Benchmarking A Concept ─ Data-driven Commercial Valuation Of A Hypersonic Impact Drilling Concept
Notice bibliographique
Résumé
Abstract Commercial valuation of a technology in Proof-of-Concept stage is often based on limited case study data, and then extrapolated to a hypothesized total market demand for that technology. The methodology presented in this paper uses a bottoms-up, data-driven, well-by-well valuation using a 60,000+ well industry benchmarking data set. The methodology was developed to support the valuation of a new technology concept using hypersonic impact drilling, then at API-17N Technology Readiness Level 1. Any new technology has a low definition of operational performance and technical capability by virtue of being in concept stage. The well dataset used for valuation analysis is relatively high-level, resulting in a significant number of assumptions and limitations. Nonetheless, the combination of a granular technology model with a large actual dataset provides insights into sensitivities and uncertainties which are unobtainable with a broad-brush, high-level approach. Based on the information available in the database, the methodology constructs a synthetic time-depth curve for drill and case operations after removal of non-productive time. Synthetic time and cost for each section are calculated for both the actual well and the technology model allowing section-by-section ‘bench-marking’ of the technology. The combined savings from technology-positive sections gives the size of the prize or commercial margin available to be shared between Operator and Supplier. We present a case study in which we modelled the initial new technology deployment concept, showing this concept to have an operational sweet spot with value rapidly decreasing away from it. An alternative, downhole deployment concept resulted in a multiple times wider applicability and a multi-billion-dollar un-risked value proposition indicative of a potentially game changing technology. Based on this new insight, the technology developer was able to pivot early on, probably avoiding costly dead-end development and market disappointment, and increase industry and investor confidence and investment. The methodology can be used to gain actionable insights at multiple levels:To obtain a mature market valuation, mature technology parameters such as reliability, directional drilling capability and all applicable hole sizes and depths are invoked.To aid the technology development and design decisions, sensitivity analyses can be performed on design parameters.To guide development requirements, a Minimum Viable Product analysis provides insight to the minimum technical requirements necessary and the de-risking work required before a technology can gain acceptance in the marketplace.To explore early applications and potential sponsoring projects, clusters of potential high-value and/or early-applications can be identified.The results from this valuation model provide insights into the potential of wells at or beyond the fringes of the database, i.e. complex wells that require extraordinarily long net times to drill.
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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 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| 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 ».