Amplitude variation with offset (AVO) analysis is an 1 efficient tool for hydrocarbon detection and identification of elastic rock properties and fluid types. It has been applied in the present study using reprocessed pre-stack 2D seismic data (1992, Caulerpa) from north-west of the Bonaparte Basin, Australia. The AVO response along the 2D pre-stack seismic data in the Laminaria High NW shelf of Australia was also investigated. Three hypotheses were suggested to investigate the AVO behaviour of the amplitude anomalies in which three different factors; fluid substitution, porosity and thickness (Wedge model) were tested. The AVO models with the synthetic gathers were analysed using log information to find which of these is the controlling parameter on the AVO analysis. AVO cross plots from the real pre-stack seismic data reveal AVO class IV (showing a negative intercept decreasing with offset). This result matches our modelled result of fluid substitution for the seismic synthetics. It is concluded that fluid substitution is the controlling parameter on the AVO analysis and therefore, the high amplitude anomaly on the seabed and the target horizon 9 is the result of changing the fluid content and the lithology along the target horizons. While changing the porosity has little effect on the amplitude variation with offset within the AVO cross plot. Finally, results from the wedge models show that a small change of thickness causes a change in the amplitude; however, this change in thickness gives a different AVO characteristic and a mismatch with the AVO result of the real 2D pre-stack seismic data. Therefore, a constant thin layer with changing fluids is more likely to be the cause of the high amplitude anomalies.
The study aims to discuss the relation between imported inflation and international trade of Iraqi economy for the period (1990-2015) by using annual data. To achieve the study aim, statistical and Econometrics methods are used through NARDL model to explain non-linear relation because it’s a model assigned to measure non-linear relations and as we know most economic relations are non-linear, beside explaining positive and negative effects of imported inflation, and to reach the research aim deductive approach was adopted through using descriptive method to describe and determine phenomenon. Beside the inductive approach by g statistical and standard tools to get the standard model explains the
... Show MoreThis work intends to develop an effective heavy metal-free modifier having properties comparable to traditional stabilizers and flame retardants, simultaneously being environmentally friendly and may be superior in many aspects. The important requirement focused on is: how to increase thermal stability and flame retardancy of flexible poly(vinyl chloride). Due to the typical materials now used with poly(vinyl chloride), which increases health and environmental concerns, utilizing a novel heavy metal-free additive will make poly(vinyl chloride) substantially safer. We have used an artificial silicate for this aim, which proved to be an efficient flame retardant and surprisingly showed excellent heat stabilizing effect. Thermal stabi
... Show MoreClean energy applications widely recognize Proton Exchange Membrane Fuel Cells (PEMFCs) for their high efficiency and environmental compatibility. Accurate parameter identification of PEMFC models is essential for enhancing system performance and reliability, particularly under dynamic operating conditions. This paper presents a novel optimization-based approach called Heterogeneous Comprehensive Learning-Bald Eagle Search (HCLBES) with enhanced exploration and exploitation capabilities for the effective modeling of PEMFC. The algorithm combines the exploration strength of the Bald Eagle Search with comprehensive learning and heterogeneity mechanisms to achieve a balanced global and local search space. In this algorithm, the number
... Show MoreThe aim of this study is to identify the effect of particle size and to increase the concentration of Iraqi bentonite on rheological properties in order to evaluate its performance and to know if it can be used as drilling fluid without additives or not. In this study, Iraqi bentonite was carried out by mineral composition (XRD), chemical composition (XRF) and Particle size distribution (PSD), and its rheological properties were measured at different particle size and concentration. The results showed that when the particle size of Iraqi bentonite decreased, and the rheological properties were increased with increased concentration of Iraqi bentonite. Also, Iraqi bentonite was unable to use as drilling fluid without certain additives.
... Show MoreApple slice grading is useful in post-harvest operations for sorting, grading, packaging, labeling, processing, storage, transportation, and meeting market demand and consumer preferences. Proper grading of apple slices can help ensure the quality, safety, and marketability of the final products, contributing to the post-harvest operations of the overall success of the apple industry. The article aims to create a convolutional neural network (CNN) model to classify images of apple slices after immersing them in atmospheric plasma at two different pressures (1 and 5 atm) and two different immersion times (3 and again 6 min) once and in filtered water based on the hardness of the slices usin
This study shows that it is possible to fabricate and characterize green bimetallic nanoparticles using eco-friendly reduction and a capping agent, which is then used for removing the orange G dye (OG) from an aqueous solution. Characterization techniques such as scanning electron microscopy (SEM), Energy Dispersive Spectroscopy (EDAX), X-Ray diffraction (XRD), and Brunauer-Emmett-Teller (BET) were applied on the resultant bimetallic nanoparticles to ensure the size, and surface area of particles nanoparticles. The results found that the removal efficiency of OG depends on the G‑Fe/Cu‑NPs concentration (0.5-2.0 g.L-1), initial pH (2‑9), OG concentration (10-50 mg.L-1), and temperature (30-50 °C). The batch experiments showed
... Show MoreMedicine is one of the fields where the advancement of computer science is making significant progress. Some diseases require an immediate diagnosis in order to improve patient outcomes. The usage of computers in medicine improves precision and accelerates data processing and diagnosis. In order to categorize biological images, hybrid machine learning, a combination of various deep learning approaches, was utilized, and a meta-heuristic algorithm was provided in this research. In addition, two different medical datasets were introduced, one covering the magnetic resonance imaging (MRI) of brain tumors and the other dealing with chest X-rays (CXRs) of COVID-19. These datasets were introduced to the combination network that contained deep lea
... Show MoreIn this golden age of rapid development surgeons realized that AI could contribute to healthcare in all aspects, especially in surgery. The aim of the study will incorporate the use of Convolutional Neural Network and Constrained Local Models (CNN-CLM) which can make improvement for the assessment of Laparoscopic Cholecystectomy (LC) surgery not only bring opportunities for surgery but also bring challenges on the way forward by using the edge cutting technology. The problem with the current method of surgery is the lack of safety and specific complications and problems associated with safety in each laparoscopic cholecystectomy procedure. When CLM is utilize into CNN models, it is effective at predicting time series tasks like iden
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