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

This work deals with preparation of zeolite 5A from Dewekhala kaolin clay in Al-Anbar region for drying and desulphurization of liquefied petroleum gas. The preparation of zeolite 5A includes treating kaolin clay with dilute hydrochloric acid 1N, treating metakaolin with NaOH solution to prepare 4A zeolite, ion exchange, and formation. For preparation of zeolite 4A, metakaolin treated at different temperatures (40, 60, 80, 90, and 100 °C) with different concentrations of sodium hydroxide solution (1, 2, 3, and 4 N) for 2 hours. The zeolite samples give the best relative crystallinity of zeolite prepared at 80 °C with NaOH concentration 3N (199%), and at 90 and 100°C with NaOH concentration solution 2N (184% and 189%, respectively). Ze

Buzurgan oil Field which is located in south of Iraq has been producing oil for five decades that caused production to drop in many oil wells. This paper provides a technical and economical comparison between the ESP and gas lift in one oil well (Bu-16) to help enhancing production and maximize revenue. Prosper software was used to build, match and design the artificial lift method for the selected well, also to predict the well behavior at different water cut values and its effect on artificial lift method efficiency. The validity of software model was confirmed by matching, where the error difference value between actual and calculated data was (-1.77%).

The ESP results showed the durability of ESP regarding th

The permeability is the most important parameter that indicates how efficient the reservoir fluids flow through the rock pores to the wellbore. Well-log evaluation and core measurements techniques are typically used to estimate it. In this paper, the permeability has been predicted by using classical and Flow zone indicator methods. A comparison between the two methods shows the superiority of the FZI method correlations, these correlations can be used to estimate permeability in un-cored wells with a good approximation.

Particulate matter (PM) emitted from diesel engine exhaust have been measured in terms of mass, using
99.98 % pure ethanol blended directly, without additives, with conventional diesel fuel (gas – oil),to
get 10 % , 15 %, 20 % ethanol emulsions . The resulting PM collected has been compared with those
from straight diesel. The engine used is a stationary single cylinder, variable compression ratio Ricardo
E6/US. This engine is fully instrumented and could run as a compression or spark ignition.
Observations showed that particulate matter (PM) emissions decrease with increasing oxygenate
content in the fuel, with some increase of fuel consumption, which is due to the lower heating value of
ethanol. The reduction in

The major of DDoS attacks use TCP protocol and the TCP SYN flooding attack is the most common one among them. The SYN Cookie mechanism is used to defend against the TCP SYN flooding attack. It is an effective defense, but it has a disadvantage of high calculations and it doesn’t differentiate spoofed packets from legitimate packets. Therefore, filtering the spoofed packet can effectively enhance the SYN Cookie activity. Hop Count Filtering (HCF) is another mechanism used at the server side to filter spoofed packets. This mechanism has a drawback of being not a perfect and final solution in defending against the TCP SYN flooding attack. An enhanced mechanism of Integrating and combining the SYN Cookie with Hop Count Filtering (HCF) mech

In this work, fluid catalytic cracking of vacuum gas oil to produce gasoline over prepared faujasite type Y zeolite was investigated using experimental laboratory plant scale of fluidized bed reactor.
The catalytic activity of prepared faujasite type NaY, NaNH4Y and NaHY zeolites was investigated. The cracking process was carried out in the temperature range 440 to 500 oC, weight hourly space velocity (WHSV) range 10 to 25 h-1 ,and atmospheric pressure . The catalytic activities of the prepared faujasite type NaY , NaNH4Y and NaHY zeolites were determined in terms of vacuum gas oil (VGO) conversion, and gasoline yield . The conversion at 500oC and WHSV10 hr-1 by using faujasite type NaY, NaNH4Y and NaHY zeolite were 50.2%, 64.1% and 6

Hollow core photonic bandgap fibers provide a new geometry for the realization and enhancement of many nonlinear optical effects. Such fibers offer novel guidance and dispersion properties that provide an advantage over conventional fibers for various applications. Dispersion, which expresses the variation with wavelength of the guided-mode group velocity, is one of the most important properties of optical fibers. Photonic crystal fibers (PCFs) offer much larger flexibility than conventional fibers with respect to tailoring of the dispersion curve. This is partly due to the large refractive-index contrast available in the silica/air microstructures, and partly due to the possibility of making complex refractive-index structure over the fibe