The Yamama Formation was studied in three wells (Fh-1, Fh-2, and Fh-3) within Faihaa oil field, south Iraq. Thin sections were studied by using the polarizing microscope examination in order to determine microfossils and biozone. Thirty-five species of benthic foraminifera were recognized, including four index species. In addition,  twelve species of calcareous green algae were recognized, including  two index species. Other fossils that were recognized in Yamama Formation include Gastropoda, Bryozoa, Coral, Rudist, and Pelecypoda.

Six biozones were observed, which are Charentia cuvillieri sp. (Range Zone of Berriasian age), Psudochryalidina infracretacea

Six main microfacies are identified which are Lime Mudstone, Bioclastic Wackeston, Bioclastic Packstone-Wackestone, Bioclastic Wackestone- Mudestone, Pelagic Mudstone–Wackestone, Bioclastic Packstone -Grainston Microfacies in addition to their associated depositional environment. The diagenesis process have affected the Mishrif rocks and played a role in deteriorating reservoir porosity in well Ga-2 and enhancing it in well Ga1,3.These processes include: cementation, micritization, recrystallization,dissolution,compaction pressure solution and dolomitization.

Five oil sample of Mashrif and Nahr Umr Formation for Amarah oil field,
southern Iraq, were taken and analyzed in Geo Mark laboratory in USA center in
order to determine the bulk properties of crude oils and carbon isotopes for these
samples in addition to determine biomarker parameters using Gas
Chromatography(GC), and Gas Chromatography Mass Spectrometry )GCMS
(analytical technique. According to these biomarker analyses of the two formation, it
is indicated that they are non-degraded, marine, non-waxy, derived from
carbonate source and deposition in anoxic marine environment. This study also
showed that the bulk properties (terpanes and steranes) of Amarah oil field are one
family, and the source rocks contai

Iraq is one of the Arabian area countries, which considered from the drier areas
on the earth, though it has two main rivers that pass through(Tigris and Euphrates);
it suffers the same problem as them (drought), only the rivers' nearby regions make
use of their water for (domestic, agricultural, and industrial purposes(.
One of the usable solutions is to utilize the groundwater (especially in the desert
regions). Using the Remote Sensing and geographic information system is a rapid
and coast effective techniques, they provide information of large and inaccessible
area within short span for assessing, monitoring, and management of groundwater
resources. In this study, an adaptive algorithm based on Canny edge dete

These days, it is crucial to discern between different types of human behavior, and artificial intelligence techniques play a big part in that.  The characteristics of the feedforward artificial neural network (FANN) algorithm and the genetic algorithm have been combined to create an important working mechanism that aids in this field. The proposed system can be used for essential tasks in life, such as analysis, automation, control, recognition, and other tasks. Crossover and mutation are the two primary mechanisms used by the genetic algorithm in the proposed system to replace the back propagation process in ANN. While the feedforward artificial neural network technique is focused on input processing, this should be based on the proce

Net pay is one of the most important parameters used in determining initial oil in place of a reservoir. It can be delineated through the using of limiting values of the petrophysical properties of the reservoir. Those limiting values are named as the cutoff. This paper provides an insight into the application of regression line method in estimating porosity, clay volume and water saturation cutoff values in Mishrif reservoir/ Missan oil fields. The study included 29 wells distributed in seven oilfields of Halfaya, Buzurgan, Dujaila, Noor, Fauqi, Amara and Kumait.

This study is carried out by applying two types of linear regressions: Least square and Reduce Major Axis Regression.

The Mishrif formation was

One of the most important problems in the oil production process and when its continuous flow, is emulsified oil (w/o emulsion), which in turn causes many problems, from the production line to the extended pipelines that are then transported to the oil refining process. It was observed that the nanomaterial (SiO₂) supported the separation process by adding it to the emulsion sample and showed a high separation rate with the demulsifiers (RB6000) and (sebamax) where the percentage of separation was greater than (90 and 80 )%  respectively, and less than that when dealing with (Sodium dodecyl sulfate and Diethylene glycol), the percentage of separation was (60% and 50%) respectively.

   The high proportion

It is very difficult to obtain the value of a rock strength along the wellbore.  The value of Rock strength utilizing to perform different analysis, for example, preventing failure of the wellbore, deciding a completion design and, control the production of sand.  In this study, utilizing sonic log data from (Bu-50) and (BU-47) wells at Buzurgan oil field.  Five formations have been studied (Mishrif, Sadia, Middle lower Kirkuk, Upper Kirkuk, and Jaddala) Firstly, calculated unconfined compressive strength (UCS) for each formation, using a sonic log method.  Then, the derived confined compressive rock strengthens from (UCS) by entering the effect of bore and hydrostatic pressure for each formation.  Evaluations th

Prediction of penetration rate (ROP) is important process in optimization of drilling due to its crucial role in lowering drilling operation costs. This process has complex nature due to too many interrelated factors that affected the rate of penetration, which make difficult predicting process. This paper shows a new technique of rate of penetration prediction by using artificial neural network technique. A three layers model composed of two hidden layers and output layer has built by using drilling parameters data extracted from mud logging and wire line log for Alhalfaya oil field. These drilling parameters includes mechanical (WOB, RPM), hydraulic (HIS), and travel transit time (DT). Five data set represented five formations gathered