The instant global trend towards developing tight reservoir is great; however, development can be very challenging due to stress and geomechanical properties effect in horizontal well placement and hydraulic fracturing design. Many parameters are known to be important to determine the suitable layer for locating horizontal well such as petrophysical and geomechanical properties. In the present study, permeability sensitivity to stress is also considered in the best layer selection for well placement. The permeability sensitivity to the stress of the layers was investigated using measurements of 27 core sample at different confining stress values. 1-D mechanical earth model (MEM) was built and converted to a 3-D full-field geomechanical model to reach perfect layer choice. The analysis of results has diagnosed the maximum horizontal stress direction of NE-SW as determined using both Fullbore Formation Micro Imager FMI and sonic scanner anisotropy analysis. The effect of porosity and permeability compaction as a result of stress changes while reservoir depletion is including on the reservoir simulation model. The choice of best layer and optimum design criteria for hydraulic fracturing is done in the current study using a compaction simulation model with the results of available measurements of geomechanical properties. The results of the simulation model show that the formation sensitivity to stress is an important factor for detecting a suitable layer for horizontal wells placement. The results of MEM indicate that horizontal stress difference (Δσ) and unconfined compressive strength (UCS) are the most important factors among geomechanical parameters affected the layer selection. From simulation results, it was found that 225 to 275 m fracture half-length gives a higher increment in oil production. The optimum number of fracture stages is noticed to be 8 to 10 stages after which the increment in production will reduce.
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In this paper, game theory was used and applied to the transport sector in Iraq, as this sector includes two axes, the public transport axis and the second axis the private transport axis, as each of these axes includes several types of transport, namely (sea transport, air transport, land transport, transport by rail, port transport) and the travel and tourism sector, as public transport lacks this sector, as the competitive advantage matrix for the transport sector was formed and after applying the MinMax-MaxMin principle to the matrix in all its stages, it was found that there was an equilibrium point except for the last stage where the equilibrium point was not available Therefore, the use of the linear programming method was
... Show MoreFind all boils down to is marked with (recruitment aesthetic of digital technology for (color) in the film novelist) And the relationship between the aesthetic employment of digital technology for (color) and its impacts on the level of artistic creativity through digital technology and its impacts on the technical and completed the final film in the film.Search and distributed at five chapters The first chapter discusses the methodological framework of the research, which included the research problem and is as follows:What is the digital technology to enrich color in the context in the film narrative to reflect the dramatic effect?And the importance of research and its objectives, including:1 - Employment aesthetic of digital technolog
... Show MoreThe Next-generation networks, such as 5G and 6G, need capacity and requirements for low latency, and high dependability. According to experts, one of the most important features of (5 and 6) G networks is network slicing. To enhance the Quality of Service (QoS), network operators may now operate many instances on the same infrastructure due to configuring able slicing QoS. Each virtualized network resource, such as connection bandwidth, buffer size, and computing functions, may have a varied number of virtualized network resources. Because network resources are limited, virtual resources of the slices must be carefully coordinated to meet the different QoS requirements of users and services. These networks may be modifie
... Show MoreFicus (FIC) leaf extract used as corrosion inhibitor for carbon steel alloy (C.S) in two corrosive environments (saline and acidic) with four concentrations (1, 2, 3 and 4 ppm) at varied temperature range between (298-328 K) using electrochemical polarization measurements. The importance of this work focused on the use the green chemistry that is far from the chemical materials effect. The results of polarization presented the FIC inhibitor consider a mixed type (anodic and cathodic) inhibitor. Tafel curve used to evaluate the corrosion inhibition activity. In a saline medium, the best inhibitor efficiency reaches to (87%) in 2 ppm and IE% reach to (99%) for HCl medium inhibited by 1ppm. Langmuir isotherm obeys the study by thermodynamic pa
... Show MoreThis work aimed to produce PVA and PVA/Ag nanofibers ultra-high sensitivity photodetector by electrospinning. The electrospinning process was used to successfully prepare PVA nanofibers and a PVA-Ag nanofiber composite. FE-SEM, XRD, UV, I-V characterizations are used to study the morphological, structural, optical, and electrical properties of the material. In contrast, the PVA-Ag nanofiber composite film displayed a cubic structure with favored orientation (200) that indicated the presence of Ag NPs in the PVA-Ag nanofibers film. While the optical energy gap for PVA was 3.96 eV, it was only 2.14 eV for PVA-Ag nanofibers composite film, making this composite sensitive to visible light, particularly green light at 550 nm with a 65% photosens
... Show MoreThis research describes a new model inspired by Mobilenetv2 that was trained on a very diverse dataset. The goal is to enable fire detection in open areas to replace physical sensor-based fire detectors and reduce false alarms of fires, to achieve the lowest losses in open areas via deep learning. A diverse fire dataset was created that combines images and videos from several sources. In addition, another self-made data set was taken from the farms of the holy shrine of Al-Hussainiya in the city of Karbala. After that, the model was trained with the collected dataset. The test accuracy of the fire dataset that was trained with the new model reached 98.87%.