MétaCan
Menu
Back to cohort
Record W4286652301 · doi:10.2475/04.2022.03

Solubility product constants for natural dolomite (0–200 °C) through a groundwater-based approach using the USGS produced water database

2022· article· en· W4286652301 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAmerican Journal of Science · 2022
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGroundwater and Isotope Geochemistry
Canadian institutionsMemorial University of Newfoundland
FundersWoodsideTullow Oil
KeywordsDolomiteMineralogyGeochemical modelingGeologySolubilityGroundwaterSolubility equilibriumChemistry

Abstract

fetched live from OpenAlex

The calculation of a reliable temperature dependent dolomite solubility product constant (K<sub>sp−dol</sub>) has been the subject of much research over the last 70 years. This study evaluates log<sub>10</sub>(<sup>a</sup>Ca<sup>2+</sup>/<sup>a</sup>Mg<sup>2+</sup>) values using PHREEQC (Pitzer approach) for a screened subset (n = 11,480) of formation waters in the U.S. Geological Survey National Produced Waters Geochemical Database V2 (PWGD), an extensive inventory of 165,960 formational waters from a range of sedimentary lithologies in North America up to 6.6 km depth (Blondes and others, 2016). Through extensive ground truthing against datasets sourced from Texas Gulf Coast basin and the Mississippi Salt Dome basin we establish both the geochemical data from the PWGD and a new geothermal model of the US that is used to determine temperatures at-formation-depth to be reliable data sources. The vast majority (90%) of PWGD samples have log<sub>10</sub>(<sup>a</sup>Ca<sup>2+</sup>/<sup>a</sup>Mg<sup>2+</sup>)-temperature values that are interpreted to be indicative of calcite-dolomite equilibrium and buffering by the bulk mineral solubilities. Using statistical models with different parameterisations (different Maier-Kelly formulas, mixed-effects models with various random effects and linear models) log<sub>10</sub>(<sup>a</sup>Ca<sup>2+</sup>/<sup>a</sup>Mg<sup>2+</sup>) values are regressed against the estimated at-formation-depth temperatures to determine K<sub>sp−dol</sub> between 0 and 200 °C. This process relies on the well constrained calcite solubility product constant (K<sub>sp−cal</sub>). Local effects that modify log<sub>10</sub>(<sup>a</sup>Ca<sup>2+</sup>/<sup>a</sup>Mg<sup>2+</sup>) values are evaluated through the addition of random effects to the mixed model which both improves the statistical reliability of the K<sub>sp−dol</sub> model and enables the determination of K<sub>sp−dol</sub> values for local dolomite phases. The nature of these local effects is open to interpretation, but we suggest the primary influence on log<sub>10</sub>(<sup>a</sup>Ca<sup>2+</sup>/<sup>a</sup>Mg<sup>2+</sup>) values is the stoichiometry of the dolomite phase systematically modifying log<sub>10</sub>(<sup>a</sup>Ca<sup>2+</sup>/<sup>a</sup>Mg<sup>2+</sup>) values. We discount the influence on log<sub>10</sub>(<sup>a</sup>Ca<sup>2+</sup>/<sup>a</sup>Mg<sup>2+</sup>) values of dolomite order, the solution ionic strength, equilibration with anhydrite and chlorite group minerals, illitization of smectite and albitization of feldspar. For the dolomite solubility equation; the mixed-effects model (model J23) chosen as most representative yields a pK<sub>sp−dol</sub> (log<sub>10</sub>K<sub>sp−dol</sub>); We determine pK<sub>sp°−dol</sub> to be −17.27 ± 0.35 (25 °C, 1 atm) which is close to prior estimates, including the most recent experimental value reported by Bénézeth and others, 2018 (pKs<sub>p°−dol</sub> = −17.19 ± 0.3) validating the groundwater regression analysis approach of this study.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.235
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.003
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.031
GPT teacher head0.257
Teacher spread0.226 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it