Firstly, what is Data Science?
Data science is using analysis of past and current data to predict future performance or results.
Oil and gas companies collect a huge amount of data in their exploration, drilling, and production activities. They have huge volumes of unused and undervalued data.
With the advances in data science and machine learning, oil companies have begun to realize the value of the data they have been collecting.
They now realise that managing this data and using it as a strategic asset can significantly impact its operational success, increase safety and reduce operational cost.
For example, in exploration, seismic data and geological data, such as rock types in nearby wells, can be used to predict oil pockets.
In production, production data can be used to forecast future production capacity, schedule production, and determine the number of future wells to be drilled.
In drilling, engineers can use drilling data to determine the best drilling locations, reduce costs, improve safety and shorten the drilling time.
Here are several articles by Yohanes Nuwara on the applications of data science and machine learning in oil and gas operations.
ML sonic log prediction in Volve field – https://towardsdatascience.com/prediction-of-p-sonic-log-in-the-volve-oil-field-using-machine-learning-9a4afdb92fe8
ML prediction in hydraulic fracturing – https://medium.com/analytics-vidhya/machine-learning-for-prediction-in-hydraulic-fracturing-43de92b0e10a
ML lithology prediction from drilling data – https://towardsdatascience.com/oilfield-lithology-prediction-from-drilling-data-with-machine-learning-520ee9ff6e7c
Rate of penetration optimization using Particle Swarm Optimization – https://towardsdatascience.com/faster-drilling-with-machine-learning-and-particle-swarm-optimization-335bb28d687
As the Oil and Gas industry grows and becomes receptive to big data and the use of Data Science, it can only move forward.
If you want to learn how to use Data Science and its applications, Yohanes Nuwara will teach “DATA SCIENCE AND MACHINE LEARNING IN OIL AND GAS” on May 7, 11, 14, 18, and 21, 2022.