Investigation and prediction of pore type system by integrating velocity deviation log, petrographic data and mercury injection capillary pressure curves in the Fahliyan Formation, the Persian Gulf Basin-Reference-Cited by-同舟云学术

Investigation and prediction of pore type system by integrating velocity deviation log, petrographic data and mercury injection capillary pressure curves in the Fahliyan Formation, the Persian Gulf Basin

Published:2023-01-14 Issue:1 Volume:38 Page:
ISSN:0891-2556
Container-title:Carbonates and Evaporites
language:en
Short-container-title:Carbonates Evaporites

Author:

Derafshi Mohammad,Kadkhodaie Ali^ORCID,Rahimpour-Bonab Hossain,Kadkhodaie-Ilkhchi Rahim,Moslman-Nejad Hamid,Ahmadi Amir

Publisher

Springer Science and Business Media LLC

Subject

Geochemistry and Petrology

Link

https://link.springer.com/content/pdf/10.1007/s13146-022-00837-7.pdf

Reference52 articles.

1. Ahr WM (2011) Geology of carbonate reservoirs: the identification, description and characterization of hydrocarbon reservoirs in carbonate rocks. Wiley, Hoboken

2. Aliakbardoust E, Rahimpour-Bonab H (2013) Effects of pore geometry and rock properties on water saturation of a carbonate reservoir. J Petrol Sci Eng 112:296–309

3. Amaefule JO et al (1993) Enhanced reservoir description: using core and log data to identify hydraulic (flow) units and predict permeability in uncored intervals/wells. SPE annual technical conference and exhibition, Houston, October 1993, pp 205–220

4. Anselmetti FS, Eberli GP (1993) Controls on sonic velocity in carbonates. Pure Appl Geophys 141:287–323

5. Anselmetti FS, Eberli GP (1999) The velocity-deviation log: a tool to predict pore type and permeability trends in carbonate drill holes from sonic and porosity or density logs. AAPG Bull 83:450–466

Cited by 3 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Stratigraphic framework and diagenetic features related to reservoir quality of the triassic carbonates in central to northern Persian Gulf;Carbonates and Evaporites;2024-04-27

2. A new insight to access carbonate reservoir quality using quality factor and velocity deviation log;Acta Geophysica;2023-12-30

3. Application of artificial neural network models and random forest algorithm for estimation of fracture intensity from petrophysical data;Journal of Petroleum Exploration and Production Technology;2023-06-05