Novi Technical Papers
Novi Technical Papers are written and peer-reviewed by experts in oil & gas, machine learning, and data science. Browse our technical papers on the latest advances in oil & gas focused machine learning and data Science
- All
- AAPG 2020
- URTeC 2020
- URTeC 2021
- URTeC 2022
- All
- AAPG 2020
- URTeC 2020
- URTeC 2021
- URTeC 2022
[URTeC 2022] The Diminishing Returns of Lateral Length Across Different Basins (ID 3723784)
The Diminishing Returns of Lateral Length Across Different Basins Talk Details:: Tuesday, June 21st at 2:15 PM | Room 371 Theme 7: Applications in Reserves …
[URTeC 2022] Accelerating field optimization for Shell in the Neuquén Basin using Novi Labs machine learning
Accelerating field optimization for Shell in the Neuquén Basin using Novi Labs machine learning AUTHORS:: DP. Zannitto2, C. Kosa1 (1. Novi Labs 2. Shell …
[URTeC 2022] Understanding the Spacing, Completions, and Geological Influences on Decline Rates and B Values (ID 3723711)
Understanding the Spacing, Completions, and Geological Influences on Decline Rates and B Values Talk Details:: Wednesday, July 28th at 11:15 AM | Room 371 Theme …
[URTeC 2022] Using Machine Learning to Customize Development Unit Spacing for Maximum Acreage Value (ID 3723023)
Using Machine Learning to Customize Development Unit Spacing for Maximum Acreage Value Talk Details:: Wednesday, July 22nd at 8:55 AM | Room 360 Theme …
[URTeC 2022] How does the impact of completions change over the life of a well? A
comparison across the major US unconventional plays using machine learning (ID 3723930)
How does the impact of completions change over the life of a well? A comparison across the major US unconventional plays using machine learning …
[URTeC 2022] How Much Better Could We Have Done? Using a Time Machine Method to Quantify the Impact of Incremental Geologic data on Machine Learning Forecast Accuracy (ID 3723907)
How Much Better Could We Have Done? Using a Time Machine Method to Quantify the Impact of Incremental Geologic data on Machine Learning Forecast Accuracy …