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DEVELOPMENT OF CRITICAL TOTAL DRAWDOWN PRESSURE AND GEOMECHANICAL PROPERTIES MODELS: A DATA-DRIVEN APPROACH

Critical total drawdown (CTD) along with the sand production index method (based on static Young’s modulus (Es) and static Poisson's Ratio (????s)) are commonly used to detect sand production. Some CTD, Es, and ????s models are used in the literature. However, these published models have limita...

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Main Author: ALAKBARI, FAHD SAEED
Format: Thesis
Language:English
Published: 2023
Subjects:
TA Engineering (General). Civil engineering (General)
Online Access:http://utpedia.utp.edu.my/id/eprint/24671/1/FahdSaeedAlakbari_19001032.pdf
http://utpedia.utp.edu.my/id/eprint/24671/
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spelling oai:utpedia.utp.edu.my:246712024-08-02T07:32:08Z http://utpedia.utp.edu.my/id/eprint/24671/ DEVELOPMENT OF CRITICAL TOTAL DRAWDOWN PRESSURE AND GEOMECHANICAL PROPERTIES MODELS: A DATA-DRIVEN APPROACH ALAKBARI, FAHD SAEED TA Engineering (General). Civil engineering (General) Critical total drawdown (CTD) along with the sand production index method (based on static Young’s modulus (Es) and static Poisson's Ratio (????s)) are commonly used to detect sand production. Some CTD, Es, and ????s models are used in the literature. However, these published models have limitations: lack of accuracy, limited data ranges, and lack of proving the relationships between the inputs and outputs. Moreover, the previous Es and ????s models which are used to determine the sand production prediction fail to detect the accurate sand onset tendency and rock’s types. This study aims to apply data-driven approaches to accurately and reliably predict the CTD, Es, and ????s for accurate evaluation of the sand rock consolidation and sand onset tendency. Different data-driven models, namely the Adaptive-Neuro-Fuzzy-Inference-System (ANFIS) and Gaussian-process-regression (GPR) were developed based on 23 wells from the Adriatic Sea for the CTD, 1853 and 1691 datasets from the United States, Malaysia, India, Saudi Arabia, and Venezuela for the Es and ????s. 2023-02 Thesis NonPeerReviewed text en http://utpedia.utp.edu.my/id/eprint/24671/1/FahdSaeedAlakbari_19001032.pdf ALAKBARI, FAHD SAEED (2023) DEVELOPMENT OF CRITICAL TOTAL DRAWDOWN PRESSURE AND GEOMECHANICAL PROPERTIES MODELS: A DATA-DRIVEN APPROACH. Doctoral thesis, UNSPECIFIED.
institution Universiti Teknologi Petronas
building UTP Resource Centre
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Petronas
content_source UTP Electronic and Digitized Intellectual Asset
url_provider http://utpedia.utp.edu.my/
language English
topic TA Engineering (General). Civil engineering (General)
spellingShingle TA Engineering (General). Civil engineering (General)
ALAKBARI, FAHD SAEED
DEVELOPMENT OF CRITICAL TOTAL DRAWDOWN PRESSURE AND GEOMECHANICAL PROPERTIES MODELS: A DATA-DRIVEN APPROACH
description Critical total drawdown (CTD) along with the sand production index method (based on static Young’s modulus (Es) and static Poisson's Ratio (????s)) are commonly used to detect sand production. Some CTD, Es, and ????s models are used in the literature. However, these published models have limitations: lack of accuracy, limited data ranges, and lack of proving the relationships between the inputs and outputs. Moreover, the previous Es and ????s models which are used to determine the sand production prediction fail to detect the accurate sand onset tendency and rock’s types. This study aims to apply data-driven approaches to accurately and reliably predict the CTD, Es, and ????s for accurate evaluation of the sand rock consolidation and sand onset tendency. Different data-driven models, namely the Adaptive-Neuro-Fuzzy-Inference-System (ANFIS) and Gaussian-process-regression (GPR) were developed based on 23 wells from the Adriatic Sea for the CTD, 1853 and 1691 datasets from the United States, Malaysia, India, Saudi Arabia, and Venezuela for the Es and ????s.
format Thesis
author ALAKBARI, FAHD SAEED
author_facet ALAKBARI, FAHD SAEED
author_sort ALAKBARI, FAHD SAEED
title DEVELOPMENT OF CRITICAL TOTAL DRAWDOWN PRESSURE AND GEOMECHANICAL PROPERTIES MODELS: A DATA-DRIVEN APPROACH
title_short DEVELOPMENT OF CRITICAL TOTAL DRAWDOWN PRESSURE AND GEOMECHANICAL PROPERTIES MODELS: A DATA-DRIVEN APPROACH
title_full DEVELOPMENT OF CRITICAL TOTAL DRAWDOWN PRESSURE AND GEOMECHANICAL PROPERTIES MODELS: A DATA-DRIVEN APPROACH
title_fullStr DEVELOPMENT OF CRITICAL TOTAL DRAWDOWN PRESSURE AND GEOMECHANICAL PROPERTIES MODELS: A DATA-DRIVEN APPROACH
title_full_unstemmed DEVELOPMENT OF CRITICAL TOTAL DRAWDOWN PRESSURE AND GEOMECHANICAL PROPERTIES MODELS: A DATA-DRIVEN APPROACH
title_sort development of critical total drawdown pressure and geomechanical properties models: a data-driven approach
publishDate 2023
url http://utpedia.utp.edu.my/id/eprint/24671/1/FahdSaeedAlakbari_19001032.pdf
http://utpedia.utp.edu.my/id/eprint/24671/
_version_ 1806446840105664512
score 13.211869

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