Horizontal wells have revolutionized hydrocarbon production by enhancing recovery efficiency and reducing environmental impact. This paper presents an enhanced Black Oil Model simulator, written in Visual Basic, for three-dimensional two-phase (oil and water) flow through porous media. Unlike most existing tools, this simulator is customized for horizontal well modeling and calibrated using extensive historical data from the South Rumaila Oilfield, Iraq. The simulator first achieves a strong match with historical pressure data (1954–2004) using vertical wells, with an average deviation of less than 5% from observed pressures, and is then applied to forecast the performance of hypothetical horizontal wells (2008–2011). The result

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In this study, optical fibers were designed and implemented as a chemical sensor based on surface plasmon resonance (SPR) to estimate the age of the oil used in electrical transformers. The study depends on the refractive indices of the oil. The sensor was created by embedding the center portion of the optical fiber in a resin block, followed by polishing, and tapering to create the optical fiber sensor. The tapering time was 50 min. The multi-mode optical fiber was coated with 60 nm thickness gold metal. The deposition length was 4 cm. The sensor's resonance wavelength was 415 nm. The primary sensor parameters were calculated, including sensitivity (6.25), signal-to-noise ratio (2.38), figure of merit (4.88), and accuracy (3.2)

New nanotechnology-based approaches are increasingly being investigated for enhanced oil recovery (EOR), with a particular focus on heavy oil reservoirs. Typically, the addition of a polymer to an injection fluid advances the sweep efficiency and mobility ratio of the fluid and leads to a higher crude oil recovery rate. However, harsh reservoir conditions, including high formation salinity and temperature, can limit the performance of such polymer fluids. Recently, nanofluids, that is, dispersions of nanoparticles (NPs) in a base fluid, have been recommended as EOR fluids; however, such nanofluids are unstable, even under ambient conditions. In this work, a combination of ZrO2 NPs and the polyacrylamide (PAM) polymer (ZrO2 NPs–PAM) was us

Precise forecasting of pore pressures is crucial for efficiently planning and drilling oil and gas wells. It reduces expenses and saves time while preventing drilling complications. Since direct measurement of pore pressure in wellbores is costly and time-intensive, the ability to estimate it using empirical or machine learning models is beneficial. The present study aims to predict pore pressure using artificial neural network. The building and testing of artificial neural network are based on the data from five oil fields and several formations. The artificial neural network model is built using a measured dataset consisting of 77 data points of Pore pressure obtained from the modular formation dynamics tester. The input variables

SAPO-11 is synthesized from silicoaluminophosphate in the presence of di-n-propylamine as a template. The results show that the sample obtained has good crystallinity, 396m2/g BET surface area, and 0.35 cm3/g pore volume. The hydroisomerization activity of (0.25)Pt (1)Zr (0.5)W/SAPO-11 catalyst was determined using n-decane and base oil. All hydroisomerization experiments of n-decane were achieved at a fixed bed plug flow reactor at a temperature range of 200-275°C and  LHSV 0.5-2h-1.  The results show that the n-decane conversion increases with increasing temperature and decreasing LHSV, the maximum conversion of 66.7 % was achieved at temperature 275°C and LHSV of 0.5 h-1. Meanwhile, the same catalyst was used to improve base oil spec

   SAPO-11 is synthesized from silicoaluminophosphate in the presence of di-n-propylamine as a template. The results show that the sample obtained has good crystallinity, 396m²/g BET surface area, and 0.35 cm³/g pore volume. The hydroisomerization activity of (0.25)Pt (1)Zr (0.5)W/SAPO-11 catalyst was determined using n-decane and base oil. All hydroisomerization experiments of n-decane were achieved at a fixed bed plug flow reactor at a temperature range of 200-275°C and  LHSV 0.5-2h^-1.  The results show that the n-decane conversion increases with increasing temperature and decreasing LHSV, the maximum conversion of 66.7 % was achieved at temperature 275°C and LHSV of 0.5 h^-1

Pure and Fe-doped zinc oxide nanocrystalline films were prepared
via a sol–gel method using -
C for 2 h.
The thin films were prepared and characterized by X-ray diffraction
(XRD), atomic force microscopy (AFM), field emission scanning
electron microscopy (FE-SEM) and UV- visible spectroscopy. The
XRD results showed that ZnO has hexagonal wurtzite structure and
the Fe ions were well incorporated into the ZnO structure. As the Fe
level increased from 2 wt% to 8 wt%, the crystallite size reduced in
comparison with the pure ZnO. The transmittance spectra were then
recorded at wavelengths ranging from 300 nm to 1000 nm. The
optical band gap energy of spin-coated films also decreased as Fe
doping concentra

The fatty acid composition in the seed and flower of Ligustrun lucidum and olive oil was studied by Gas Chromatography. Results showed that the main components of seed oil were Palmitic (C16:0) 5,893% ,Palmitolic acid (C16:1)0,398%, Steaeic (C18:0)2,911% ,Oleic (C18:1)74,984%,Linoleic (C18:2) 12,959%,and Linolenic (C18:3) 0,997%. The proportion of unsaturated fatty acid was above 89,338%, so the seed oil of L. lucidum ait belonged to unsaturated oil which possessed promising application. The components of flower oil were Palmitic (C16:0) 65,674% ,Palmitolic acid (C16:1)6,516%, Steaeic (C18:0)2,641% ,Oleic (C18:1)14,707%,Linoleic (C18:2) 3,113%,and Linolenic (C18:3) 2,70%. The proportion of unsaturated fatty acid and saturated fatty acid wa

The emergence of oil fields and subsequent changes in adjacent land use are known to affect settlements and communities. Everywhere the industry emerges, there is little understanding about the impact of oil fields on land use in the surrounding areas. The oil industry in Iraq is one of the most important industries and is almost the main industry in the Iraqi economic sector, and it is very clear that this industry is spread over large areas, and at the same time adjoins with population communities linked to it developmentally.

The rapid development and expansion of oil extraction activities in various regions has led to many challenges related to land-use planning and management. Here, the problem of research  arises on th