By Ted Padova
The vintage Acrobat and PDF reference, up to date to hide the most recent release
Consistently the main authoritative and complete source at the Acrobat PDF structure, this commonplace reference returns with in-depth insurance of the latest model of Acrobat. Written through bestselling writer Ted Padova, this booklet is filled with real-world insights and strategies won from Padova's day-by-day use of Acrobat lower than time limit constraints. You'll observe every little thing there's to grasp approximately utilizing Acrobat X for print prepress, the web, CD-ROMs, and different kinds of media.
• well known writer Ted Padova stocks every little thing you want to find out about the newest unencumber of Acrobat—Acrobat X
• Explores the up-to-date features of the hot Acrobat and utilizing it for print prepress, the web, CD-ROMs, and more
As the last word source for all issues Acrobat and PDF-related, Adobe Acrobat X PDF Bible is an replace of a vintage.
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Extra info for Adobe Acrobat X PDF Bible
However, there are no connections between the nodes belonging to the same layer. The data flow between the layers is feed-forward. Basic algorithm of ANN is represented by the equation, where x is the neural network input vector (seismic attribute), y(x) is the output vector (reservoir property), fi(x) is basic function, wi is the weighting vector, and i 19 is the nwnber of nodes. , 1986). , 1994a, 1994b; Ronen eta!. , 1994). S 1. sh~4) -. ' N i_F~. Iow. u2100m_ h . -... 1200m_h<~a udlayer2---sha \ .
2 0 11- - 15 1 2- 11 19 . 02 S - 99 Figure 13. Porosity lateral distribution for the 10 microseconds interval ofEJ reservoir. In judging the validity of the maps two approaches were taken. Firstly, wellbased approach, to check the agreement between predicted values at well locations and the average values form log analysis for the relevant wells. Secondly, macro approach, to check the soundness of the maps from the point view of reservoir geology. 49 y 13-69 40-44 37-19 33-94 30-68 27-+3 2 .. 93 17 - 68 1 ..
The result is quite conformable to the estimation (27 m of prediction versus 24 m of observation). The points understood by our studies are summarized as follows: Monte Carlo Simulation is an effective method in the cases when factual well data are few or too concentrated so that it is difficult to obtain the relationship between lithological characteristics and seismic responses by traditional methods. Using the pseudo wells generated by the simulation, the lack of sample data can be compensated to a great extent.