Jassim Mohammed Al Said Naji

@uotechnology.edu.iq

University of Technology, Oil and Gas Engineering Department
university of technology

Jassim Mohammed Al Said Naji


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https://researchid.co/jassim94
Jassim M. Al Said Naji, currently works at Oil and Gas Engineering Department,
I have experience in many of petroleum Engineering software for example, Petrel, PROSPER, PVTP, MBAL, .....etc.

EDUCATION

Master in Petroleum Engineering

RESEARCH, TEACHING, or OTHER INTERESTS

Engineering, Fuel Technology, Energy, Engineering
5

Scopus Publications

31

Scholar Citations

4

Scholar h-index

Scopus Publications

  • Prediction of Sand Product in the First Period of Production/Case Study of the Asmari Reservoir
    Jassim M. Al Said Naji, Ghassan H. Abdul-Majeed, Ali K. Alhuraishawy, Fadhil S. Kadhim, Ghazwan N. S. Jreou, et al.
    Petroleum Chemistry, 2024
  • Estimating the Petrophysical Properties Cutoff Values for Net Pay Determination: A Case Study of Khasib Formation, Southern Iraq
    Alyaa M. Ali, Jassim M. Al-Said Naji, Mohammed A. Ahmed
    Petroleum Chemistry, 2024
  • Asphaltene Phase Behavior Modeling Using Peng-Robinson 78A-EOS for a Crude Oil Sample from Buzurgan Oil Field
    Mohammed A. Ahmed, Jassim M. Al-Said Naji, Alyaa M. Ali, Ali Qasim Al-Khafaje
    Petroleum Chemistry, 2024
  • Prediction of Sonic Shear Wave Using Artificial Neural Network
    Jassim Naji, Ghassan Abdul-Majeed, Ali Alhuraishawy
    Iraqi Geological Journal, 2022
    Shear wave time is an important parameter participating in the calculation of rock mechanics properties. Many evaluation processes including wellbore stability analysis and sand production prediction are based on rock mechanics properties so these processes are directly related to the estimation of shear wave time. Several empirical correlations have been developed to predict shear wave time using regression analysis and artificial neural network techniques for the estimation of relationships between a dependent variable and one or more independent variables for certain conditions of the reservoir. However, they are not appropriate for reservoirs with different conditions as well as all effective parameters are not considered in previous relationships. In this study, the artificial neural network is adopted for predicting shear wave time using datasets consisting of 1922 data points for a certain directional oil well from Iraqi Fauqi oil field wells. Two sets of input parameters are tried: the first trial includes the readings of seven logs (Gamma-ray, caliper, compressional sonic wave, density, neutron, deep resistivity, true vertical depth), while the second trial includes the azimuth and the inclination angles in addition to the above seven readings. The optimum structure for both datasets is obtained using 12 neurons in a single hidden layer (ANN-7-12-1 and ANN-9-12-1). The statistical results reveal that an improvement is achieved when the well azimuth and inclination are included in the ANN model. A mathematical model with high performance using an artificial neural network has been developed. The mean square error and the determination coefficient for the developed model were 14.22 and 0.952 for ANN-7-12-1, while they were 9.62 and 0.966 for ANN-9-12-1, respectively. This study presents a simple mathematical model for further determination of shear wave velocities using ANN techniques which can be then integrated with the existent petroleum software programs.
  • Study of different geostatistical methods to model formation porosity (Cast study of Zubair formation in Luhais oil field)
    Jassim M. Al Musawi, Mohammed S. Al Jawad
    Iop Conference Series Materials Science and Engineering, 2019
    This study is concerned with making comparison in using different geostatistical methods for porosity distribution of upper shale member - Zubair formation in Luhais oil field which was chosen to study. Kriging, Gaussian random function simulation and sequential Gaussian simulation geostatistical methods were adopted in this study. After preparing all needed data which are contour map, well heads of 12 wells, well tops and porosity from CPI log. Petrel software 2009 was used for porosity distribution of mentioned formation in methods that are showed above. Comparisons were made among these three methods in order to choose the best one, the comparing criteria was according to different statistical information and variograms analysis of entered porosity which was scaled up and modeled. The best method gave porosity distribution in model closest to enter porosity that represent real porosity of Zubair formation. The comparison proved that sequential Gaussian simulation is the best model of porosity distribution followed by Gaussian random function simulation and kriging methods respectively. Based on the results obtained, it was concluded that the distribution accuracy of the porosity or other petrophysics properties is one of the main factors that affect building correct geological model that represents the base of reservoir model and also pore volume (Oil reserve) value was affected by geostatistical methods variation.

RECENT SCHOLAR PUBLICATIONS

  • Three-Dimensional Geological Model of the Nahr Umr Reservoir in Al Rafidain Oil Field
    JMAS Naji
    Iraqi Journal of Oil and Gas Research (IJOGR) 6 (1), 1-13 , 2026
    2026
  • A Hybrid Approach to Petrophysical Characterization of the Nahr-Umr Formation in the Abu-Amood Oil Field: Combining Statistical and Conventional Methods
    MA Ahmed, JM Al Said Naji, AM Ali
    International Journal of Mining and Geo-Engineering , 2026
    2026
  • Deterministic and Probabilistic Approaches for Estimating Oil Reserve in Carbonate Reservoir: A Case Study for the Buzrgan Oil Field, Southern Iraq
    JMAS Naji, MA Ahmed
    Journal of Engineering 32 (4), 16-34 , 2026
    2026
  • Recent Trends and Challenges in Project Management of Oil and Gas Projects: A Systematic Review.
    MM Al-Bdairi, JM Al Said Naji, HK Abed
    Iraqi Journal of Oil and Gas Research (IJOGR) 5 (2), 51-58 , 2025
    2025
    Citations: 2
  • Prediction of sand product in the first period of production/case study of the Asmari reservoir
    JMAS Naji, GH Abdul-Majeed, AK Alhuraishawy, FS Kadhim, GNS Jreou, ...
    Petroleum Chemistry 64 (8), 1023-1030 , 2024
    2024
    Citations: 2
  • Estimating the Petrophysical Properties Cutoff Values for Net Pay Determination: A Case Study of Khasib Formation, Southern Iraq
    AM Ali, JMAS Naji, MA Ahmed
    Petroleum Chemistry 64 (7), 820-828 , 2024
    2024
  • Asphaltene Phase Behavior Modeling Using Peng-Robinson 78A-EOS for a Crude Oil Sample from Buzurgan Oil Field
    MA Ahmed, JMAS Naji, AM Ali, AQ Al-Khafaje
    Petroleum Chemistry 64 (7), 840-848 , 2024
    2024
    Citations: 1
  • Effect of Using Different Property Modelling Strategies on the Calculated Value of the Initial Oil in Place by Volumetric Method
    AMF Jassim M. Al Said Naji, Mohammed A. Ahmed, Hijran M. Hammad
    Iraqi Journal of Oil & Gas Research 3 (2), 50-62 , 2023
    2023
    Citations: 2
  • Detection of Over Normal Pore Pressure Intervals by Using Well Logs
    JMAS Naji, GH Abdul-Majeed, AK Alhuraishawy, A Talib
    Journal of Petroleum Research and Studies 13 (3), 59-73 , 2023
    2023
    Citations: 1
  • Prediction of Sanding Likelihood Intervals Using Different Approaches
    JMAS Naji
    مجلة البحوث و الدراسات النفطية , 2023 ‎
    2023
    Citations: 3
  • Intelligent approach for investigating reservoir heterogeneity effect on sonic shear wave
    JMAS Naji, GH Abdul-Majeed, AK Alhuraishawy
    Journal of Petroleum Research and Studies 13 (1), 56-73 , 2023
    2023
    Citations: 4
  • Comparison of estimation sonic shear wave time using empirical correlations and artificial neural network
    JMAS Naji
    Iraqi journal of chemical and petroleum engineering , 2022
    2022
    Citations: 8
  • Prediction of sonic shear wave using artificial neural network
    JMAS Naji, GH Abdul-Majeed, AK Alhuraishawy
    The Iraqi Geological Journal, 152-164 , 2022
    2022
    Citations: 4
  • Study of different geostatistical methods to model formation porosity (Cast study of Zubair formation in Luhais oil field)
    JM Al Musawi, MS Al Jawad
    IOP Conference Series: Materials Science and Engineering 579 (1), 012031 , 2019
    2019
    Citations: 4

MOST CITED SCHOLAR PUBLICATIONS

  • Comparison of estimation sonic shear wave time using empirical correlations and artificial neural network
    JMAS Naji
    Iraqi journal of chemical and petroleum engineering , 2022
    2022
    Citations: 8
  • Intelligent approach for investigating reservoir heterogeneity effect on sonic shear wave
    JMAS Naji, GH Abdul-Majeed, AK Alhuraishawy
    Journal of Petroleum Research and Studies 13 (1), 56-73 , 2023
    2023
    Citations: 4
  • Prediction of sonic shear wave using artificial neural network
    JMAS Naji, GH Abdul-Majeed, AK Alhuraishawy
    The Iraqi Geological Journal, 152-164 , 2022
    2022
    Citations: 4
  • Study of different geostatistical methods to model formation porosity (Cast study of Zubair formation in Luhais oil field)
    JM Al Musawi, MS Al Jawad
    IOP Conference Series: Materials Science and Engineering 579 (1), 012031 , 2019
    2019
    Citations: 4
  • Prediction of Sanding Likelihood Intervals Using Different Approaches
    JMAS Naji
    مجلة البحوث و الدراسات النفطية , 2023 ‎
    2023
    Citations: 3
  • Recent Trends and Challenges in Project Management of Oil and Gas Projects: A Systematic Review.
    MM Al-Bdairi, JM Al Said Naji, HK Abed
    Iraqi Journal of Oil and Gas Research (IJOGR) 5 (2), 51-58 , 2025
    2025
    Citations: 2
  • Prediction of sand product in the first period of production/case study of the Asmari reservoir
    JMAS Naji, GH Abdul-Majeed, AK Alhuraishawy, FS Kadhim, GNS Jreou, ...
    Petroleum Chemistry 64 (8), 1023-1030 , 2024
    2024
    Citations: 2
  • Effect of Using Different Property Modelling Strategies on the Calculated Value of the Initial Oil in Place by Volumetric Method
    AMF Jassim M. Al Said Naji, Mohammed A. Ahmed, Hijran M. Hammad
    Iraqi Journal of Oil & Gas Research 3 (2), 50-62 , 2023
    2023
    Citations: 2
  • Asphaltene Phase Behavior Modeling Using Peng-Robinson 78A-EOS for a Crude Oil Sample from Buzurgan Oil Field
    MA Ahmed, JMAS Naji, AM Ali, AQ Al-Khafaje
    Petroleum Chemistry 64 (7), 840-848 , 2024
    2024
    Citations: 1
  • Detection of Over Normal Pore Pressure Intervals by Using Well Logs
    JMAS Naji, GH Abdul-Majeed, AK Alhuraishawy, A Talib
    Journal of Petroleum Research and Studies 13 (3), 59-73 , 2023
    2023
    Citations: 1
  • Three-Dimensional Geological Model of the Nahr Umr Reservoir in Al Rafidain Oil Field
    JMAS Naji
    Iraqi Journal of Oil and Gas Research (IJOGR) 6 (1), 1-13 , 2026
    2026
  • A Hybrid Approach to Petrophysical Characterization of the Nahr-Umr Formation in the Abu-Amood Oil Field: Combining Statistical and Conventional Methods
    MA Ahmed, JM Al Said Naji, AM Ali
    International Journal of Mining and Geo-Engineering , 2026
    2026
  • Deterministic and Probabilistic Approaches for Estimating Oil Reserve in Carbonate Reservoir: A Case Study for the Buzrgan Oil Field, Southern Iraq
    JMAS Naji, MA Ahmed
    Journal of Engineering 32 (4), 16-34 , 2026
    2026
  • Estimating the Petrophysical Properties Cutoff Values for Net Pay Determination: A Case Study of Khasib Formation, Southern Iraq
    AM Ali, JMAS Naji, MA Ahmed
    Petroleum Chemistry 64 (7), 820-828 , 2024
    2024