Estimation of Rock Compressive Strength Using Downhole Weight-on-Bit and Drilling Models
Notice bibliographique
Résumé
Abstract In unconventional gas and tight oil plays, knowledge of the in situ rock mechanical profiles of the reservoir interval is critical in planning horizontal well trajectories and landing zones, placement of perforation clusters along the lateral, and optimal hydraulic fracture stimulation design. In current practice, vertical pilot holes and/or the laterals are logged after drilling, and the sonic and neutron log results are interpreted along with mechanical rock properties measured in the laboratory on core material. However, coring, logging, and core analyses are expensive and time consuming. In addition, as they are typically only performed in a few wells that are assumed to be representative, there is considerable uncertainty in extrapolating results across wide areas with known variability in stratigraphy, faults, thicknesses, hydrocarbon saturations, etc. This paper reports a method for estimating mechanical rock properties and in situ rock mechanical profiles in every well in a development, based on calibration from initial rock core analyses plus drilling data that is routinely acquired. Wellbore friction analysis was coupled with a torque and drag model to estimate in situ unconfined compressive strength (UCS) and Young's modulus (YM) profiles. The key process steps include: Calculate the weight and wellbore friction force of each element of the drill string from bottom to the surface;Adjust the hook load (HL) by subtracting the weight of the hook and entire drill string;Iteratively compute the friction coefficient to match calculated and observed HL;Estimate downhole weight-on-bit (DWOB) by applying a stand pipe pressure correction to the calculated HL and considering potential sliding and abrasiveness;Use a rate of penetration (ROP) model developed for polycrystalline diamond compact (PDC) drill bits considering a force balance between a drill bit geometry and formation and a wear function depending upon the formation abrasiveness and bit hydraulics to compute confined compressive strength (CCS). The resulting CCS was correlated to UCS and YM using regression constants obtained from laboratory triaxial test data on whole core. Using examples from horizontal wells in a siltstone play in Alberta, Canada, this manuscript demonstrates a workflow to estimate rock strength from drilling data. The predicted UCS and YM values were compared with log data and potential uncertainties arising out of drilling data are discussed. Introduction In conventional and unconventional plays alike, a typical way to characterize the subsurface is to make measurements of the formation penetrated by the wellbore with logging tools that are either carried behind the drill bit (logging while drilling) or else run in the well after the drill string is removed (wireline or drill pipe-conveyed logging). Because this adds cost and risk, for unconventional gas or tight oil (UGTO) projects that may have hundreds to even thousands of producers, typically only early appraisal wells plus later, areally scattered wells are designed with extensive logging and laboratory core characterization programs. The assumption is that lateral variability and local heterogeneties are not great and that these data-rich penetrations sufficiently constrain the reservoir properties in the areas between them. In UGTO projects, good representations of the in situ stress profile and geomechanical rock properties are required to optimize the well trajectories and landing zones, placement of perforation clusters along the lateral, and hydraulic fracture stimulation design.
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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 | 0,000 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 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 | 0,001 | 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 ».