Low salinity (LS) water flooding is a promising EOR method which has been examined by many experimental studies and field pilots for a variety of reservoirs and oils. This paper investigates applying LS flooding to a heavy oil. Increasing the LS water temperature improves heavy oil recovery by achieving higher sweep efficiency and improving oil mobility by lowering its viscosity. Steam flooding projects have reported many problems such as steam gravity override, but override can be lessened if the steam is is alternated with hot LS water. In this study, a series of reservoir sandstone cores were obtained from Bartlesville Sandstone (in Eastern Kansas) and aged with heavy crude oil (from the same reservoir) at 95°C for 45 days. Five reservoir cores were used in this study, and five treatments were performed. They were flooded with (a) steam; (b) formation hot water (FHW); (c) low salinity hot water (LSHW; (d) steam + FHW; and (e) steam + LSHW (so-called LSASF). The laboratory experiments showed that basic water flooding using FW recovered approximately 50% of OOIP. After that initial flood, upon switching to the various steam, FHW, LSHW, steam + FHW, and steam + LSHW treatments, the incremental oil recoveries were 5, 3.1, 6.3, 7.5, and 12% OOIP, respectively. The contact angle measurements showed that injecting steam + LSHW alters the wettability considerably more than using steam + FHW. The results of this work show that water flooding using LSHW in reservoir cores could improve oil recovery significantly because it both reduces oil viscosity and alters the rock wettability towards more water-wet. The results also showed using LSHW alternated with steam is more beneficial than using steam only or alternated with regular water due to the combined benefits of reducing gravity override and altering the wettability. Using LSHW water is more economical than using steam and gives significantly improved oil recovery, and using LSHW is more beneficial than ambient temperature LS water.
The transfer function model the basic concepts in the time series. This model is used in the case of multivariate time series. As for the design of this model, it depends on the available data in the time series and other information in the series so when the representation of the transfer function model depends on the representation of the data In this research, the transfer function has been estimated using the style nonparametric represented in two method local linear regression and cubic smoothing spline method The method of semi-parametric represented use semiparametric single index model, With four proposals, , That the goal of this research is comparing the capabilities of the above mentioned m
... Show MoreEstimation of mechanical and physical rock properties is an essential issue in applications related to reservoir geomechanics. Carbonate rocks have complex depositional environments and digenetic processes which alter the rock mechanical properties to varying degrees even at a small distance. This study has been conducted on seventeen core plug samples that have been taken from different formations of carbonate reservoirs in the Fauqi oil field (Jeribe, Khasib, and Mishrif formations). While the rock mechanical and petrophysical properties have been measured in the laboratory including the unconfined compressive strength, Young's modulus, bulk density, porosity, compressional and shear -waves, well logs have been used to do a compar
... Show MoreIn this study, 20 patients were selected having renal failure .10 patients were hemo& 10 peritoneal dialysis procedure. Patients had been given r HuEPO subcutaneous with supplement of Iron dextran after di alysis . Hemoglobin Hb concentration Hematocrit(Hct),serum I ron ,total Iron binding capacity, transferrin saturation percent Ts%
& Serum ferritin were measured. Non significant chan
... Show MoreThe thyroid gland is a vital part of the overall endocrine system, which is regulated some of body function as oxygen use, basal metabolic rate, growth, cellular metabolism and development This study shed light on a number of extracts that have been shown to have beneficial effects on the thyroid and its function, as well as the various factors linked to thyroid dysfunction. The experiment was conducted to determine the effect of a mixture of two extracts of "Fucus vesiculosus (150 mg/ kg) with Coleus forskohlii (1000 mg/ kg) and Rosmarinus officinalis (220 mg/ kg) with Camellia sinensis (1.25 mg/ kg)" on thyroid hormones as well as lipids profile and tested the effectiveness of two drugs one of them stimulates the hormones of the thyroid (
... Show MoreIn this paper, the theoretical cross section in pre-equilibrium nuclear reaction has been studied for the reaction at energy 22.4 MeV. Ericson’s formula of partial level density PLD and their corrections (William’s correction and spin correction) have been substituted in the theoretical cross section and compared with the experimental data for nucleus. It has been found that the theoretical cross section with one-component PLD from Ericson’s formula when doesn’t agree with the experimental value and when . There is little agreement only at the high value of energy range with the experimental cross section. The theoretical cross section that depends on the one-component William's formula and on-component corrected to spi
... Show MoreIn the presence of multi-collinearity problem, the parameter estimation method based on the ordinary least squares procedure is unsatisfactory. In 1970, Hoerl and Kennard insert analternative method labeled as estimator of ridge regression.
In such estimator, ridge parameter plays an important role in estimation. Various methods were proposed by many statisticians to select the biasing constant (ridge parameter). Another popular method that is used to deal with the multi-collinearity problem is the principal component method. In this paper,we employ the simulation technique to compare the performance of principal component estimator with some types of ordinary ridge regression estimators based on the value of t
... Show MoreThis research discussed, the process of comparison between the regression model of partial least squares and tree regression, where these models included two types of statistical methods represented by the first type "parameter statistics" of the partial least squares, which is adopted when the number of variables is greater than the number of observations and also when the number of observations larger than the number of variables, the second type is the "nonparametric statistic" represented by tree regression, which is the division of data in a hierarchical way. The regression models for the two models were estimated, and then the comparison between them, where the comparison between these methods was according to a Mean Square
... Show MoreRutting has a significant impact on the pavements' performance. Rutting depth is often used as a parameter to assess the quality of pavements. The Asphalt Institute (AI) design method prescribes a maximum allowable rutting depth of 13mm, whereas the AASHTO design method stipulates a critical serviceability index of 2.5 which is equivalent to an average rutting depth of 15mm. In this research, static and repeated compression tests were performed to evaluate the permanent strain based on (1) the relationship between mix properties (asphalt content and type), and (2) testing temperature. The results indicated that the accumulated plastic strain was higher during the repeated load test than that during the static load tests. Notably, temperatur
... Show MoreThe aim of the research is to study the comparison between (ARIMA) Auto Regressive Integrated Moving Average and(ANNs) Artificial Neural Networks models and to select the best one for prediction the monthly relative humidity values depending upon the standard errors between estimated and observe values . It has been noted that both can be used for estimation and the best on among is (ANNs) as the values (MAE,RMSE, R2) is )0.036816,0.0466,0.91) respectively for the best formula for model (ARIMA) (6,0,2)(6,0,1) whereas the values of estimates relative to model (ANNs) for the best formula (5,5,1) is (0.0109, 0.0139 ,0.991) respectively. so that model (ANNs) is superior than (ARIMA) in a such evaluation.