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Syntactic pattern recognition for seismic oil exploration /
The use of pattern recognition has become more and more important in seismic oil exploration. Interpreting a large volume of seismic data is a challenging problem. Seismic reflection data in the one-shot seismogram and stacked seismogram may contain some structural information from the response of t...
| Clasificación: | Libro Electrónico |
|---|---|
| Autor principal: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
River Edge, NJ :
World Scientific,
2002.
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| Colección: | Series in machine perception and artificial intelligence ;
v. 46. |
| Temas: | |
| Acceso en línea: | Texto completo |
Tabla de Contenidos:
- AUTHOR'S BIOGRAPHY; PREFACE; CONTENTS; 1 INTRODUCTION TO SYNTACTIC PATTERN RECOGNITION; 1.1. SUMMARY; 1.2. INTRODUCTION; 1.3. ORGANIZATION OF THIS BOOK; 2 INTRODUCTION TO FORMAL LANGUAGES AND AUTOMATA; 2.1. SUMMARY; 2.2. LANGUAGES AND GRAMMARS; 2.3. FINITE-STATE AUTOMATON; 2.4. EARLEY'S PARSING; 2.5. FINITE-STATE GRAMMATICAL INFERENCE; 2.6. STRING DISTANCE COMPUTATION; 3 ERROR-CORRECTING FINITE-STATE AUTOMATON FOR RECOGNITION OF RICKER WAVELETS; 3.1. SUMMARY; 3.2. INTRODUCTION; 3.3. SYNTACTIC PATTERN RECOGNITION; 3.3.1. Training and Testing Ricker Wavelets.
- 3.3.2. Location of Waveforms and Pattern Representation3.4. EXPANDED GRAMMARS; 3.4.1. General Expanded Finite-State Grammar; 3.4.2. Restricted Expanded Finite-State Grammar; 3.5. MINIMUM-DISTANCE ERROR-CORRECTING FINITE-STATE PARSING; 3.6. CLASSIFICATION OF RICKER WAVELETS; 3.7. DISCUSSION AND CONCLUSIONS; 4 ATTRIBUTED GRAMMAR AND ERROR-CORRECTING EARLEY'S PARSING; 4.1. SUMMARY; 4.2. INTRODUCTION; 4.3. ATTRIBUTED PRIMITIVES AND STRING; 4.4. DEFINITION OF ERROR TRANSFORMATIONS FOR ATTRIBUTED STRINGS; 4.5. INFERENCE OF ATTRIBUTED GRAMMAR.
- 4.6. MINIMUM-DISTANCE ERROR-CORRECTING EARLEY'S PARSING FOR ATTRIBUTED STRING4.7. EXPERIMENT; 5 ATTRIBUTED GRAMMAR AND MATCH PRIMITIVE MEASURE (MPM) FOR RECOGNITION OF SEISMIC WAVELETS; 5.1. SUMMARY; 5.2. SIMILARITY MEASURE OF ATTRIBUTED STRING MATCHING; 5.3. INFERENCE OF ATTRIBUTED GRAMMAR; 5.4. TOP-DOWN PARSING USING MPM; 5.5. EXPERIMENTS OF SEISMIC PATTERN RECOGNITION; 5.5.1. Recognition of Seismic Ricker Wavelets; 5.5.2. Recognition of Wavelets in Real Seismogram; 5.6. CONCLUSIONS; 6 STRING DISTANCE AND LIKELIHOOD RATIO TEST FOR DETECTION OF CANDIDATE BRIGHT SPOT; 6.1. SUMMARY.
- 6.2. INTRODUCTION6.3. OPTIMAL QUANTIZATION ENCODING; 6.4. LIKELIHOOD RATIO TEST (LRT); 6.5. LEVENSHTEIN DISTANCE AND ERROR PROBABILITY; 6.6. EXPERIMENT AT MISSISSIPPI CANYON; 6.6.1. Likelihood Ratio Test (LRT); 6.6.2. Threshold for Global Detection; 6.6.3. Threshold for the Detection of Candidate Bright Spot; 6.7. EXPERIMENT AT HIGH ISLAND; 7 TREE GRAMMAR AND AUTOMATON FOR SEISMIC PATTERN RECOGNITION; 7.1. SUMMARY; 7.2. INTRODUCTION; 7.3. TREE GRAMMAR AND LANGUAGE; 7.4. TREE AUTOMATON; 7.5. TREE REPRESENTATIONS OF PATTERNS; 7.6. INFERENCE OF EXPANSIVE TREE GRAMMAR.
- 7.7. WEIGHTED MINIMUM-DISTANCE SPECTA7.8. MODIFIED MAXIMUM-LIKELIHOOD SPECTA; 7.9. MINIMUM DISTANCE GECTA; 7.10. EXPERIMENTS ON INPUT TESTING SEISMOGRAMS; 7.11. DISCUSSION AND CONCLUSIONS; 8 A HIERARCHICAL RECOGNITION SYSTEM OF SEISMIC PATTERNS AND FUTURE STUDY; 8.1. SUMMARY; 8.2. INTRODUCTION; 8.3. SYNTACTIC PATTERN RECOGNITION; 8.3.1. Linking Processing and Segmentation; 8.3.2. Primitive Recognition; 8.3.3. Training Patterns; 8.3.4. Grammatical Inference; 8.3.5. Finite-state Error Correcting Parsing; 8.4. COMMON-SOURCE SIMULATED SEISMOGRAM RESULTS; 8.5. STACKED SIMULATED SEISMOGRAM RESULTS.