A fast, robust and portable Witsml to BSON parser

My portfolio

Nodal analysis using Python

Data Analytics on the Insights of Upstream and Downstream of Oil Production for Forecasting

Reformat fracking production numbers from West Virginia to a format more useful to GIS

NTNU Master Thesis, Energy and Process Engineering Department, Specialization: Industrial Process Technology

A fast way to check and work with .dlis files.

Oil Production Flow Rate Prediction with Deep Neural Network Algorithm such as Recurrent Neural Network (RNN) and Long-Short Term Memory (LSTM). This Model will testing with Validation method called Walk-Forward Validation (WFV). Basically the validation seperate in two part, the first WFV over actual data and WFV over predicted data.

Calculator written in Python to calculate dimensions of a separator for separation of oil and gas with user inputted parameters.

Plotting well trajectory and horizon with volve dataset

A data prediction algorithm implemented in Python to infer depth and casing size data of California oil wells missing data using surrounding wells in the same oil field. Python libraries such as pandas for manipulating dataframes and geopy were utilized.

Simple tubing counting tool

Exploration of data and technologies of the oil and gas sector

Code for Open-FF constructor scripts; A project to transform the industry's FracFocus disclosure data into a usable resource.

Fire and Smoke Detection for Oil Industry Safety | YOLOv9

landing page for OppinetSIM by RC-OPPINET ITB

Official Node.js API wrapper for energypriceapi.com

A professional web platform for showcasing industrial lubricants and oils, designed for seamless user experience and reliable performance

This project provides a thorough analysis of the crude oil production data from the Volve field, offering valuable insights into production trends and future forecasts.

This Python script creates a Streamlit web application for a quick IPR Calculation for both an oil and gas reservoir. It collects user input test data and with it performs a curve fitting using scipy.optimize, fitting the Inflow Performance Relationship curve to the data.