

A practical application of synthetic logs derived from drilling parameters for geomechanical modeling and drilling optimization
An review of the practical applications of synthetic AI-predicted logs for calculating geomechnical properties and improve drilling efficiency
Authors
Saudi Aramco and Quantico
Publication
Private
Year
2022
Novel machine learning workflow for rock property prediction in the geologically complex presalt Santos basin, Brazil
A unique workflow for rock property prediction based on supervised artificial neural networks to characterize carbonate reservoirs in the Santos Basin, Brazil.
Authors
Quantico & Shell
Publication
Private
Year
2021
Using Machine Learning to Better Define Landing Zones
A study that focuses on using machine learning to better define landing zones in thin targets.
Authors
Quantico & TGS
Publication
Private
Year
2020
Seeing-ahead-of-the-bit: A game changer enabled by Machine Learning
A study that covers the fundamentals of machine learning and autonomous real-time earth models.
Authors
Quantico
Publication
ARMA
Year
2020
Artificial Intelligence Logs for Formation Evaluation Using Case Studies in Gulf of Mexico and Trinidad & Tobago
Using machine learning to create formation evaluation logs from drilling data in the Gulf of Mexico.
Authors
Shell & Quantico
Publication
SPE
Year
2019
Optimization of Bakken Well Completions in a Multivariate World
Optimization of well completions using QFrac in the Bakken Formation.
Authors
Sinclair Oil Corp, Drilling Info, Quantico
Publication
SPE
Year
2018
Big Data Yields Completion Optimization: Using Drilling Data to Optimize Completion Efficiency in a Low Permeability Formation
Study focused on the growth of fractures from stage clusters.
Authors
Frac Diagnostic LLC & Quantico
Publication
SPE
Year
2016