Improved Estimation of Gas Well Deliverability from Single-Point Tests
Notice bibliographique
Résumé
Abstract Chase and Alkandari developed dimensionless inflow performance (IPR) curves for predicting the stabilized deliverability of hydraulically fractured gas wells using just a single-point test, namely a pressure build-up or draw-down test. Unfractured wells can also be analyzed by converting the apparent skin factor to an equivalent ratio of Xe/Xf. Results obtained from the dimensionless IPR curve model can be used to generate values of n and C for the equation of stabilized deliverability. This research describes the process used to evaluate the effectiveness of the single-point model using data from twenty-five Canadian well tests and nine simulated well tests. The tests were analyzed using four-point test methods, the dimensionless IPR curve method, and by assuming that the exponent of the stabilized deliverability equation was equal to one. The absolute value of error between the AOF predicted using multi-point deliverability test analysis methods and the dimensionless IPR curve method for the twenty-five Canadian wells was 9.2 %, with a standard deviation of 8.7 %. The absolute value of error between the AOF predicted using multipoint deliverability test analysis methods and the dimensionless IPR curve method for the nine simulated wells was 5.1 % with a standard deviation of 4.7 %. The absolute value of error between the AOF predicted using multi-point test methods and by assuming that the exponent of the stabilized deliverability equation was equal to one for the twenty-five wells was 30.5 % with a standard deviation of 25.2 %. Introduction The deliverability or inflow performance of a gas well is usually predicted by utilizing one of three well testing methods: the conventional backpressure test(1); the isochronal test(2); or the modified isochronal test(3). All three methods normally require that four flow tests be performed on a well, including one to stabilization, to accurately predict stabilized deliverability. Industry practice sometimes shortcuts these methods utilizing just three, two and sometimes just one flow test. In the latter case, the exponent, n, of the stabilized deliverability equation, given by equation (1) is frequently assumed to be equal to one in order to estimate deliverability. Equation (1) (Available in full paper) Chase and Alkandari(4) developed a single-point test method that uses dimensionless IPR curves for predicting the inflow performance of fractured gas wells producing under stabilized or pseudosteady state flow conditions. The model was developed in an attempt to better estimate gas well deliverability when just a one-point test, namely a drawdown or build-up test, is conducted. The following equation serves as the basis for the single-point dimensionless IPR curve method. Equation (2)(Available in full paper) The SPE paper by Chase and Alkandari describes how Monte Carlo simulation was used to develop the model and generate values for the coefficient M and exponent N as a function of Xe/Xf. The M values were plotted versus the Xe/Xfratio on a log-log plot and a least squares cubic fit of the data was obtained resulting in equation (3). Equation (3)(Available in full paper)
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
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 | 0,002 | 0,006 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,002 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 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 ».