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Drilling Project

Description

This repository contains the code for the paper title "A New Method for Determination of Optimal Borehole Drilling Location Considering Drilling Cost Minimization and Sustainable Groundwater Management".

Experimental Environment

python libraries, including

  • NumPy
  • SkLearn
  • Scipy
  • pandas
  • matplotlib
  • pickle
  • seaborn
  • xgboost

Steps to build

  • train_depth_model is a pre-trained model to predict the drilling depth using chained LSTM.
  • train_soil_model is a pret-rained ensemble model to classify the soil color and land layer. The model is an ensemble of SVM, GNB, GBM, and RF.
  • train_water_model is a pre-trained model to predict ground water level using chained LSTM.
  • Optimization.py is a python script to find optimal location utilizing the above pretrained models in a given geographical area.

Run Optimization

Set x and y axis (Location) bounds on line 162 and 163 of Optimization.py

Run python Optimization.py

Architecture of the drilling project

image