District Engineer, Samson Energy
Kale Wallace first started using Mathematica in university courses and has since used it in his work at Southwestern Energy and Samson Energy for data handling and image processing. At Southwestern Energy, Wallace built a well productivity prediction model analyzing millions of lines of data and using machine learning to predict well performance based on drilling and completion parameters. He has also created field-development visualizations showing wells brought online and their corresponding production and cashflow. His replication of the ARIES economics engine in Mathematica allowed probabilistic (Monte Carlo) economics methods, full-field development scenarios, break-even calculations, and go-forward recommendations to be evaluated much more quickly than could be done in ARIES.