Evaluations of Productivity, Injectivity and Wellbore Integrity of Gas (CH4/CO2) Storage
Bibliographic record
Abstract
Gases such as CO2/CH4/H2 are injected, stored and produced later in high-permeability and large pore volume underground. With different thermal-hydraulic-mechanical characteristics at different depth, gas properties such as gas density and thermal conductivity may vary due to either formation pressure and temperature changes. Different injectivity/productivity and THM responses in vicinity of a wellbore at a given depth vary with depth. Consequently different critical pressures of wellbore integrity (fracturing/collapse) may be expected accordingly. An analytical solution of coupled HM model with a pressure- and depth-dependent fluid density corresponding to the formation thermal gradient is developed. Comparing to a typical gas flow, a supercritical pressure/temperature at different depth must be identified above these critical temperature/pressure the density change must be considered. Different mass productivity/injectivity may be obtained at each depth of the opensection, leading to a total different result from those utilized conventionally. Furthermore due to density-dependent effect, the changes in pore pressure, the corresponding gradient, and the effective stresses profile in vicinity of a wellbore may lead to a serious wellbore integrity issues such as hydraulic fracturing and critical wellbore collapse. We conclude that a density change over an order of 103 may be found for CH4/CO2 at the depth where critical pressure/temperature is surpassed. A wellbore solution with coupled THM model and non-linear diffusion equation for gaseous like CO2 is developed. Laplace transform technique is applied for the coupled solution. The induced pore pressure and stresses are calculated to determine the critical wellbore pressure and temperature at different depth for wellbore stability and undesired fracturing. We conclude density change under different depths may correspond to different tempo-spatial pressure and stress changes in vicinity of a wellbore, particularly when supercritical condition is reached. Such a density-dependent pressure and stress changes may lead to different wellbore collapse and fracturing pressures subject to a inflow or outflow conditions, respectively. Different injectivity and productivity in terms of mass flow may also obtained at different depths. Thus a depth-dependent critical pressure and temperature may be generated at different depths. A maximum/minimum wellbore pressures must be determined to balance the maximum injectivity/productivity and wellbore integrity, i.e. fracturing/collapsing.
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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 | 0.000 |
| 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".