Rune Inversion (April 2019) - Artificial Intelligence
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The very first Seismic Post-Stack Inversion algorithm that allows to estimate Velocity and Density separately; with no well logs data required! Inverted Density and Velocity used as a base for Vclay, Porosity and Reservoir quality attribute - (1-Vclay)*Phi computations.
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High-speed HighRes velocity estimation from seismic data
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.
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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
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Post stack process with demigration and migration for easy structural interpretation.
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
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Seismic attributes - are quantities extracted or derived from seismic data. These attributes 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 attributes that include classic set and Q-factor, Phase decomposition and Lithology.