Shear wave velocity is an important feature in the seismic exploration that could be utilized in reservoir development strategy and characterization. Its vital applications in petrophysics, seismic, and geomechanics to predict rock elastic and inelastic properties are essential elements of good stability and fracturing orientation, identification of matrix mineral and gas-bearing formations. However, the shear wave velocity that is usually obtained from core analysis which is an expensive and time-consuming process and dipole sonic imager tool is not commonly available in all wells. In this study, a statistical method is presented to predict shear wave velocity from wireline log data. The model concentrated to predict shear wave velocity from petrophysical parameters and any pair of compressional wave velocity, porosity and density in carbonate rocks. The established method can estimate shear wave velocity in carbonate rocks with a correlation coefficient of close to unity.
Background: Candida tropicalis is one of the most causes of vulvovaginal candidiasis (VVC) in women. Systemic candidiasis and candidemia may also occur in pregnancies. Objective: This study was carried out to detect and isolate of this yeast from aborted placenta, which may cause severe complications such as spontaneous abortion. Materials and methods: Fresh aborted placenta were collected and washed by normal saline to remove the blood. Then, cut it into portions and place it in test tube containing 5 ml of normal saline. Finally, shake for 10 minutes, after that, cultured for microbial isolation. Isolation and detection were done by some conventional methods with Api candida and CHROMagar. Results: The results showed that four iso
... Show MoreOne of the costliest problems facing the production of hydrocarbons in unconsolidated sandstone reservoirs is the production of sand once hydrocarbon production starts. The sanding start prediction model is very important to decide on sand control in the future, including whether or when sand control should be used. This research developed an easy-to-use Computer program to determine the beginning of sanding sites in the driven area. The model is based on estimating the critical pressure drop that occurs when sand is onset to produced. The outcomes have been drawn as a function of the free sand production with the critical flow rates for reservoir pressure decline. The results show that the pressure drawdown required to
... Show MoreThe aim of this study is to investigate the feasibility of underground storage of gas in Um El-Radhuma formation /Ratawi field. This formation is an aquifer consisting of a high permeable dolomitebeds overlain by impermeable anhydrite bed of Rus formation. Interactive petrophysics (IP), Petrel REand Eclipse 100 softwares were used to conduct a well log interpretation, build a reservoir simulationmodel and predict the reservoir behavior during storage respectively. A black oil, three dimensionaland two phase fluid model has been used. The results showed that the upper part of Um El-Radhumaformation is suitable for underground gas storage, because of the seal of its cap rock and capability ofreserving gas in the reservoir. It was foun
... Show MoreThis research presents a method for calculating stress ratio to predict fracture pressure gradient. It also, describes a correlation and list ideas about this correlation. Using the data collected from four wells, which are the deepest in southern Iraqi oil fields (3000 to 6000) m and belonged to four oil fields. These wells are passing through the following formations: Y, Su, G, N, Sa, Al, M, Ad, and B. A correlation method was applied to calculate fracture pressure gradient immediately in terms of both overburden and pore pressure gradient with an accurate results. Based on the results of our previous research , the data were used to calculate and plot the effective stresses. Many equations relating horizontal effective stress and vertica
... Show MoreAbstract:
Interest in the topic of prediction has increased in recent years and appeared modern methods such as Artificial Neural Networks models, if these methods are able to learn and adapt self with any model, and does not require assumptions on the nature of the time series. On the other hand, the methods currently used to predict the classic method such as Box-Jenkins may be difficult to diagnose chain and modeling because they assume strict conditions.
... Show More
Massive multiple-input multiple-output (massive-MIMO) is a promising technology for next generation wireless communications systems due to its capability to increase the data rate and meet the enormous ongoing data traffic explosion. However, in non-reciprocal channels, such as those encountered in frequency division duplex (FDD) systems, channel state information (CSI) estimation using downlink (DL) training sequence is to date very challenging issue, especially when the channel exhibits a shorter coherence time. In particular, the availability of sufficiently accurate CSI at the base transceiver station (BTS) allows an efficient precoding design in the DL transmission to be achieved, and thus, reliable communication systems can be obtaine
... Show MoreThe objective of this study is to examine the properties of Bayes estimators of the shape parameter of the Power Function Distribution (PFD-I), by using two different prior distributions for the parameter θ and different loss functions that were compared with the maximum likelihood estimators. In many practical applications, we may have two different prior information about the prior distribution for the shape parameter of the Power Function Distribution, which influences the parameter estimation. So, we used two different kinds of conjugate priors of shape parameter θ of the <
... Show More