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Study On The Method Of Formation Pressure Prediction In Geological Environment Modeling

Posted on:2011-07-01Degree:MasterType:Thesis
Country:ChinaCandidate:W FuFull Text:PDF
GTID:2120360308490332Subject:Information and Communication Engineering
Abstract/Summary:PDF Full Text Request
Formation pressure is an important parameter during oil&gas prospecting and exploitation. The accurate prediction of formation pressure before drilling can help to ensure safety in drilling, raise the drilling efficiency and reduce the drilling costs, et al.Based on the key project of SinoPec---'Drilling Simulation Based on Drilling Engineering Geology Database', this thesis mainly studies on the method of formation pressure prediction in drilling simulation. Its main contributions are as follows:1. Traditional prediction methods make the main use of the relationship between seismic velocity data and the formation pressure model to establish a normal compaction trend line and then calculate the formation pressure. Therefore, in this thesis, the formation pressure prediction method based on the normal compaction trend line method is studied first.2. The formation pressure prediction method based on Fillippone formula is studied. The results show that this method needn't any normal compaction trend. It is easy to use and has high prediction accuracy.3. In this paper, a new formation pressure prediction method based on hybrid genetic algorithm is proposed in order to improve the accuracy of the Fillippone formula method. First, rock density is calculated by the seismic velocity. Then matrix density and porosity are calculated through the hybrid genetic algorithm. Finally, the formation pressure is calculated according to Fillippone formula method. Compared with traditional methods, this method needn't any normal compaction trend and good result can be obtained with this method for the shale sand formation with good adaptability and accuracy.
Keywords/Search Tags:Formation Pressure, Parameter prediction, Fillippone, Seismic Velocity, Hybrid Genetic Algorithm
PDF Full Text Request
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