Evaluation of NaCl and MgCl2 heat exchange fluids in a deep binary geothermal system in a sedimentary halite formation
Bibliographic record
Abstract
Abstract Halite formations are attractive geothermal reservoirs due to their high heat conductivity, resulting in higher temperatures than other formations at similar depths. However, halite formations are highly reactive with undersaturated water. An understanding of the geochemical reactions that occur within halite-saturated formation waters can inform decision making regarding well construction, prevention of well clogging, formation dissolution, and thermal short-circuiting. Batch reaction and numerical 3-D flow and equilibrium reactive transport modeling were used to characterize the produced NaCl-brine in a well targeting a halite-saturated formation. The potential for inhibition of precipitation and dissolution using an MgCl 2 -brine and NaCl + MgCl 2 -brine were also investigated. Within the injection well, heating of an NaCl-brine from 70 to 120 °C caused the solubility of halite to decrease, resulting in the potential dissolution of 0.479 mol kg −1 halite at the formation. Conversely, cooling from 120 to 100 °C in the production well resulted in potential precipitation of 0.196 mol kg −1 halite. Concurrent precipitation of anhydrite is also expected. Introduction of MgCl 2 into the heat exchange brine, which has a common Cl − ion, resulted in a decreased potential for dissolution by 0.290 mol kg −1 halite within the formation, as well as decreased precipitation within the production well, compared to the NaCl-brine. The halite solubility was altered by changes in pressure up to 0.045 mol kg −1 . This indicates that designing and monitoring the composition of heat exchange fluids in highly saline environments is an important component in geothermal project design.
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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 | 0.001 | 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 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".