How did the model come up with its prediction? Here we look at an example use case in the Williston Basin, using Novi’s Production Modeler to see which wells the model thought were Analogs.

What are the best remaining acreage blocks in Whiting’s North Dakota portfolio? With Prediction Engine, you can quickly and easily lay out well sticks and get predictions for different designs. Here, we walk you through how to configure & generate economics across the acreage.

At $30 oil, marginal zones become uneconomic. What is the impact on EURs and returns if those zones are infilled two years in the future? In this video, we take a look at the impact of delays on Bone Springs Third Sand and Wolfcamp A, B, and C zones in Parsley’s newly-acquired legacy Jagged Peak acreage in the southeastern Delaware Basin.

In this video we walk through how Novi Shapley data and confidence interval data can be used to gain confidence in machine learning model predictions and handicap possible well performance using model confidence as a proxy for risk. You can review the blog post here.

In this Novi product video, Novi Technical Advisor John Chaplin walks through how a user can create Novi Prediction Engine Outputs, using NBL’s DUC inventory as an example, and publish these to Novi Cloud for analysis. To see the full description of the inputs and how we put this together read the blog post here.

In this Novi product video, Novi Technical Advisor John Chaplin walks through an analysis of NBL’s Delaware DUC inventory and suggests changes in completion design in this sub $30 WTI price environment based on Novi Prediction Engine Outputs published to Novi Cloud. To see the full description of the inputs and how we put this together read the blog post here.

In this Novi product video, Novi Technical Advisor John Chaplin walks through and analysis of QEP’s Midland asset and suggests changes in capital allocation in this sub $30 WTI price environment based on Novi Prediction Engine Outputs published to Novi Cloud. To see the full description of the inputs and how we put this together read the blog post here.

This video goes into detail on Novi’s subsurface model for the Williston Basin in North Dakota and is incorporated in a Novi blog post on this same subject. Novi algorithms analyzed & extracted log data, conducted a principal component analysis, and used that information for model training. When combined with SHAP values, this workflow becomes a powerful way to generate rock quality maps using machine learning.

A live video demonstration of Novi’s Prediction Engine version 2 software. Quickly create robust economic scenarios when valuing acreage, searching for the best development scenario given capital constraints, or understanding how Novi’s models interpret subsurface, stacking, spacing and stimulation intensity scenarios.

Should all formations be developed at the same time (co-develop) or, should an Operator develop first tier formation targets first, then infill secondary formations later? This video demonstrates how Novi Data consumed through Novi Cloud can help answer this complex question, and define the economic loss of infilling vs. co-development.