Mineral Filling Pattern in Complex Fracture System of Carbonate Reservoirs: Implications from Geochemical Modeling of Water-Rock Interaction
Bibliographic record
Abstract
Much research has been conducted on physical and numerical modeling that focus on stress state and structural controls on subsurface geofluid flow, yet very few attempts have been made to discover and quantify the mineral precipitation/dissolution kinetics in complex fracture system such as Tarim Basin of China. We conducted a geochemical simulation study using the outcrop fracture networks in Ordovician carbonate rocks in Tabei Outcrop Area of Tarim Basin. Structural analysis, filling analysis within the fracture networks and surrounding rocks were used to constrain the generation and geochemical evolution of the geofluids. Using an advanced reactive transport simulation platform TOUGHREACT, a pertinent thermodynamic system was applied to establish the geological model of the fracture-surrounding rock, where the corresponding calcium carbonate (CaCO3) solution was configured to replace the deep saturated hydrothermal fluids. Different types of mineral parameters were considered with material balance and phase equilibrium calculation to perform numerical simulation of multi-field, e.g., pressure field, temperature field, seepage field and chemical field under formation conditions. The simulation results were consistent with field observations. The major findings of this simulation study include: (1) Along with fluid injection, local dissolution occurred within the fractures and matrix, but with the gradual saturation of calcium ions and the increasing pH value, considerable calcite precipitation occurred. (2) The dissolution/precipitation in different fractures was mainly affected by their structure and physical properties, resulting in changes in fluid flow rate, temperature, pressure and ion concentration over time. (3) In the same group, the degree of mineral filling of small-aperture fractures, low-angle fractures and shallow fractures was significantly higher than other types of fractures. (4) The better the connectivity between reticular fractures and the higher the linear density of fractures, the lower the mineral filling degree. (5) Dissolution phenomenon strengthened within large-aperture conjugated fractures gradually along the flow direction. The proposed methodologies in this study can be applied to model effective fracture filling of other deep reservoirs.
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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 | 0.000 |
| 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 | 0.001 | 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".