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Intelligent Reservoir Characterization are increasingly replaced by stochastic and soft computing-based methods. The diversity of soft computing applications in oil field problems and prevalence of their acceptance are manifested by the overwhelming interest in the topics covered in this book. Future research should focus on the integra女歌星 发表于 2025-3-25 18:39:59
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Application of Self-Organizing Feature Maps to Reservoir Characterizationrvised neural networks. The three cases can be summarized as: 1) estimation based on spatial information only, 2) estimation guided by seismic data, and 3) analysis using an unsupervised neural network approach..A numerical study described in the first approach shows that it compares reasonably well纤细 发表于 2025-3-26 10:02:27
Inverting SP Logs Using Artificial Neural Networks and the Application in Reservoir Characterisatione ratio of mud resistivity to formation resistivity. They are designed so that this ratio scales the characteristic length as well as the relative weight in each depth interval. These filters are applied to artificial wells with predefined sequences of shales and sands of varying thickness, shalinesfinite 发表于 2025-3-26 13:29:33
The Application of Fuzzy Logic and Genetic Algorithms to Reservoir Characterization and Modelingdimentological controls on reservoir quality distribution as well an input to 3D reservoir models. Litho-facies and permeability prediction have presented a challenge due to the lack of borehole tools that measure them directly. We demonstrate, using several field examples, how these new predictiveEthics 发表于 2025-3-26 20:08:03
A New Technique to Estimate the Hydrocarbon Saturation in Shaly Formations: A Field Example in the Btion, the log analyst would need a . that reflects the actual distribution of hydrocarbon saturation to which all the above shaly models can be compared. A new technique to which the different shaly models can be compared is developed by the aid of well logs and special core analysis..The applicatio