GROUNDWATER MODELING OF THE BAZURGAN OIL FIELD AREA
محتوى المقالة الرئيسي
الملخص
The hydraulic performance of the aquifer has been investigated thlough the use of a computer program package.
The hydrogeological information which are required for aquifer simulation have been collected from various sources, evaluated, then used as an input data for the computer package. Due to the
scarcity of "data, it has been a difficult task to delimit the location and type of the hydraulic
boundaries along the northem and eastern sides of the area for modeling purpose. Accordingly, three cases are treated depending on the assumed nature of the boundaries. In the first all the boundaries are assumed at constant head. In the second, the northern and eastem boundaries are assumed to be of no flow type, whereas the Tigris river and AI- Musharah river both of which representing the west,rn and southern boundaries are treated as constant head. The third case is similar to the first; however the effect of Al- Teeb River and the marshes in the south are also taken into consideration.
The steady- state natural head distribution prior to the effect of any external stresses irave been obtained by the steady- state treatment, and by the tursteady- state treatment for a very long simulation period. Both results gave nearly similar head clistribution which is comparable tairly well with measured head values. The steady- state head distribution is used as initial head values in the subsequent unsteady- state treatments.
The drawdown distribution for the effect of existing wells, and proposed plans for future groundwater exploitation have been determined. It is found that the aquifer is capable to yield good quantities of water
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المراجع
Ahmad Ghasempoor (1997), Automatic Adjustment of cutting conditions in turning, univ. Of polytechnic Department Of Mach; Aero space and Industrial Eng.
Bahaa. Ibraheem. K and Nabeil .k .AL - Sahib (20A2), Surface Finish Characteristics in turning processes, J. of science and Eng. AL - Anbar univ. lraq , Vol2 NO .2.0
M. Hasegawa A. Seirey and R.A.Lindberg (1976), surface roughness model for turning, Tribology Int., December. p285-289.
N. Costa. B. Ribeiro (1998), A neural Prediction Model for monitoring and Fault Diagnosis of a plastic Injection Molding Process, CISUC Department of Eng. Informatics, combra, Portugal, 1998.
N. Costa, A Tuna, B. Ribeiro, Monitoring an Industrial plastic Injection Moulding Machine using Neural networks, CISUC - Department of Eng. Informatics, combra, Portugal,
R.G. Khunchustombham and G.M. Zhang (2001), A neural Approach to on-line Monitoring of a turning process. The mechanical Research Report Univ of Maryland, system Research center
Sarah, S.Y. Alice E smith (1996), Process Monitoring of Abrasive Flow Machining using A neural Network predictive model, university of Pittsburgh, dept of Industrial Eng
Tugral Ozel: Abhijit Nodgir (2002), Prediction of Flank Wear by using back propagation neural network modeling when cutting hardened H-13 steel with chamfered and honed CBN tool, Int. J.Of Machine tools and manufacture, 42, 287-297
T. Munakata. (1998), Fundamentals Of The New Artificial Intelligence. Beyond Tradition a paradigs, Springer-Verlag New York Inc.