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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.
|
| Colección: | Series in machine perception and artificial intelligence ;
v. 46. |
| Temas: | |
| Acceso en línea: | Texto completo |
MARC
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| 100 | 1 | |a Huang, Kou-Yuan. | |
| 245 | 1 | 0 | |a Syntactic pattern recognition for seismic oil exploration / |c Kou-Yuan Huang. |
| 260 | |a River Edge, NJ : |b World Scientific, |c 2002. | ||
| 300 | |a 1 online resource (xiv, 133 pages) : |b illustrations | ||
| 336 | |a text |b txt |2 rdacontent | ||
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| 490 | 1 | |a Series in machine perception and artificial intelligence ; |v v. 46 | |
| 504 | |a Includes bibliographical references (pages 123-129) and index. | ||
| 588 | 0 | |a Print version record. | |
| 505 | 0 | |a 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. | |
| 505 | 8 | |a 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. | |
| 505 | 8 | |a 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. | |
| 505 | 8 | |a 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. | |
| 505 | 8 | |a 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. | |
| 520 | |a 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 the subsurface. Syntactic/structural pattern recognition techniques can recognize the structural seismic patterns and improve seismic interpretations. The syntactic analysis methods include: (1) the error-correcting finite-state parsing, (2) the modified error-correcting Earley's parsing, (3) the par. | ||
| 590 | |a eBooks on EBSCOhost |b EBSCO eBook Subscription Academic Collection - Worldwide | ||
| 590 | |a ProQuest Ebook Central |b Ebook Central Academic Complete | ||
| 650 | 0 | |a Petroleum |x Prospecting |x Data processing. | |
| 650 | 0 | |a Pattern recognition systems. | |
| 650 | 0 | |a Seismic reflection method |x Data processing. | |
| 650 | 6 | |a Pétrole |x Prospection |x Informatique. | |
| 650 | 6 | |a Reconnaissance des formes (Informatique) | |
| 650 | 6 | |a Méthode sismique-réflexion |x Informatique. | |
| 650 | 7 | |a TECHNOLOGY & ENGINEERING |x Mining. |2 bisacsh | |
| 650 | 7 | |a Pattern recognition systems |2 fast | |
| 650 | 7 | |a Petroleum |x Prospecting |x Data processing |2 fast | |
| 650 | 7 | |a Seismic reflection method |x Data processing |2 fast | |
| 758 | |i has work: |a Syntactic pattern recognition for seismic oil exploration (Text) |1 https://id.oclc.org/worldcat/entity/E39PCG4BbXhFwGdcHwjtxRtjbq |4 https://id.oclc.org/worldcat/ontology/hasWork | ||
| 776 | 0 | 8 | |i Print version: |a Huang, Kou-Yuan. |t Syntactic pattern recognition for seismic oil exploration. |d River Edge, NJ : World Scientific, 2002 |z 9810246005 |z 9789810246006 |w (DLC) 2002514235 |w (OCoLC)50134555 |
| 830 | 0 | |a Series in machine perception and artificial intelligence ; |v v. 46. | |
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