Re-Using Oil and Gas Wells for Geothermal Energy: Feasibility, Benefits, and Challenges
Bibliographic record
Abstract
Abstract This study investigates the technical feasibility, economic viability and key challenges of repurposing shut-in, suspended, or unproductive oil and gas wells for geothermal energy extraction. A techno-economic analysis is conducted, focusing on closed-loop geothermal conversion strategies and their implementation in the subsurface geothermal gradient ranges of Alberta. The methodology of this study consists of three key stages. Firstly, technical viability of the well conversion has been assessed by evaluating parameters such as depth, bottomhole temperature and geothermal gradient of the location. Then a simple analytical solution has been used to determine an estimation of the energy extraction potential. Secondly, numerical simulation is used to analyze the behavior of the closed-loop geothermal systems. These analyses are done for two subsurface temperature gradients (25 and 45 °C/km), four water circulation rates (100, 250, 500 and 1000 m3/day), three water injection temperatures (10, 20, and 30 °C), and four well configurations. The analyses reveal the significance of subsurface temperature gradient, injection temperature and insulation on the heat harvest, and highlight the importance of optimizing fluid circulation rates to balance energy output and efficiency. In the third stage of the work economic assessment places the capital cost at C$1M per well, with installation variability leading to a sensitivity range of +30%/-20%. At a 9% discount rate, project Net Present Values (NPV) range from -$0.4M to $0.8M, and Internal Rates of Return (IRR) vary from −7.5% to 23.6%, influenced by electricity pricing ($45–$75/MWh) and carbon tax scenarios ($170–$300/tonne CO₂e). Despite economic and technical challenges, a successful implementation faces various critical hurdles such as underground infrastructure adaptation, well integrity, and regulatory considerations, which are discussed in the discussion section. By integrating analytical and numerical modelling, and economical analysis, this study provides a workflow to evaluate repurposing oil and gas wells into a closed-loop geothermal system.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".