Artificial Intelligence Gives Crude Oil Price Forecasting New Ground

The best way to predict the future is to invent it via cutting-edge technologies. The accurate crude oil price forecasting is mandatory for enterprises to grow in this meantime where the recession has altered everything and ruined the way businesses operate. Now, a question arises, why is crude oil so important? In short, its shortage can annihilate even the global economy.

The unrefined or raw petroleum is called crude oil when refined, it yields a lot of byproducts, hydrocarbons, and their derivatives. As the oil and gas sector is competitive, their pricing depends on limitless factors, which can be internal or external.

In this article, we will elaborate on some challenges to crude oil price forecasting and solutions to these challenges from oil and gas Industry experts. Let’s start by elaborating on current crude oil prices globally.

Current Crude Oil Prices: Statistics, Trends

Bloomberg reported– The current WTI (West Texas Intermediate) crude oil prices in January 2023 in the United States are about $81.62/bbl, Brent crude oil is about $87.61/bbl, and Natural gas is $3.52/MMBtu. These prices are expected to fluctuate in upcoming months but they may change due to external factors including democratic policies, crude oil investors, taxes, and the economy of a country.

In addition, the annual average of OPEC oil prices by August 2022 is $105.1/bbl. This is an increase from $69.72/bbl. compared to the previous year and comes in the wake of sanctions on Russia due to the Russia-Ukraine war as well as global energy supply shortage. For the moment, let’s shed some light on crude oil price forecasting techniques using artificial intelligence and machine learning to avoid any capital investment in the Oil & Gas industry.

Crude Oil Price Forecasting Techniques

Oil and gas prices are volatile and fluctuate depending on numerous factors. This volatility can be handled using different machine and deep learning techniques. The algorithms assist in various verticals of forecasting, but they are pretty helpful in analyzing crude oil data. We have considerable forecasting techniques as below:

Time Series Forecasting

Time series forecasting is performed using various techniques, including Non-heuristic (Artificial Neural Network), Stochastic (Jump diffusion), and Linear Regression (ARIMA, GARCH). These strategies are applied according to underlying use cases, data availability, and business requirements. Furthermore, time series forecasting works on historical data to predict future outcomes over time labeled data.

Data Mining

Data mining has changed the way price prediction is done due to abundant data resources. Data analytics uses data mining to recognize massive datasets’ patterns, correlations, and anomalies. In addition, Fuzzy Logic and Chaotic Models are used in crude oil price forecasting.

Reinforcement Learning

One step ahead to digital transformation where machines behave according to argument data insights and activity feeds. In reinforcement learning, machines forecast crude oil prices based on penalty and reward. In addition, It uses Game Theory and production cost-based algorithms for simple crude oil price forecasting.

Global Challenges to Businesses for Today’s Volatile Oil Prices

The ongoing fluctuating prices of crude oil and natural gas result in business crises. The petrochemical companies lose millions of dollars when they buy and sell products at different places without any fixed plan or schedule. Moreover, businesses face the following challenges due to crude oil price volatility.

Crude Oil Demand and Supply

The abrupt trends in crude oil supply and demand are the biggest challenges to businesses these days. The imbalance between supply and demand results in high prices & challenges to petrochemical companies. In addition, the United States, Saudi Arabia, and Russia are three big oil producers around the globe, So demand & supply are also affected by international relations.

Regional Crisis

The international relationships between countries, states, or regions also affect commodity prices, including crude oils. In the United States, the oil prices are not controlled by the government itself, but oil suppliers or importers from different states of America decide petrochemical prices.

In other words, It’ll not be wrong that the oil prices are fixed by gigantic companies around multiple states of America. Furthermore, the political bodies with billions of dollars worth also put some part in determining crude oil pricing. So, our time series crude oil price forecasting techniques assist businesses in growing in such an unpredictable market.

Exploration Field Hurdles

The extraction of crude oil varies in the form where the traces of oil are found. It can be from oceans or mountains with the hardest crust to drill. The extraction of crude oil from oceans sometimes results in costs because it depends on how much effort and time were put into extracting the crude oil. On the other hand, mountains with the hardest crust also result in high upstream costs & ultimately result in volatile oil prices.


The continuous weather changes affect the upstream process and result in delays. Exploration near oceans is unpredictable due to abrupt weather changes & high equipment maintenance. These natural factors also put efforts into the fuel market.

Fuel Market Volatility

As we discussed earlier, the pricing of crude or raw oils relies on countless factors, but our time series forecasting tools can assist businesses with high accuracy. The crude oil price forecasting can be done accurately with the help of a controlled environment & solutions from data analytics companies that can assist in market volatility prediction.

How Odyssey Analytics Transforms Crude Oil Business: Solution to Challenges

Artificial intelligence has changed how businesses operate and regulate their operations via digital transformation. Odyssey Analytics has been in the data analysis and data science domain for two years, with four products in time series forecasting, computer vision & data analytics.

Odyssey analytics data engineers, analysts, and scientists work on common grounds to get an efficient solution for crude oil price forecasting to help oil and gas companies maximize profits and grow exponentially without any risk of loose business capital.

Frequently Asked Questions

What is crude oil?

The unprocessed or raw petroleum material is said to be crude oil. The crude oil is processed using refineries to extract byproducts and additional hydrocarbons and their derivatives.

What are the techniques to forecast oil prices?

There are multiple techniques in artificial intelligence and machine learning for price forecasting, but time series forecasting uses statistical analysis, data mining, and simulations using reinforcement learning techniques.

How to optimize the oil pricing process?

The oil pricing process can be optimized by deploying an automatic or self-decisive system when making decisions based on real-time scenarios and reacting accordingly.

How does artificial intelligence help oil and gas companies?

The oil and gas industry is volatile, and prices fluctuate regularly. On the other hand, this industry is also dangerous and critical for workers. So, artificial intelligence will automate the process from upstream to downstream via data analytics and forecasting.

How many liters are there in one barrel?

Generally, One barrel (bbl) of oil contains approximately 159 liters (L) of fuel.