Drilling Simulation Improves Field Communication and Reduces Drilling Cost in Western Canada
Notice bibliographique
Résumé
Abstract During the past two years a drilling simulator has been applied in a pre-simulated and follow-up mode on dozens of well in Western Canada. Using a commercially available rate of penetration (ROP) drilling simulator, the drilling learning curve of mature fields in Western Canada is significantly improved. The ROP drilling simulator optimizes the bit runs, drilling parameters and pull depths prior to spud by applying offset drilling data and records. The drilling cost is maintained consistent and or reduced from well to well and pacesetter performance is constantly copied or improved. After simulating and obtaining the optimum operating conditions for the individual drilling bits, the optimum parameters were sent to the company man and drillers in advance. This has shown to be an efficient way of communicating and obtaining optimal results. During drilling the home office is in communication with the field as daily updates of field parameters are compared to the preplanned scenario. These parameters include the operating parameters, calculated bit wear and updated rock strength compared to the pre-simulated values. This paper presents field examples where the pre-simulation and daily drilling data are compared. The improved communication points from the updates are given in examples as well as how this improves the overall performance. Introduction To be able to simulate drilling performance prior to actually drilling the wells, the drilling simulation optimization software, "Optimizer"1, was utilized. The software uses nearby offset well drilling data and records to calculate the different formations drillability on a meter by meter or less basis. This is done by taking the meter by meter drilling data for each offset bit run in conjunction with the offset field reported bit wear, pore pressure and lithology composition. Through different bit type inverted ROP models the drillability or Apparent Rock Strength Log (ARSL) is predicted using an iterative process in the simulator. The converged ARSL for all the bit runs total the drilling resistance for all the different formations on a meter by meter basis penetrated by the offset wells. The process of calculating the ARSL in the simulator involves the use of the offset operating parameters like weight on bit (WOB), bit rotational speed (RPM), flow rate, mud weight, bit wear, ROP, detailed bit type and design in addition to formation geology and pore pressure. The ARSL2-3 can also be obtained using log properties but care must be used. The ARSL from the reference well is further either stretched or shrunk to fit the geological prognosis for the planned well to be drilled. This is done so the ARSL match the formation tops for the new survey. The optimization of the drilling process for the upcoming well is then done by trying out different drilling scenarios including bit type selection and designs, pull depths and different optimal sets and distributions of operating parameters throughout bit runs. This is initially a trial and error process but after a little learning with the simulator quick and obvious conclusions can be drawn regarding bits types and designs and pull depths.
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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 | 0,000 | 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 | 0,000 |
| Science ouverte | 0,000 | 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 ».