Injection Temperature Impacts on Reservoir Response during CO2 Storage
Bibliographic record
Abstract
Summary Sustained injection of industrial-scale volumes of cold CO2 into warmer subsurface rock will result in extensive cooling which can alter rock mass mechanical behavior and fluid migration characteristics. Advanced simulation tools are available to assess and characterize such phenomena; however, the effective use of these tools requires appropriate injection temperatures and rock thermophysical parameters (in addition to geomechanical and hydraulic properties). The primary objective of this study was to demonstrate the sensitivity of injection-induced tensile fracturing and fault reactivation to injection temperature and reservoir thermophysical properties during CO2 injection operations. This was achieved by (1) compiling and reviewing thermophysical parameter data available for formations in the province of Alberta, Canada, and CO2 injection temperature records for CO2 injection projects in western Canada and (2) using a 3D, physics-based, fully integrated hydraulic fracturing and reservoir simulation numerical model to examine the geomechanical response of several potential CO2 reservoirs in the Alberta Basin as a function of injection temperature, thermal conductivity (TC), and coefficient of linear thermal expansion (CLTE) values. The simulation results indicate that reducing the fluid injection temperature from 15°C (assumed in previous work) to 2°C (conservative value selected based on temperature data reviewed in this work) could trigger extensive vertical (20–130 m high, 100–600 m long) tensile fractures with rapid fracture initiation and full vertical growth within short periods (weeks to months) and continued horizontal length increase. When low values for thermophysical properties are used, the results show that thermally-induced tensile fracturing is unlikely, whereas the use of high values results in extensive tensile fracturing in all simulations. A similar conclusion was reached for the thermally-induced reactivation (unclamping) of proximal, critically-stressed faults. Notably, slip is predicted for all simulations where high thermophysical property values are used. This confirms that accurate determination of minimum fluid injection temperature and thermophysical parameters is important for containment risk assessment for commercial-scale CO2 storage projects. Another significant outcome of this work is the observation that most thermophysical parameters in the available data were measured using experimental conditions and/or temperature paths that are not representative of CO2 injection projects. As such, the development and validation of best practice approaches for accurate assessment of these parameters seem necessary.
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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 | 0.001 | 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 | 0.001 |
| 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".