An Integrated Framework to Automate the Prediction of oil by Applying Machine Learning Techniques on the Information Retrieved from Upstream Segment

Dr. Mohammed. Faisal, A.K. Kavuru, Dr.R.J. Ramasree and Sree Vaishnavi Yalakaturi

Oil and Gas is the industry with a large share of economy and is the main income source for many of the countries in the world. There are many technology advancements in each stream of the industry and the implementation of Machine learning tools, and technologies are helping in achieving high productivity. The current paper focuses on upstream segment production area, where the data is generated along with the Oil from the wells as a data stream and is analysed in detail to predict the average oil rate. R language is used to input the data that is extracted from oil wells and Linear Regression is applied to predict the average oil rate based on various dependent variables.

Volume 12 | 04-Special Issue

Pages: 320-331

DOI: 10.5373/JARDCS/V12SP4/20201495