An analytical model to determine a reservoir capacity for wastewater disposal with consideration of geomechanics and extractions
Bibliographic record
Abstract
ABSTRACT: Reservoir capacity in injection wells depends on size, compressibility, and the maximum allowable pressure before risking formation integrity. Studies link saltwater disposal (SWD) operations to fault reactivation, while permeability, reservoir fluid properties, and mineralogy also influence subsurface response. Geomechanical effects, including poroelastic and thermoelastic stress changes, complicate reservoir behavior and must be carefully considered in SWD design. This study presents an analytical approach to determine the maximum injection volume and pressure constraints using pressure superposition principles. The model assumes a homogeneous reservoir with infinite-acting, open, or closed boundaries and multiple wells, operating at a constant rate. A geomechanical framework estimates fracturing pressure gradients by considering in-situ stress changes, rock properties, and thermal effects of cold-water injection. The study assesses pressure evolution in sensitive regions to ensure safe injection and prevent formation damage. Applied to a mature hydrocarbon-producing region with 274 wells, including plugged and abandoned (PA) wells from the 1940s to 2024, it uses pressure superposition to estimate average reservoir pressure and identify sensitive areas. The maximum sustainable injection capacity is determined by combining statistical reservoir characterization with geomechanical constraints. This approach optimizes SWD design, monitors injection pressures, and ensures reservoir integrity.
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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 | 0.000 | 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".