Oilfield Technology: Mastering Well Placement Through Reinforcement Learning
ORIGINALLY PUBLISHED: AUGUST 2021
AUTHOR: VIDYASAGAR ANANTHAN & OTHERS FOR OILFIELD TECHNOLOGY
Los Angeles, CA
Vidyasagar Ananthan, Senior Machine Learning Scientist for Beyond Limits, penned a technical article that was published in the August issue of Oilfield Technology, discussing the important role reinforcement learning plays in the optimization of well placement and field planning for the upstream sector.
“Appraising the preservation of hydrocarbons within discovery fields is a critical aspect during exploration. This involves detailed seismic surveys, geostatistical analyses and subsequent high-resolution simulations involving geological models or digital twins representing the natural subsurface strata. In order to understand the practical production limit of a field, it is necessary to find the best possible drilling locations, trajectories and control strategies given practical constraints – constituting the field planning process. Optimal placement and control of wells within such a greenfield development is a sequential decision-making problem of spatiotemporal nature.”
Read the full article, Mastering Well Placement Through Reinforcement Learning, on pages 75-79, HERE.
DEEP DIVE INTO ALL BEYOND LIMITS’ PRODUCTS & SOLUTIONS OPTIMIZING THE UPSTREAM SECTOR – HERE.