Results 1 to 10 of about 72 (65)

Machine Learning in Electrofacies Classification and Subsurface Lithology Interpretation: A Rough Set Theory Approach

Applied Sciences, 2020
Initially, electrofacies were introduced to define a set of recorded well log responses in order to characterize and distinguish a bed from the other rock units, as an advancement to the conventional application of well logs.
Touhid Mohammad Hossain, Junzo Watada, Izzatdin A. Aziz, Maman Hermana   +3 more
doaj   +3 more sources

The Application of Pattern Recognition in Electrofacies Analysis

Journal of Applied Mathematics, 2014
Pattern recognition is an important analytical tool in electrofacies analysis. In this paper, we study several commonly used clustering and classification algorithms.
Huan Li, Xiao Yang, Wenhong Wei
doaj   +2 more sources

Analyzing the impact of clay minerals on the reservoir quality of the Lower Goru Formation using Unsupervised Machine Learning. [PDF]

PLoS ONE
The reservoir quality of the Lower Goru Formation is highly variable due to its heterogeneous nature influenced by sea level fluctuations during the Early Cretaceous period.
Kausar Noreen, Tahir Azeem, Faisal Rehman, Yawar Amin, Qazi Adnan Ahmad, Mureed Hussain   +5 more
doaj   +2 more sources

Integrating NMR and machine learning for pore-type driven rock classification in the heterogeneous Asmari carbonate reservoirs [PDF]

Scientific Reports
The Asmari Formation’s complex heterogeneity presents fundamental challenges for reservoir characterization, where conventional lithology-based methods inadequately capture dynamic fluid behavior and pore-scale productivity controls.
Maryam Veysi, Ali Kadkhodaie, Mehran Arian, Mohsen Aleali, Zahra Maleki, Pooria Kianoush   +5 more
doaj   +2 more sources

Enhancing formation resistivity factor estimation in carbonate reservoirs using electrical zone indicator and multi-resolution graph-based clustering methods [PDF]

Scientific Reports
The complex pore structure of carbonate rocks often results in scattered data in the relationship between formation resistivity factor (FRF) and porosity, posing significant challenges for accurate reservoir characterization. Although traditional methods
Milad Mohammadi, Mohammad Emami Niri, Abbas Bahroudi, Aboozar Soleymanzadeh, Shahin Kord   +4 more
doaj   +2 more sources

A comparative study of 3D FZI and electrofacies modeling using seismic attribute analysis and neural network technique: A case study of Cheshmeh-Khosh Oil field in Iran

Petroleum, 2016
Electrofacies are used to determine reservoir rock properties, especially permeability, to simulate fluid flow in porous media. These are determined based on classification of similar logs among different groups of logging data.
Mahdi Rastegarnia, Ali Sanati, Dariush Javani   +2 more
doaj   +3 more sources

Integrating petrophysical data into efficient iterative cluster analysis for electrofacies identification in clastic reservoirs

Energy Geoscience
Efficient iterative unsupervised machine learning involving probabilistic clustering analysis with the expectation-maximization (EM) clustering algorithm is applied to categorize reservoir facies by exploiting latent and observable well-log variables ...
Mohammed A. Abbas, Watheq J. Al-Mudhafar, Aqsa Anees, David A. Wood   +3 more
doaj   +3 more sources

K-Mean Clustering Analysis and Logistic Boosting Regression for Rock Facies Characterization and Classification in Zubair Reservoir in Luhais Oil Field, Southern Iraq

Iraqi Geological Journal, 2021
Identifying rock facies from petrophysical logs is a crucial step in the evaluation and characterization of hydrocarbon reservoirs. The rock facies can be obtained either from core analysis (lithofacies) or from well logging data (electrofacies). In this
Mohammed Albuslimi
doaj   +1 more source

Microfacies analysis of the Palaeocene Lockhart limestone on the eastern margin of the Upper Indus Basin (Pakistan): Implications for the depositional environment and reservoir characteristics

The Depositional Record, Volume 9, Issue 1, Page 152-173, February 2023., 2023
The Lockhart Limestone represents a deepening upward sequence deposited underneath the shelf margin system tract and highstand systems tract in a regressive environment that could reflect good reservoir characteristics, has the potential to serve as an excellent hydrocarbon reservoir rock, and could be a primary target for future hydrocarbon ...
Ahmer Bilal, Renchao Yang, Hammad Tariq Janjuhah, Muhammad Saleem Mughal, Yang Li, George Kontakiotis, Nils Lenhardt   +6 more
wiley   +1 more source

Multiparameter Logging Evaluation of Chang 73 Shale Oil in the Jiyuan Area, Ordos Basin

Geofluids, Volume 2023, Issue 1, 2023., 2023
The accurate evaluation of shale oil and gas reservoirs is of great significance to the integrated development of geology and engineering. Based on the core analysis, conventional logging, and array acoustic logging data, the total organic carbon, hydrocarbon generation potential, brittleness, and anisotropy of shale reservoirs were calculated.
Bobiao Liu, Chengqian Tan, Yinchao Huai, Yuhan Tan, Han Zhang, Zhao Feng, Yang Wang   +6 more
wiley   +1 more source