当社グループは 3,000 以上の世界的なカンファレンスシリーズ 米国、ヨーロッパ、世界中で毎年イベントが開催されます。 1,000 のより科学的な学会からの支援を受けたアジア および 700 以上の オープン アクセスを発行ジャーナルには 50,000 人以上の著名人が掲載されており、科学者が編集委員として名高い
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700 ジャーナル と 15,000,000 人の読者 各ジャーナルは 25,000 人以上の読者を獲得
Qays MS, Wan IWY
The Bai Hassan Field is one of the Iraq’s giant oil fields with multiple pay zones similar to most of the northern Iraq oil fields. Knowledge of pore pressure is essential for economically and save well planning and efï¬Âcient reservoir modeling. Pore pressure prediction has an important application in proper selection of the casing points and a reliable mud weight. In addition, using cost-effective methods of pore pressure prediction, which give extensive and continuous range of data, is much reasonable than direct measuring of pore pressure. The main objective of this project is to determine the pore pressure using well log data in Bai Hassan oil ï¬Âelds. To obtain this goal, the formation pore pressure is predicted from well logging data by applying three different methods including the Eaton, the Bowers and the compressibility methods. Predicted results have to show that the best correlation with the measured pressure data must achieved by the modiï¬Âed Eaton method with Eaton's exponent of about 0.5. Finally, in order to generate the 3D pore pressure model, well-log-based estimated pore pressures from the Eaton method will upscale and distribute throughout the 3D structural grid using a geo statistical approach. The 3D pore pressure model has to show good agreement with the well-log-based estimated pore pressure and the measured pressure obtained from modular formation dynamics tester.