Modeling and simulation of neutron-gamma density logging: Impact of mudcake thickness and barite content on measurement accuracy

This study investigates the influence of mudcake thickness and barite weight fraction on Neutron-Gamma Density (NGD) logging measurements, applying both NGD-FC and NGD-TC methods to simulate the interactions of fast neutrons and gamma rays in a wellbore environment. Initially, based on fast neutron and gamma diffusion theory and incorporating the build-up factor, a mathematical model of the well logging tool was constructed. To validate this model and enable more detailed analysis, simulations were conducted using the MCNP code, which provided the response of the tool under varying conditions. Simulated responses were then compared with theoretical predictions to ensure model accuracy. The research examines mudcake conditions with thicknesses ranging from 3 to 12 mm and barite weight fractions of 10 %–30 %, highlighting that NGD-TC is particularly sensitive to mudcake thickness, as evidenced by a Max Error increasing from 22.36 % to 44.07 %. Conversely, NGD-FC maintains lower and more stable errors (15.91–19.58) under similar conditions, though it shows higher sensitivity to barite content due to fast neutron scattering influences. Overall, this study emphasizes the importance of selecting the appropriate NGD method to ensure reliable measurements in complex wellbore environments. By fine-tuning calibration coefficients and understanding the interaction mechanisms that influence neutron and gamma flux, the research enhances the accuracy of NGD logging, thereby supporting improved decision-making in resource extraction and subsurface evaluations. • Developed a mathematical model of Neutron-Gamma Density (NGD) logging tool based on fast neutron and gamma diffusion theory, incorporating the build-up factor. • Conducted simulations in MCNP to validate the model, achieving close agreement between theoretical and simulated responses. • Analyzed the impact of mudcake thickness and barite weight fractions on NGD measurements, highlighting the sensitivity of NGD-TC and NGD-FC methods to these variables. • Confirmed that NGD-FC is more stable across varying mudcake conditions, maintaining lower Max but showing greater sensitivity to barite content due to fast neutron scattering effects. • Optimized calibration coefficients for both methods, with NGD-FC proving more robust than NGD-TC in thick, high-density mudcake environments.

Authors

Institutions

Publication Details

Journal
Nuclear Engineering and Technology
Published
2025-09-04
DOI
https://doi.org/10.1016/j.net.2025.103883
Primary Topic
Nuclear Physics and Applications
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Modeling and simulation of neutron-gamma density logging: Impact of mudcake thickness and barite content on measurement accuracy

Seyed Abolfazl Hosseini, Abolfazl Rafizade
Nuclear Engineering and Technology
Nuclear Physics and Applications
article

Modeling and simulation of neutron-gamma density logging: Impact of mudcake thickness and barite content on measurement accuracy

Seyed Abolfazl Hosseini, Abolfazl Rafizade
article en

Abstract

This study investigates the influence of mudcake thickness and barite weight fraction on Neutron-Gamma Density (NGD) logging measurements, applying both NGD-FC and NGD-TC methods to simulate the interactions of fast neutrons and gamma rays in a wellbore environment. Initially, based on fast neutron and gamma diffusion theory and incorporating the build-up factor, a mathematical model of the well logging tool was constructed. To validate this model and enable more detailed analysis, simulations were conducted using the MCNP code, which provided the response of the tool under varying conditions. Simulated responses were then compared with theoretical predictions to ensure model accuracy. The research examines mudcake conditions with thicknesses ranging from 3 to 12 mm and barite weight fractions of 10 %–30 %, highlighting that NGD-TC is particularly sensitive to mudcake thickness, as evidenced by a Max Error increasing from 22.36 % to 44.07 %. Conversely, NGD-FC maintains lower and more stable errors (15.91–19.58) under similar conditions, though it shows higher sensitivity to barite content due to fast neutron scattering influences. Overall, this study emphasizes the importance of selecting the appropriate NGD method to ensure reliable measurements in complex wellbore environments. By fine-tuning calibration coefficients and understanding the interaction mechanisms that influence neutron and gamma flux, the research enhances the accuracy of NGD logging, thereby supporting improved decision-making in resource extraction and subsurface evaluations. • Developed a mathematical model of Neutron-Gamma Density (NGD) logging tool based on fast neutron and gamma diffusion theory, incorporating the build-up factor. • Conducted simulations in MCNP to validate the model, achieving close agreement between theoretical and simulated responses. • Analyzed the impact of mudcake thickness and barite weight fractions on NGD measurements, highlighting the sensitivity of NGD-TC and NGD-FC methods to these variables. • Confirmed that NGD-FC is more stable across varying mudcake conditions, maintaining lower Max but showing greater sensitivity to barite content due to fast neutron scattering effects. • Optimized calibration coefficients for both methods, with NGD-FC proving more robust than NGD-TC in thick, high-density mudcake environments.

Nuclear Engineering and TechnologyVol. 58(1)
Sharif University of Technology (IR)
Sharif University of Technology
Openalex Percentile: Top 70%
Nuclear Physics and Applications
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.