فهرست مطالب

Iranian Journal of Oil & Gas Science and Technology
Volume:12 Issue: 2, Spring 2023

  • تاریخ انتشار: 1402/09/28
  • تعداد عناوین: 2
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  • Improving Fluid Flow Through Low Permeability Reservoir in the presence of Nanoparticles: An Experimental Core Fooding WAG Tests
    Yaser Ahmadi * Page 2

    Recently nanoparticles are used for improving the volume of oil and gas production and Enhanced Oil Recovery (EOR) purposes. Based on our recent researches, using nanoparticles such as Silica and Calcium oxide has a good potential for changing mechanisms in the porous media such as interfacial tension and wettability. For finding the application of nanoparticles in the porous media, low permeability carbonate plugs were selected, and two main steps were used , including 1) Using CaO and SiO2 nanoparticles for wettability alteration, interfacial tension reduction, and improving fluid flow through porous media 2) Surveying the application of nanoparticles on the water alternative gas (NCs assisted WAG) test. The Zeta potential amounts are stable at condition of -56.4±2 mV and -44.0±3 mV for Calcium oxide and Silica nanoparticles, respectively at optimum nanoparticles concentration of 15 ppm. Calcium oxide and Silica nanoparticles have effectively altered the wettability from oil-wet to water-wet by surveying the intersection of two-phase relative permeability. Moreover, CaO nanoparticles had better performance in low permeability carbonate porous media than SiO2 nanoparticles with regards to wettability alteration to water wet. Based on the results and better version of CaO, it was selected for performing NCs assisted WAG tests at WAG ratios of 1:1, 40 ℃, and 15 ppm.The recovery factor was increased from 42.9 % to 73 % in the presence of CaO during performing NCs assisted WAG tests, and residual oil saturation was decreased from 40.9 % to 19.4 %.

    Keywords: Calcium oxide nanoparticles, Silica, WAG, Wettability, low permeability reservoir
  • Mehrdad Safarpour, MohammadAli Riahi *, Mehran Rahimi Pages 13-39

    The main purpose of this paper is to estimate and evaluate the petrophysical properties of the Ghar Formation in the Hindijan and Bahregansar oilfields using a combination of seismic and well logs data. In this study, following a step-by-step regression approach: first; sonic, density, and, porosity well-log data are collected. Second; seismic attributes, including amplitude, phase, frequency, and acoustic impedance are extracted from the seismic lines intersecting the wellbore locations. Then, using the MFLN and PNN intelligent systems, a relationship between porosity, shale volume, saturation, and seismic attributes is established. Using this relationship, the physical and petrophysical properties of the reservoir in the Ghar Formation are estimated and evaluated. We estimated the reservoir porosity between 15% and 20%, which is higher in the Hendijan oilfield as compared to the Bahregansar oilfield. The amount of water saturation in the Ghar formation varies between 25 and 30 percent. On the other hand, the amount of clay content and shale volume of the Ghar Formation in the Hendijan field is higher than that of the Bahregansar oil field.

    Keywords: Bahregansar, Ghar Formation, Hendijan, Neural Networks, Seismic attributes