Recent research
PSS-Geo has internal research teams which continuity developing new modules and approaches for different parts of geo exploration. We collaborate and sponsor research institutes and consortia. Our partners: Delphi (Holland), WIT (Germany), IPGG SB RAS (Russia), UiO (Norway) and others.
V. Kalashnikova, R. Øverås. Seismic Absorption estimation for Reservoir Prediction using Prony Decomposition (EAGE 2018, ThA1113)
Potential of Prony and Phase Decompositions for Reservoir Prediction Vita V. Kalashnikova, Rune Øverås, Arif Butt and Stéphanie Guidard. Extended Abstract GeoConvention2018
Prony Decomposition for Sealing and Leaking fault analysis Vita V. Kalashnikova, Arif Butt and Stéphanie Guidard. Extended Abstract GeoConvention2018
High Resolution Velocity Attribute for Reservoirs, Lithology and Pore Pressure Prediction Vita V. Kalashnikova, Rune Øverås, Ivar Meisingset, Daria Krasova and Arif Butt. Extended Abstract GeoConvention2018
Construction Technique Of High Resolution Velocity Field - New Attribute For Seismic Interpretation,
R. Øverås,V. Kalashnikova,S.Guidard and I. Meisingset. Extended Abstract PESGB and EAGE First Velocity Workshop,Th AI01, 2018
Seismic Profile R.Øverås, V.Kalashnikova pp.26-28, 2015-07
Seismic Data Attributes - new look at the old techniques, Kalashnikova V., Muzi J.,2015, The Firts, May, p28-31.
Depth migration model building and model verification sequence, by Juri Muzi 2015
Depth migration model building
and model verification sequence,
The First, SPE Norway
R. MacKinnon, J.Muzi and V.Kalashnikova, 2015
EAGE 2015 Full QI Johan Castberg Fast Track
EAGE 2015 List of techniques promo
PSS-Geo QI recommendation steps
NCS, 2014 Poster
15 years processing on NCS
NCS, 2014 Poster
Quantitative Interpretation
Seismic Data Attributes PSS-Geo Manual 2015 by V.Kalashnikova
Fist Break 2013 post Data Adaptive Ghostbuster
All Seismic Processing Deghosting techniques. 2013 R.Øverås, V.Kalashnikova
Publications
PSS-Geo AS developed a processing flow for High-Resolution Velocity construction based on two methods: Amplitude Inversion combined with Dynamic Auto Correlation or combined with Dynamic Time Warping. By combinations these two methods, High-Resolution Velocity field can be generated quickly, without big machine computation power. Implementation of High-Resolution velocity field is a useful attribute for seismic interpretation: lithology, geohazard and fluid prediction.
Interval stacking velocity Interval HighRes Velocity
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Artificial Intelligence - Rock properties prediction from Seismic traces
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Lend seismic data shallow noise reduction through single time offset gain variable function
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Full Wave Form Migration: computations for production
Phase Decomposition
Thin layers and HC effects are often accompanied by phase anomalies. It can be detected by decomposing the phase.
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Noise Reduction
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Tenzor based regularization
-noise reduction
-faults preservation
Post stack process with demigration and migration for easy structural interpretation.
Gravitymagnetic surveys on Drons
accompanied with shallow seismic or Radar scan for engineering and archeology needs.
PSS-Geo accomplished development of engineering solution of light weight Dron servery acquisition. Field' tests were carry out in several terrais. First archeological servery for research planned on summer 2018 in Romsdal Fjord, Norway, Viking's barrows.
Learn more..
Q- factor estimation
Thin layers and HC effects are often accompanied by phase anomalies. It can be detected by decomposing the phase.
 Integrated Fluid FactorWisting Barents Sea PSS-Geo Seismic Data Attributes / Data of MultiClient Geophysical ASA |  Fluid Factor weighted frequencyWisting Barents Sea PSS-Geo Seismic Data Attributes / Data of MultiClient Geophysical ASA |  Integrated Fluid Factor weit. freq.Wisting Barents Sea PSS-Geo Seismic Data Attributes / Data of MultiClient Geophysical ASA |
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 Section colored by AVO classesWisting Barents Sea PSS-Geo Seismic Data Attributes / Data of MultiClient Geophysical ASA |
PSS-Geo Seismic Data Attributes
Seismic attributes - is a quantity extracted or derived from seismic data that can be analyzed in order to enhance information that might be more subtle in a traditional seismic image, leading to a better geological or geophysical interpretation of the data.
We suggest a package of the attributes that include classic set and Q-factor, Phase decomposition and Lithology.
