The Use of Offshore Wind to Reduce Greenhouse Gas Emissions in Offshore Hydrocarbon Production - A Case Study
Bibliographic record
Abstract
Abstract The move to reduce greenhouse gas emissions in the offshore hydrocarbons production industry has resulted in a growing interest in the possibility of using offshore wind to reduce on-platform power generation. However, the integration of floating wind power into a brownfield development project offshore has not yet been undertaken nor has any operating greenfield projects incorporated floating wind electrification into their design. A number of smaller pilot projects exist in the floating offshore wind area consisting of single prototype floating towers to demonstrate a design concept, but these are providing power back to shore. Where electrification of offshore facilities has taken place, they have utilized shore-based power. In this paper, the authors present a case study of electrifying brownfield and greenfield oil and gas production facilities via offshore wind farms and the technical challenges associated with this transformation. Intecsea has recently completed a generic investigation into the electrification of floating offshore oil and gas host facilities offshore Newfoundland, Canada using floating wind power. Electrification of floating host facilities eliminates or reduces the requirement for local power generation via turbine generators at the host facility, decreasing operational expenditure and total emissions from the facility. This work has included the investigation of existing offshore wind projects, equipment requirements and technical readiness, floating wind array best practices, greenhouse gas emissions reduction and required capital expenditure (capex). In this paper, the authors present a case study of electrifying floating brownfield and greenfield oil and gas production facilities using offshore wind farms and the technical challenges associated with this transformation. Challenges identified for the electrification of floating offshore facilities include: challenges associated with dynamic cabling at different water depths determination of best cable configuration and array layout determination of the best suited support structure (floating foundation) sizing of generator (can have a significant effect on the tower's performance) best anchoring solutions; optimization of power tie-in and storage insufficient real estate or weight capacity (for brownfield applications). The authors provide details on wind farm requirements and tie-in for electrification of offshore production facilities for different scenarios. A summary of modifications/additions required at a brownfield host facility for power supply by wind power array are presented. Related to floating production facilities, an investigation of ongoing project work related to dynamic, disconnectable cables which will operate in the upper end of MVAC, HVAC or HVDC range has been carried out and is presented. For cases selected, avoided GHG emissions and associated capex are estimated and presented. The use of offshore floating wind to supplement/replace on platform power generation is part of the ongoing global energy transition.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".