):  
North Sea ◽  
Field Trial ◽  
Low Frequency ◽  
The North ◽  
The North Sea ◽  
Offshore Field ◽  
Hydrocarbon Deposits

Frequency-dependent velocity analysis and offset-dependent low-frequency amplitude anomalies from hydrocarbon-bearing reservoirs in the southern North Sea, Norwegian sector

Geophysics ◽  
2017 ◽  
Vol 82 (6) ◽  
pp. N51-N60 ◽  
Author(s):  
Sayyid Suhail Ahmad ◽  
R. James Brown ◽  
Alejandro Escalona ◽  
Børge O. Rosland
Keyword(s):  
North Sea ◽  
High Frequency ◽  
Spectral Decomposition ◽  
Low Frequency ◽  
Velocity Analysis ◽  
Frequency Dependent ◽  
Lower Velocity ◽  
The North ◽  
Significant Difference ◽  
The North Sea

Our aim was to identify some of the characteristics of low-frequency anomalies. Specifically, we have looked, in 3D broadband data from the North Sea, for any offset dependence in these anomalies and any frequency-related change in normal moveout (NMO) velocity that could influence stacking power over different frequencies. After high-resolution spectral decomposition, two types of low-frequency anomaly have been identified associated with hydrocarbon-bearing reservoirs: (1) at the reservoir top and (2) below the reservoir, with a time delay of approximately 100–200 ms. Both types of anomalies indicate offset dependence. On the near-offset stacks, they are relatively strong, but they tend to be absent on the far-offset stacks. In addition, horizon velocity analysis, which was performed along the horizons picked at the tops of reservoir and nonreservoir intervals, has revealed frequency-dependent NMO velocity. For nonreservoir events, we found no significant difference between the NMO velocities for the low-frequency and high-frequency filtered common-midpoint gathers. However, along the anomalously low-frequency events observed at the tops of, and below, oil-bearing reservoirs, lower velocity is observed for low-frequency and higher velocity for high-frequency filtered gathers. If these properties turn out to be universally typical, increased understanding and inclusion of them could lead to improved workflows and help increase the reliability of low-frequency analysis as a hydrocarbon indicator.

A VSP field trial using distributed acoustic sensing in a producing well in the North Sea

First Break ◽  
2013 ◽  
Vol 31 (1993) ◽  
Author(s):  
K. Nørgaard Madsen ◽  
M. Thompson ◽  
T. Parker ◽  
D. Finfer
Keyword(s):  
North Sea ◽  
Field Trial ◽  
Acoustic Sensing ◽  
The North ◽  
The North Sea ◽  
Distributed Acoustic Sensing

scholarly journals Multi-decadal variability in seasonal mean sea level along the North Sea coast

Ocean Science ◽  
2018 ◽  
Vol 14 (6) ◽  
pp. 1491-1501 ◽  
Author(s):  
Thomas Frederikse ◽  
Theo Gerkema
Keyword(s):  
Sea Level ◽  
North Sea ◽  
Large Scale ◽  
Decadal Variability ◽  
Low Frequency ◽  
Sea Level Pressure ◽  
Mean Sea Level ◽  
Level Pressure ◽  
The North ◽  
The North Sea

Abstract. Seasonal deviations from annual-mean sea level in the North Sea region show a large low-frequency component with substantial variability at decadal and multi-decadal timescales. In this study, we quantify low-frequency variability in seasonal deviations from annual-mean sea level and look for drivers of this variability. The amplitude, as well as the temporal evolution of this multi-decadal variability shows substantial variations over the North Sea region, and this spatial pattern is similar to the well-known pattern of the influence of winds and pressure changes on sea level at higher frequencies. The largest low-frequency signals are found in the German Bight and along the Norwegian coast. We find that the variability is much stronger in winter and autumn than in other seasons and that this winter and autumn variability is predominantly driven by wind and sea-level pressure anomalies which are related to large-scale atmospheric patterns. For the spring and summer seasons, this atmospheric forcing explains a smaller fraction of the observed variability. Large-scale atmospheric patterns have been derived from a principal component analysis of sea-level pressure. The first principal component of sea-level pressure over the North Atlantic Ocean, which is linked to the North Atlantic Oscillation (NAO), explains the largest fraction of winter-mean variability for most stations, while for some stations, the variability consists of a combination of multiple principal components. The low-frequency variability in season-mean sea level can manifest itself as trends in short records of seasonal sea level. For multiple stations around the North Sea, running-mean 40-year trends for autumn and winter sea level often exceed the long-term trends in annual mean sea level, while for spring and summer, the seasonal trends have a similar order of magnitude as the annual-mean trends. Removing the variability explained by atmospheric variability vastly reduces the seasonal trends, especially in winter and autumn.

scholarly journals Multidecadal variability in seasonal mean sea level along the North Sea coast

2018 ◽  
Author(s):  
Thomas Frederikse ◽  
Theo Gerkema
Keyword(s):  
Sea Level ◽  
North Sea ◽  
Large Scale ◽  
Low Frequency ◽  
Principal Component ◽  
Sea Level Pressure ◽  
Mean Sea Level ◽  
Level Pressure ◽  
The North ◽  
The North Sea

Abstract. Seasonal deviations from annual-mean sea level in the North Sea region show a large low-frequency component with substantial variability at decadal and multi-decadal time scales. In this study, we quantify low-frequency seasonal variations from annual-mean sea level and look for drivers of this variability. The amplitude, as well as the temporal evolution of this multi-decadal variability shows substantial variations over the North Sea region, and this spatial pattern is similar to the well-known pattern of the influence of winds and pressure changes on sea level on higher frequencies. The largest low-frequency signals are found in the German Bight and along the Norwegian coast. We find that the variability is much stronger in winter and autumn than in other seasons, and that this winter and autumn variability is predominantly driven by wind and sea-level pressure anomalies which have their cause in large-scale atmospheric patterns. For the spring and summer seasons, only a small fraction of the observed variability can be explained by local and large-scale atmospheric changes. Large-scale atmospheric patterns have been derived from a principal component analysis of sea-level pressure. The first principal component of sea-level pressure over the North Atlantic Ocean, which is linked to the North Atlantic Oscillation (NAO), explains the largest fraction of winter-mean variability for most stations, while for some stations, the variability consists of a combination of multiple principal components. The low-frequency variability in season-mean sea level can manifest itself as trends in short records of seasonal sea level. For multiple stations around the North Sea, running-mean 40-year trends for autumn and winter sea level often exceed the long-term trends in annual mean sea level, while for spring and summer, the seasonal trends have a similar order of magnitude as the annual-mean trends. Removing the variability explained by atmospheric variability vastly reduces the seasonal trends, especially in winter and autumn.

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