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 from five drilled wells were involved in modeling process.Approximatlly,85 % of these data were used for training the ANN models, and 15% to assess their accuracy and direction of stability. The results of the simulation showed good matching between the raw data and the predicted values of ROP by Artificial Neural Network (ANN) model. In addition, a good fitness was obtained in the estimation of drilling cost from ANN method when compared to the raw data.
The Mishrif Formation is one of the most important formation in oil fields, which is located in southern part of Iraq, and it is of Upper Cretaceous age. Tuba field is located nearly 40 km SW – Basrah city. It is bounded from east by Zubair oil field (5 km distance) and from west by Rumaila (2 km distance). The Tuba oil field is situated between Zubair oil field in the east and Rumaila in the west, and is separated by two depressions.
The rock (core and chips) samples have been collected systematically from cores of Mishrif Formation that are available from stores of southern oil company to prepare thin sections and slides—these slides have been examined by using microscope. These samples have been taken from all parts of the rese
In this study, a qualitative seismic velocity interpretation is made up through using 2D-seismic reflection data on Luhais oil field in southern of Iraq which is situated at about 105 Km to the east from the Basra city. Luhais oil field was chosen to study the type and nature of the distribution of the seismic velocities of Nahr Umr and Zubair Formations in order to show its explorational importance, where these formations contain abundant quantities of hydrocarbons. Picking of the tops of Nahr Umr and Zubair was carried out from the synthetic seismogram which is calculated from sonic-logs and check shot of well Lu-2. Velocity model was obtained via using an implementation of Petrel program version, 2013 and was corrected according to to
... Show MoreThe study intends to interpretation of well logs to determine the petrophysical parameters for Khasib, Tanuma, and Sa'di formations in Halfaya Oil Field. Where this field is located 30 kilometers south-east of the Amara city and it is considered as one of the important fields in Iraq because of the high production of oil, because Khasib, Tanuma, and Sa'di are f carbonates reservoirs formations and important after the Mishrif Formation because of the lack of thickness of the formations compared to the amount of oil production. The Matrix Identification (MID) and the M-N crossplot were used to determine the lithology and mineralogy of the formations; through the diagrm it was found the three formations consisted mainly of calcite with some
... Show MoreMany oil and gas processes, including oil recovery, oil transportation, and petroleum processing, are negatively impacted by the precipitation and deposition of asphaltene. Screening methods for determining the stability of asphaltenes in crude oil have been developed due to the high cost of remediating asphaltene deposition in crude oil production and processing. The colloidal instability index, the Asphaltene-resin ratio, the De Boer plot, and the modified colloidal instability index were used to predict the stability of asphaltene in crude oil in this study. The screening approaches were investigated in detail, as done for the experimental results obtained from them. The factors regulating the asphaltene precipitation are different fr
... Show MoreThe EMERGE application from Hampsson-Russell suite programs was used in the present study. It is an interesting domain for seismic attributes that predict some of reservoir three dimensional or two dimensional properties, as well as their combination. The objective of this study is to differentiate reservoir/non reservoir units with well data in the Yamama Formation by using seismic tools. P-impedance volume (density x velocity of P-wave) was used in this research to perform a three dimensional seismic model on the oilfield of Nasiriya by using post-stack data of 5 wells. The data (training and application) were utilized in the EMERGE analysis for estimating the reservoir properties of P-wave ve
... Show MoreIn this paper, we present a Branch and Bound (B&B) algorithm of scheduling (n) jobs on a single machine to minimize the sum total completion time, total tardiness, total earliness, number of tardy jobs and total late work with unequal release dates. We proposed six heuristic methods for account upper bound. Also to obtain lower bound (LB) to this problem we modified a (LB) select from literature, with (Moore algorithm and Lawler's algorithm). And some dominance rules were suggested. Also, two special cases were derived. Computational experience showed the proposed (B&B) algorithm was effective in solving problems with up to (16) jobs, also the upper bounds and the lower bound were effective in restr
... Show MoreIn light of the development in computer science and modern technologies, the impersonation crime rate has increased. Consequently, face recognition technology and biometric systems have been employed for security purposes in a variety of applications including human-computer interaction, surveillance systems, etc. Building an advanced sophisticated model to tackle impersonation-related crimes is essential. This study proposes classification Machine Learning (ML) and Deep Learning (DL) models, utilizing Viola-Jones, Linear Discriminant Analysis (LDA), Mutual Information (MI), and Analysis of Variance (ANOVA) techniques. The two proposed facial classification systems are J48 with LDA feature extraction method as input, and a one-dimen
... Show MoreThe possibility of predicting the mass transfer controlled CaCO3 scale removal rate has been investigated.
Experiments were carried out using chelating agents as a cleaning solution at different time and Reynolds’s number. The results of CaCO3 scale removal or (mass transfer rate) (as it is the controlling process) are compared with proposed model of prandtl’s and Taylor particularly based on the concept of analogy among momentum and mass transfer.
Correlation for the variation of Sherwood number ( or mass transfer rate ) with Reynolds’s number have been obtained .