Výsledky vyhledávání - "Mohammad Mehrad"

Akademický článek

Hybrid Machine-Learning Model for Accurate Prediction of Filtration Volume in Water-Based Drilling Fluids

Autor: Shadfar Davoodi, Mohammed Al-Rubaii, David A. Wood, Mohammed Al-Shargabi, Mohammad Mehrad, Valeriy S. Rukavishnikov

Publikováno v: Applied Sciences, Vol 14, Iss 19, p 9035 (2024)

Accurately predicting the filtration volume (FV) in drilling fluid (DF) is crucial for avoiding drilling problems such as a stuck pipe and minimizing DF impacts on formations during drilling. Traditional FV measurement relies on human-centric experim

Externí odkaz: https://doaj.org/article/d5c6ad8d4e184232977742b9b4dc452b

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Akademický článek

A new robust predictive model for lost circulation rate using convolutional neural network: A case study from Marun Oilfield

Autor: Farshad Jafarizadeh, Babak Larki, Bamdad Kazemi, Mohammad Mehrad, Sina Rashidi, Jalil Ghavidel Neycharan, Mehdi Gandomgoun, Mohammad Hossein Gandomgoun

Publikováno v: Petroleum, Vol 9, Iss 3, Pp 468-485 (2023)

A major cause of some of serious issues encountered in a drilling project, including wellbore instability, formation damage, and drilling string stuck – which are known to increase non-productive time (NPT) and hence the drilling cost – is what w

Externí odkaz: https://doaj.org/article/6f5bcfc7b9ab4f85bd273eebe727956c

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Akademický článek

Estimation of geomechanical rock characteristics from specific energy data using combination of wavelet transform with ANFIS-PSO algorithm

Autor: Mohammad Mohammadi Behboud, Ahmad Ramezanzadeh, Behzad Tokhmechi, Mohammad Mehrad, Shadfar Davoodi

Publikováno v: Journal of Petroleum Exploration and Production Technology, Vol 13, Iss 8, Pp 1715-1740 (2023)

Abstract The geomechanical characteristics of a drill formation are uncontrollable factors that are crucial to determining the optimal controllable parameters for a drilling operation. In the present study, data collected in wells drilled in the Maru

Externí odkaz: https://doaj.org/article/a98fa9b1ef7b4d21aac5cbe442583f77

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Akademický článek

Design and validation of a therapy program based on the internal family systems model and its efficacy on internet addiction

Autor: Mohammad Mehrad Sadr, Ahmad Borjali, Hossein Eskandary, Ali Delavar

Publikováno v: مجله علوم روانشناختی, Vol 22, Iss 121, Pp 19-36 (2023)

Background: Different treatment approaches only target internet addiction symptoms and do not address its cause. The internal family systems model is a non-pathological and experiential approach to treating disorders that deals with the cause instead

Externí odkaz: https://doaj.org/article/665a060bb5fa49ebb23c4b3532a773b4

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Akademický článek

Prediction of permeability from well logs using a new hybrid machine learning algorithm

Autor: Morteza Matinkia, Romina Hashami, Mohammad Mehrad, Mohammad Reza Hajsaeedi, Arian Velayati

Publikováno v: Petroleum, Vol 9, Iss 1, Pp 108-123 (2023)

Permeability is a measure of fluid transmissibility in the rock and is a crucial concept in the evaluation of formations and the production of hydrocarbon from the reservoirs. Various techniques such as intelligent methods have been introduced to est

Externí odkaz: https://doaj.org/article/cf4ce6f703aa4c2286e45606ec1d89e7

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Akademický článek

Prediction of permeability of highly heterogeneous hydrocarbon reservoir from conventional petrophysical logs using optimized data-driven algorithms

Autor: Amirhossein Sheykhinasab, Amir Ali Mohseni, Arash Barahooie Bahari, Ehsan Naruei, Shadfar Davoodi, Aliakbar Aghaz, Mohammad Mehrad

Publikováno v: Journal of Petroleum Exploration and Production Technology, Vol 13, Iss 2, Pp 661-689 (2022)

Abstract Permeability is an important parameter in the petrophysical study of a reservoir and serves as a key tool in the development of an oilfield. This is while its prediction, especially in carbonate reservoirs with their relatively lower levels

Externí odkaz: https://doaj.org/article/8c6c3197e9714e7890181643ff05e905

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Akademický článek

Numerical Investigation of the Impact of Geomechanical Parameters of Formations on Well Integrity of One of the Iranian Oil Fields

Autor: Eissa Khodami, Ahmad Ramezanzadeh, Mehdi Noroozi, Mohammad Mehrad

Publikováno v: International Journal of Mining and Geo-Engineering, Vol 54, Iss 2, Pp 179-183 (2020)

Well integrity is defined as the application of technical and operational solutions to reduce the uncontrollable risk of fluids leakage in the well lifetime. In any drilling and production operation, lack of knowledge about geomechanical behavior of

Externí odkaz: https://doaj.org/article/7339e20aded64be4affcabcf072076c6

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Akademický článek

Confirmatory Factor Structure of Depression, Anxiety and Stress Scale in Students

Autor: Yousef Aazami, Mahdi Khanjani, Mohammad Mehrad Sader

Publikováno v: Journal of Mazandaran University of Medical Sciences, Vol 27, Iss 154, Pp 94-106 (2017)

Background and purpose: Depression, anxiety, and stress and measuring their levels are regarded as important issues in health. This research aimed at investigating the sex equivalence and invariance of Depression, Anxiety and Stress Scale (DASS) in I

Externí odkaz: https://doaj.org/article/28782800159e4e4ba37cd4d3011b3fcd

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