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Geosymphony - Lithofacies Prediction
Lithofacies defines a body of rock on the basis of its distinctive lithological properties, including its composition, grain texture, bedding characteristics, sedimentary structures and biological features. The primary task of geological and engineering characterization of a petroleum reservoir is to determine the various lithofacies of the reservoir rocks through the analysis of cores extracted from wells.
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To initiate the zonation process, it is essential to first segment the continuous logs into discrete zones that exhibit similar properties. These zones serve as the fundamental units of reference for establishing correlations between wells.
The specific context and objectives of the analysis will determine the characteristics of the zones, which may represent lithostratigraphic or petrophysical units, or other meaningful geological entities.
Facies derived from log measurements are equivalent but not identical to the lithofacies inferred from core data. This is due to the fact that logfacies result from the indirect response of logs to lithology and fluid, while lithofacies are defined directly based on the visible characteristics of rocks.
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Geosymphony - Lithofacies Well Prediction
This seismic facies prediction provides an effective way to estimate reservoir properties by integrating different seismic attributes using pattern recognition algorithms, despite the lack of consistency in geological information and parameters such as the number of facies and the input seismic attributes. This allows us to leverage relevant knowledge from other locations. Furthermore, we can utilize the self-organizing map technique, which is capable of distinguishing between different traces.
Geosymphony - Lithofacies Seismic 2D/3D Prediction
This seismic facies prediction provides an effective way to estimate reservoir properties by integrating different seismic attributes using pattern recognition algorithms, despite the lack of consistency in geological information and parameters such as the number of facies and the input seismic attributes. This allows us to leverage relevant knowledge from other locations. Furthermore, we can utilize the self-organizing map technique, which is capable of distinguishing between different traces.
Geosymphony - Lithofacies Map Prediction
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