diff --git a/notebooks/examples_of_NeqSim_in_Colab.ipynb b/notebooks/examples_of_NeqSim_in_Colab.ipynb index 4b761f08..4f0fb703 100644 --- a/notebooks/examples_of_NeqSim_in_Colab.ipynb +++ b/notebooks/examples_of_NeqSim_in_Colab.ipynb @@ -398,7 +398,7 @@ "\n", "* [Methanol, MEG and AA-LDHI hydrate management choices](flowassurance/hydrate_mitigation_chemical_choice_4016.ipynb): source-pinned three-phase CPA hydrate curves, flowline margins, synthetic-water scale pH screens and the separate AA-LDHI qualification boundary.\n", "* **Advanced** - [Hot-oil commissioning of subsea jumpers with NeqSim and machine learning](flowassurance/hot_oil_commissioning_neqsim_ml.ipynb): follow hot oil displacing cold diesel; calculate properties, wax, wall heat storage, risk and pressure; check conservation and discretization; compare RF/MLP surrogates and explicit restart scenarios.\n", - "* [CO₂ hydrate calculations with NeqSim: brines, inhibitors and drilling-fluid examples](flowassurance/co2_hydrate_brines_and_drilling_fluids.ipynb): updated CO₂/brine solver with a 10 wt% KCl regression at 11.3 bara, pressure/inventory phase checks and hydt unit comparison; hands-on setup, single-point calculations, parameter sweeps and result interpretation; executed brine/MEG/CO₂–CH₄ examples, published-data comparison, practice tasks and a clearly synthetic laboratory-correlation workflow.\n", + "* [CO₂ hydrate calculations with NeqSim: brines, inhibitors and drilling-fluid examples](flowassurance/co2_hydrate_brines_and_drilling_fluids.ipynb): updated CO₂/brine solver with a 10 wt% KCl regression at 11.3 bara, pressure/inventory phase checks and hydt unit comparison; hands-on setup, single-point calculations, parameter sweeps and result interpretation; executed brine/MEG/CO₂–CH₄ examples, Burgass NaCl plus 110 Dholabhai (1993) pure-water/single/mixed-salt endpoints, family error metrics and experimental discussion, practice tasks and a clearly synthetic laboratory-correlation workflow.\n", "* [Thermodynamics of natural gas hydrates — CPA equilibrium, MEG and salt inhibition, and arrival-process screening](thermodynamics/thermodynamics_of_natural_gas_hydrates.ipynb)\n", "* [Wax appearance, model tuning, and flowline operability with NeqSim](thermodynamics/thermodynamicsOfWax.ipynb): characterize a reservoir fluid, calculate and tune wax precipitation, map WAT and wax fraction, and screen cooling and insulation scenarios along a segmented flowline.\n", "* [Mineral-scale thermodynamics and flowline control with NeqSim](thermodynamics/ThermodynamicsOfMineralScale.ipynb): calculate Electrolyte-CPA aqueous speciation and saturation indices, screen water chemistry and incompatible-brine mixing, profile flowline risk, assess inhibitor dose, and couple multiphase hydraulics to deposition.\n", @@ -623,4 +623,3 @@ "nbformat": 4, "nbformat_minor": 0 } - diff --git a/notebooks/flowassurance/co2_hydrate_brines_and_drilling_fluids.ipynb b/notebooks/flowassurance/co2_hydrate_brines_and_drilling_fluids.ipynb index 63693bce..5ff70f37 100644 --- a/notebooks/flowassurance/co2_hydrate_brines_and_drilling_fluids.ipynb +++ b/notebooks/flowassurance/co2_hydrate_brines_and_drilling_fluids.ipynb @@ -43,7 +43,7 @@ "| Can salt and a thermodynamic inhibitor be combined? | MEG dosage with 5 wt% NaCl brine | MEG represents a known molecule; not a generic polymer |\n", "| Does the incoming gas matter? | Pure CO₂ versus a CO₂/CH₄ feed | Feed composition differs from the equilibrium gas composition |\n", "| Is all dissolved CO₂ equivalent to free CO₂? | Finite-inventory examples and phase diagnostics | Saturated and undersaturated systems are different problems |\n", - "| How good are the predictions? | Published NaCl dissociation points, residuals, balances and seed checks | A small benchmark is not full mud qualification |\n", + "| How good are the predictions? | Burgass NaCl and Dholabhai single/mixed-salt data, residuals, balances and seed checks | A small benchmark is not full mud qualification |\n", "| Can brine calculations support a mud correlation? | Explicitly synthetic lab workflow; held-out pressure levels | Replace synthetic data with representative experiments |\n", "| How can results be reused? | CSV tables, figures, laboratory template and provenance JSON | No hydrate kinetics, plugging or well-control solution is inferred |\n", "\n", @@ -74,7 +74,7 @@ "1. Open the notebook in Colab and connect to a fresh **Python 3** runtime.\n", "2. Select **Runtime → Run all**. The first cells install dependencies and prepare the Java library.\n", "3. Wait for the setup and calculations to finish, then compare your tables and plots with the\n", - " saved outputs. The recorded calculation run took about 3.3 minutes, excluding the Java build.\n", + " saved outputs. The recorded calculation run took about 5 minutes, excluding the Java build.\n", "4. To change a recipe, edit the input settings described below. Restart the runtime and run all\n", " cells again so dependent calculations and cached results are recomputed consistently.\n", "5. Use the Colab Files panel to download the generated files from `co2_hydrate_results/`.\n", @@ -492,8 +492,8 @@ "\n", "A practical route is to test the **base brine → filtrate → complete mud** at matched compositions.\n", "A filtrate result can separate dissolved-additive effects from particle-related effects.\n", - "A KCl or mixed-salt calculation is a demonstration of the API, not a claim that its parameters\n", - "have been benchmarked for a particular commercial mud." + "Section 9 benchmarks KCl and mixed salts against measured brine endpoints.\n", + "That evidence does not validate parameters for a particular commercial mud." ] }, { @@ -571,7 +571,7 @@ " \n", " \n", " seconds\n", - " 2.75869\n", + " 2.48336\n", " \n", " \n", " balance_error\n", @@ -646,7 +646,7 @@ "pressure_bara 50\n", "hydrate_temperature_c 7.3415\n", "hydrate_residual -2.077e-10\n", - "seconds 2.75869\n", + "seconds 2.48336\n", "balance_error 1.11022e-16\n", "charge_error 0\n", "ion_leak 1e-50\n", @@ -984,7 +984,7 @@ " \n", " \n", " seconds\n", - " 0.235005\n", + " 0.266121\n", " \n", " \n", " balance_error\n", @@ -1059,7 +1059,7 @@ "pressure_bara 11.3\n", "hydrate_temperature_c -2.54566\n", "hydrate_residual -1.78966e-08\n", - "seconds 0.235005\n", + "seconds 0.266121\n", "balance_error 1.11022e-16\n", "charge_error 0\n", "ion_leak 1e-50\n", @@ -1120,7 +1120,7 @@ " AQUEOUS\n", " False\n", " 0\n", - " 0.118576\n", + " 0.198925\n", " \n", " \n", " 1\n", @@ -1130,7 +1130,7 @@ " AQUEOUS\n", " False\n", " 0\n", - " 0.274022\n", + " 0.171231\n", " \n", " \n", " 2\n", @@ -1140,7 +1140,7 @@ " GAS+AQUEOUS\n", " True\n", " 0\n", - " 0.312931\n", + " 0.169454\n", " \n", " \n", " 3\n", @@ -1150,7 +1150,7 @@ " GAS+AQUEOUS\n", " True\n", " 0\n", - " 0.402595\n", + " 0.220648\n", " \n", " \n", " 4\n", @@ -1160,7 +1160,7 @@ " AQUEOUS\n", " False\n", " 0\n", - " 0.188818\n", + " 0.191697\n", " \n", " \n", " 5\n", @@ -1170,7 +1170,7 @@ " AQUEOUS\n", " False\n", " 0\n", - " 0.238381\n", + " 0.173368\n", " \n", " \n", " 6\n", @@ -1180,7 +1180,7 @@ " GAS+AQUEOUS\n", " True\n", " 0\n", - " 0.294228\n", + " 0.163904\n", " \n", " \n", " 7\n", @@ -1190,7 +1190,7 @@ " GAS+AQUEOUS\n", " True\n", " 0\n", - " 0.376747\n", + " 0.391516\n", " \n", " \n", " 8\n", @@ -1200,7 +1200,7 @@ " AQUEOUS\n", " False\n", " 0\n", - " 0.21475\n", + " 0.085285\n", " \n", " \n", " 9\n", @@ -1210,7 +1210,7 @@ " AQUEOUS\n", " False\n", " 0\n", - " 0.13904\n", + " 0.153061\n", " \n", " \n", " 10\n", @@ -1220,7 +1220,7 @@ " GAS+AQUEOUS\n", " True\n", " 0\n", - " 0.303113\n", + " 0.248078\n", " \n", " \n", " 11\n", @@ -1230,7 +1230,7 @@ " GAS+AQUEOUS\n", " True\n", " 0\n", - " 0.538614\n", + " 0.303968\n", " \n", " \n", " 12\n", @@ -1240,7 +1240,7 @@ " AQUEOUS\n", " False\n", " 0\n", - " 0.104583\n", + " 0.145554\n", " \n", " \n", " 13\n", @@ -1250,7 +1250,7 @@ " AQUEOUS\n", " False\n", " 0\n", - " 0.193918\n", + " 0.37163\n", " \n", " \n", " 14\n", @@ -1260,7 +1260,7 @@ " AQUEOUS\n", " False\n", " 0\n", - " 0.472505\n", + " 0.283532\n", " \n", " \n", " 15\n", @@ -1270,7 +1270,7 @@ " GAS+AQUEOUS\n", " True\n", " 0\n", - " 0.416016\n", + " 0.462262\n", " \n", " \n", "\n", @@ -1296,22 +1296,22 @@ "15 20 10 2.54305 GAS+AQUEOUS True \n", "\n", " Feed error [mol/mol feed] Seconds \n", - "0 0 0.118576 \n", - "1 0 0.274022 \n", - "2 0 0.312931 \n", - "3 0 0.402595 \n", - "4 0 0.188818 \n", - "5 0 0.238381 \n", - "6 0 0.294228 \n", - "7 0 0.376747 \n", - "8 0 0.21475 \n", - "9 0 0.13904 \n", - "10 0 0.303113 \n", - "11 0 0.538614 \n", - "12 0 0.104583 \n", - "13 0 0.193918 \n", - "14 0 0.472505 \n", - "15 0 0.416016 " + "0 0 0.198925 \n", + "1 0 0.171231 \n", + "2 0 0.169454 \n", + "3 0 0.220648 \n", + "4 0 0.191697 \n", + "5 0 0.173368 \n", + "6 0 0.163904 \n", + "7 0 0.391516 \n", + "8 0 0.085285 \n", + "9 0 0.153061 \n", + "10 0 0.248078 \n", + "11 0 0.303968 \n", + "12 0 0.145554 \n", + "13 0 0.37163 \n", + "14 0 0.283532 \n", + "15 0 0.462262 " ] }, "metadata": {}, @@ -2863,6 +2863,2611 @@ "show_figure(figure, \"05_published_benchmark\")" ] }, + { + "cell_type": "markdown", + "id": "9e9bcdff", + "metadata": {}, + "source": [ + "### 9.1. Dholabhai, Kalogerakis and Bishnoi (1993): a wider salt benchmark\n", + "\n", + "**Source:** *Equilibrium Conditions for Carbon Dioxide Hydrate Formation in Aqueous\n", + "Electrolyte Solutions*, J. Chem. Eng. Data **38**, 650–654,\n", + "[doi:10.1021/je00012a045](https://doi.org/10.1021/je00012a045).\n", + "The numerical data below were manually transcribed and visually checked against the supplied\n", + "paper: solution recipes from Table I (p. 651), measured endpoints from Tables III–IV\n", + "(pp. 651–652). The paper is copyright ACS; no paper pages or figures are redistributed here.\n", + "\n", + "The experiment measured **aqueous solution + CO₂ vapor + incipient hydrate** using a\n", + "pressure-search procedure. Hydrates were first formed, then pressure was reduced and adjusted\n", + "until temperature and pressure remained steady for 3–4 hours with a small hydrate quantity.\n", + "CO₂ purity was 99.99%. These are equilibrium endpoints, not induction-time or growth-rate data.\n", + "\n", + "- Match each **measured** wet-basis salt composition, including 10.02 wt% for K10, rather\n", + " than replacing it with the nominal label. Use 1 kg water and the conversion in Section 3.\n", + "- Convert $P_{bar}=10P_{MPa}$ and $T_{°C}=T_K-273.15$. The paper added atmospheric pressure\n", + " to the corrected gauge reading; the tabulated pressure is used as absolute pressure.\n", + "- Use the same electrolyte CPA / GF model and sufficient CO₂ inventory (10 mol/kg water),\n", + " without fitting any parameters to this paper. Require convergence, conservation, a CO₂-rich\n", + " phase and the solver's saturated-boundary diagnostic. Audit the returned phase label;\n", + " agreement with a vapor experiment requires GAS+AQUEOUS.\n", + "- Include all pure-water, NaCl, KCl, CaCl₂, NaCl–KCl and NaCl–CaCl₂ endpoints. The five\n", + " synthetic-seawater points are excluded: Table II includes MgCl₂, KBr, Na₂SO₄, NaF and\n", + " SrCl₂ beyond this notebook's three-salt recipe builder. Replacing seawater with NaCl would\n", + " change the experiment. No seawater accuracy is claimed.\n", + "\n", + "The paper spans about 259–281 K and 0.9–4.1 MPa. Several brines are below 273.15 K:\n", + "their measurements concern liquid brine, not automatically ice–hydrate coexistence.\n", + "This calculation does not test ice stability or salt precipitation. Report discrepancies as\n", + "model evidence within the measured liquid-brine regime, with those solid-phase limits retained." + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "id": "584ea7fb", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Transcribed 110 endpoints from 28 solutions.\n", + "Vapor/aqueous saturated boundaries: 110.\n", + "Errors are NeqSim minus experiment; positive means a higher predicted boundary.\n" + ] + }, + { + "data": { + "text/markdown": [ + "**Measured recipes from Table I (wet basis)**" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "
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solutionNaCl_wt_percentKCl_wt_percentCaCl2_wt_percent
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2Na3-23.0200
3Na3-33.0200
4Na5-1500
5Na5-2500
6Na10-110.0200
7Na10-21000
8Na151500
9Na2020.0300
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11K505.010
12K10010.020
13K15014.970
14Ca3003.03
15Ca5005.02
16Ca10009.99
17Ca150014.97
18Ca200019.96
19Na3K33.013.020
20Na5K555.010
21Na7K106.99100
22Na15K515.015.030
23Na3Ca33.0303.03
24Na8Ca28.0102.03
25Na2Ca82.0208
26Na5Ca155.02014.7
27Na15Ca515.0105.03
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solutionpressure_barameasured_cpredicted_cerror_Kcomparable
0water13.40.61.12440.5244True
1water16.42.362.76730.4073True
2water19.853.954.27750.3275True
3water25.25.896.08680.1968True
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solutionpressure_barameasured_cpredicted_cerror_Kcomparable
0Na3-129.555.85.92770.1277True
1Na3-123.093.884.1530.273True
2Na3-118.372.022.40430.3843True
3Na3-113.04-0.95-0.34390.6061True
4Na3-214.340.060.42180.3618True
5Na3-339.077.777.7259-0.0441True
6Na5-130.044.825.13180.3118True
7Na5-120.161.882.24120.3612True
8Na5-115.97-0.10.42540.5254True
9Na5-113.06-1.97-1.19270.7773True
10Na5-237.666.816.5867-0.2233True
11Na10-137.814.043.9393-0.1007True
12Na10-136.713.863.7672-0.0928True
13Na10-231.552.972.844-0.126True
14Na10-231.492.922.8317-0.0883True
15Na10-224.090.931.00980.0798True
16Na10-216.56-2.14-1.78390.3561True
17Na10-211.62-5.12-4.58890.5311True
18Na1532.39-0.14-0.4296-0.2896True
19Na1524.69-2.1-2.1859-0.0859True
20Na1517.03-4.95-4.85270.0973True
21Na1512.12-7.77-7.46250.3075True
22Na2026.3-6.3-6.5272-0.2272True
23Na2022.08-7.86-7.67550.1845True
24Na2016.06-9.86-9.9166-0.0566True
\n", + "
" + ], + "text/plain": [ + " solution pressure_bara measured_c predicted_c error_K comparable\n", + "0 Na3-1 29.55 5.8 5.9277 0.1277 True\n", + "1 Na3-1 23.09 3.88 4.153 0.273 True\n", + "2 Na3-1 18.37 2.02 2.4043 0.3843 True\n", + "3 Na3-1 13.04 -0.95 -0.3439 0.6061 True\n", + "4 Na3-2 14.34 0.06 0.4218 0.3618 True\n", + "5 Na3-3 39.07 7.77 7.7259 -0.0441 True\n", + "6 Na5-1 30.04 4.82 5.1318 0.3118 True\n", + "7 Na5-1 20.16 1.88 2.2412 0.3612 True\n", + "8 Na5-1 15.97 -0.1 0.4254 0.5254 True\n", + "9 Na5-1 13.06 -1.97 -1.1927 0.7773 True\n", + "10 Na5-2 37.66 6.81 6.5867 -0.2233 True\n", + "11 Na10-1 37.81 4.04 3.9393 -0.1007 True\n", + "12 Na10-1 36.71 3.86 3.7672 -0.0928 True\n", + "13 Na10-2 31.55 2.97 2.844 -0.126 True\n", + "14 Na10-2 31.49 2.92 2.8317 -0.0883 True\n", + "15 Na10-2 24.09 0.93 1.0098 0.0798 True\n", + "16 Na10-2 16.56 -2.14 -1.7839 0.3561 True\n", + "17 Na10-2 11.62 -5.12 -4.5889 0.5311 True\n", + "18 Na15 32.39 -0.14 -0.4296 -0.2896 True\n", + "19 Na15 24.69 -2.1 -2.1859 -0.0859 True\n", + "20 Na15 17.03 -4.95 -4.8527 0.0973 True\n", + "21 Na15 12.12 -7.77 -7.4625 0.3075 True\n", + "22 Na20 26.3 -6.3 -6.5272 -0.2272 True\n", + "23 Na20 22.08 -7.86 -7.6755 0.1845 True\n", + "24 Na20 16.06 -9.86 -9.9166 -0.0566 True" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/markdown": [ + "**KCl: every measured point**" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "
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solutionpressure_barameasured_cpredicted_cerror_Kcomparable
0K338.347.948.05320.1132True
1K332.336.846.94770.1077True
2K327.65.535.84360.3136True
3K321.543.63.99940.3994True
4K316.541.421.9230.503True
5K313.26-0.480.12340.6034True
6K539.057.327.77580.4558True
7K538.617.287.70450.4245True
8K533.246.286.71780.4378True
9K529.65.465.90540.4454True
10K521.292.883.43010.5501True
11K5170.981.63790.6579True
12K513.25-1.09-0.41120.6788True
13K1034.854.717.1822.472True
14K1028.073.195.43892.2489True
15K1018.48-0.071.85121.9212True
16K1011.3-4.13-2.54651.5835True
17K1514.15-4.120.35754.4775True
18K1520.95-0.934.355.28True
19K1529.011.437.59096.1609True
20K1535.752.869.5896.729True
\n", + "
" + ], + "text/plain": [ + " solution pressure_bara measured_c predicted_c error_K comparable\n", + "0 K3 38.34 7.94 8.0532 0.1132 True\n", + "1 K3 32.33 6.84 6.9477 0.1077 True\n", + "2 K3 27.6 5.53 5.8436 0.3136 True\n", + "3 K3 21.54 3.6 3.9994 0.3994 True\n", + "4 K3 16.54 1.42 1.923 0.503 True\n", + "5 K3 13.26 -0.48 0.1234 0.6034 True\n", + "6 K5 39.05 7.32 7.7758 0.4558 True\n", + "7 K5 38.61 7.28 7.7045 0.4245 True\n", + "8 K5 33.24 6.28 6.7178 0.4378 True\n", + "9 K5 29.6 5.46 5.9054 0.4454 True\n", + "10 K5 21.29 2.88 3.4301 0.5501 True\n", + "11 K5 17 0.98 1.6379 0.6579 True\n", + "12 K5 13.25 -1.09 -0.4112 0.6788 True\n", + "13 K10 34.85 4.71 7.182 2.472 True\n", + "14 K10 28.07 3.19 5.4389 2.2489 True\n", + "15 K10 18.48 -0.07 1.8512 1.9212 True\n", + "16 K10 11.3 -4.13 -2.5465 1.5835 True\n", + "17 K15 14.15 -4.12 0.3575 4.4775 True\n", + "18 K15 20.95 -0.93 4.35 5.28 True\n", + "19 K15 29.01 1.43 7.5909 6.1609 True\n", + "20 K15 35.75 2.86 9.589 6.729 True" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/markdown": [ + "**CaCl2: every measured point**" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "
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solutionpressure_barameasured_cpredicted_cerror_Kcomparable
0Ca318.272.372.640.27True
1Ca313.02-0.57-0.08720.4828True
2Ca325.2955.11190.1119True
3Ca337.027.727.7105-0.0095True
4Ca528.055.065.07540.0154True
5Ca536.576.926.8454-0.0746True
6Ca518.721.912.05820.1482True
7Ca511.84-2.07-1.6340.436True
8Ca1015.11-2.3-2.14340.1566True
9Ca1011.02-5.1-4.72720.3728True
10Ca1021.980.810.7948-0.0152True
11Ca1034.64.114.011-0.099True
12Ca1038.244.714.6394-0.0706True
13Ca1532.210.020.38790.3679True
14Ca1521.38-3.03-2.72820.3018True
15Ca1514.97-5.78-5.63410.1459True
16Ca159.6-9.73-9.37530.3547True
17Ca2026.9-6.5-4.35452.1455True
18Ca2020.52-8.57-6.79281.7772True
19Ca2015.04-11.15-9.64421.5058True
20Ca2010.51-13.96-12.94131.0187True
\n", + "
" + ], + "text/plain": [ + " solution pressure_bara measured_c predicted_c error_K comparable\n", + "0 Ca3 18.27 2.37 2.64 0.27 True\n", + "1 Ca3 13.02 -0.57 -0.0872 0.4828 True\n", + "2 Ca3 25.29 5 5.1119 0.1119 True\n", + "3 Ca3 37.02 7.72 7.7105 -0.0095 True\n", + "4 Ca5 28.05 5.06 5.0754 0.0154 True\n", + "5 Ca5 36.57 6.92 6.8454 -0.0746 True\n", + "6 Ca5 18.72 1.91 2.0582 0.1482 True\n", + "7 Ca5 11.84 -2.07 -1.634 0.436 True\n", + "8 Ca10 15.11 -2.3 -2.1434 0.1566 True\n", + "9 Ca10 11.02 -5.1 -4.7272 0.3728 True\n", + "10 Ca10 21.98 0.81 0.7948 -0.0152 True\n", + "11 Ca10 34.6 4.11 4.011 -0.099 True\n", + "12 Ca10 38.24 4.71 4.6394 -0.0706 True\n", + "13 Ca15 32.21 0.02 0.3879 0.3679 True\n", + "14 Ca15 21.38 -3.03 -2.7282 0.3018 True\n", + "15 Ca15 14.97 -5.78 -5.6341 0.1459 True\n", + "16 Ca15 9.6 -9.73 -9.3753 0.3547 True\n", + "17 Ca20 26.9 -6.5 -4.3545 2.1455 True\n", + "18 Ca20 20.52 -8.57 -6.7928 1.7772 True\n", + "19 Ca20 15.04 -11.15 -9.6442 1.5058 True\n", + "20 Ca20 10.51 -13.96 -12.9413 1.0187 True" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/markdown": [ + "**NaCl + KCl: every measured point**" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "
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solutionpressure_barameasured_cpredicted_cerror_Kcomparable
0Na3K339.766.726.7164-0.0036True
1Na3K335.736.146.0627-0.0773True
2Na3K323.172.923.05130.1313True
3Na3K318.140.871.17670.3067True
4Na3K313.26-1.65-1.33620.3138True
5Na5K513.47-3.18-3.02770.1523True
6Na5K516.6-1.43-1.33350.0965True
7Na5K522.580.961.07090.1109True
8Na5K534.324.174.0609-0.1091True
9Na7K1014.82-5.58-4.75890.8211True
10Na7K1021.8-2.67-1.26951.4005True
11Na7K1030.44-0.081.64181.7218True
12Na7K1034.550.932.6941.764True
13Na15K512.18-10.22-11.6142-1.3942True
14Na15K518.72-6.85-8.2538-1.4038True
15Na15K523.88-4.97-6.4385-1.4685True
16Na15K530.5-3.33-4.7216-1.3916True
\n", + "
" + ], + "text/plain": [ + " solution pressure_bara measured_c predicted_c error_K comparable\n", + "0 Na3K3 39.76 6.72 6.7164 -0.0036 True\n", + "1 Na3K3 35.73 6.14 6.0627 -0.0773 True\n", + "2 Na3K3 23.17 2.92 3.0513 0.1313 True\n", + "3 Na3K3 18.14 0.87 1.1767 0.3067 True\n", + "4 Na3K3 13.26 -1.65 -1.3362 0.3138 True\n", + "5 Na5K5 13.47 -3.18 -3.0277 0.1523 True\n", + "6 Na5K5 16.6 -1.43 -1.3335 0.0965 True\n", + "7 Na5K5 22.58 0.96 1.0709 0.1109 True\n", + "8 Na5K5 34.32 4.17 4.0609 -0.1091 True\n", + "9 Na7K10 14.82 -5.58 -4.7589 0.8211 True\n", + "10 Na7K10 21.8 -2.67 -1.2695 1.4005 True\n", + "11 Na7K10 30.44 -0.08 1.6418 1.7218 True\n", + "12 Na7K10 34.55 0.93 2.694 1.764 True\n", + "13 Na15K5 12.18 -10.22 -11.6142 -1.3942 True\n", + "14 Na15K5 18.72 -6.85 -8.2538 -1.4038 True\n", + "15 Na15K5 23.88 -4.97 -6.4385 -1.4685 True\n", + "16 Na15K5 30.5 -3.33 -4.7216 -1.3916 True" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/markdown": [ + "**NaCl + CaCl2: every measured point**" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "
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solutionpressure_barameasured_cpredicted_cerror_Kcomparable
0Na3Ca335.956.025.9832-0.0368True
1Na3Ca327.384.174.17320.0032True
2Na3Ca322.272.582.67510.0951True
3Na3Ca313.75-1.37-1.09060.2794True
4Na3Ca312.58-2.16-1.81340.3466True
5Na8Ca210.86-5.38-5.16860.2114True
6Na8Ca216.23-2.08-1.96750.1125True
7Na8Ca221.120.010.03120.0212True
8Na8Ca230.892.852.6881-0.1619True
9Na2Ca836.974.334.1692-0.1608True
10Na2Ca831.013.173.0424-0.1276True
11Na2Ca819.09-0.43-0.4783-0.0483True
12Na2Ca810.53-5.36-5.24930.1107True
13Na5Ca1529.35-5.81-4.98720.8228True
14Na5Ca1524.9-6.86-6.26350.5965True
15Na5Ca1518.78-9.04-8.54460.4954True
16Na5Ca1512.88-12.06-11.69180.3682True
17Na5Ca1510.42-14-13.48320.5168True
18Na15Ca526.65-5.76-6.9465-1.1865True
19Na15Ca521.12-7.48-8.5128-1.0328True
20Na15Ca516.09-9.61-10.4686-0.8586True
21Na15Ca59.09-14.13-14.832-0.702True
\n", + "
" + ], + "text/plain": [ + " solution pressure_bara measured_c predicted_c error_K comparable\n", + "0 Na3Ca3 35.95 6.02 5.9832 -0.0368 True\n", + "1 Na3Ca3 27.38 4.17 4.1732 0.0032 True\n", + "2 Na3Ca3 22.27 2.58 2.6751 0.0951 True\n", + "3 Na3Ca3 13.75 -1.37 -1.0906 0.2794 True\n", + "4 Na3Ca3 12.58 -2.16 -1.8134 0.3466 True\n", + "5 Na8Ca2 10.86 -5.38 -5.1686 0.2114 True\n", + "6 Na8Ca2 16.23 -2.08 -1.9675 0.1125 True\n", + "7 Na8Ca2 21.12 0.01 0.0312 0.0212 True\n", + "8 Na8Ca2 30.89 2.85 2.6881 -0.1619 True\n", + "9 Na2Ca8 36.97 4.33 4.1692 -0.1608 True\n", + "10 Na2Ca8 31.01 3.17 3.0424 -0.1276 True\n", + "11 Na2Ca8 19.09 -0.43 -0.4783 -0.0483 True\n", + "12 Na2Ca8 10.53 -5.36 -5.2493 0.1107 True\n", + "13 Na5Ca15 29.35 -5.81 -4.9872 0.8228 True\n", + "14 Na5Ca15 24.9 -6.86 -6.2635 0.5965 True\n", + "15 Na5Ca15 18.78 -9.04 -8.5446 0.4954 True\n", + "16 Na5Ca15 12.88 -12.06 -11.6918 0.3682 True\n", + "17 Na5Ca15 10.42 -14 -13.4832 0.5168 True\n", + "18 Na15Ca5 26.65 -5.76 -6.9465 -1.1865 True\n", + "19 Na15Ca5 21.12 -7.48 -8.5128 -1.0328 True\n", + "20 Na15Ca5 16.09 -9.61 -10.4686 -0.8586 True\n", + "21 Na15Ca5 9.09 -14.13 -14.832 -0.702 True" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "
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FamilyMeasuredComparedBias [K]MAE [K]RMSE [K]Max absolute error [K]
0Pure water440.3640.3640.3830.5244
1NaCl25250.1580.26480.32490.7773
2KCl21211.74111.74112.68516.729
3CaCl221210.44490.47050.76082.1455
4NaCl + KCl17170.05710.74510.99981.764
5NaCl + CaCl22222-0.01520.37710.51061.1865
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" + ], + "text/plain": [ + " Family Measured Compared Bias [K] MAE [K] RMSE [K] Max absolute error [K]\n", + "0 Pure water 4 4 0.364 0.364 0.383 0.5244\n", + "1 NaCl 25 25 0.158 0.2648 0.3249 0.7773\n", + "2 KCl 21 21 1.7411 1.7411 2.6851 6.729\n", + "3 CaCl2 21 21 0.4449 0.4705 0.7608 2.1455\n", + "4 NaCl + KCl 17 17 0.0571 0.7451 0.9998 1.764\n", + "5 NaCl + CaCl2 22 22 -0.0152 0.3771 0.5106 1.1865" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/markdown": [ + "**Per-recipe errors: distinguish concentration and mixture effects**" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "
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SolutionComparedBias [K]MAE [K]RMSE [K]Min error [K]Max error [K]
0water40.3640.3640.3830.19680.5244
1Na3-140.34780.34780.38920.12770.6061
2Na3-210.36180.36180.36180.36180.3618
3Na3-31-0.04410.04410.0441-0.0441-0.0441
4Na5-140.49390.49390.52630.31180.7773
5Na5-21-0.22330.22330.2233-0.2233-0.2233
6Na10-12-0.09670.09670.0968-0.1007-0.0928
7Na10-250.15050.23620.2963-0.1260.5311
8Na1540.00730.19510.221-0.28960.3075
9Na203-0.03310.15610.1721-0.22720.1845
10K360.34010.34010.38720.10770.6034
11K570.52150.52150.53110.42450.6788
12K1042.05642.05642.08371.58352.472
13K1545.66185.66185.72634.47756.729
14Ca340.21380.21860.2822-0.00950.4828
15Ca540.13120.16850.2334-0.07460.436
16Ca1050.06890.14280.1889-0.0990.3728
17Ca1540.29260.29260.30560.14590.3679
18Ca2041.61181.61181.66331.01872.1455
19Na3K350.13420.16650.2077-0.07730.3138
20Na5K540.06270.11720.1191-0.10910.1523
21Na7K1041.42691.42691.47580.82111.764
22Na15K54-1.41451.41451.4149-1.4685-1.3916
23Na3Ca350.13750.15220.2043-0.03680.3466
24Na8Ca240.04580.12680.145-0.16190.2114
25Na2Ca84-0.05650.11180.1191-0.16080.1107
26Na5Ca1550.560.560.57980.36820.8228
27Na15Ca54-0.9450.9450.9624-1.1865-0.702
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" + ], + "text/plain": [ + " Solution Compared Bias [K] MAE [K] RMSE [K] Min error [K] Max error [K]\n", + "0 water 4 0.364 0.364 0.383 0.1968 0.5244\n", + "1 Na3-1 4 0.3478 0.3478 0.3892 0.1277 0.6061\n", + "2 Na3-2 1 0.3618 0.3618 0.3618 0.3618 0.3618\n", + "3 Na3-3 1 -0.0441 0.0441 0.0441 -0.0441 -0.0441\n", + "4 Na5-1 4 0.4939 0.4939 0.5263 0.3118 0.7773\n", + "5 Na5-2 1 -0.2233 0.2233 0.2233 -0.2233 -0.2233\n", + "6 Na10-1 2 -0.0967 0.0967 0.0968 -0.1007 -0.0928\n", + "7 Na10-2 5 0.1505 0.2362 0.2963 -0.126 0.5311\n", + "8 Na15 4 0.0073 0.1951 0.221 -0.2896 0.3075\n", + "9 Na20 3 -0.0331 0.1561 0.1721 -0.2272 0.1845\n", + "10 K3 6 0.3401 0.3401 0.3872 0.1077 0.6034\n", + "11 K5 7 0.5215 0.5215 0.5311 0.4245 0.6788\n", + "12 K10 4 2.0564 2.0564 2.0837 1.5835 2.472\n", + "13 K15 4 5.6618 5.6618 5.7263 4.4775 6.729\n", + "14 Ca3 4 0.2138 0.2186 0.2822 -0.0095 0.4828\n", + "15 Ca5 4 0.1312 0.1685 0.2334 -0.0746 0.436\n", + "16 Ca10 5 0.0689 0.1428 0.1889 -0.099 0.3728\n", + "17 Ca15 4 0.2926 0.2926 0.3056 0.1459 0.3679\n", + "18 Ca20 4 1.6118 1.6118 1.6633 1.0187 2.1455\n", + "19 Na3K3 5 0.1342 0.1665 0.2077 -0.0773 0.3138\n", + "20 Na5K5 4 0.0627 0.1172 0.1191 -0.1091 0.1523\n", + "21 Na7K10 4 1.4269 1.4269 1.4758 0.8211 1.764\n", + "22 Na15K5 4 -1.4145 1.4145 1.4149 -1.4685 -1.3916\n", + "23 Na3Ca3 5 0.1375 0.1522 0.2043 -0.0368 0.3466\n", + "24 Na8Ca2 4 0.0458 0.1268 0.145 -0.1619 0.2114\n", + "25 Na2Ca8 4 -0.0565 0.1118 0.1191 -0.1608 0.1107\n", + "26 Na5Ca15 5 0.56 0.56 0.5798 0.3682 0.8228\n", + "27 Na15Ca5 4 -0.945 0.945 0.9624 -1.1865 -0.702" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# (solution label, NaCl wt%, KCl wt%, CaCl2 wt%, measured (K, MPa) pairs)\n", + "# Table I recipes and Tables III–IV endpoints; table membership retained per point.\n", + "dholabhai_series = [\n", + " (\"water\", 0, 0, 0, [(273.75, 1.340), (275.51, 1.640),\n", + " (277.10, 1.985), (279.04, 2.520)]),\n", + " (\"Na3-1\", 3.00, 0, 0, [(278.95, 2.955), (277.03, 2.309),\n", + " (275.17, 1.837), (272.20, 1.304)]),\n", + " (\"Na3-2\", 3.02, 0, 0, [(273.21, 1.434)]),\n", + " (\"Na3-3\", 3.02, 0, 0, [(280.92, 3.907)]),\n", + " (\"Na5-1\", 5.00, 0, 0, [(277.97, 3.004), (275.03, 2.016),\n", + " (273.05, 1.597), (271.18, 1.306)]),\n", + " (\"Na5-2\", 5.00, 0, 0, [(279.96, 3.766)]),\n", + " (\"Na10-1\", 10.02, 0, 0, [(277.19, 3.781), (277.01, 3.671)]),\n", + " (\"Na10-2\", 10.00, 0, 0, [(276.12, 3.155), (276.07, 3.149),\n", + " (274.08, 2.409), (271.01, 1.656), (268.03, 1.162)]),\n", + " (\"Na15\", 15.00, 0, 0, [(273.01, 3.239), (271.05, 2.469),\n", + " (268.20, 1.703), (265.38, 1.212)]),\n", + " (\"Na20\", 20.03, 0, 0, [(266.85, 2.630), (265.29, 2.208), (263.29, 1.606)]),\n", + " (\"K3\", 0, 3.00, 0, [(281.09, 3.834), (279.99, 3.233), (278.68, 2.760),\n", + " (276.75, 2.154), (274.57, 1.654), (272.67, 1.326)]),\n", + " (\"K5\", 0, 5.01, 0, [(280.47, 3.905), (280.43, 3.861), (279.43, 3.324),\n", + " (278.61, 2.960), (276.03, 2.129), (274.13, 1.700), (272.06, 1.325)]),\n", + " (\"K10\", 0, 10.02, 0, [(277.86, 3.485), (276.34, 2.807),\n", + " (273.08, 1.848), (269.02, 1.130)]),\n", + " (\"K15\", 0, 14.97, 0, [(269.03, 1.415), (272.22, 2.095),\n", + " (274.58, 2.901), (276.01, 3.575)]),\n", + " (\"Ca3\", 0, 0, 3.03, [(275.52, 1.827), (272.58, 1.302),\n", + " (278.15, 2.529), (280.87, 3.702)]),\n", + " (\"Ca5\", 0, 0, 5.02, [(278.21, 2.805), (280.07, 3.657),\n", + " (275.06, 1.872), (271.08, 1.184)]),\n", + " (\"Ca10\", 0, 0, 9.99, [(270.85, 1.511), (268.05, 1.102), (273.96, 2.198),\n", + " (277.26, 3.460), (277.86, 3.824)]),\n", + " (\"Ca15\", 0, 0, 14.97, [(273.17, 3.221), (270.12, 2.138),\n", + " (267.37, 1.497), (263.42, 0.960)]),\n", + " (\"Ca20\", 0, 0, 19.96, [(266.65, 2.690), (264.58, 2.052),\n", + " (262.00, 1.504), (259.19, 1.051)]),\n", + " (\"Na3K3\", 3.01, 3.02, 0, [(279.87, 3.976), (279.29, 3.573),\n", + " (276.07, 2.317), (274.02, 1.814), (271.50, 1.326)]),\n", + " (\"Na5K5\", 5.00, 5.01, 0, [(269.97, 1.347), (271.72, 1.660),\n", + " (274.11, 2.258), (277.32, 3.432)]),\n", + " (\"Na7K10\", 6.99, 10.00, 0, [(267.57, 1.482), (270.48, 2.180),\n", + " (273.07, 3.044), (274.08, 3.455)]),\n", + " (\"Na15K5\", 15.01, 5.03, 0, [(262.93, 1.218), (266.30, 1.872),\n", + " (268.18, 2.388), (269.82, 3.050)]),\n", + " (\"Na3Ca3\", 3.03, 0, 3.03, [(279.17, 3.595), (277.32, 2.738),\n", + " (275.73, 2.227), (271.78, 1.375), (270.99, 1.258)]),\n", + " (\"Na8Ca2\", 8.01, 0, 2.03, [(267.77, 1.086), (271.07, 1.623),\n", + " (273.16, 2.112), (276.00, 3.089)]),\n", + " (\"Na2Ca8\", 2.02, 0, 8.00, [(277.48, 3.697), (276.32, 3.101),\n", + " (272.72, 1.909), (267.79, 1.053)]),\n", + " (\"Na5Ca15\", 5.02, 0, 14.70, [(267.34, 2.935), (266.29, 2.490),\n", + " (264.11, 1.878), (261.09, 1.288), (259.15, 1.042)]),\n", + " (\"Na15Ca5\", 15.01, 0, 5.03, [(267.39, 2.665), (265.67, 2.112),\n", + " (263.54, 1.609), (259.02, 0.909)]),\n", + "]\n", + "\n", + "dholabhai_rows = []\n", + "for solution, nacl, kcl, cacl2, points in dholabhai_series:\n", + " salts = {\n", + " name: percent for name, percent in zip([\"NaCl\", \"KCl\", \"CaCl2\"], [nacl, kcl, cacl2])\n", + " if percent > 0\n", + " }\n", + " family = \" + \".join(salts) if salts else \"Pure water\"\n", + " source_table = \"III\" if solution in [row[0] for row in dholabhai_series[:15]] else \"IV\"\n", + " for temperature_K, pressure_MPa in points:\n", + " result, fluid = hydrate_point(pressure_MPa * 10.0, salts)\n", + " comparable = (\n", + " result[\"accepted\"]\n", + " and result[\"saturated_co2_boundary\"]\n", + " and result[\"phases\"] == \"GAS+AQUEOUS\"\n", + " )\n", + " dholabhai_rows.append({\n", + " \"solution\": solution,\n", + " \"family\": family,\n", + " \"table\": source_table,\n", + " \"NaCl_wt_percent\": nacl,\n", + " \"KCl_wt_percent\": kcl,\n", + " \"CaCl2_wt_percent\": cacl2,\n", + " \"salt_total_wt_percent\": nacl + kcl + cacl2,\n", + " \"measured_K\": temperature_K,\n", + " \"pressure_MPa\": pressure_MPa,\n", + " \"pressure_bara\": pressure_MPa * 10.0,\n", + " \"measured_c\": temperature_K - 273.15,\n", + " \"predicted_c\": result[\"hydrate_temperature_c\"] if comparable else np.nan,\n", + " \"raw_returned_c\": result[\"hydrate_temperature_c\"],\n", + " \"comparable\": comparable,\n", + " \"material_phases\": result[\"phases\"],\n", + " \"numerically_accepted\": result[\"accepted\"],\n", + " \"saturated_boundary\": result[\"saturated_co2_boundary\"],\n", + " \"hydrate_residual\": result[\"hydrate_residual\"],\n", + " \"original_feed_error\": result[\"original_feed_error\"],\n", + " })\n", + "dholabhai = pd.DataFrame(dholabhai_rows)\n", + "dholabhai[\"error_K\"] = dholabhai[\"predicted_c\"] - dholabhai[\"measured_c\"]\n", + "print(f\"Transcribed {len(dholabhai)} endpoints from {len(dholabhai_series)} solutions.\")\n", + "print(f\"Vapor/aqueous saturated boundaries: {dholabhai['comparable'].sum()}.\")\n", + "display(Markdown(\"**Measured recipes from Table I (wet basis)**\"))\n", + "recipe_columns = [\"solution\", \"NaCl_wt_percent\", \"KCl_wt_percent\", \"CaCl2_wt_percent\"]\n", + "display(dholabhai[recipe_columns].drop_duplicates().reset_index(drop=True))\n", + "comparison_columns = [\n", + " \"solution\", \"pressure_bara\", \"measured_c\", \"predicted_c\", \"error_K\", \"comparable\",\n", + "]\n", + "for family, group in dholabhai.groupby(\"family\", sort=False):\n", + " display(Markdown(f\"**{family}: every measured point**\"))\n", + " display(group[comparison_columns].round(4).reset_index(drop=True))\n", + "if not dholabhai[\"comparable\"].all():\n", + " display(Markdown(\"**Excluded model states: retained for diagnosis, omitted from metrics.**\"))\n", + " display(dholabhai.loc[~dholabhai[\"comparable\"]])\n", + "\n", + "metric_rows = []\n", + "for family, group in dholabhai.groupby(\"family\", sort=False):\n", + " errors = group.loc[group[\"comparable\"], \"error_K\"]\n", + " metric_rows.append({\n", + " \"Family\": family,\n", + " \"Measured\": len(group),\n", + " \"Compared\": len(errors),\n", + " \"Bias [K]\": errors.mean(),\n", + " \"MAE [K]\": errors.abs().mean(),\n", + " \"RMSE [K]\": np.sqrt(np.mean(errors ** 2)),\n", + " \"Max absolute error [K]\": errors.abs().max(),\n", + " })\n", + "dholabhai_metrics = pd.DataFrame(metric_rows)\n", + "display(dholabhai_metrics.round(4))\n", + "print(\"Errors are NeqSim minus experiment; positive means a higher predicted boundary.\")\n", + "\n", + "recipe_metric_rows = []\n", + "for solution, group in dholabhai.groupby(\"solution\", sort=False):\n", + " errors = group.loc[group[\"comparable\"], \"error_K\"]\n", + " recipe_metric_rows.append({\n", + " \"Solution\": solution,\n", + " \"Compared\": len(errors),\n", + " \"Bias [K]\": errors.mean(),\n", + " \"MAE [K]\": errors.abs().mean(),\n", + " \"RMSE [K]\": np.sqrt(np.mean(errors ** 2)),\n", + " \"Min error [K]\": errors.min(),\n", + " \"Max error [K]\": errors.max(),\n", + " })\n", + "dholabhai_recipe_metrics = pd.DataFrame(recipe_metric_rows)\n", + "display(Markdown(\"**Per-recipe errors: distinguish concentration and mixture effects**\"))\n", + "display(dholabhai_recipe_metrics.round(4))\n" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "id": "b60a09fe", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "families = list(dholabhai[\"family\"].unique())\n", + "figure, axes = plt.subplots(2, 3, figsize=(15, 9), layout=\"constrained\")\n", + "for axis, family in zip(axes.flat, families):\n", + " family_data = dholabhai.loc[dholabhai[\"family\"] == family]\n", + " for index, (solution, group) in enumerate(\n", + " family_data.groupby(\"solution\", sort=False)\n", + " ):\n", + " group = group.sort_values(\"pressure_bara\")\n", + " colors = plt.rcParams[\"axes.prop_cycle\"].by_key()[\"color\"]\n", + " color = colors[index % len(colors)]\n", + " axis.scatter(group[\"measured_c\"], group[\"pressure_bara\"], color=color, s=24)\n", + " axis.plot(group[\"predicted_c\"], group[\"pressure_bara\"], \"x--\",\n", + " color=color, markersize=5, linewidth=1.2, label=solution)\n", + " axis.set(title=family, xlabel=\"Temperature [°C]\", ylabel=\"Pressure [bara]\")\n", + " axis.legend(fontsize=8, ncols=2)\n", + "figure.suptitle(\"Dholabhai (1993): circles = measured; crosses/dashes = NeqSim\")\n", + "show_figure(figure, \"08_dholabhai_pressure_temperature\")\n", + "\n", + "figure, axes = plt.subplots(1, 2, figsize=(12, 5), layout=\"constrained\")\n", + "for family, group in dholabhai.groupby(\"family\", sort=False):\n", + " axes[0].scatter(group[\"pressure_bara\"], group[\"error_K\"], s=24, label=family)\n", + " axes[1].scatter(group[\"salt_total_wt_percent\"], group[\"error_K\"], s=24, label=family)\n", + "for axis in axes:\n", + " axis.axhline(0, color=\"black\", linewidth=1)\n", + " axis.set_ylabel(\"NeqSim minus measured temperature [K]\")\n", + "axes[0].set_xlabel(\"Pressure [bara]\")\n", + "axes[1].set_xlabel(\"Total dissolved salt [wt% of water + salts]\")\n", + "axes[0].legend(fontsize=8, loc=\"best\")\n", + "figure.suptitle(\"Independent residuals: no parameter fit or empirical correction\")\n", + "show_figure(figure, \"09_dholabhai_residuals\")" + ] + }, + { + "cell_type": "markdown", + "id": "1b9c1130", + "metadata": {}, + "source": [ + "### 9.2. How to interpret the comparison\n", + "\n", + "**Numerical convergence and experimental accuracy answer different questions.** The repaired\n", + "KCl solver now returns a conserved saturated boundary. Its error against K10 is still measured\n", + "below. Use the 10.02 wt% recipe and sufficient CO₂ when assessing the paper; the user's\n", + "10.00 wt% / 2.805906013 mol case is a nearby numerical regression, not an exact reproduction.\n", + "\n", + "The paper's RTD accuracy is ±0.06 K and its pressure-gauge accuracy is ±15 kPa. The differential\n", + "pressure instrument (±30 kPa) was a constancy check. These instrument specifications are\n", + "**not** a reported combined or expanded uncertainty of each equilibrium endpoint. Do not use\n", + "±0.06 K alone as a pass/fail accuracy threshold: pressure, salinity, endpoint search and\n", + "repeatability also matter. For scale, the paper's empirical K10 regression (Table V) is\n", + "\n", + "$$\\ln(P/\\mathrm{MPa})=A/(T/\\mathrm{K})+B,\\qquad A=-9562.36,\\quad B=35.64$$\n", + "\n", + "Differentiation gives $dT/dP=-T^2/(AP)$, with $P$ in MPa and $T$ in K. At its 1.130 MPa,\n", + "269.02 K endpoint, ±0.015 MPa corresponds to approximately ±0.10 K temperature sensitivity.\n", + "This is an orientation calculation, not an uncertainty budget. Table V's K10 regression\n", + "standard error, 54.18 kPa, describes the pressure fit scatter and is not instrument uncertainty.\n", + "The paper's solid curves are empirical regressions; dashed curves are its thermodynamic\n", + "predictions. Neither curve is a NeqSim prediction. Here only the measured endpoints are\n", + "validation targets; no regression coefficient is fitted to NeqSim.\n", + "\n", + "**Diagnosing discrepancies.** Pure-water residuals test the combined guest-fugacity/hydrate\n", + "baseline. Additional concentration-dependent residuals in saline systems can indicate aqueous\n", + "water-activity or CO₂-solubility parameter limitations; mixture residuals also test interaction\n", + "terms. These are hypotheses, not an identification of a single cause. The hydrate cage model,\n", + "guest EOS, phase selection, water activity and salinity basis all affect the root. Equal salt\n", + "wt% does not mean equal molality or ionic strength, especially for CaCl₂. Keep family metrics\n", + "and high-salinity points visible instead of quoting a single pooled accuracy figure.\n", + "\n", + "**What the saved results show.** KCl residuals grow strongly between K3/K5, K10 and K15.\n", + "The 14.97 wt% recipe is substantially less accurate than the 3–5 wt% recipes. Positive\n", + "temperature errors mean the predicted salt inhibition is too weak relative to the measured\n", + "boundary. The discrepancy also occurs at above-zero experimental temperatures, so an omitted\n", + "ice check cannot by itself explain the full KCl pattern. High-concentration CaCl₂ also loses\n", + "accuracy. For mixed NaCl–KCl, positive Na7K10 and negative Na15K5 biases partly cancel in\n", + "the family signed mean; the per-recipe table prevents that cancellation from hiding the errors.\n", + "The pure-water baseline error is much smaller than the largest concentrated-KCl discrepancy.\n", + "These observations motivate ion-specific thermodynamic investigation, without proving its cause.\n", + "\n", + "The dedicated follow-up is [NeqSim #4234](https://github.com/equinor/neqsim/issues/4234),\n", + "coordinated with #3144. This comparison preserves the existing model and exposes its residuals;\n", + "it does not apply the synthetic mud correction to experimental data.\n", + "\n", + "**Scope.** The earlier Burgass NaCl benchmark remains separate because it covers different\n", + "compositions and pressures. Good agreement there cannot establish KCl or mixed-salt accuracy\n", + "here. The 1993 data broaden experimental evidence for dissolved salts; they do not qualify\n", + "MEG, reactive buffered mud, solids/polymer effects, complete drilling fluids, or hydrate kinetics." + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "id": "a1957b09", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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CaseTemperature [°C]
0Paper K10: 10.02 wt% KCl-4.13
1NeqSim: 10.02 wt%, 10 mol CO2-2.54651
2NeqSim: 10.00 wt%, 10 mol CO2-2.54569
3NeqSim: 10.02 wt%, 2.805906013 mol CO2-2.54649
\n", + "
" + ], + "text/plain": [ + " Case Temperature [°C]\n", + "0 Paper K10: 10.02 wt% KCl -4.13\n", + "1 NeqSim: 10.02 wt%, 10 mol CO2 -2.54651\n", + "2 NeqSim: 10.00 wt%, 10 mol CO2 -2.54569\n", + "3 NeqSim: 10.02 wt%, 2.805906013 mol CO2 -2.54649" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/markdown": [ + "At **11.30 bara**, measured K10 is **-4.130 °C**, while the matched recipe predicts **-2.547 °C** (error **+1.583 K**). Changing 10.02 to 10.00 wt% shifts the prediction by **+0.0008 K**. The smaller saturated inventory shifts it by **+0.0000 K**. The pressure-instrument sensitivity scale is **0.100 K**. These controls distinguish composition and inventory effects from model discrepancy." + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/markdown": [ + "The largest family RMSE in this run is **KCl**, **2.685 K**, over **21/21** measured points. The table above is the accuracy evidence; numerical acceptance alone is insufficient." + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "k10_low = dholabhai.loc[\n", + " (dholabhai[\"solution\"] == \"K10\") & (dholabhai[\"pressure_MPa\"] == 1.130)\n", + "].iloc[0]\n", + "k10_nominal, _ = hydrate_point(11.3, {\"KCl\": 10.0})\n", + "k10_inventory, _ = hydrate_point(11.3, {\"KCl\": 10.02}, gas_amounts={\"CO2\": 2.805906013})\n", + "assert k10_nominal[\"accepted\"] and k10_inventory[\"accepted\"]\n", + "assert k10_inventory[\"saturated_co2_boundary\"]\n", + "concentration_shift_K = k10_nominal[\"hydrate_temperature_c\"] - k10_low[\"predicted_c\"]\n", + "pressure_sensitivity_K = -(269.02 ** 2) / (-9562.36 * 1.130) * 0.015\n", + "display(pd.DataFrame([\n", + " {\"Case\": \"Paper K10: 10.02 wt% KCl\", \"Temperature [°C]\": k10_low[\"measured_c\"]},\n", + " {\"Case\": \"NeqSim: 10.02 wt%, 10 mol CO2\", \"Temperature [°C]\": k10_low[\"predicted_c\"]},\n", + " {\"Case\": \"NeqSim: 10.00 wt%, 10 mol CO2\",\n", + " \"Temperature [°C]\": k10_nominal[\"hydrate_temperature_c\"]},\n", + " {\"Case\": \"NeqSim: 10.02 wt%, 2.805906013 mol CO2\",\n", + " \"Temperature [°C]\": k10_inventory[\"hydrate_temperature_c\"]},\n", + "]).round(5))\n", + "display(Markdown(\n", + " f\"At **11.30 bara**, measured K10 is **{k10_low['measured_c']:.3f} °C**, \"\n", + " f\"while the matched recipe predicts **{k10_low['predicted_c']:.3f} °C** \"\n", + " f\"(error **{k10_low['error_K']:+.3f} K**). Changing 10.02 to 10.00 wt% shifts \"\n", + " f\"the prediction by **{concentration_shift_K:+.4f} K**. \"\n", + " f\"The smaller saturated inventory shifts it by \"\n", + " f\"**{k10_inventory['hydrate_temperature_c'] - k10_low['predicted_c']:+.4f} K**. \"\n", + " f\"The pressure-instrument sensitivity scale is **{pressure_sensitivity_K:.3f} K**. \"\n", + " \"These controls distinguish composition and inventory effects from model discrepancy.\"\n", + "))\n", + "worst_family = dholabhai_metrics.loc[dholabhai_metrics[\"RMSE [K]\"].idxmax()]\n", + "display(Markdown(\n", + " f\"The largest family RMSE in this run is **{worst_family['Family']}**, \"\n", + " f\"**{worst_family['RMSE [K]']:.3f} K**, over \"\n", + " f\"**{int(worst_family['Compared'])}/{int(worst_family['Measured'])}** measured points. \"\n", + " \"The table above is the accuracy evidence; numerical acceptance alone is insufficient.\"\n", + "))" + ] + }, { "cell_type": "markdown", "id": "98a3aba6", @@ -2891,7 +5496,7 @@ }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 18, "id": "dd5c4ca4", "metadata": {}, "outputs": [ @@ -3337,7 +5942,7 @@ }, { "cell_type": "code", - "execution_count": 16, + "execution_count": 19, "id": "2d226391", "metadata": {}, "outputs": [ @@ -3526,7 +6131,7 @@ }, { "cell_type": "code", - "execution_count": 17, + "execution_count": 20, "id": "ccaa8c32", "metadata": {}, "outputs": [ @@ -3584,7 +6189,7 @@ }, { "cell_type": "code", - "execution_count": 18, + "execution_count": 21, "id": "9c3cb33b", "metadata": {}, "outputs": [ @@ -3788,7 +6393,7 @@ }, { "cell_type": "code", - "execution_count": 19, + "execution_count": 22, "id": "03ce6aea", "metadata": {}, "outputs": [ @@ -3938,7 +6543,7 @@ }, { "cell_type": "code", - "execution_count": 20, + "execution_count": 23, "id": "e631c28d", "metadata": {}, "outputs": [ @@ -3946,7 +6551,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "Passed 19 numerical/workflow checks; 85 accepted runs.\n", + "Passed 22 numerical/workflow checks; 197 accepted runs.\n", "Maximum component error: 5.379e-14\n", "Maximum aqueous charge error: 5.096e-12\n", "Maximum hydrate residual: 9.783e-07\n" @@ -4032,96 +6637,111 @@ " \n", " \n", " 0\n", - " All 36 principal curve attempts recorded\n", + " All 110 supported Dholabhai points retained\n", " True\n", " \n", " \n", " 1\n", - " 20, 50 and 100 bara controls accepted for every recipe\n", + " All Dholabhai states numerically accepted and vapor-comparable\n", " True\n", " \n", " \n", " 2\n", - " Accepted principal boundaries increase with pressure\n", + " Dholabhai errors finite for every comparable point\n", " True\n", " \n", " \n", " 3\n", - " Rejected points excluded from principal temperature table\n", + " All 36 principal curve attempts recorded\n", " True\n", " \n", " \n", " 4\n", - " NaCl concentration depresses each curve\n", + " 20, 50 and 100 bara controls accepted for every recipe\n", " True\n", " \n", " \n", " 5\n", - " MEG depresses both pressure cases\n", + " Accepted principal boundaries increase with pressure\n", " True\n", " \n", " \n", " 6\n", - " Water activities finite and in (0,1]\n", + " Rejected points excluded from principal temperature table\n", " True\n", " \n", " \n", " 7\n", - " Component inventory error below 1e-8\n", + " NaCl concentration depresses each curve\n", " True\n", " \n", " \n", " 8\n", - " Aqueous charge error below 1e-8\n", + " MEG depresses both pressure cases\n", " True\n", " \n", " \n", " 9\n", - " Ions confined to aqueous phase\n", + " Water activities finite and in (0,1]\n", " True\n", " \n", " \n", " 10\n", - " Reactive carbon error below 1e-6 mol\n", + " Component inventory error below 1e-8\n", " True\n", " \n", " \n", " 11\n", - " Starting-temperature spread below 0.002 K\n", + " Aqueous charge error below 1e-8\n", " True\n", " \n", " \n", " 12\n", - " All ten published points calculated\n", + " Ions confined to aqueous phase\n", " True\n", " \n", " \n", " 13\n", - " No pressure-level leakage in fitting\n", + " Reactive carbon error below 1e-6 mol\n", " True\n", " \n", " \n", " 14\n", - " High-pressure control now conserved and saturated\n", + " Starting-temperature spread below 0.002 K\n", " True\n", " \n", " \n", " 15\n", - " NaCl-CaCl2 control now conserves original feed\n", + " All ten published points calculated\n", " True\n", " \n", " \n", " 16\n", - " Reported KCl case converged and saturated\n", + " No pressure-level leakage in fitting\n", " True\n", " \n", " \n", " 17\n", - " KCl saturated inventory spread below 0.005 K\n", + " High-pressure control now conserved and saturated\n", " True\n", " \n", " \n", " 18\n", + " NaCl-CaCl2 control now conserves original feed\n", + " True\n", + " \n", + " \n", + " 19\n", + " Reported KCl case converged and saturated\n", + " True\n", + " \n", + " \n", + " 20\n", + " KCl saturated inventory spread below 0.005 K\n", + " True\n", + " \n", + " \n", + " 21\n", " Accepted non-reactive original feed conserved\n", " True\n", " \n", @@ -4130,26 +6750,29 @@ "" ], "text/plain": [ - " Check Passed\n", - "0 All 36 principal curve attempts recorded True\n", - "1 20, 50 and 100 bara controls accepted for every recipe True\n", - "2 Accepted principal boundaries increase with pressure True\n", - "3 Rejected points excluded from principal temperature table True\n", - "4 NaCl concentration depresses each curve True\n", - "5 MEG depresses both pressure cases True\n", - "6 Water activities finite and in (0,1] True\n", - "7 Component inventory error below 1e-8 True\n", - "8 Aqueous charge error below 1e-8 True\n", - "9 Ions confined to aqueous phase True\n", - "10 Reactive carbon error below 1e-6 mol True\n", - "11 Starting-temperature spread below 0.002 K True\n", - "12 All ten published points calculated True\n", - "13 No pressure-level leakage in fitting True\n", - "14 High-pressure control now conserved and saturated True\n", - "15 NaCl-CaCl2 control now conserves original feed True\n", - "16 Reported KCl case converged and saturated True\n", - "17 KCl saturated inventory spread below 0.005 K True\n", - "18 Accepted non-reactive original feed conserved True" + " Check Passed\n", + "0 All 110 supported Dholabhai points retained True\n", + "1 All Dholabhai states numerically accepted and vapor-comparable True\n", + "2 Dholabhai errors finite for every comparable point True\n", + "3 All 36 principal curve attempts recorded True\n", + "4 20, 50 and 100 bara controls accepted for every recipe True\n", + "5 Accepted principal boundaries increase with pressure True\n", + "6 Rejected points excluded from principal temperature table True\n", + "7 NaCl concentration depresses each curve True\n", + "8 MEG depresses both pressure cases True\n", + "9 Water activities finite and in (0,1] True\n", + "10 Component inventory error below 1e-8 True\n", + "11 Aqueous charge error below 1e-8 True\n", + "12 Ions confined to aqueous phase True\n", + "13 Reactive carbon error below 1e-6 mol True\n", + "14 Starting-temperature spread below 0.002 K True\n", + "15 All ten published points calculated True\n", + "16 No pressure-level leakage in fitting True\n", + "17 High-pressure control now conserved and saturated True\n", + "18 NaCl-CaCl2 control now conserves original feed True\n", + "19 Reported KCl case converged and saturated True\n", + "20 KCl saturated inventory spread below 0.005 K True\n", + "21 Accepted non-reactive original feed conserved True" ] }, "metadata": {}, @@ -4172,6 +6795,13 @@ " - seed_table[\"Calculated boundary [°C]\"].min())\n", "accepted_runs = pd.DataFrame([row for row in all_runs if row[\"accepted\"]])\n", "checks = {\n", + " \"All 110 supported Dholabhai points retained\": len(dholabhai) == 110,\n", + " \"All Dholabhai states numerically accepted and vapor-comparable\": bool(\n", + " dholabhai[\"comparable\"].all()\n", + " ),\n", + " \"Dholabhai errors finite for every comparable point\": bool(\n", + " np.isfinite(dholabhai.loc[dholabhai[\"comparable\"], \"error_K\"]).all()\n", + " ),\n", " \"All 36 principal curve attempts recorded\": len(curves) == 36,\n", " \"20, 50 and 100 bara controls accepted for every recipe\": bool(\n", " curves.loc[curves[\"pressure_bara\"].isin([20.0, 50.0, 100.0]), \"accepted\"].all()\n", @@ -4273,7 +6903,7 @@ }, { "cell_type": "code", - "execution_count": 21, + "execution_count": 24, "id": "28529e1b", "metadata": {}, "outputs": [ @@ -4283,7 +6913,8 @@ "text": [ "At 50 bara: fresh water 9.954 °C; 5 wt% NaCl 7.341 °C.\n", "Independent NaCl benchmark MAE: 0.143 K across ten points.\n", - "Mud correction: SYNTHETIC demonstration; replace with laboratory evidence.\n" + "Mud correction: SYNTHETIC demonstration; replace with laboratory evidence.\n", + "Dholabhai K10 at 11.3 bara: model minus experiment +1.583 K.\n" ] }, { @@ -4349,86 +6980,111 @@ " \n", " \n", " 7\n", - " all_calculation_diagnostics.csv\n", - " 22751\n", + " 08_dholabhai_pressure_temperature.png\n", + " 332029\n", " \n", " \n", " 8\n", - " brine_curves.csv\n", - " 10811\n", + " 09_dholabhai_residuals.png\n", + " 90993\n", " \n", " \n", " 9\n", + " all_calculation_diagnostics.csv\n", + " 54685\n", + " \n", + " \n", + " 10\n", + " brine_curves.csv\n", + " 10807\n", + " \n", + " \n", + " 11\n", " calcium_component_balance_control.csv\n", " 351\n", " \n", " \n", - " 10\n", + " 12\n", " correlation_coefficients.csv\n", " 179\n", " \n", " \n", - " 11\n", + " 13\n", " correlation_data_and_predictions.csv\n", " 8439\n", " \n", " \n", - " 12\n", + " 14\n", + " dholabhai_1993_comparison.csv\n", + " 22352\n", + " \n", + " \n", + " 15\n", + " dholabhai_1993_family_metrics.csv\n", + " 617\n", + " \n", + " \n", + " 16\n", + " dholabhai_1993_recipe_metrics.csv\n", + " 3034\n", + " \n", + " \n", + " 17\n", " finite_inventory_screen.csv\n", " 192\n", " \n", " \n", - " 13\n", + " 18\n", " guest_composition_screen.csv\n", " 439\n", " \n", " \n", - " 14\n", + " 19\n", " illustrative_temperature_margin.csv\n", " 689\n", " \n", " \n", - " 15\n", + " 20\n", " kcl_pressure_inventory_regression.csv\n", - " 1336\n", + " 1337\n", " \n", " \n", - " 16\n", + " 21\n", " laboratory_input_template.csv\n", " 163\n", " \n", " \n", - " 17\n", + " 22\n", " meg_screen.csv\n", " 583\n", " \n", " \n", - " 18\n", + " 23\n", " provenance.json\n", - " 1083\n", + " 3150\n", " \n", " \n", - " 19\n", + " 24\n", " published_nacl_benchmark.csv\n", " 889\n", " \n", " \n", - " 20\n", + " 25\n", " reactive_species.csv\n", " 213\n", " \n", " \n", - " 21\n", + " 26\n", " synthetic_lab_data.csv\n", " 5413\n", " \n", " \n", - " 22\n", + " 27\n", " validation_checks.csv\n", - " 912\n", + " 1085\n", " \n", " \n", - " 23\n", + " 28\n", " water_activity.csv\n", " 345\n", " \n", @@ -4445,23 +7101,28 @@ "4 05_published_benchmark.png 124353\n", "5 06_synthetic_fit_validation.png 91254\n", "6 07_temperature_margin.png 100277\n", - "7 all_calculation_diagnostics.csv 22751\n", - "8 brine_curves.csv 10811\n", - "9 calcium_component_balance_control.csv 351\n", - "10 correlation_coefficients.csv 179\n", - "11 correlation_data_and_predictions.csv 8439\n", - "12 finite_inventory_screen.csv 192\n", - "13 guest_composition_screen.csv 439\n", - "14 illustrative_temperature_margin.csv 689\n", - "15 kcl_pressure_inventory_regression.csv 1336\n", - "16 laboratory_input_template.csv 163\n", - "17 meg_screen.csv 583\n", - "18 provenance.json 1083\n", - "19 published_nacl_benchmark.csv 889\n", - "20 reactive_species.csv 213\n", - "21 synthetic_lab_data.csv 5413\n", - "22 validation_checks.csv 912\n", - "23 water_activity.csv 345" + "7 08_dholabhai_pressure_temperature.png 332029\n", + "8 09_dholabhai_residuals.png 90993\n", + "9 all_calculation_diagnostics.csv 54685\n", + "10 brine_curves.csv 10807\n", + "11 calcium_component_balance_control.csv 351\n", + "12 correlation_coefficients.csv 179\n", + "13 correlation_data_and_predictions.csv 8439\n", + "14 dholabhai_1993_comparison.csv 22352\n", + "15 dholabhai_1993_family_metrics.csv 617\n", + "16 dholabhai_1993_recipe_metrics.csv 3034\n", + "17 finite_inventory_screen.csv 192\n", + "18 guest_composition_screen.csv 439\n", + "19 illustrative_temperature_margin.csv 689\n", + "20 kcl_pressure_inventory_regression.csv 1337\n", + "21 laboratory_input_template.csv 163\n", + "22 meg_screen.csv 583\n", + "23 provenance.json 3150\n", + "24 published_nacl_benchmark.csv 889\n", + "25 reactive_species.csv 213\n", + "26 synthetic_lab_data.csv 5413\n", + "27 validation_checks.csv 1085\n", + "28 water_activity.csv 345" ] }, "metadata": {}, @@ -4470,6 +7131,9 @@ ], "source": [ "export_tables = {\n", + " \"dholabhai_1993_comparison.csv\": dholabhai,\n", + " \"dholabhai_1993_family_metrics.csv\": dholabhai_metrics,\n", + " \"dholabhai_1993_recipe_metrics.csv\": dholabhai_recipe_metrics,\n", " \"brine_curves.csv\": curves,\n", " \"kcl_pressure_inventory_regression.csv\": kcl_table,\n", " \"water_activity.csv\": activity_table,\n", @@ -4495,6 +7159,15 @@ " \"doi\": \"10.2516/stet/2023005\", \"table\": 4, \"license\": \"CC BY 4.0\",\n", " \"points\": len(published), \"MAE_K\": benchmark_mae_K, \"RMSE_K\": benchmark_rmse_K,\n", " },\n", + " \"dholabhai_benchmark\": {\n", + " \"doi\": \"10.1021/je00012a045\", \"tables\": [\"I\", \"III\", \"IV\"],\n", + " \"source\": \"User-supplied paper; manually transcribed numerical endpoints\",\n", + " \"points\": len(dholabhai), \"compared\": int(dholabhai[\"comparable\"].sum()),\n", + " \"excluded\": \"Five synthetic seawater points: recipe outside the three-salt builder\",\n", + " \"family_metrics\": dholabhai_metrics.to_dict(orient=\"records\"),\n", + " \"parameters_fitted\": False,\n", + " \"accuracy_follow_up\": \"https://github.com/equinor/neqsim/issues/4234\",\n", + " },\n", " \"synthetic_correlation\": bool(using_synthetic_data),\n", " \"numerical_checks_passed\": len(checks),\n", " \"known_phase_state_issue\": \"https://github.com/equinor/neqsim/issues/3584\",\n", @@ -4508,7 +7181,8 @@ "print(f\"At 50 bara: fresh water {curve_cache[('Fresh water', 50.0)]:.3f} °C; \"\n", " f\"5 wt% NaCl {curve_cache[('NaCl 5%', 50.0)]:.3f} °C.\")\n", "print(f\"Independent NaCl benchmark MAE: {benchmark_mae_K:.3f} K across ten points.\")\n", - "print(\"Mud correction: SYNTHETIC demonstration; replace with laboratory evidence.\")" + "print(\"Mud correction: SYNTHETIC demonstration; replace with laboratory evidence.\")\n", + "print(f\"Dholabhai K10 at 11.3 bara: model minus experiment {k10_low['error_K']:+.3f} K.\")" ] }, { @@ -4528,6 +7202,12 @@ "\n", "**Primary experimental literature**\n", "\n", + "- Dholabhai, P. D., Kalogerakis, N. and Bishnoi, P. R. (1993).\n", + " *Equilibrium Conditions for Carbon Dioxide Hydrate Formation in Aqueous Electrolyte Solutions*.\n", + " J. Chem. Eng. Data 38, 650–654. [doi:10.1021/je00012a045](https://doi.org/10.1021/je00012a045).\n", + " Section 9 uses Table I recipes and all non-seawater endpoints in Tables III–IV.\n", + " The supplied ACS paper is the transcription source; original figures/PDF are not redistributed.\n", + "\n", "- Burgass, R., Chapoy, A., Askvik, K. M., Neeraas, B. O. and Li, X. (2023).\n", " *CO₂ hydrate formation in NaCl systems and undersaturated aqueous solutions*.\n", " Science and Technology for Energy Transition 78, 8.\n", @@ -4544,6 +7224,10 @@ "\n", "**Tracked improvements**\n", "\n", + "- [#4234: KCl and mixed-brine hydrate accuracy against Dholabhai (1993)](https://github.com/equinor/neqsim/issues/4234):\n", + " concentration-dependent KCl discrepancy despite convergence and conserved phase inventories;\n", + " water-activity, solubility and ion-specific parameter investigation under #3144.\n", + "\n", "- [#3584: CO₂–brine hydrate phase-state selection](https://github.com/equinor/neqsim/issues/3584):\n", " high-salinity/high-pressure and finite-CO₂ inventory qualification; structured residual/phase diagnostics.\n", "- [#3585: NaCl–CaCl₂ component-inventory imbalance](https://github.com/equinor/neqsim/issues/3585):\n", @@ -4564,7 +7248,8 @@ "criteria have been invented. The disclosed synthetic correlation is an executable statistical example.\n", "\n", "The KCl regression adds numerical evidence for the reported low-pressure case.\n", - "It adds no KCl experimental data or fitted parameters. The repaired September defects\n", + "The separate Dholabhai comparison adds KCl and mixed-salt experimental evidence,\n", + "with visible model discrepancies and no fitted parameters. The repaired September defects\n", "remain linked as implementation history; their original rejected results are replaced\n", "by fresh execution of the same inputs.\n" ] diff --git a/notebooks/maintenance_ledger/co2_hydrate_drilling_fluids_20260908.json b/notebooks/maintenance_ledger/co2_hydrate_drilling_fluids_20260908.json index 2a1c095f..3e2d8d27 100644 --- a/notebooks/maintenance_ledger/co2_hydrate_drilling_fluids_20260908.json +++ b/notebooks/maintenance_ledger/co2_hydrate_drilling_fluids_20260908.json @@ -1,12 +1,12 @@ { "schema_version": 1, "shard": "co2-hydrate-drilling-fluids-20260908", - "updated_at": "2026-10-05T15:03:41.708994+00:00", + "updated_at": "2026-10-05T21:20:53.534087+00:00", "notebooks": [ { "path": "notebooks/flowassurance/co2_hydrate_brines_and_drilling_fluids.ipynb", "verified_date": "2026-10-05", - "verified_at_utc": "2026-10-05T15:03:41.708994+00:00", + "verified_at_utc": "2026-10-05T21:20:53.534087+00:00", "neqsim_version": "3.20.0 Python bridge; source-built Java 3.23.0 runtime", "neqsim_java_commit": "f59810115c07d9a3ef479e55be45a5972963231d", "neqsim_jar_sha256": "e26d9dd82e86d351fa58fe05e04801e2af6aebb17d19081c690736d924536f19", @@ -21,15 +21,15 @@ "scipy": "1.17.0" }, "execution_status": "passed", - "execution_method": "All 21 code cells executed top to bottom in a fresh Python/IPython process and fresh JVM using scripts/execute_notebook_inprocess.py. Verified clean source-built JAR reused via NEQSIM_SOURCE_ROOT and NEQSIM_SOURCE_JAR; class origin and SHA-256 asserted. Every result-bearing output and all seven figures retained. Hosted Colab installation and remote source checkout were not exercised locally.", - "execution_seconds": 198.1, - "code_cells": 21, - "substantive_code_cells": 21, - "markdown_cells": 24, - "git_blob_sha1": "63693bce99487ebb1aab3eb953f6a22a5d11b35f", - "notebook_bytes": 898834, + "execution_method": "All 24 code cells executed in order in a fresh Python/IPython process and JVM. Immutable source checkout and previously source-built JAR were verified against the existing SHA-256 and source files; class origin asserted. Every result, nine plots, and 110 experimental endpoints retained. Hosted Colab install/build was not rerun locally.", + "execution_seconds": 253.4, + "code_cells": 24, + "substantive_code_cells": 24, + "markdown_cells": 26, + "git_blob_sha1": "5ff70f3731d2c6be04496f84b4a5e5ede4375245", + "notebook_bytes": 1435071, "publication": { - "branch": "codex/fix-kcl-hydrate-notebook-20261005", + "branch": "codex/hydrate-dholabhai-comparison-20261005", "mode": "focused draft pull request", "files": [ "notebooks/flowassurance/co2_hydrate_brines_and_drilling_fluids.ipynb", @@ -47,7 +47,8 @@ "10 wt% KCl at 11.3 bara and 2.805906013 mol CO2/kg water", "Pressure/inventory phase classification and saturated-inventory independence", "hydt kelvin return, structure-I overload and fresh-fluid comparison", - "Conservation against the original input inventory and structured solver diagnostics" + "Conservation against the original input inventory and structured solver diagnostics", + "Independent pure-water, single-salt and binary-brine hydrate comparison against 110 Dholabhai (1993) endpoints with numerical diagnostics and family/recipe residuals" ], "independent_validation": { "doi": "10.2516/stet/2023005", @@ -60,12 +61,12 @@ "interpretation": "Limited NaCl benchmark; no KCl calibration or commercial-mud qualification." }, "engineering_validation": { - "named_assertions_passed": 19, + "named_assertions_passed": 22, "assertions_failed": 0, "principal_curve_attempts": 36, "principal_curve_accepted": 36, - "all_hydrate_attempts": 85, - "accepted_hydrate_attempts": 85, + "all_hydrate_attempts": 197, + "accepted_hydrate_attempts": 197, "max_accepted_component_error": 5.379030554308883e-14, "max_accepted_original_feed_error": 5.380506159803984e-14, "max_accepted_charge_error": 5.096317915411774e-12, @@ -86,12 +87,12 @@ } }, "rendered_visual_validation": { - "renderer": "nbconvert 7.17.1 HTML; MathJax 3.2.2 SVG; WeasyPrint 70 PDF and Poppler PNG", - "display_equations_inspected": 7, - "inline_equations_inspected": 19, - "figures_inspected": 7, + "renderer": "nbconvert HTML, MathJax 3.2.2 SVG, WeasyPrint PDF and Poppler PNG", + "display_equations_inspected": 8, + "inline_equations_inspected": 24, + "figures_inspected": 9, "result": "passed", - "notes": "All Markdown and result cells inspected; equations, figures, units, legends and tables checked. Diagnostic column width and scientific number display avoid truncated check labels and residuals rounded to apparent zero." + "notes": "Every Markdown/result cell inspected; all equations, tables, plots and units checked. Catalog text fully rendered and inspected; scientific figures inspected individually." }, "repository_validation": { "checker_unit_tests": "6 passed", @@ -101,7 +102,7 @@ "pre_commit": "No .pre-commit-config.yaml on the inspected Colab base; workflow runs notebook checker.", "ci": "pending" }, - "documentation_impact": "Updates source-pin/restart guidance, KCl pressure/inventory teaching, hydt kelvin and overload explanation, repaired historical defect examples, diagnostics and CSV export. Catalog entry and this ledger updated. No Java API, salt/hydrate parameters or library implementation changed.", + "documentation_impact": "Adds Dholabhai measured recipes, complete supported-point comparison, family/per-recipe metrics, two figures, matched K10 concentration/inventory controls, experimental uncertainty and model-discrepancy discussion, CSV exports and citation. Catalog and this ledger updated. No Java API or model parameters changed.", "issue_handling": [ { "url": "https://github.com/equinor/neqsim/issues/3584", @@ -110,9 +111,13 @@ { "url": "https://github.com/equinor/neqsim/issues/3585", "handling": "Existing inventory repair used; NaCl-CaCl2 feed passes original-feed conservation." + }, + { + "url": "https://github.com/equinor/neqsim/issues/4234", + "handling": "Dedicated empirical accuracy follow-up; no fitting in this comparison." } ], - "improvement_assessment": "Reported hang reproduced on the stale September pin and resolved by existing current source fixes. No distinct new NeqSim library defect reproduced; no duplicate issue filed.", + "improvement_assessment": "KCl model-accuracy limitation documented in equinor/neqsim#4234 under #3144; not a recurrence of the numerical hang. No model fitted to this paper.", "previous_validation": { "source_commit": "76f14ae079a7b1db1888203d20e11a6433774b4c", "validation_date": "2026-09-08", @@ -130,7 +135,375 @@ "principal_curve_attempts": 36, "principal_curve_accepted": 35, "note": "Historical evidence; superseded by clean execution of the updated source pin." - } + }, + "neqsim_java_master_inspected": "17c0beca5a5ca53401fa214c2a542892e5a6a467", + "master_comparison": "No thermo, hydrate flash, electrolyte or database changes from tested pin.", + "dholabhai_validation": { + "doi": "10.1021/je00012a045", + "tables": [ + "I", + "III", + "IV" + ], + "source": "User-supplied paper; manually transcribed numerical endpoints", + "points": 110, + "compared": 110, + "excluded": "Five synthetic seawater points: recipe outside the three-salt builder", + "family_metrics": [ + { + "Family": "Pure water", + "Measured": 4, + "Compared": 4, + "Bias [K]": 0.3639718239515872, + "MAE [K]": 0.3639718239515872, + "RMSE [K]": 0.3830125365504527, + "Max absolute error [K]": 0.5243938347231278 + }, + { + "Family": "NaCl", + "Measured": 25, + "Compared": 25, + "Bias [K]": 0.15801747910150651, + "MAE [K]": 0.2647777588608801, + "RMSE [K]": 0.32486187038181336, + "Max absolute error [K]": 0.7773410951842266 + }, + { + "Family": "KCl", + "Measured": 21, + "Compared": 21, + "Bias [K]": 1.7411253670351812, + "MAE [K]": 1.7411253670351812, + "RMSE [K]": 2.685081832407701, + "Max absolute error [K]": 6.729003869912958 + }, + { + "Family": "CaCl2", + "Measured": 21, + "Compared": 21, + "Bias [K]": 0.4448687376450569, + "MAE [K]": 0.47048312904848627, + "RMSE [K]": 0.7608002512078572, + "Max absolute error [K]": 2.145490223592219 + }, + { + "Family": "NaCl + KCl", + "Measured": 17, + "Compared": 17, + "Bias [K]": 0.05710972524584309, + "MAE [K]": 0.7451141124244901, + "RMSE [K]": 0.9997587971638354, + "Max absolute error [K]": 1.7640223174028051 + }, + { + "Family": "NaCl + CaCl2", + "Measured": 22, + "Compared": 22, + "Bias [K]": -0.01524452654061034, + "MAE [K]": 0.37705945714725947, + "RMSE [K]": 0.5105665176898994, + "Max absolute error [K]": 1.186529079953857 + } + ], + "parameters_fitted": false, + "accuracy_follow_up": "https://github.com/equinor/neqsim/issues/4234", + "recipe_count": 28, + "excluded_seawater_points": 5, + "original_units": { + "temperature": "K", + "pressure": "MPa" + }, + "pressure_basis": "absolute: corrected gauge reading plus atmosphere in the paper", + "salt_basis": "mass percent of water plus all dissolved salts, Table I actual values", + "paper_sha256": "229d7d6a011d2bc63dc2d56ec84af7ab1942511ceacd71f6206f7a62b8014765", + "access_conditions": "User-supplied ACS copyrighted paper; factual numerical transcription. No paper pages, figures or PDF redistributed.", + "recipe_metrics": [ + { + "Solution": "water", + "Compared": 4, + "Bias [K]": 0.3639718239515872, + "MAE [K]": 0.3639718239515872, + "RMSE [K]": 0.3830125365504527, + "Min error [K]": 0.1967875349310475, + "Max error [K]": 0.5243938347231278 + }, + { + "Solution": "Na3-1", + "Compared": 4, + "Bias [K]": 0.3477767342162963, + "MAE [K]": 0.3477767342162963, + "RMSE [K]": 0.3891925871958145, + "Min error [K]": 0.1276623547657323, + "Max error [K]": 0.6060719764695364 + }, + { + "Solution": "Na3-2", + "Compared": 1, + "Bias [K]": 0.3618092085234252, + "MAE [K]": 0.3618092085234252, + "RMSE [K]": 0.3618092085234252, + "Min error [K]": 0.3618092085234252, + "Max error [K]": 0.3618092085234252 + }, + { + "Solution": "Na3-3", + "Compared": 1, + "Bias [K]": -0.044139815524943, + "MAE [K]": 0.044139815524943, + "RMSE [K]": 0.044139815524943, + "Min error [K]": -0.044139815524943, + "Max error [K]": -0.044139815524943 + }, + { + "Solution": "Na5-1", + "Compared": 4, + "Bias [K]": 0.4939312713169244, + "MAE [K]": 0.4939312713169244, + "RMSE [K]": 0.5263035496206743, + "Min error [K]": 0.3117722678024393, + "Max error [K]": 0.7773410951842266 + }, + { + "Solution": "Na5-2", + "Compared": 1, + "Bias [K]": -0.2233135520441465, + "MAE [K]": 0.2233135520441465, + "RMSE [K]": 0.2233135520441465, + "Min error [K]": -0.2233135520441465, + "Max error [K]": -0.2233135520441465 + }, + { + "Solution": "Na10-1", + "Compared": 2, + "Bias [K]": -0.0967227684019746, + "MAE [K]": 0.0967227684019746, + "RMSE [K]": 0.0968029155125083, + "Min error [K]": -0.1006611087097439, + "Max error [K]": -0.0927844280942054 + }, + { + "Solution": "Na10-2", + "Compared": 5, + "Bias [K]": 0.1505309560605951, + "MAE [K]": 0.236233116737128, + "RMSE [K]": 0.2962645837769826, + "Min error [K]": -0.1260039275048825, + "Max error [K]": 0.531083075277536 + }, + { + "Solution": "Na15", + "Compared": 4, + "Bias [K]": 0.0073302246820219, + "MAE [K]": 0.1950904463798792, + "RMSE [K]": 0.2209570313280566, + "Min error [K]": -0.2895708933221499, + "Max error [K]": 0.3075423986202281 + }, + { + "Solution": "Na20", + "Compared": 3, + "Bias [K]": -0.0330936759255564, + "MAE [K]": 0.1561254890958328, + "RMSE [K]": 0.1721427224915065, + "Min error [K]": -0.2272434745776195, + "Max error [K]": 0.1845477197554146 + }, + { + "Solution": "K3", + "Compared": 6, + "Bias [K]": 0.3400518262451442, + "MAE [K]": 0.3400518262451442, + "RMSE [K]": 0.3871564822812567, + "Min error [K]": 0.1077415950883278, + "Max error [K]": 0.6033697674800464 + }, + { + "Solution": "K5", + "Compared": 7, + "Bias [K]": 0.5214696766857401, + "MAE [K]": 0.5214696766857401, + "RMSE [K]": 0.5310665844154743, + "Min error [K]": 0.4244962785168127, + "Max error [K]": 0.6788289152129323 + }, + { + "Solution": "K10", + "Compared": 4, + "Bias [K]": 2.056410731209624, + "MAE [K]": 2.056410731209624, + "RMSE [K]": 2.083688640731458, + "Min error [K]": 1.5834853509147138, + "Max error [K]": 2.4720390600299997 + }, + { + "Solution": "K15", + "Compared": 4, + "Bias [K]": 5.661847772157316, + "MAE [K]": 5.661847772157316, + "RMSE [K]": 5.726306774548871, + "Min error [K]": 4.477513615322721, + "Max error [K]": 6.729003869912958 + }, + { + "Solution": "Ca3", + "Compared": 4, + "Bias [K]": 0.2138087640509809, + "MAE [K]": 0.218556645079758, + "RMSE [K]": 0.2822304836804269, + "Min error [K]": -0.0094957620575542, + "Max error [K]": 0.482801819277995 + }, + { + "Solution": "Ca5", + "Compared": 4, + "Bias [K]": 0.1312393476264759, + "MAE [K]": 0.1685436460759746, + "RMSE [K]": 0.2333741709171692, + "Min error [K]": -0.0746085968989973, + "Max error [K]": 0.435992477865966 + }, + { + "Solution": "Ca10", + "Compared": 5, + "Bias [K]": 0.0689090433379647, + "MAE [K]": 0.1428477436497473, + "RMSE [K]": 0.1889431294106265, + "Min error [K]": -0.0990009000423128, + "Max error [K]": 0.3727507573752859 + }, + { + "Solution": "Ca15", + "Compared": 4, + "Bias [K]": 0.2925894817580285, + "MAE [K]": 0.2925894817580285, + "RMSE [K]": 0.3055930777255068, + "Min error [K]": 0.1459495808307451, + "Max error [K]": 0.3678909782612436 + }, + { + "Solution": "Ca20", + "Compared": 4, + "Bias [K]": 1.6117869750286076, + "MAE [K]": 1.6117869750286076, + "RMSE [K]": 1.6633280810881284, + "Min error [K]": 1.018679175139198, + "Max error [K]": 2.145490223592219 + }, + { + "Solution": "Na3K3", + "Compared": 5, + "Bias [K]": 0.1341771918263134, + "MAE [K]": 0.1665289357648248, + "RMSE [K]": 0.2077153294797957, + "Min error [K]": -0.0772794177613036, + "Max error [K]": 0.3137855993855964 + }, + { + "Solution": "Na5K5", + "Compared": 4, + "Bias [K]": 0.0626582963828639, + "MAE [K]": 0.1172039927521382, + "RMSE [K]": 0.1190740219907959, + "Min error [K]": -0.1090913927385486, + "Max error [K]": 0.1523227454111406 + }, + { + "Solution": "Na7K10", + "Compared": 4, + "Bias [K]": 1.4268531807374956, + "MAE [K]": 1.4268531807374956, + "RMSE [K]": 1.475801649248203, + "Min error [K]": 0.821105651898165, + "Max error [K]": 1.7640223174028051 + }, + { + "Solution": "Na15K5", + "Compared": 4, + "Bias [K]": -1.414516634608418, + "MAE [K]": 1.414516634608418, + "RMSE [K]": 1.4148670679217996, + "Min error [K]": -1.4684805759328017, + "Max error [K]": -1.3915922237843006 + }, + { + "Solution": "Na3Ca3", + "Compared": 5, + "Bias [K]": 0.1375118701681231, + "MAE [K]": 0.1522163646830449, + "RMSE [K]": 0.2042579163404697, + "Min error [K]": -0.0367612362873046, + "Max error [K]": 0.3466357046389134 + }, + { + "Solution": "Na8Ca2", + "Compared": 4, + "Bias [K]": 0.0458206756673149, + "MAE [K]": 0.1267876040098343, + "RMSE [K]": 0.144952123722395, + "Min error [K]": -0.1619338566850388, + "Max error [K]": 0.2114326195965645 + }, + { + "Solution": "Na2Ca8", + "Compared": 4, + "Bias [K]": -0.0565060348203303, + "MAE [K]": 0.1118383603220252, + "RMSE [K]": 0.1190746244802942, + "Min error [K]": -0.1607910711805402, + "Max error [K]": 0.1106646510033897 + }, + { + "Solution": "Na5Ca15", + "Compared": 5, + "Bias [K]": 0.5599524878375064, + "MAE [K]": 0.5599524878375064, + "RMSE [K]": 0.5798214012575342, + "Min error [K]": 0.3682485387117822, + "Max error [K]": 0.8228473050418756 + }, + { + "Solution": "Na15Ca5", + "Compared": 4, + "Bias [K]": -0.9449899843273784, + "MAE [K]": 0.9449899843273784, + "RMSE [K]": 0.9623654985899016, + "Min error [K]": -1.186529079953857, + "Max error [K]": -0.7019803566178666 + } + ], + "k10_at_11_3_bara": { + "solution": "K10", + "family": "KCl", + "table": "III", + "NaCl_wt_percent": 0.0, + "KCl_wt_percent": 10.02, + "CaCl2_wt_percent": 0.0, + "salt_total_wt_percent": 10.02, + "measured_K": 269.02, + "pressure_MPa": 1.13, + "pressure_bara": 11.3, + "measured_c": -4.129999999999996, + "predicted_c": -2.5465146490852817, + "raw_returned_c": -2.5465146490852817, + "comparable": true, + "material_phases": "GAS+AQUEOUS", + "numerically_accepted": true, + "saturated_boundary": true, + "hydrate_residual": -1.5598766722746404e-10, + "original_feed_error": 1.0373514122669443e-16, + "error_K": 1.5834853509147138 + }, + "interpretation": "Reliable numerical boundaries, with concentration-dependent KCl accuracy gap and opposing mixture biases. No fitting or empirical correction. Solid-phase stability and full mud qualification remain outside scope." + }, + "validation_history": [ + { + "verified_at_utc": "2026-10-05T15:03:41.708994+00:00", + "code_cells": 21, + "execution_seconds": 198.1, + "git_blob_sha1": "63693bce99487ebb1aab3eb953f6a22a5d11b35f", + "note": "October KCl hang repair validation, before Dholabhai comparison." + } + ] } ] }