Turning a Liability into an Asset: Re-purposing Inactive Petroleum Wells for Geothermal Energy Production
Bibliographic record
Abstract
There are over 600,000 registered oil and gas wells in the province of Alberta, many of these are inactive wells that do not produce resource yet do present a significant environmental risk and financial liability in cleanup costs. There are no regulations stipulating the maximum length of time a well can be left suspended and, in recent years, an increasing number of wells have been put into the suspended state by owners. Paper 1 of this thesis uses a large data set obtained from the Alberta Energy Regulator to calculate the average volume of methane emissions from a leaking well and results indicating that leak duration and rate may be increasing over the years. Further, we provide simple social-cost-of methane computations which show that, under the right conditions, responsible policies can incentivise well owners towards remediation and reclamation and support efforts to flight climate change. In paper 2 we present an opportunity to mitigate the financial and environmental risk posed by these wells through retrofitting a selection of them for direct-use geothermal heat energy production. The goal of this paper is to assess the techno-economic feasibility of using the legacy oil and gas infrastructure to produce geothermal energy and improve the productivity of a cattle ranch by increasing the temperature of the drinking water available to cattle during the cold winter months. We estimate the average cost to retrofit one of the five suspended wells on ranch property at $212,999 and that it would require three retrofit wells to provide sufficient energy to raise the cattle drinking water temperature from 2.5°C to 10°C. Based on all estimated costs and revenues expected over the life of the project, we calculate that the project’s expected net present value is negative $845,775. A key result of this paper is the creation of a model of well retrofit costs that can be expanded to further research and other geothermal re-purposing projects. In paper 3, I use publicly available data from the GeoScout online database of petroleum wells, and the well retrofit cost model presented in paper 2 of this thesis to identify promising retrofit candidate wells. This paper first sorts and quantifies Alberta’s wells by vertical depth, age, and regulatory status. Then I apply the cost retrofit model and bottom hole temperature data to rank each well by their likelihood of techno-economic retrofit success. The analysis finds 179,446 unique wellbores within Alberta that possess a vertical depth equal to or greater than 1000 metres; these can be retrofit at an average cost of $225,000. I also create a list of the top 100 retrofit candidate wells, demonstrating that suitable candidates may exist throughout all regions of the province.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".