Knowing the production potential of an oil well is the most critical information Oil and Gas producers need. Knowing how long a well will produce for and what the expected output will be allows for better profits and resource management.
When an oil and gas client’s existing methodologies failed to accurately manage their reserves, our solution involved the construction of several advanced statistical model tests to better understand the problem. Equipped with this data, new methodologies were tested in concert with current Monte Carlo methods to confirm the validity of our new designs. The result was a more accurate management system, increased revenue and extended well output timelines.
This was an earlier project utilizing big data, machine learning and AI analysis to discover new relevant information that was previously ignored by the Oil and Gas industry. Once configured the AI was set upon decades of historical data using unsupervised machine learning tools to discover these new metrics that were previously ignored. After identifying several new relevant metrics to increase efficiency in well production and prediction confidence several hundred wells that were considered high value wells were actually revealed to be the exact opposite and should be released to reduce loss. On the flip side of this about 50 wells that were being considered for sale were taken off the market because of higher expected output or had their sales prices adjusted to reflect this new information. This allowed the client to make millions more in revenue.
The Nu-Worx teams’ knowledge in big data, AI and machine learning could easily see such a solution be implemented in almost any aging industry to find new metrics to increase a client’s competitive advantage in the industry. In today’s world data is power.