Published paper in Journal of Natural Gas Science and Engineering on evaluation of production drivers in the Marcellus Shale using machine learning approaches
Artificial intelligence and machine learning (ML) are being applied to many oil and gas (O&G) applications and seen as novel techniques that may facilitate efficiency gains in exploration and production operations. Significant improvements in that regard are likely to occur when ML can be applied to evaluate O&G challenges with inherent synergies that may have […]
