LiDAR Technology as a Means of Improving Geologic, Geophysical and Reservoir Engineering Evaluations: From Rocks to Realistic Fluid Flow Models
Notice bibliographique
Résumé
Abstract Outcrops of the Milk River Formation (sandstone, Cretaceous age) at the Writing on Stone Provincial Park in Alberta, Canada have been scanned using ground LiDAR (light detection and ranging) technology. Milk River outcrops represent a real 3D challenge for this technology because of the complexity of hoodoos emanating from pronounced erosion in the area as a result of wind, water and ice following the melting of ice at the end of the last ice age. In addition to the 3D complexity of the hoodoos, the Milk River Formation at Writing on Stone was selected for this project because the geology, studied in detail previously, is characterized by intervals that include a range of sand-rich lithofacies, and is distinguished primarily by subtle differences in grain size and current structures of the sandstones. Also present in the area are relatively flat 2D cliff faces and subvertical fractures. The outcrop exemplifies a challenge for realistic fluid flow modeling. This is of practical importance because these types of rocks develop significant hydrocarbon reservoirs in the Western Canadian sedimentary basin and throughout the world. When buried significant volumes of gas can be trapped in tight formations of similar age. This paper describes an evaluation sequence that includes the planning for LiDAR data collection, actual work and rock sample collection in outcrops, the interpretation and integration with geoscience in a 3D visualization room, and the potential for improved drilling and completion techniques, and reservoir simulation by using the concept ‘from rocks to realistic fluid flow models’. It is concluded that LiDAR provides a powerful technique for sound interpretation of reservoirs rocks and their integration with other sources of information. Introduction The present study was undertaken to test and evaluate the capabilities and limitations of ground-based laser scanning technology (LiDAR) for the construction of reservoir models based on surface outcrops. A multidisciplinary team of the University of Calgary has embarked on a project to investigate and better characterize tight gas/fractured reservoirs, in which the study of outcrop analogues is an integral part. The multidisciplinary research project is called GFREE, an acronym that stands for the integration of geoscience (G), formation evaluation (F), reservoir drilling, completion and stimulation (R), reservoir engineering (RE), and economics and externalities (EE). Before investing heavily in expensive, up-todate LiDAR hardware and software, and in the time and effort of researchers, a pilot study was deemed to be necessary to evaluate the feasibility and usefulness of LiDAR-based mapping/imaging methods. The University of Calgary and the University of Texas at Dallas joined forces to achieve this objective. Herein we report on this pilot study of the various phases in the use of LiDAR, that is, data acquisition, data and image processing, and possible qualitative and quantitative applications of the resulting model. The rocks chosen for the pilot study are the Virgelle Member sandstones at Writing-on-Stone Provincial Park (WOS) in southern Alberta, an area with relatively continuous, superbly exposed outcrops along the Milk River valley.
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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 | 0,000 |
| 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 ».