Developing a Machine Learning Based Approach for Fractured Zone Detection by Using Petrophysical Logs

Text Registration

Developing a Machine Learning Based Approach for Fractured Zone Detection by Using Petrophysical Logs

Status

Published

on 2 Jul 2021

Year of Creation

2021

Haleh Azizi

Registration Number

TX0008997947

on 2 Jul 2021

The U.S. Copyright record (Registration Number: TX0008997947) dated 2 Jul 2021, pertains to an electronic file (eService) titled "Developing a Machine Learning Based Approach for Fractured Zone Detection by Using Petrophysical Logs" created in 2021. The copyright holder is Haleh Azizi, known for their creative contributions in text registration. For any inquiries concerning this copyrighted material, kindly reach out to Haleh Azizi.

Haleh Azizi

Application Details

Registration Number

TX0008997947

Registration Date

7/2/2021

Year of Creation

2021

Agency Marc Code

DLC-CO

Record Status

New

Physical Description

Electronic file (eService)

First Publication Nation

United States

Personal Authors

Haleh Azizi

Notes

Rights Note: Mark Dill, ProQuest, LLC, 789 E. Eisenhower Parkway, Ann Arbor, MI, 48108-3218, United States, (800) 521-0600, disspub@proquest.com

Statements

Application Title Statement: Developing a Machine Learning Based Approach for Fractured Zone Detection by Using Petrophysical Logs

Author Statement: Haleh Azizi Citizenship: not known Authorship: text

Notes

Rights Note: Mark Dill, ProQuest, LLC, 789 E. Eisenhower Parkway, Ann Arbor, MI, 48108-3218, United States, (800) 521-0600, disspub@proquest.com

Statements

Application Title Statement: Developing a Machine Learning Based Approach for Fractured Zone Detection by Using Petrophysical Logs

Author Statement: Haleh Azizi Citizenship: not known Authorship: text

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