Experimental Study of Stability and Integrity of Cement in Wellbores Used for CO2 Storage
Bibliographic record
Abstract
Abstract This paper examines the results obtained from several sets of experimental work conducted on cement deterioration in environments similar to those found in CO2 injection and storage projects. The study consisted of preparing and investigating the behavior of several hundred samples of cement in presence of various concentrations of sulphate, from 0.1 wt% up to 6%, as well as CO2 at 2200 psi and 55 °C. Effect of sulphate on cement was studied at 30 °C, 55 °C, and 75 °C. The two common classes of cement of Type 10 and Class G were tested during this study. A total of 300 identical cubic and 400 identical cylindrical samples were tested. The change in permeability, compressive strength, and shear and hydraulic bonding strength for these samples were monitored after 2, 4, 6, 8, 10 and 12 months. Additionally, scanning electron microscope (SEM) was used for investigating the rate of diffusion of sulphur and CO2 into cement. Lab results showed that sulphate ions and CO2 improve the performance of cement during the first few months. However, the effect is reversed under prolonged experiments. The highest reduction in performance was observed for hydraulic shear bonding, which indicates the highest risk of CO2 leakage is between the cement and casing. Introduction Geological storage of CO2 in depleted and partially depleted oil fields has gained increasing interests around the globe as an economically viable means of reducing emissions of CO2 while recovering extra oil. In these projects, CO2 is injected into the oil-bearing formations through injection wells, and oil is produced via production wells. An example of such CO2 EOR/storage project is the IEA GHG Weyburn CO2 Monitoring and Storage Project, where it is predicted that about 20 million tons of CO2 will be stored underground in Weyburn oil field throughout the life of this project. However, one of the major challenges encountered for any CO2 storage project is the potential risk of CO2 leakage back to surface. Although there are a variety of potential pathways for CO2leakage, it is widely accepted that the single most important path of CO2 leakage is through wellbores. There are hundreds of thousands of wellbores, both operational and abandoned, in North America. For instance, over 360,000 active oil and gas wells are registered with the Railroad Commission of State of Texas. It is estimated that the total deep holes in Texas are around 1.5 million. Therefore, it becomes clear that understanding the magnitude of potential risk and developing suitable mitigation responses for CO2 leakage, when CO2 is stored in oil reservoirs, would be directly related to our understanding of the potential CO2 leakage through wellbores. Several research groups have focused on investigating CO2 leakage through wellbores, and one of the main areas of interest has been the stability and integrity of the cement used in wellbores. The goal of these studies has been to quantify the change in physical and chemical characteristics of cement in environments similar to those found in CO2 storage operations.
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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 | 0.000 | 0.001 |
| 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 | 0.001 | 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".