Laser is a powerful device that has a wide range of applications in fields ranging from materials science and manufacturing to medicine and fibre optic communications. One remarkable

   Nanoparticles (NPs) have unique capabilities that make them an eye-opener opportunity for the upstream oil industry. Their nano-size allows them to flow within reservoir rocks without the fear of retention between micro-sized pores. Incorporating NPs with drilling and completion fluids has proved to be an effective additive that improves various properties such as mud rheology, filtration, thermal conductivity, and wellbore stability. However, the biodegradability of drilling fluid chemicals is becoming a global issue as the discharged wetted cuttings raise toxicity concerns and environmental hazards. Therefore, it is urged to utilize chemicals that tend to break down and susceptible to biodegradation. This research presents the pra

Characterized Iraq, being one of the oldest countries where oil was discovered in the Middle East since 1927, and possess a vast oil reserves. In addition, the production and marketing of Iraqi oil continued since 1934 and until the present time. Over the past eight decades, the range of economic benefit of the financial Iraq’s oil resources varied according to the applicable forms of investments in the oil sector in Iraq.

This research included a study

This study utilizes streamline simulation to model fluid flow in the complex subsurface environment of the Mishrif reservoir in Iraq's Buzurgan oil field. The reservoir faces challenges from high-pressure depletion and a substantial increase in water cut during production, prompting the need for innovative reservoir management. The primary focus is on optimizing water injection procedures to reduce water cuts and enhance overall reservoir performance. Three waterflooding tactics were examined: normal conditions without injectors or producers, normal conditions with 30 injectors and 80 producers and streamline simulation using the frontsim simulator. Three main strategies were employed to streamline water injection in targeted areas.

In this study the assessment radon concentration in sludge of Oil
Fields in North Oil Company (N.O.C.) of Iraq have been studied
using CR-39 solid–state nuclear track detector technique. A total of
34 samples selected from 12 oil stations in the company have been
placed in the dosimeters. The average radon concentration was found
to be 162.29 Bq/m³ which is fortunately lower than the standard
international limit. The potential alpha energy concentration and
annual effective dose have been calculated. A proportional
relationship between the annual effective dose and radon
concentration within the studied region has been certified.

We explore the transform coefficients of fractal and exploit new method to improve the compression capabilities of these schemes. In most of the standard encoder/ decoder systems the quantization/ de-quantization managed as a separate step, here we introduce new way (method) to work (managed) simultaneously. Additional compression is achieved by this method with high image quality as you will see later.

This paper presents the matrix completion problem for image denoising. Three problems based on matrix norm are performing: Spectral norm minimization problem (SNP), Nuclear norm minimization problem (NNP), and Weighted nuclear norm minimization problem (WNNP). In general, images representing by a matrix this matrix contains the information of the image, some information is irrelevant or unfavorable, so to overcome this unwanted information in the image matrix, information completion is used to comperes the matrix and remove this unwanted information. The unwanted information is handled by defining {0,1}-operator under some threshold. Applying this operator on a given ma

The field of autonomous robotic systems has advanced tremendously in the last few years, allowing them to perform complicated tasks in various contexts. One of the most important and useful applications of guide robots is the support of the blind. The successful implementation of this study requires a more accurate and powerful self-localization system for guide robots in indoor environments. This paper proposes a self-localization system for guide robots.  To successfully implement this study, images were collected from the perspective of a robot inside a room, and a deep learning system such as a convolutional neural network (CNN) was used. An image-based self-localization guide robot image-classification system delivers a more accura