Potential CO2 and brine leakage through wellbore pathways for geologic CO2 sequestration using the National Risk Assessment Partnership tools: Application to the Big Sky Regional Partnership
Why this work is in the frame
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Bibliographic record
Abstract
Geologic CO 2 sequestration (GCS) has received high-level attention from the global scientific community as a response to climate change due to higher concentrations of CO 2 in the atmosphere. However, GCS in saline aquifers poses certain risks including CO 2 /brine leakage through wells or non-sealing faults into groundwater or to the earth’s surface. Understanding crucial reservoir parameters and other geologic features affecting the likelihood of these leakage occurrences will aid the decision-making process regarding GCS operations. In this study, we develop a science-based methodology for quantifying risk profiles at geologic CO 2 sequestration sites as part of US DOE’s National Risk Assessment Partnership (NRAP). We apply NRAP tools to a field scale project in a fractured saline aquifer located at Kevin Dome, Montana, which is part of DOE’s Big Sky Carbon Sequestration Partnership project. Risks associated with GCS injection and monitoring are difficult to quantify due to a dearth of data and uncertainties. One solution is running a large number of numerical simulations of the primary CO 2 injection reservoir, shallow reservoirs/aquifers, faults, and wells to address leakage risks and uncertainties. However, a full-physics simulation is not computationally feasible because the model is too large and requires fine spatial and temporal discretization to accurately reproduce complex multiphase flow processes. We employ the NRAP Integrated Assessment Model (NRAP-IAM), a hybrid system model developed by the US-DOE for use in performance and quantitative risk assessment of CO 2 sequestration. The IAM model requires reduced order models (ROMs) developed from numerical reservoir simulations of a primary CO 2 injection reservoir. The ROMs are linked with discrete components of the NRAP-IAM including shallow reservoirs/aquifers and the atmosphere through potential leakage pathways. A powerful stochastic framework allows NRAP-IAM to be used to explore complex interactions among a large number of uncertain variables and to help evaluate the likely performance of potential sequestration sites. Using the NRAP-IAM, we find that the potential amount of CO 2 leakage is most sensitive to values of permeability, end-point CO 2 relative permeability, hysteresis of CO 2 relative permeability, capillary pressure, and permeability of confining rocks. In addition to demonstrating the application of the NRAP risk assessment tools, this work shows that GCS in the Kevin Dome has a higher probability of encountering injectivity limitations during injection of CO 2 into the Middle Duperow formation than previous studies have calculated. Finally, we estimate very low risk of CO 2 leakage to the atmosphere unless the quality of the legacy well completions is extremely poor.
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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 | 0.001 |
| 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 it