From 1c2b4d2455446a2b357fe1373fcca4bc074f05f5 Mon Sep 17 00:00:00 2001 From: "James L. Makela" Date: Tue, 22 Nov 2016 01:37:51 -0800 Subject: [PATCH] Oil Properties Estimation: Added an addendum section on heavy volatile components - In this section we come to a solution to the problem as it exists. --- .../notebooks/Oil_Properties_Estimation.ipynb | 418 ++++++++++++++++-- 1 file changed, 391 insertions(+), 27 deletions(-) diff --git a/documentation/notebooks/Oil_Properties_Estimation.ipynb b/documentation/notebooks/Oil_Properties_Estimation.ipynb index 0d06469..d53247e 100644 --- a/documentation/notebooks/Oil_Properties_Estimation.ipynb +++ b/documentation/notebooks/Oil_Properties_Estimation.ipynb @@ -144,6 +144,8 @@ "bonny_light = session.query(ImportedRecord).filter(ImportedRecord.oil_name == 'BONNY LIGHT').one()\n", "petro_star = session.query(ImportedRecord).filter(ImportedRecord.oil_name ==\n", " 'FUEL OIL NO.1 (DIESEL/HEATING FUEL), PETRO STAR').one()\n", + "ifo_180 = session.query(ImportedRecord).filter(ImportedRecord.oil_name == 'IFO 180').one()\n", + "boscan = session.query(ImportedRecord).filter(ImportedRecord.oil_name == 'BOSCAN, OIL & GAS').one()\n", "\n", "print ans_mp\n", "print ans_2002\n", @@ -977,7 +979,7 @@ { "data": { "text/plain": [ - "" + "" ] }, "execution_count": 7, @@ -988,7 +990,7 @@ "data": { "image/png": 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1ytI+depUrF27FlevXi021oqiVJlL3Mq1LdU+/LY+0sNx4TjTJoUiNW81gCam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\n/Ho+3PgyB65gAxSTnjaAvHVzQqldRERERA6PMtgBKNpcxOIXPmHBnCI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7gu6cjDrJ2m5r8cvrl3EH37sXPv8cvvsO7r7bSsTnzIECBTLuHEqlkY6UK+Uh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\no0fD4MFw4gQ89ZQzQ3755Rd8qsErB9NnyRu8d/sCyl1RPgeCFREREX9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"text/plain": [ - "" + "" ] }, "metadata": {}, @@ -1182,7 +1184,7 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 9, "metadata": { "collapsed": false }, @@ -1190,10 +1192,10 @@ { "data": { "text/plain": [ - "" + "" ] }, - "execution_count": 10, + "execution_count": 9, "metadata": {}, "output_type": "execute_result" }, @@ -1201,7 +1203,7 @@ "data": { "image/png": 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bs379eoYPH+5T7CIiIiLe7C4uZlF+PksLCrigSROeb96cbnV4Imh1qdylHvFl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\n4w0W3XILZT4fy7Zvx554wuvyREREpJ3TkC7tyordu5np9/P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"text/plain": [ - "" + "" ] }, "metadata": {}, @@ -1287,7 +1289,7 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 10, "metadata": { "collapsed": false }, @@ -1304,10 +1306,10 @@ { "data": { "text/plain": [ - "" + "" ] }, - "execution_count": 11, + "execution_count": 10, "metadata": {}, "output_type": "execute_result" }, @@ -1315,7 +1317,7 @@ "data": { "image/png": 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wc0i+yzfNOUB0TDyThs+n/dYkeNWZOVdzXnzKoIuIiIj4qW1bYeZUZ7a8bBln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\nEl5/fSwzHvlql8+Wt5UZdEmS1Ag6kkE34tIkli6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"text/plain": [ - "" + "" ] }, "metadata": {}, @@ -1418,7 +1420,7 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 11, "metadata": { "collapsed": false }, @@ -1571,7 +1573,7 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 12, "metadata": { "collapsed": true }, @@ -1639,7 +1641,7 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 13, "metadata": { "collapsed": false }, @@ -1843,7 +1845,7 @@ }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 14, "metadata": { "collapsed": false }, @@ -1947,7 +1949,7 @@ }, { "cell_type": "code", - "execution_count": 16, + "execution_count": 15, "metadata": { "collapsed": false }, @@ -2092,7 +2094,7 @@ }, { "cell_type": "code", - "execution_count": 17, + "execution_count": 16, "metadata": { "collapsed": false }, @@ -2224,7 +2226,7 @@ }, { "cell_type": "code", - "execution_count": 18, + "execution_count": 17, "metadata": { "collapsed": false }, @@ -2321,7 +2323,7 @@ }, { "cell_type": "code", - "execution_count": 20, + "execution_count": 18, "metadata": { "collapsed": false }, @@ -2329,10 +2331,10 @@ { "data": { "text/plain": [ - "" + "" ] }, - "execution_count": 20, + "execution_count": 18, "metadata": {}, "output_type": "execute_result" }, @@ -2340,7 +2342,7 @@ "data": { "image/png": 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RERGRHKcCPRh0kmieG8MYNrEpb08aVS9lcCl3wab8BZdyJxJcKtDTrLgYioq8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\nFl2DJKmBRMQJwLXAFpn5z6LrkaRm4xl0SdLqDgJmd9ScR8S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"text/plain": [ - "" + "" ] }, "metadata": {}, @@ -2465,7 +2467,7 @@ }, { "cell_type": "code", - "execution_count": 21, + "execution_count": 19, "metadata": { "collapsed": false }, @@ -2676,7 +2678,7 @@ }, { "cell_type": "code", - "execution_count": 22, + "execution_count": 20, "metadata": { "collapsed": false }, @@ -2821,7 +2823,7 @@ }, { "cell_type": "code", - "execution_count": 23, + "execution_count": 21, "metadata": { "collapsed": false }, @@ -3010,7 +3012,7 @@ }, { "cell_type": "code", - "execution_count": 24, + "execution_count": 22, "metadata": { "collapsed": false }, @@ -3111,6 +3113,368 @@ "Otherwise, $f_{sulf} = 0$" ] }, + { + "cell_type": "markdown", + "metadata": { + "collapsed": true + }, + "source": [ + "## Addendum 1" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "collapsed": true + }, + "source": [ + "###
Addressing Heavy Volatile components
" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "In practice, we have seen that certain oil records in our database result in heavy estimated saturate and aromatic components. That is to say we have saturates and aromatic components that have a higher density than our resins and asphaltenes. Intuitively this does not seem right, and we can identify some things we are doing in our estimations that would cause this:" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "- We have set a hard-coded density of $1100 \\, kg/m^3$ in the case of resins and asphaltenes, which is why we are getting the rejections. Maybe this value should be higher.\n", + "- We estimate our component densities based on a Watson characterization factor combined with a component boiling point. And as the boiling temperature rises, our component density calculation will eventually rise to a value higher than $1100 \\, kg/m^3$. Maybe we should consider that the volatile component boiling points will not exceed a certain threshold." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "And after discussing this at great length, we have decided that:" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "- $1100 \\, kg/m^3$ is probably a reasonable value for our inert components.\n", + "- We should set a cap density for the volatile components so they do not exceed that of the involitile components." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "So how might we do this? Well the most reasonable way to do this would probably be to alter our distillation temperature curve. Right now it is a linear function that extends from a fraction of $0$ to a fraction of $(1 - f_{res} - f_{asph})$. We could put a threshold limit that would level the curve at a certain upper temperature." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "To do this, we will make use of a generalized logistic function or Richard's curve. This should allow us to make our distillation function flexible and not add to the software complexity of our estimations." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "$$\n", + "\\begin{align}\n", + "Y(x, M) &= \\text{generalized logistic function} \\cr\n", + "&= A + \\frac{K - A}{(C + Qe^{-B(x - M)})^{1/\\nu}} \\cr\n", + "&= 0 + \\frac{1 - 0}{(1 + e^{-20(x - M)})^{1/\\nu}} \\cr\n", + "&= \\frac{1}{(1 + e^{-20(x - M)})^{1/\\nu}} \\cr\n", + "\\cr\n", + "\\zeta &= \\text{smoothing factor for when we cross the M boundary} \\cr\n", + "&\\approx 0.03 \\cr\n", + "\\cr\n", + "x_s &= \\text{smooth-clipped x value} \\cr\n", + "&= x - x \\cdot Y(x, M) + M \\cdot Y(x, M) \\cr\n", + "&= x - \\frac{x}{(1 + e^{-20(x - M)})^{1/(1 + \\zeta)}} + \\frac{M}{(1 + e^{-20(x - M)})^{1/(1 - \\zeta)}} \\cr\n", + "\\end{align}\n", + "$$" + ] + }, + { + "cell_type": "code", + "execution_count": 23, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "def smooth_clip(x, M, zeta=0.03):\n", + " '''\n", + " The parameters nu, and B have been tweaked a bit to show a smooth\n", + " Transition as we cross the M boundary.\n", + " '''\n", + " return (x -\n", + " (x / (1.0 + np.e ** (-15 * (x - M))) ** (1.0 / (1 + zeta)) ) +\n", + " (M / (1.0 + np.e ** (-15 * (x - M))) ** (1.0 / (1 - zeta)) ))\n", + "\n", + "def linear_curve(x, a, b, M, zeta=0.09):\n", + " x_c = smooth_clip(x, M, zeta)\n", + "\n", + " return (a * x_c + b)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "image/png": 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cwsy+L+lzkgadc4vGeQ05RIKRQ9S3kRFp82Zv8O3v93KHjg62OwAAkqmUHCKs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\nYAAAAKTO/wcuq81352v1MwAAAABJRU5ErkJggg==\n", + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plt.figure(figsize=(12, 6)) # make the drawing area a bit bigger\n", + "\n", + "ax1 = plt.subplot(111)\n", + "\n", + "x = np.linspace(-1.0, 5.0, 100)\n", + "\n", + "# let's plot the function (x + 3), limited at 3\n", + "# this should give us a zero crossing of y=3.0,\n", + "# and an upper limit of y=6.0\n", + "y = linear_curve(x, 1.0, 3.0, 3.0, 0.09)\n", + "\n", + "ax1.plot(x, x, linewidth=1)\n", + "ax1.plot(x, y, linewidth=1)\n", + "\n", + "plt.axhline(0)\n", + "plt.axvline(0)\n", + "\n", + "show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Ok, this is a pretty reasonable, but general, example of what we would like to do. Let's see what it looks like using distillation cut data. First, let's estimate what our cutoff should be for $T_i$. From Section 19 (Component Density), our density formulas are:" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "$$\n", + "\\begin{align}\n", + "\\rho try_{arom,i} &= 1000 \\cdot {\\root 3 \\of { 1.8 \\cdot T_{arom,i}} \\over K_{arom,w} } \\cr\n", + "\\frac{\\rho try_{arom,i} \\cdot K_{arom,w}}{1000} &= \\root 3 \\of { 1.8 \\cdot T_{arom,i}} \\cr\n", + "\\left( \\frac{\\rho try_{arom,i} \\cdot K_{arom,w}}{1000} \\right)^3 &= 1.8 \\cdot T_{arom,i} \\cr\n", + "\\left( \\frac{\\rho try_{arom,i} \\cdot K_{arom,w}}{1000} \\right)^3 \\cdot \\frac{1}{1.8} &= T_{arom,i} \\cr\n", + "\\left( \\frac{1100 \\cdot 10}{1000} \\right)^3 \\cdot \\frac{1}{1.8} &= T_{arom,i} \\cr\n", + "\\frac{1331}{1.8} &= T_{arom,i} \\cr\n", + "739.444 &= T_{arom,i} \\cr\n", + "\\cr\n", + "\\rho try_{sat,i} &= 1000 \\cdot {\\root 3 \\of { 1.8 \\cdot T_{sat,i}} \\over K_{sat,w} } \\cr\n", + "\\left( \\frac{\\rho try_{sat,i} \\cdot K_{sat,w}}{1000} \\right)^3 \\cdot \\frac{1}{1.8} &= T_{sat,i} \\cr\n", + "\\left( \\frac{1100 \\cdot 12}{1000} \\right)^3 \\cdot \\frac{1}{1.8} &= T_{sat,i} \\cr\n", + "\\frac{2299.968}{1.8} &= T_{sat,i} \\cr\n", + "1277.76 &= T_{sat,i} \\cr\n", + "\\end{align}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Based on the above, it is likely that our aromatic components will become heavier than the inert components at around $739^\\circ K$.
\n", + "Our saturate components will eventually appear too heavy, but at such a great temperature it is unlikely to happen." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "So let's choose 739 as our temperature cutoff." + ] + }, + { + "cell_type": "code", + "execution_count": 25, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "def linear_curve(x, a, b):\n", + " return (a * x + b)\n", + "\n", + "\n", + "def inverse_linear_old(y, a, b):\n", + " return (y - b) / a\n", + "\n", + "\n", + "def inverse_linear_curve(y, a, b, M, zeta=0.12):\n", + " y_c = smooth_clip(y, M, zeta)\n", + "\n", + " return (y_c - b) / a\n", + "\n", + "\n", + "def oil_normalized_cut_values(imported_rec, num_cuts=10):\n", + " f_res, f_asph = oil_inert_fractions(imported_rec)\n", + " \n", + " culled_cuts = list(oil_culled_cuts(imported_rec))\n", + "\n", + " if len(culled_cuts) == 0:\n", + " if imported_rec.api is not None:\n", + " oil_api = imported_rec.api\n", + " else:\n", + " oil_rho = oil_density_at_temp(imported_rec, 288.15)\n", + " oil_api = estimate_api_from_density(oil_rho)\n", + "\n", + " BP_i = estimate_cut_temps_from_api(oil_api)\n", + " fevap_i = np.cumsum(estimate_n_fmasses(f_res, f_asph))\n", + " else:\n", + " BP_i, fevap_i = zip(*[(c.vapor_temp_k, c.fraction)\n", + " for c in culled_cuts])\n", + "\n", + " popt, pcov = curve_fit(linear_curve, BP_i, fevap_i)\n", + " f_cutoff = linear_curve(732.0, *popt) # value of asymptote center (< 739)\n", + " popt = popt.tolist() + [f_cutoff]\n", + "\n", + " fevap_i = np.linspace(0.0, 1.0 - f_res - f_asph, (num_cuts * 2) + 1)[1:]\n", + " T_i = np.clip(inverse_linear_curve(fevap_i, *popt), 0.0, 5000.0)\n", + "\n", + " fevap_i = fevap_i.reshape(-1,2)[:,1]\n", + " T_i = T_i.reshape(-1,2)[:,0]\n", + "\n", + " above_zero = T_i > 0.0\n", + " T_i = T_i[above_zero]\n", + " fevap_i = fevap_i[above_zero]\n", + "\n", + " return T_i, fevap_i\n" + ] + }, + { + "cell_type": "code", + "execution_count": 28, + "metadata": { + "collapsed": false, + "scrolled": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[] []\n", + "[ 306.9722499 385.73017816 463.82469565 539.90156544 611.12972805\n", + " 671.9191463 714.00757852 733.92280116 738.6594428 737.51952485]\n" + ] + }, + { + "data": { + "image/png": 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Fv6MSKTzqQRcRERHfWQuLF7sZ5r/84lpaunaF00/3OzKRk6M56CIiIhKWMjPh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\nGfSKuWcBXPVlePqX8A9nwuXXwBu2LzsqSZIktYo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+ "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plt.figure(1, figsize=(12,6))\n", + "ax = plt.subplot(111)\n", + "\n", + "obj = boscan\n", + "\n", + "plt.xlabel('% Evap')\n", + "plt.ylabel(r'$T_i$', fontsize=16)\n", + "plt.grid()\n", + "\n", + "# plot our distillation curve\n", + "boiling_points = [c.vapor_temp_k for c in oil_culled_cuts(obj)]\n", + "cum_fractions = [c.fraction for c in oil_culled_cuts(obj)]\n", + "print boiling_points, cum_fractions\n", + "\n", + "if len(boiling_points) == 0:\n", + " if obj.api is not None:\n", + " oil_api = obj.api\n", + " else:\n", + " oil_rho = oil_density_at_temp(obj, 288.15)\n", + " oil_api = estimate_api_from_density(oil_rho)\n", + "\n", + " f_res, f_asph = oil_inert_fractions(obj)\n", + " boiling_points = estimate_cut_temps_from_api(oil_api)\n", + " cum_fractions = np.cumsum(estimate_n_fmasses(f_res, f_asph))\n", + "\n", + "popt, pcov = curve_fit(linear_curve, boiling_points, cum_fractions)\n", + "\n", + "new_fracs = np.linspace(0.0001, 0.9999, 100)\n", + "new_temps = np.clip(inverse_linear_old(new_fracs, *popt), 0.0, 5000.0)\n", + "plt.plot(new_fracs, new_temps, '-b', label=\"Distillation Curve\")\n", + "\n", + "\n", + "# now plot the N fractions we intend to use\n", + "new_temps, new_fracs = oil_normalized_cut_values(obj)\n", + "print new_temps\n", + "plt.plot(new_fracs, new_temps, 'go', label=\"Estimated Cuts\")\n", + "\n", + "# plot our inert fraction\n", + "plt.plot(1.0, 1015.0, 'go')\n", + "\n", + "# now we would like to graph the quantized \"areas\"\n", + "# that our fractional masses represent\n", + "def make_shaded_region(f_low, f_high,\n", + " t_low, t_high,\n", + " facecolor='0.8'):\n", + " ix = (f_low, f_high)\n", + " iy = (t_low, t_high)\n", + " verts = [(x, y) for x in ix for y in iy]\n", + " verts[2:] = reversed(verts[2:])\n", + " poly = Polygon(verts, facecolor=facecolor, edgecolor='k')\n", + " ax.add_patch(poly)\n", + "\n", + "for r in zip([0.0] + new_fracs.tolist(),\n", + " new_fracs,\n", + " [inverse_linear(0.0, *popt)] + new_temps.tolist(),\n", + " new_temps):\n", + " make_shaded_region(*r, facecolor='#ddeeff')\n", + "\n", + "# make the shaded region for our inert fraction\n", + "make_shaded_region(new_fracs[-1], 1.0,\n", + " new_temps[-1], 1015.0)\n", + "\n", + "# ticks for the shaded region\n", + "extraticks = [low,]\n", + "extralabels = [r'${f_{inert}}$',]\n", + "plt.xticks(list(plt.xticks()[0]) + extraticks,\n", + " list(plt.xticks()[0]) + extralabels)\n", + "\n", + "for tick in ax.xaxis.get_major_ticks():\n", + " if tick.label.get_text().find('inert') >= 0:\n", + " tick.label.set_fontsize(16)\n", + " tick.label.set_rotation('vertical')\n", + "\n", + "plt.axhline(739, color='r')\n", + "plt.legend(loc='upper left')\n", + "\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Ok, that seems like a pretty reasonable response. This solution will require some peer review from Chris, Bill, and Robert, but it will certainly prevent our estimation methods from returning volatile oil fractions with higher densities than the inert fractions." + ] + }, { "cell_type": "code", "execution_count": null,