Real-Time Detection of Karstification Hazards While Drilling in Carbonates

Danil Maksimov, Alexey Pavlov and Sigbjørn Sangesland
Additional contact information
Danil Maksimov: Department of Geoscience and Petroleum, NTNU Norwegian University of Science and Technology, S.P. Andersens vei 15a, NO-7491 Trondheim, Norway
Alexey Pavlov: Department of Geoscience and Petroleum, NTNU Norwegian University of Science and Technology, S.P. Andersens vei 15a, NO-7491 Trondheim, Norway
Sigbjørn Sangesland: Department of Geoscience and Petroleum, NTNU Norwegian University of Science and Technology, S.P. Andersens vei 15a, NO-7491 Trondheim, Norway

Energies, 2022, vol. 15, issue 14, 1-17

Abstract: The nature of carbonate deposition can cause the development of unique geological features such as cavities and vugs called karsts. Encountering karsts while drilling can lead to serious consequences. To improve drilling safety in intervals of karstification, it is important to detect karsts as early as possible. The use of state-of-the-art geophysical methods cannot guarantee early or even real-time detection of karsts or karstification zones. In this paper we demonstrate, based on an analysis of 20 wells drilled in karstified carbonates in the Barents Sea, that a karst that is dangerous for drilling is often surrounded by one or more other karstification objects, thus forming a karstification zone. These zones can be detected in real time through certain patterns in drillstring mechanics and mud flow measurements. They can serve as indicators of intervals with a high likelihood of encountering karsts. The identified patterns corresponding to various karstification objects are summarized in a table and can be used by drilling engineers. Apart from that, these patterns can also be utilized for training machine learning algorithms for the automatic detection of karstification zones.

Keywords: carbonate; karst; geophysics; hazards mapping; karst prediction (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2022
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/1996-1073/15/14/4951/pdf (application/pdf)
https://www.mdpi.com/1996-1073/15/14/4951/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jeners:v:15:y:2022:i:14:p:4951-:d:857248

Access Statistics for this article

Energies is currently edited by Ms. Agatha Cao

More articles in Energies from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().