Drilling deviated wells is a frequently used approach in the oil and gas industry to increase the productivity of wells in reservoirs with a small thickness. Drilling these wells has been a challenge due to the low rate of penetration (ROP) and severe wellbore instability issues. The objective of this research is to reach a better drilling performance by reducing drilling time and increasing wellbore stability.

In this work, the first step was to develop a model that predicts the ROP for deviated wells by applying Artificial Neural Networks (ANNs). In the modeling, azimuth (AZI) and inclination (INC) of the wellbore trajectory, controllable drilling parameters, unconfined compressive strength (UCS), formation

Drilling deviated wells is a frequently used approach in the oil and gas industry to increase the productivity of wells in reservoirs with a small thickness. Drilling these wells has been a challenge due to the low rate of penetration (ROP) and severe wellbore instability issues. The objective of this research is to reach a better drilling performance by reducing drilling time and increasing wellbore stability.

In this work, the first step was to develop a model that predicts the ROP for deviated wells by applying Artificial Neural Networks (ANNs). In the modeling, azimuth (AZI) and inclination (INC) of the wellbore trajectory, controllable drilling parameters, unconfined compressive strength (UCS), formation

Biofilm formation is one of the biggest challenges of scientists. Role of heavy metals in forming biofilm is not clear enough. Here, the effect of lead on biofilm formation by Bacillus spp. isolated from soil in terms of biofilm formation and remove was studied. In present study, 10 isolates of Bacillus spp were isolated from soil. The ability of all isolates to form biofilm was evaluated. The effect of lead on biofilm formation was studied by adding lead (pb) before forming biofilm. In another experiment the lead was added after biofilm formation to study the effect of lead on biofilm remove. The current study, showed the ability of all studied isolates to form biofilm. Maximum biofilm formation by Bacillus spp isolate number 8 (B8) follow

The physical and elastic characteristics of rocks determine rock strengths in general. Rock strength is frequently assessed using porosity well logs such as neutron and sonic logs. The essential criteria for estimating rock mechanic parameters in petroleum engineering research are uniaxial compressive strength and elastic modulus. Indirect estimation using well-log data is necessary to measure these variables. This study attempts to create a single regression model that can accurately forecast rock mechanic characteristics for the Harth Carbonate Formation in the Fauqi oil field. According to the findings of this study, petrophysical parameters are reliable indexes for determining rock mechanical properties having good performance p

Knowing the distribution of the mechanical rock properties and in-situ stresses for the field of interest is essential for many applications concerning reservoir geomechanics, including wellbore instability analysis, hydraulic fracturing, sand production, reservoir compaction, subsidence and water/gas injection throughout the filed life cycle. Determining the rock's mechanical properties is challenging because they cannot be directly measured at the borehole. The recovered carbonate core samples are limited and only provide discrete data for specific depths. This study focuses on creating a detailed 1D geomechanical model of the Mishrif reservoir in the Nasriyah oil field to identify the fault regime type for each unit in the format