A collection of Wells/Drilling Engineering tools, focused on well trajectory planning for the time being.

The python tool for well trajectories

Leveraging matplotlib to visualize well drilling and construction

This is class project I conducted as team leader. I developed Matlab code to calculate the wellbore stability considering Mohr-Columb failure criteria in gemomechanical calculations. Example cases was studied using the code and based on results conclusions about wellbore stability during drilling was reached.

A repo containing Jupyter notebooks where ensemble algorithms are investigated to attempt predicting the downhole concentration of cuttings in oil wells using surface data.

A probability based approach to characterize lithology using drilling data and Random Forests

Lost Circulation Material

Symbolic Regression is used for developing ROP model.

An intelligent package for solving hydrogeology engineering issues

Change Point Detection task solutions and experiments for directional drilling operation at thin oil layer / Решение задачи поиска точек перехода между песчанистым и глинистым пластом во-время направленного бурения скважины.

A code for Machine Learning model to predict rate of penetration in Drilling operation with Linear Regression, Random Forest, and Decision Tree

ProtoType of a Dia plug-in which provides structures and shapes for basic well diagrams.

To calculate the pressure losses, cuttings transport ratio (hole cleaning performance) and graphically show sensitivity analysis by considering multiple factors. involved in wellbore cleaning..

Drilling Data Collector

This repository contains a detailed numerical simulation of the dynamic descent of a core sample inside upward-inclined boreholes, considering fluid flow, buoyancy, drag, viscous shear, and gravitational forces. The model is based on explicit time integration and critical limit analyses for drilling fluid parameters.