Reservoir Characterisation
Previous to Quantitative Interpretation, deciding on oil well placements amounted to near guess work. At Pays International we employ a more surgical approach, increasing the success and profitability of an oil field through powerful seismic data analysis techniques.
Through these techniques we are able to give your petroleum engineers and geologists the best possible information on where the next well should be drilled.
Pre-Stack Inversion
Structural Analysis
Machine Learning Classification
Seismic Inversion
Pre-Stack Enhancement
Firstly we check the current quality of your data using five separate tests. For each test we have the capability to correct any flaws we find, ensuring your data provides a strong foundation for inversion, fault analysis and classification
Structural Analysis
The latest in fault analysis, curvature analysis and RGB blending techniques. Structural analysis provides an accurate insight into the structure in and around your reservoir.
Machine Learning Classification
From your well data, estimates can be made about the importance of certain attributes in terms of likelihood of finding oil. Our machine learning algorithm learns from these data and predicts where to drill the next well.
Seismic Inversion
Porosity, fluid prediction and brittleness index are the most crucial factors in oil exploration. Seismic inversion calculates these factors from your data.