Neural_Networks_for_logs_generation

Generation of Sonic logs using Conventional logs using optimized neural Networks Pipeline.

Task:- Application of Artificial Neural Networks for Synthetic log (sonic) prediction

Install the Required Python Libraries

• pip3 install numpy

• pip3 install pandas

• pip3 install matplotlib

• pip3 install seaborn

• pip3 install sklearn

Data Description:

train.csv All the values equals to -999 are marked as missing values. Columns corresponding to various logs in train.csv

• CAL - Caliper, unit in Inch,
• CNC - Neutron, unit in dec
• GR - Gamma Ray, unit in API
• HRD - Deep Resisitivity, unit in Ohm per meter
• HRM - Medium Resistivity, unit in Ohm per meter
• PE - Photo-electric Factor, unit in Barn,
• ZDEN - Density, unit in Gram per cubit meter,
• DTC - Compressional Travel-time, unit in nanosecond per foot,
• DTS - Shear Travel-time, unit in nanosecond per foot

Prediction results:-

• Visualization
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