Abstract: Embodiments of systems and methods for predicting when a dry oil producing well is expected to transition to a wet oil producing well, the system configured to generate predictions from multiple databases of information. A first database is designed to store real time data about an active producing well and a second database can be a historical production information database, such as an Online Transactions Processing (OLTP) database. The data from both databases can be normalized, compared, and correlated to create a predictive model that accurately predicts when a particular well is expected to transition from a dry oil producing well to a wet oil producing well. The system and method can be configured to use many different techniques including an autoregressive integrated moving average equation to create a predictive model based off the normalized data from the multiple databases.

Abstract: Embodiments of systems and methods for predicting when a dry oil producing well is expected to transition to a wet oil producing well, the system configured to generate predictions from multiple databases of information. A first database is designed to store real time data about an active producing well and a second database can be a historical production information database, such as an Online Transactions Processing (OLTP) database. The data from both databases can be normalized, compared, and correlated to create a predictive model that accurately predicts when a particular well is expected to transition from a dry oil producing well to a wet oil producing well. The system and method can be configured to use many different techniques including an autoregressive integrated moving average equation to create a predictive model based off the normalized data from the multiple databases.