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AI_ML_Seismic_Log

Rock properties estimation are always challenging part of geoscientific tasks but rewarding if it goes in right direction. Acoustic impedance(AI) is the product of sound wave velocity and medium density. In general, rocks with lower density (lower seismic wave velocity) tend to have higher porosity which can be host of fluids, attractive for hydrocarbon resource exploration. Conventionally, impedance can be estimated through inverse theory application but in this practice.

In this research, we will try to predict AI as continuous value. Attributes that we will use as input should be vintages from seismic data becuase we want to build a model that would be able to predict AI in all area of interest that have seismic coverage.

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This is for AI prediction using seismic attributes

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