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papers

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

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