Notice bibliographique
Résumé
Abstract In drilling simulation of wells there exists a need for accurate determination of the percentage of the different lithologies as a function of depth to better predict the bit wear distribution for different drill bits. A simple approach using Gamma Ray (GR) log readings for shallow wells in Alberta, Canada was initially used for lithological determination. It is generally in good agreement with shale and sand lithology content and where there are no other probable lithological types as in deeper formations in the area where limestone, dolomite, coal and anhydrite exists. It is in many cases difficult to understand the exact behavior of log responses especially in complex lithologies. A new cross plot approach is used in this paper to take into account all the lithological possibilities. The cross plots are normally used in well log analysis for interpreting both for lithology type and quantity using two or more forms of data. It is also a convenient way to analyze the log responses together; and set the limitations for each curve with boundaries. In this paper, the neutron density cross plot is used to obtain the different type and percent lithology. All the lithological differentiations are calibrated as mathematical models using offset wells. The two methods (using only GR and the new cross plot model) are compared for use in central Alberta, Canada wells. In conclusion it is seen that the GR method match for shale and sand sequences and mixtures but that the cross plot approach matches both sand and shale sequences as well as formations where limestone and dolomite exist. Introduction During the past years, formation evaluation methods have been developed using log data for lithological determination. Well logs give a continuous survey of the formation crossed by the well and it has been shown that it gives a good idea of the lithology. Physical parameters can be recorded by logging tools for lithological description of the formation (i.e. Gamma ray spectrometry and photoelectric). A common method in log interpretation is to use different kind of cross plots for various log readings which are useful in simple formation types but become ambiguous for complex lithologies. The accuracy is also dependant on the geological history of the area.1, 2 Different types of log data can be used for lithological determination purposes with the help of the cross plots. Cross plots with new boundaries are used with log data to predict formation lithological percentages utilizing for the geological sequences in Central Alberta, Canada. The new cross plot approach is compared to drilled cuttings collected versus depth from wells in the area with good agreement. Technical Approach Subsurface lithological interpretations were historically obtained from collected drilled cuttings whereas today when using wireline logs all the detailed data for an entire interval or section is obtained. Different logs respond differently to matrix minerals and the analysis of the logs can be used to estimate the formation type and characteristics in most all lithologies.
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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 | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,001 |
| 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 ».