New Approach to Deepwater-Drilling-Data Analysis Enhances Real-Time Capabilities
Notice bibliographique
Résumé
This article, written by Editorial Manager Adam Wilson, contains highlights of paper SPE 146624, ’A New Approach to Deepwater Drilling Data Analysis Offers Enhanced Real Time Capabilities in a Post Macondo World,’ by John F. Greve, SPE, Chevron Deepwater Gulf of Mexico Business Unit, prepared for the 2011 SPE Annual Technical Conference and Exhibition, Denver, 30 October-2 November. The paper has not been peer reviewed. Deepwater drilling activity in the Gulf of Mexico is no longer a given in the aftermath of the BP Macondo blowout. The new and ever-evolving process to apply for drilling permits and operate now greatly depends on thorough real-time monitoring of pertinent surface and downhole data. A new method for loading and analyzing live time and depth data showed merit during 2010 trials on two deepwater wells, one offshore eastern Canada and the other offshore west of the Shetland Islands. Rapid data access and standardized visualization of high-resolution time, depth, and survey data are vital to ensure that the occasional well-control event does not become today’s worldwide news headline. Background—Real-Time Data Collection The Wellbore Information Transfer Standard Markup Language (WITSML) well-data exchange protocol introduced in the mid-1990s continues to gain popularity as a standardized means to deliver drilling and logging data to the client operator. An increasing number of software programs are offering WITSML links to load depth-based data into programs for petrophysical analysis, pore-pressure estimation, and 3D visualization of well logs vs. seismic data. For roughly a decade, large service companies have offered Web-based viewing of drilling-gauge displays and real-time depth-based data. Even though Internet access to WITSML data has been available to client operators, little benefit has been derived from the time-based data because of inherent limitations of depth-focused Web-based viewers. A new vendor-neutral WITSML-based data viewer capable of easily connecting to multiple WITSML vendors combines real-time synchronous depth and time viewing of drilling, logging-while-drilling (LWD), and mud-logging data in a variety of graphical displays. Historical Perspective on Collection of Time-Based Drilling Data For many decades, time-based drilling data have been recorded with mechanical devices. Special 24-hour multiscale paper forms were loaded on a cylindrical drum every day. Because the chart was under a protective lid and sometimes covered by dirt and mud, it was considered more of a midnight chart-replacement chore for a roughneck than a useful tool. The charts rarely made it to the operator’s office and were often lost or thrown out.
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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 | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
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 ».