Data Mining for Oil & Gas

The process of exploring and exploiting Oil and Gas (O&G) generates a lot of data that can bring more efficiency to the industry. With the high rate of data expansion, companies are scrambling to develop ways to develop near-real-time predictive analytics, data mining and machine learning capabilities, and are expanding their data storage infrastructure and resources. With these new developments come the challenges of managing data growth, integrating intelligence tools, and analyzing the data to glean useful insights. O&G companies need data driven solutions to economically extract value from very large volumes of a wide variety of data generated from exploration, well drilling, and production devices and sensors.

Data mining for the O&G industry includes the following roles throughout the lifecycle of the reservoir: locating hydrocarbons, managing geological data, drilling and formation evaluation, well construction, well completion, and optimizing production through the life of the oil field. For each of these phases, data mining plays a significant role. Depending on which phase we are talking about, knowledge creation through scientific models, data analytics, and machine learning, and an effective, productive, and on demand data insight are critical for decision making within the organization.

This community forum stems from the first Workshop on Data Mining for Oil and Gas (DM4OG'17) and aims to provide a hub for data scientists, computer scientists, geoscientists, and engineers that work on the significant challenges arising from the synergy between data science, machine learning, and the modeling and optimization problems in the O&G industry.

INESC TEC - Laboratório Associado