Data · dataset · 2016
Method of predicting soil mechanical parameters in shallow formation while jetting process in deep-water drilling
Listed in DataCite
The mechanical properties of shallow soils in deep water play an important role in drilling design and construction as well as later oil and gas development.
Description
Since it is difficult to collect soil samples from layers deeper than 10 m below the sea floor, the acquisition of shallow soil mechanics, based on the variation of drilling parameters in the deep-water drilling process, is not only economical but also reliable. In this article, we analyze the variation of subsea soil properties based on the variation of deep-water jet-drilling construction parameters, calculate the lateral friction resistance of conductor by use of weight-on-bit (WOB) and displacement parameters in the jetting process, and determine the drilled formation’s shear strength and internal friction angle in consideration of restored friction resistance.
To verify the accuracy of the prediction-while-drilling model on seabed shallow soil mechanics, indoor unit and field simulation experiments were separately conducted. Moreover, the calculations from field application examples indicate that the prediction-while-drilling of deep-water seabed shallow soil mechanics achieves high conformity with the local practice results, which also indicates that this method could effectively guide field construction operations.
Links
Where it is published
- Repository landing page tandf.figshare.com/articles/dataset/Method_of_Predicting_Soil_Mechanical_Paramete… ↗
landing page · from DataCite
- Repository landing page tandf.figshare.com/articles/dataset/Method_of_Predicting_Soil_Mechanical_Paramete… ↗
landing page · from DataCite
- DOI doi.org/10.6084/m9.figshare.3398467 ↗
DOI / persistent id · from DataCite
- DOI doi.org/10.6084/m9.figshare.3398467.v2 ↗
DOI / persistent id · from DataCite
Documentation and papers
- Creative Commons Attribution 4.0 International creativecommons.org/licenses/by/4.0/legalcode ↗
license · from DataCite
- IsSupplementTo 10.1080/1064119x.2016.1190430 doi.org/10.1080/1064119x.2016.1190430 ↗
publication · from DataCite
Catalogue records · 4
- DataCite API api.datacite.org/dois/10.6084/m9.figshare.3398467 ↗
metadata API · from DataCite
- DataCite API api.datacite.org/dois/10.6084/m9.figshare.3398467.v2 ↗
metadata API · from DataCite
- DataCite Commons commons.datacite.org/doi.org/10.6084/m9.figshare.3398467.v2 ↗
catalogue entry · from DataCite
- DataCite Commons commons.datacite.org/doi.org/10.6084/m9.figshare.3398467 ↗
catalogue entry · from DataCite
Topics
- Stated by source
- Biological sciences · Biological sciences · Chemical sciences · Chemical sciences · Earth and related environmental sciences · Earth and related environmental sciences · Physical sciences · Physical sciences
- Inferred from text
- Simulation 75%
Related
Provenance · 2 source records, 17 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| DataCite | 10.6084/m9.figshare.3398467 | 11 d ago | JSON v1 |
| DataCite | 10.6084/m9.figshare.3398467.v2 | 11 d ago | JSON v1 |
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