Publications by authors named "Abolfazl Dehghan Monfared"

Article Synopsis
  • Reservoir petrophysical assessments are crucial for determining hydrocarbon reserves and characterizing reservoir layers through advanced logging technology that measures essential parameters like porosity and rock properties.
  • This study evaluates a specific reservoir, identifying productive zones by analyzing well logging data and applying various machine learning methods to model water saturation.
  • The AdaBoost model outperformed others in estimating water saturation with low error rates, while the GP model also showed good accuracy, highlighting the effectiveness of machine learning in petrophysical evaluations.
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The precipitation and deposition of asphaltene on solid surfaces present a significant challenge throughout all stages of petroleum recovery, from hydrocarbon reservoirs in porous media to wellbore and transfer pipelines. A comprehensive understanding of asphaltene aggregation phenomena is crucial for controlling deposition issues. In addition to experimental studies, accurate prediction of asphaltene aggregation kinetics, which has received less attention in previous research, is essential.

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In this research, the solid-liquid adsorption systems for MSAC (PbFeO spinel-activated carbon)-phenol and pristine activated carbon-phenol were scrutinized from the thermodynamics and statistical physics (sta-phy) viewpoints. Experimental results indicated that MSAC composite outperformed pristine AC for the uptake of phenol from waste streams. By increasing the process temperature, the amount of phenol adsorbed onto both adsorbents, MSAC composite and pristine AC, decreased.

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Fixed-bed studies for phenol uptake from water were carried out using a novel Pb-Fe spinel-activated carbon adsorbent. A characterization phase including TGA, FTIR, SEM, and BET analyses was performed for the developed active carbon. In column studies, the influence of initial phenol concentration, column bed height, and the solution flow rate was investigated at natural pH.

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A novel lead ferrite-magnetic activated carbon (lead ferrite-MAC) composite was developed using the chemical co-precipitation method. Instrumental analyses such as X-ray diffraction (XRD), scanning electron microscopy (SEM), Fourier-transform infrared spectroscopy (FTIR), and Brunauer-Emmett-Teller (BET) analysis were performed to characterize adsorbent. The uptake of phenol from aqueous solutions using the developed adsorbent was compared to that of pristine activated carbon.

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