The most significant function in oil exploration is determining the reservoir facies, which are based mostly on the primary features of rocks. Porosity, water saturation, and shale volume as well as sonic log and Bulk density are the types of input data utilized in Interactive Petrophysics software to compute rock facies. These data are used to create 15 clusters and four groups of rock facies. Furthermore, the accurate matching between core and well-log data is established by the neural network technique. In the current study, to evaluate the applicability of the cluster analysis approach, the result of rock facies from 29 wells derived from cluster analysis were utilized to redistribute the petrophysical properties for six units of Mishrif Formation; MA, MB11, MB12, MB21, MC1, and MC2. The precise facies modelling is constructed by using Petrel software while applying different appropriate scale-up methods. Consequently, the petrophysical properties such as porosity, water saturation and permeability are distributed within each unit depending on facies modelling. The Net to a gross parameter which has a significant impact on determining original oil in place (OIIP) also calculated and distributed using facies modelling. The facies modelling is performed to obtain an accurate estimation of OIIP. Finally, the results of the facies investigation have a significant effect on petrophysical properties and therefore affect the estimation of OIIP by 2\% for the whole Mishrif Formation.
The interests toward developing accurate automatic face emotion recognition methodologies are growing vastly, and it is still one of an ever growing research field in the region of computer vision, artificial intelligent and automation. However, there is a challenge to build an automated system which equals human ability to recognize facial emotion because of the lack of an effective facial feature descriptor and the difficulty of choosing proper classification method. In this paper, a geometric based feature vector has been proposed. For the classification purpose, three different types of classification methods are tested: statistical, artificial neural network (NN) and Support Vector Machine (SVM). A modified K-Means clustering algorithm
... Show More
(2)
This study investigates the impact of spatial resolution enhancement on supervised classification accuracy using Landsat 9 satellite imagery, achieved through pan-sharpening techniques leveraging Sentinel-2 data. Various methods were employed to synthesize a panchromatic (PAN) band from Sentinel-2 data, including dimension reduction algorithms and weighted averages based on correlation coefficients and standard deviation. Three pan-sharpening algorithms (Gram-Schmidt, Principal Components Analysis, Nearest Neighbour Diffusion) were employed, and their efficacy was assessed using seven fidelity criteria. Classification tasks were performed utilizing Support Vector Machine and Maximum Likelihood algorithms. Results reveal that specifi
... Show More
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
... Show More
(91)
(89)
(2)
The Ratawi Oil Field (ROF) is one of Iraq's most important oil fields because of its significant economic oil reserves. The major oil reserves of ROF are in the Mishrif Formation. The main objective of this paper is to assess the petrophysical properties, lithology identification, and hydrocarbon potential of the Mishrif Formation using interpreting data from five open-hole logs of wells RT-2, RT-4, RT-5, RT-6, and RT-42. Understanding reservoir properties allows for a more accurate assessment of recoverable oil reserves. The rock type (limestone) and permeability variations help tailor oil extraction methods, extraction methods and improving recovery techniques. The petrophysical properties were calculated using Interactive Petroph
... Show More
(1)
(1)
(1)
The reserve estimation process is continuous during the life of the field due to risk and inaccuracy that are considered an endemic problem thereby must be studied. Furthermore, the truth and properly defined hydrocarbon content can be identified just only at the field depletion. As a result, reserve estimation challenge is a function of time and available data. Reserve estimation can be divided into five types: analogy, volumetric, decline curve analysis, material balance and reservoir simulation, each of them differs from another to the kind of data required. The choice of the suitable and appropriate method relies on reservoir maturity, heterogeneity in the reservoir and data acquisition required. In this research, three types of rese
... Show More
(2)
To test the effect of 4 levels of nitrogen (i.e. 0, 45, 90 and 135 Kg N ha-1) as urea (46% N) and 3 levels of phosphorus (i.e. 0, 17.5 and 35 Kg P ha-1) as triple superphosphate (21.8% P) on yield and concentration of dill (Anethum graveolens L. local cultivar) seed oil this experiment was carried out during winter season of 1999 - 2000 at the experimental field of Agriculture College, Abu-Ghraib.
Both fertilizers were applied in two equal splits, first at seeds sowing and the second was added one month after emergence. Dried and ground seed samples were subjected to water distillation for extraction of volatile oils
Result indicated that fertilization of dill plants with 90 Kg N
... Show More
(1)
(6)
(1)