Oil Production Forecasting: Multivariate Time Series Analysis

Ongoing Research Project

Welcome to my ongoing research project on multivariate time series forecasting of oil production. Please note that this project is currently under research and has not been deployed yet.

Introduction

This project focuses on developing a forecasting model for oil production using advanced machine learning techniques and optimization algorithms. The project includes the development of a Genetic Algorithm-Temporal Convolutional Neural Network-Long Short-Term Memory (GA-TCN-LSTM) ensemble model, as well as benchmarking against conventional models such as Recurrent Neural Network (RNN), Gated Recurrent Unit (GRU), Long Short-Term Memory (LSTM), and Temporal Convolutional Network (TCN).

Additionally, the project includes exploratory data analysis and data cleaning using our custom-built odc module. The module is designed to detect, visualize, and treat outliers in oil well datasets and is readily available in the odc repository.

Motivation

Accurate oil production forecasting is of paramount importance for oil and gas companies, governments, and policy-makers. It enables informed decision-making regarding production rates, inventory management, and revenue estimation.

Conventional forecasting methods often fall short in capturing the complexities and dynamic changes inherent in oil production systems. To address this challenge, I have incorporated advanced machine learning techniques and optimization algorithms. By leveraging these tools, I aim to capture the intricacies of the system and identify the optimal combination of hyperparameters for each model. My ultimate goal is to provide decision-makers with reliable information that enhances the forecasting process and improves decision-making.

Please note that this project is still in the research phase, and the results and conclusions are subject to further analysis and refinement. I appreciate your interest and invite you to explore my portfolio to learn more about this project and other research endeavors I am currently involved in. Stay tuned for updates as I continue to enhance the accuracy and reliability of oil production forecasting.

If you would like to have a closer look at the project, you can view the source code on GitHub by clicking on Source Code.