This book deals with image-processing problems that arise in the pro­ cess of automating some aspects of well log analysis. Each problem is first described in log analysis terms - that is, what task is performed by a log analyst and how it is accomplished in manual processing. Then algorithms for automating each function are presented and their meanings from the point of view of log analysis and image processing are explained. The term image processing is understood here, in its broadest sense, as any processing of any images. I developed many of the algorithms presented in this book for par­ ticular independent applications. Later, when I realized that they used some common techniques for analysis of logging curves, I applied these techniques in designing new algorithms. To present the algorithms here, I first formulate a minimization principle that has proved useful in a number of applications. Then I describe image-processing problems and their solutions based on this principle and some other common techniques. Finally, I describe al­ ternative approaches. At first reading, readers may choose to skip the chapter describing the minimization principle and come back to it later when they have seen how the principle can be applied. This order of reading is further justified by the fact that the formulas that apply the general principle are different for each application, so their derivation is repeated each time independently.

lgrsnf/A:\Springer\bok%3A978-94-009-4670-5.pdf

nexusstc/Image Processing in Well Log Analysis/8931b99213ae3e25c9a9f5a50180ea0d.pdf

zlib/Business & Economics/Mathematical Economics/Mark G. Kerzner (auth.)/Image Processing in Well Log Analysis_2239602.pdf

Springer Science + Business Media BV

Netherlands, Netherlands

Dordrecht, 1986

lg1070636

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Content:
Front Matter....Pages i-xiv
An Overview....Pages 1-4
The Minimization Principle....Pages 5-9
Computing the Shear Wave Velocity Log: Curve Detection in Noisy Pictures....Pages 11-20
Dipmeter Correlation: A Pattern-Matching Problem....Pages 21-40
Depth Matching: A Pattern-Matching Problem....Pages 41-60
Dipmeter PostProcessing: An Image-Sharpening Problem....Pages 61-78
Coloring a Computed Dipmeter Log: Feature Identification....Pages 79-85
Blocking: Curve Shape Analysis....Pages 87-94
Conclusion: Directions for Future Research....Pages 95-97
An Algorithm to Implement the Minimization Principle....Pages 99-109
An Algorithm to Implement the Modified Minimization Principle....Pages 111-117
Forms of Activity Function....Pages 119-120
Back Matter....Pages 121-123

2013-12-12