Details
| Originalsprache | Englisch |
|---|---|
| Titel des Sammelwerks | Computational and Experimental Simulations in Engineering |
| Untertitel | Proceedings of ICCES 2024 |
| Herausgeber/-innen | Kun Zhou |
| Herausgeber (Verlag) | Springer Science and Business Media B.V. |
| Seiten | 975-983 |
| Seitenumfang | 9 |
| ISBN (elektronisch) | 978-3-031-77489-8 |
| ISBN (Print) | 9783031774881, 978-3-031-77491-1 |
| Publikationsstatus | Veröffentlicht - 2025 |
| Veranstaltung | 30th International Conference on Computational and Experimental Engineering and Sciences, ICCES 2024 - Singapore, Singapur Dauer: 3 Aug. 2024 → 6 Aug. 2024 |
Publikationsreihe
| Name | Mechanisms and Machine Science |
|---|---|
| Band | 173 MMS |
| ISSN (Print) | 2211-0984 |
| ISSN (elektronisch) | 2211-0992 |
Abstract
In deep and ultra-deep complex formations, strong heterogeneity poses challenges to predictability. The acquisition, transmission, and integration of formation-engineering data are complex, influenced by intricate subsurface conditions. Additionally, the accuracy of physical modeling for drill ability of formations is constrained, and the uncertainty in rock-breaking mechanics further complicates matters. Traditional spatial interpolation methods struggle to ensure modeling accuracy, especially in cases of abrupt changes in formations. To address these challenges, this paper proposes an attribute-constrained method for modeling formation drill ability based on seismic and borehole data. Under the constraint of seismic attributes, the limited drill ability information from wells is interpolated and extrapolated according to the geological “facies” characteristics represented by attribute descriptions. A three-dimensional formation drill ability model is established, providing a better simulation of variations and uncertainties in deep formations.
ASJC Scopus Sachgebiete
- Ingenieurwesen (insg.)
- Werkstoffmechanik
- Ingenieurwesen (insg.)
- Maschinenbau
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Computational and Experimental Simulations in Engineering : Proceedings of ICCES 2024. Hrsg. / Kun Zhou. Springer Science and Business Media B.V., 2025. S. 975-983 (Mechanisms and Machine Science; Band 173 MMS).
Publikation: Beitrag in Buch/Bericht/Sammelwerk/Konferenzband › Aufsatz in Konferenzband › Forschung › Peer-Review
}
TY - GEN
T1 - Seismic Attribute-Constrained Stratigraphic Drill Ability Modeling Method
AU - Yan, Ding
AU - Meng, Cui
AU - Yi, Cui
AU - Reyu, Gao
AU - Ge, Wang
AU - Fei, Zhao
N1 - Publisher Copyright: © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.
PY - 2025
Y1 - 2025
N2 - In deep and ultra-deep complex formations, strong heterogeneity poses challenges to predictability. The acquisition, transmission, and integration of formation-engineering data are complex, influenced by intricate subsurface conditions. Additionally, the accuracy of physical modeling for drill ability of formations is constrained, and the uncertainty in rock-breaking mechanics further complicates matters. Traditional spatial interpolation methods struggle to ensure modeling accuracy, especially in cases of abrupt changes in formations. To address these challenges, this paper proposes an attribute-constrained method for modeling formation drill ability based on seismic and borehole data. Under the constraint of seismic attributes, the limited drill ability information from wells is interpolated and extrapolated according to the geological “facies” characteristics represented by attribute descriptions. A three-dimensional formation drill ability model is established, providing a better simulation of variations and uncertainties in deep formations.
AB - In deep and ultra-deep complex formations, strong heterogeneity poses challenges to predictability. The acquisition, transmission, and integration of formation-engineering data are complex, influenced by intricate subsurface conditions. Additionally, the accuracy of physical modeling for drill ability of formations is constrained, and the uncertainty in rock-breaking mechanics further complicates matters. Traditional spatial interpolation methods struggle to ensure modeling accuracy, especially in cases of abrupt changes in formations. To address these challenges, this paper proposes an attribute-constrained method for modeling formation drill ability based on seismic and borehole data. Under the constraint of seismic attributes, the limited drill ability information from wells is interpolated and extrapolated according to the geological “facies” characteristics represented by attribute descriptions. A three-dimensional formation drill ability model is established, providing a better simulation of variations and uncertainties in deep formations.
KW - attribute-constrained interpolation
KW - formation drill ability
KW - Seismic attributes
KW - spatial modeling
UR - http://www.scopus.com/inward/record.url?scp=85211928234&partnerID=8YFLogxK
U2 - 10.1007/978-3-031-77489-8_76
DO - 10.1007/978-3-031-77489-8_76
M3 - Conference contribution
AN - SCOPUS:85211928234
SN - 9783031774881
SN - 978-3-031-77491-1
T3 - Mechanisms and Machine Science
SP - 975
EP - 983
BT - Computational and Experimental Simulations in Engineering
A2 - Zhou, Kun
PB - Springer Science and Business Media B.V.
T2 - 30th International Conference on Computational and Experimental Engineering and Sciences, ICCES 2024
Y2 - 3 August 2024 through 6 August 2024
ER -