A Method Of Safe Mud Density Window And Casing Program Determination With Credibility

The formation pressure information in deep or ultra-deep wells is hard to be described accurately for the complex formation or pressure conditions and lack of offset references. In this thesis, the distribution of parameters in the pressure prediction model are determined via probability analysis method by investigating the uncertain factors in formation pressure prediction. The formation pressure profiles with credibility are acquired by direct theoretical caculation or Monte Carlo method. The safe mud density window with credibility are obtained by using pressure constraint criteria, and then the bottom-up and top-down casing program design methods according to the pressure profiles with credibility are presented. After that, the continuous casing point selection can be conducted. This method avoids the pilot caculation and varification process aiming at shut-in kicking and differential pressure sticking depths in the conventional design method. The continuous design can be conducted under the constraints with no need to determine casing setting depth by pilot caculation. The results acquired by this method is a continuous range. In the practical design, the final casing program can be determined by casing point selection range combining fomation geological information. A deep well in noutheast of Sichuan Province (Well Puguang 4 ) is used as a design example, and by comparison the design results show agreements with the real information. Meanwhile, The thesis presents a probabilistic risk analysis method applied for analyzing quantitatively the risk of the casing program design. The probabilistic risk analysis model for casing point selection had been established. The model generally includes four sub-models and each of them can make quantitative risk analysis on lost circulation, kicking, collapse and sticking respectively. This model can be used to make quantitative risk analysis on different casing point selection designs of the same well. The analysis results can provide valuable information for designers.