Results 11 to 20 of about 588 (117)
Open Geosciences, 2014 Identifying reservoir electrofacies has an important role in determining hydrocarbon bearing intervals. In this study, electrofacies of the Kockatea Formation in the Perth Basin were determined via cluster analysis.
Reza Rezaee +2 more
exaly +4 more sources
Permeability prediction using hydraulic flow units and electrofacies analysis [PDF]
Energy Geoscience, 2020 It is essential to characterize fluid flow in porous media to have a better understanding of petrophysical properties. Many approaches were developed to determine reservoir permeability among which the integrated analysis of hydraulic flow unit (HFU) and
Raoof Gholami, Arshad Raza, Reza Rezaee
exaly +5 more sources
Prediction of Electrofacies Based on Flow Units Using NMR Data and SVM Method: a Case Study in Cheshmeh Khush Field, Southern Iran [PDF]
Journal of Petroleum Science and Technology, 2017 The classification of well-log responses into separate flow units for generating local permeability models is often used to predict the spatial distribution of permeability in heterogeneous reservoirs.
Mahdi Rastegarnia +3 more
doaj +3 more sources
Petrophysical Properties and Identification of Electrofacies from Well Log Data of Nahr Umr Formation in Subba Oilfield, Southern Iraq [PDF]
Iraqi Geological Journal, 2023 The main purpose of this study is to identify electrofacies and evaluate the petrophysical properties of the Nahr Umr Formation in four wells: A, B, C, and D in the Subba oilfield, southern Iraq.
Sura Al-Ghanim +2 more
doaj +2 more sources
Energy GeoscienceEfficient 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 +3 more
doaj +2 more sources
Electrofacies classification of a mixed carbonate-siliciclastic reservoir using machine learning techniques [PDF]
Jurnal NaturalMany scientific fields, including the geosciences, have successfully employed machine learning to address numerous significant issues. Current studies show that the application of machine learning within the geosciences is still in its early stages, and ...
MUHAMMAD RIDHA ADHARI +3 more
doaj +2 more sources
Journal of Petroleum Exploration and Production TechnologyElectrofacies classification is essential for reservoir characterization, as it links well-log responses to lithological and petrophysical properties. A data-driven workflow was developed for electrofacies classification using routine well logs from an ...
Sadegh Saffarzadeh Hosseini +2 more
doaj +2 more sources
Reservoir Quality Evaluation based on Integration of Artificial Intelligence and NMR-derived Electrofacies [PDF]
Journal of Petroleum Science and Technology, 2022 Logarithmic Mean of Transverse relaxation time (T2LM) and total porosity of the Combinable Magnetic Resonance tool (TCMR) are the main parameters of the Nuclear Magnetic Resonance (NMR) log which provide very substantial information for reservoir ...
Reza Hoveyzavi +3 more
doaj +1 more source
Petroleum, 2023 The Oligo-Miocene Asmari Formation is one of the most important hydrocarbon reservoirs in the Middle East. The oilfield under study is one of the largest oilfields in the Zagros basin with the Asmari Formation being the major reservoir rock.
Raeza Mirzaee Mahmoodabadi +1 more
doaj +1 more source
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 +6 more
wiley +1 more source