Permeability Estimation From Inflow Data During Underbalanced Drilling
Notice bibliographique
Résumé
Abstract Underbalanced drilling has become increasingly popular as it prevents fluid invasion during drilling operations. Consequently, formation damage may be reduced. This is particularly important in the case of depleted reservoirs or when horizontal and deviated wells are drilled. As a result of the lower pressure in the wellbore there is an inflow from the reservoir into the wellbore, which is continuously measured at the wellhead. This inflow carries information about the reservoir. The objective of this paper is to develop a mathematical model and its associated interpretation methods to estimate reservoir permeability and its variation along the wellbore using the inflow measurements at the wellhead. The traditional methods of pressure and rate transient analysis are not applicable to underbalanced drilling data particularly because the length of the producing interval is continuously increasing with time. In this paper we will develop a mathematical model accounting for this complication. This model calculates inflow rates in the forward mode and the reservoir permeability when used in the backward mode. We have validated our methodology against synthetic data obtained from numerical simulation, and applied it to a number of actual field cases. In field studies, after estimation of the permeability profile along the wellbore, the estimated permeability values were used along with reported bottomhole pressure after end of drilling to calculate gas inflow. This was then compared with the measured total inflow. Good agreement was obtained between the predicted and measured values. Furthermore, a number of sensitivity studies were conducted to examine the sensitivity of the estimated permeability to errors in the reported inflow information and the pressure drop along the wellbore. The results reported in the paper indicate that the estimated permeability profile remained relatively unchanged. Introduction Formation testing during under-balanced (UB) drilling relies on the hypothesis that inflow rate contains enough information from the reservoir to enable determination of some reservoir properties. Acquisition of the flow rate and bottomhole pressure data, and their analysis can offer information about the permeability and its variation along the length of the wellbore. Analyzing the UB drilling data has been the subject of many papers, some of more recent ones are reviewed below. Hunt and Rester[4] modify the standard pressure transient analysis techniques to include time-dependent boundary conditions, which account for the variable well length as the drilling bit progresses in the reservoir. The reservoir parameters are calculated based on a trial and error procedure as part of a history-matching exercise. A more recent paper of the authors[5] extends this to multilayer reservoirs. Kneissl[6] suggests introducing fluctuations to the bottomhole pressure during drilling to calculate both the permeability and the pore pressure during UB drilling. Similarly, Vefring et al[9] show that introducing fluctuations to bottomhole pressure while drilling, can improve the estimation results for calculating both permeability and pore pressure simultaneously. In this paper, as well as their earlier work[8], the authors tie in a dynamic well-flow model with a simple transient reservoir model.
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Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,002 |
| 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 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,001 | 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 source (Gemma direct ou Codex distillé), 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 ».