Notice bibliographique
Résumé
Technology Focus Many innovative advances in the seismic method have been introduced over recent years. In this discussion, I will focus on the topic of sampling. A key example is the azimuthal sampling in full-azimuth 3D surveys—surveys that are needed, for instance, to characterize fractures. Full-azimuth geometries typically call for an expensive explosion in the amount of data needing to be acquired. A way to reduce the acquisition cost is to rely instead on interpolation, but aliasing issues limit the spatial frequencies that can be recovered. In the marine world, an innovation to address this has been to collect crossline-oriented, particle-acceleration measurements in addition to the usual pressure measurements (made by hydrophones). Particle acceleration is related directly to the spatial gradient of the pressure. Knowing both the pressure and the pressure derivative extends the ability for successful interpolation. Another innovation in use today is to abandon the traditional inline/crossline field geometry by shooting in circular tracks instead. Regardless of whether straight lines or circular tracks are used, platforms and other obstructions block access to towed streamers. Placing receiver nodes on the seabed is a very popular way around this problem when corals are not present. Otherwise, wave- and solar-powered unmanned surface vehicles provide a new, tantalizing alternative innovation. Each of these bathtub-sized crafts independently tows a hydrophone array. In the onshore world, one of the big advances for addressing increased sampling requirements has been to go to 24-hour shooting with continuous recording of simultaneously sweeping vibrators. This has been enabled by innovations in both acquisition and processing. In acquisition, the introduction of vibrator command-and-control systems means that the vibrator drivers no longer must wait for the start signal from the recording truck. In processing, the development of deblending algorithms enables the overlapping field records to be separated. These advances dramatically increase the number of records that can be acquired each day—especially in desert regions. An innovation for improving this efficiency even further is to skip over some of the source and receiver positions in a carefully specified, random-looking fashion adopted from the science of compressive sampling. (By relying on sparsity in an appropriate transform domain, data processing can reconstruct the seismic signal adequately from the reduced data set.) Finally, yet another form of sampling of interest today is the time interval between consecutive monitor surveys in 4D programs. Recent innovations enable frequent, lower-cost monitor surveys to see small, rapid changes in deepwater reservoirs. For more information, see the featured papers. Recommended additional reading at OnePetro: www.onepetro.org. SPE 187203 Look-Ahead Geosteering By Means of Real-Time Integration of Logging-While-Drilling Measurements With Surface Seismic by F. Arata, Eni, et al. SPE 184029 Seismic Airborne TEM Joint Inversion and Surface Consistent Refraction Analysis: New Technologies for Complex Near-Surface Corrections by Daniele Colombo, Saudi Aramco, et al. URTeC 2670158 The Use of Time-Lapse Seismic Attributes for Characterizing Hydraulic Fractures in a Tight Siltstone Reservoir by N. Riazi, University of Calgary, et al.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».