Journal of
Systemics, Cybernetics and Informatics
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ISSN: 1690-4524 (Online)


Peer Reviewed Journal via three different mandatory reviewing processes, since 2006, and, from September 2020, a fourth mandatory peer-editing has been added.

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Published by
The International Institute of Informatics and Cybernetics


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(A Community of about 40.000.000 Academics)


Honorary Editorial Advisory Board's Chair
William Lesso (1931-2015)

Editor-in-Chief
Nagib C. Callaos


Sponsored by
The International Institute of
Informatics and Systemics

www.iiis.org
 

Editorial Advisory Board

Quality Assurance

Editors

Journal's Reviewers
Call for Special Articles
 

Description and Aims

Submission of Articles

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Information to Contributors

Editorial Peer Review Methodology

Integrating Reviewing Processes


Quantitative Endosurgery Process Analysis by Machine Learning Method
Bojan Nokovic, Andrew Lambe
(pages: 1-7)

Modelling Student Performance in a Structural Steel Graduate-Based Module: A Comparative Analysis Between K-Nearest Neighbor and Dummy Classifiers
Masengo Ilunga, Omphemetse Zimbili, Phahlani Mampilo, Agarwal Abhishek
(pages: 8-15)

Interoperable Digital Skills for Foreign Languages Education in the COVID-19 Paradigm
Rusudan Makhachashvili, Ivan Semenist, Iryna Vorotnykova
(pages: 16-20)

Education, Training and Informatics Go Hand in Hand in (Foreign) Higher Education Institutions (HEIs) – Case Studies From Live and Online Classrooms
Ekaterini Nikolarea
(pages: 21-29)

Enhancing Pedagogical and Digital Competencies Through Digital Tools: A Proposal for Semi-schooled Language Teaching Programs in Oaxaca, Mexico
José de Jesús Bautista Hernández, Eduardo Bustos Farías, Norma Patricia Maldonado Reynoso
(pages: 30-35)

Railway Track Degradation Modelling Using Finite Element Analysis: A Case Study in South Africa
Ntombela Lunga, Masengo Ilunga
(pages: 36-50)

Continuum of Academic Collaboration: Issues of Inconsistent Terminology in Multilingual Context
Cristo Leon, James Lipuma, Marcos O. Cabobianco, Maria B. Daizo
(pages: 51-62)

Peat Resource Management and Climate Change Mitigation Issues – Case of Latvia
Anita Titova, Natalja Lace
(pages: 63-70)

Using Geospatial Computation Intelligence for Mapping Temporal Evolution of Urban Built-up in Selected Areas of the Ekurhuleni Municipality, South Africa
Jo-Anne Correia, Masengo Ilunga
(pages: 71-80)

Cybernetics and Informatics of Generative AI for Transdisciplinary Communication in Education
Rusudan Makhachashvili, Ivan Semenist
(pages: 81-88)

Navigating Psychological Riptides: How Seafarers Cope and Seek Help for Mental Health Needs
Coleen Abadicio, Stella Louise Arenas, Rosette Renee Hahn, Angel Berry Maleriado, Ramon Miguel Mariano, Rodolfo Antonio Ma. Zabella, Genejane Adarlo
(pages: 89-98)


 

Abstracts

 


ABSTRACT


Monte Carlo Numerical Models for Nuclear Logging Applications

Fusheng Li, Xiaogang Han


Nuclear logging is one of most important logging services provided by many oil service companies. The main parameters of interest are formation porosity, bulk density, and natural radiation. Other services are also provided from using complex nuclear logging tools, such as formation lithology/mineralogy, etc. Some parameters can be measured by using neutron logging tools and some can only be measured by using a gamma ray tool. To understand the response of nuclear logging tools, the neutron transport/diffusion theory and photon diffusion theory are needed. Unfortunately, for most cases there are no analytical answers if complex tool geometry is involved. For many years, Monte Carlo numerical models have been used by nuclear scientists in the well logging industry to address these challenges. The models have been widely employed in the optimization of nuclear logging tool design, and the development of interpretation methods for nuclear logs. They have also been used to predict the response of nuclear logging systems for forward simulation problems. In this case, the system parameters including geometry, materials and nuclear sources, etc., are pre-defined and the transportation and interactions of nuclear particles (such as neutrons, photons and/or electrons) in the regions of interest are simulated according to detailed nuclear physics theory and their nuclear cross-section data (probability of interacting). Then the deposited energies of particles entering the detectors are recorded and tallied and the tool responses to such a scenario are generated. A general-purpose code named Monte Carlo N– Particle (MCNP) has been the industry-standard for some time. In this paper, we briefly introduce the fundamental principles of Monte Carlo numerical modeling and review the physics of MCNP. Some of the latest developments of Monte Carlo Models are also reviewed. A variety of examples are presented to illustrate the uses of Monte Carlo numerical models for the development of major nuclear logging tools, including compensated neutron porosity, compensated density, natural gamma ray and a nuclear geo-mechanical tool.

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