Reviewing Delaware Basin production drivers with Novi Cloud Outputs
Novi Releases Data Engine!
Novi Presents at SPE Dallas Section Study Group: Machine Learning 101 in the Midland Basin
AAPG 2020: Before the Basin Model: Using ML & Formation Tops to Understand the Effect of Burial History (ID 4694)
AAPG 2020: Tailoring Completions to Geology: A Machine Learning Approach (ID 4686)
AAPG 2020: Prior Well Depletion or Interwell Spacing? Isolating the Causes of Spacing Degradation in the Williston Basin (ID 4697)
Novi Water Modeling featured in JPT September Issue
URTeC 2020: Deriving Time-Dependent Scaling Factors for Completions Parameters in the Williston Basin using a Multi-Target Machine Learning Model and Shap Values (ID 3103)
URTeC 2020: Predicting Water Production in the Williston Basin using a Machine Learning Model (ID 2756)
URTeC 2020: Decomposition of Publicly Reported Combined Hydrocarbon Streams using Machine Learning in the Montney and Duvernay (ID 2795)
URTeC 2020: GeoSHAP: A Novel Method of Deriving Rock Quality Index from Machine Learning Models and Principal Components Analysis (ID 2743)
URTeC 2020: The Impact of Interwell Spacing Over Time: A Machine Learning Approach (ID 2676)
URTeC 2020: The Impact of Spacing and Time on Gas/Oil Ratio in the Permian Basin: A Multi-Target Machine Learning Approach (ID 2800)
URTeC 2020: Evaluating the Impact of Precision Targeting on Production in the Midland Basin using Machine Learning Algorithms (ID 3062)
URTeC 2020: Benchmarking Operator Performance in the Williston Basin using a Predictive Machine Learning Model (ID 2750)
Contributing Wells — Using Novi Production Modeler Software to See Which Wells Contributed to the Prediction
Using Prediction Engine to Evaluate Whiting’s Undrilled Acreage
Impact of delay-and-infill strategy on recoveries and returns :: Parsley – Jagged Peak acreage
Using game theory and confidence interval outputs from a machine learning model to risk adjust oil well returns
Iterating and optimizing completion designs across NBL’s entire Delaware DUC inventory in minutes
Given sub-$30 wti strip, how can NBL maximize returns on their DUC inventory?
Changing plans on a dime: analyzing QEP’s Midland asset given sub-$30 WTI strip with Novi Prediction Engine
Deriving a regional subsurface model in a day from logs and tops – Novi Subsurface data extraction workflow
AAPG Explorer article “Is the Next Oil Production Breakthrough Already Here?” featuring Novi President Jon Ludwig
Prediction Engine Version 2 Software Demonstration
SHELL iSHALE® COLLABORATES WITH NOVI
JPT Article Featuring Novi – Rapid Evaluation of Development Ideas Has Engineers Thinking: What If?
Novi / Range Resources SPE-191796-18ERM-MS: Integrating Big Data Analytics Into Development Planning Optimization
Co-Develop vs. Infill – A Complex Question
Barclays Bank "Frac to the Future" Analyst Report (rel: January 2020)
Evaluating PV10 acquisition scenarios using Novi Cloud outputs in Spotfire
Using Novi Prediction Engine to evaluate Parsley Energy’s acquisition of Jagged Peak
Novi AAPG ACE 2019 Paper – Production and Subsurface Machine Learning Model for Predicting Hydrocarbon Recovery
Picking the Best Statistical Approach for Modeling Hydrocarbon Systems
5 Ways to Prevent Over-Engineered and Overpriced Wells