PyReSim_PVT_GUI.ipynb

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\n",
                "text/plain": "<Figure size 432x288 with 1 Axes>"
              }
            ],
            "_view_module": "@jupyter-widgets/output",
            "_model_module_version": "1.0.0",
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  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/yohanesnuwara/pyresim/blob/master/PyReSim_PVT_GUI.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Tzce613oA_x4",
        "colab_type": "text"
      },
      "source": [
        "# PyReSim (Python Reservoir Simulation) PVT GUI\n",
        "\n",
        "Gas, oil, and water PVT correlations Guided User Interface (GUI)\n",
        "\n",
        "@author: Yohanes Nuwara<br>\n",
        "@email: ign.nuwara97@gmail.com"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "d4kh4gAk9WR3",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "import numpy as np\n",
        "import matplotlib.pyplot as plt\n",
        "import pandas as pd\n",
        "\n",
        "from __future__ import print_function\n",
        "from ipywidgets import interact, interactive, fixed, interact_manual, ToggleButtons\n",
        "import ipywidgets as widgets"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "f2CirplP9ohX",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 138
        },
        "outputId": "26a4ab9e-0f44-458b-9849-7a8887d0ce4c"
      },
      "source": [
        "!git clone https://github.com/yohanesnuwara/pyresim\n",
        "\n",
        "import sys\n",
        "sys.path.append('/content/pyresim/functions')\n",
        "\n",
        "from pvt_correlation import *"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Cloning into 'pyresim'...\n",
            "remote: Enumerating objects: 227, done.\u001b[K\n",
            "remote: Counting objects: 100% (227/227), done.\u001b[K\n",
            "remote: Compressing objects: 100% (226/226), done.\u001b[K\n",
            "remote: Total 1258 (delta 142), reused 0 (delta 0), pack-reused 1031\u001b[K\n",
            "Receiving objects: 100% (1258/1258), 713.18 KiB | 967.00 KiB/s, done.\n",
            "Resolving deltas: 100% (767/767), done.\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "AYg9BgXxA4CC",
        "colab_type": "text"
      },
      "source": [
        "## Gas\n",
        "\n",
        "Input to gas PVT are:\n",
        "\n",
        "* `pressure`: Pressure (psia)\n",
        "* `temp`: Temperature (°F)\n",
        "* `sg`: Specific gravity\n",
        "* `x_h2s`: H2S mole fraction in gas\n",
        "* `x_co2`: CO2 mole fraction in gas"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "f6myAsGbhJog",
        "colab_type": "text"
      },
      "source": [
        "### PVT Calculator"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "hP99J3dLAnyV",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 276
        },
        "outputId": "070f83fc-9147-43b7-823d-3fdc27a72e74"
      },
      "source": [
        "\"\"\"\n",
        "INPUT\n",
        "\"\"\"\n",
        "\n",
        "pressure = 2200 # psi\n",
        "temp = 80 # Fahrenheit\n",
        "sg = 0.7 # specific gravity\n",
        "x_h2s = 0.05 # mole fraction of H2S in gas\n",
        "x_co2 = 0.16 # mole fraction of CO2 in gas\n",
        "\n",
        "\"\"\"\n",
        "CALCULATOR\n",
        "\"\"\"\n",
        "\n",
        "# calculate pseudoproperties using Sutton (1985), Wichert and Aziz (1972)\n",
        "P_pc, T_pc, P_pr, T_pr = gas_pseudoprops(temp, pressure, sg, x_h2s, x_co2)\n",
        "\n",
        "# calculate z-factor using Dranchuk-Aboukassem (1975)\n",
        "pseudo_rho, z_factor = gas_zfactor(T_pr, P_pr)\n",
        "\n",
        "# calculate density\n",
        "rhogas = gas_density(temp, pressure, sg, z_factor)\n",
        "\n",
        "# calculate gas FVF\n",
        "Bg = gas_fvf(z_factor, temp, pressure)\n",
        "\n",
        "# calculate isothermal compressibility using Trube (1957) and Mattar (1975)\n",
        "cgas = gas_compressibility(T_pr, P_pr, pseudo_rho, z_factor, P_pc)\n",
        "\n",
        "# calculate viscosity using Lee et al (1966)\n",
        "viscogas = gas_mu(temp, rhogas, sg)\n",
        "\n",
        "print('=== Gas PVT Correlation Calculator === \\n')\n",
        "print('Your Input:')\n",
        "print('Pressure: {} psia'.format(pressure))\n",
        "print('Temperature: {} °F'.format(temp))\n",
        "print('Specific Gravity: {}'.format(sg))\n",
        "print('H2S Mole Fraction: {}'.format(x_h2s))\n",
        "print('CO2 Mole Fraction: {} \\n'.format(x_co2))\n",
        "\n",
        "print('PVT Output:')\n",
        "print('z-factor (Dranchuk-Aboukassem, 1975): {}'.format(z_factor))\n",
        "print('Density: {} lb/ft3'.format(rhogas))\n",
        "print('FVF: {} res ft3/scf'.format(Bg))\n",
        "print('Isothermal compressibility (Trube, 1957; Mattar, 1975): {} microsip'.format(cgas * 1E+6))\n",
        "print('Viscosity (Lee et al, 1966): {} cp'.format(viscogas))"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "=== Gas PVT Correlation Calculator === \n",
            "\n",
            "Your Input:\n",
            "Pressure: 2200 psia\n",
            "Temperature: 80 °F\n",
            "Specific Gravity: 0.7\n",
            "H2S Mole Fraction: 0.05\n",
            "CO2 Mole Fraction: 0.16 \n",
            "\n",
            "PVT Output:\n",
            "z-factor (Dranchuk-Aboukassem, 1975): 0.7838763704841918\n",
            "Density: 9.826813243351449 lb/ft3\n",
            "FVF: 0.005437782389502583 res ft3/scf\n",
            "Isothermal compressibility (Trube, 1957; Mattar, 1975): 435.56613399411094 microsip\n",
            "Viscosity (Lee et al, 1966): 0.01726394862816872 cp\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "MNt20U5nW0SU",
        "colab_type": "text"
      },
      "source": [
        "### Compressibility (z) Factor - interactive"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "YvE19E1jASIJ",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 429,
          "referenced_widgets": [
            "14af8458b6834a8ead209791fa1ae013",
            "5b0e5c79a8a545839f87bb531c8e85d9",
            "f067234638b64ae2a56162bed3690ac8",
            "cb140a1eb26c42c0bfc27b1c2e3f3f1d",
            "e89b481be9be40aeae559acd65a3ee92",
            "a4ff41bb2cb148c3a136b09a79958e40",
            "e16ae9db81364cca9bed30f05fccdca8",
            "166ae60c1a4e40c69f474583de6e1e9c",
            "6a489baf5bb941c2ba747c1af0748eba",
            "29bee5eca20a4f909fc0ce31e3a66e75",
            "99af7b6567674bc38bf7028d8730440e",
            "8539617072ef421ea78249e878bf93aa",
            "5c4efad2c316499a9ef385beb54ebe73",
            "5df399dfdd7c4cf4a6176ff5297e53eb",
            "89e67111cd03418b8244bf5d1a76f7cd",
            "c1d1ec89eb3a48ad9f04fb355ee33a31"
          ]
        },
        "outputId": "1b69d187-10f5-4402-8a37-150cb5724072"
      },
      "source": [
        "@interact\n",
        "\n",
        "def interactive_gas_zfactor(temp=(110, 572), sg=(0.57, 1.4), x_h2s=(0, 0.4), \n",
        "                            x_co2=(0, 0.4)):\n",
        "  \n",
        "  pressure = np.linspace(50, 5000, 451)\n",
        "\n",
        "  # calculate pseudoproperties using Sutton (1985), Wichert and Aziz (1972)\n",
        "  P_pc = []; P_pr = []\n",
        "  for i in range(len(pressure)):\n",
        "    P_pc_, T_pc_, P_pr_, T_pr = gas_pseudoprops(temp, pressure[i], sg, x_h2s, x_co2)\n",
        "    P_pc.append(P_pc_)\n",
        "    P_pr.append(P_pr_)\n",
        "\n",
        "  # calculate z-factor using Dranchuk-Aboukassem (1975)\n",
        "  z_factor = []\n",
        "  for j in range(len(P_pr)):\n",
        "    pseudo_rho, z_ = gas_zfactor(T_pr, P_pr[j])\n",
        "    z_factor.append(z_)\n",
        "  \n",
        "  # plot z-factor vs pressure\n",
        "  plt.plot(pressure, z_factor, color='red')\n",
        "  plt.xlim(min(pressure), max(pressure))\n",
        "  plt.ylim(0.4, 1.4)\n",
        "  plt.title('Plot of Gas z-factor vs Pressure', size=15, pad=10)\n",
        "  plt.xlabel('Pressure (psig)')\n",
        "  plt.ylabel('z-factor')\n",
        "\n",
        "  plt.grid()\n",
        "  plt.show()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "14af8458b6834a8ead209791fa1ae013",
              "version_minor": 0,
              "version_major": 2
            },
            "text/plain": [
              "interactive(children=(IntSlider(value=341, description='temp', max=572, min=110), FloatSlider(value=0.98499999…"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "vBVzXQm8wqNT",
        "colab_type": "text"
      },
      "source": [
        "### Density - interactive"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "sD5ANzXAwt9l",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "@interact\n",
        "\n",
        "def interactive_gas_density(temp=(110, 572), sg=(0.57, 1.4), x_h2s=(0, 0.4), \n",
        "                            x_co2=(0, 0.4)):\n",
        "  \n",
        "  pressure = np.linspace(50, 5000, 451)\n",
        "\n",
        "  # calculate pseudoproperties using Sutton (1985), Wichert and Aziz (1972)\n",
        "  P_pc = []; P_pr = []\n",
        "  for i in range(len(pressure)):\n",
        "    P_pc_, T_pc_, P_pr_, T_pr = gas_pseudoprops(temp, pressure[i], sg, x_h2s, x_co2)\n",
        "    P_pc.append(P_pc_)\n",
        "    P_pr.append(P_pr_)\n",
        "\n",
        "  # calculate z-factor using Dranchuk-Aboukassem (1975)\n",
        "  z_factor = []\n",
        "  for j in range(len(P_pr)):\n",
        "    pseudo_rho, z_ = gas_zfactor(T_pr, P_pr[j])\n",
        "    z_factor.append(z_)    \n",
        "  \n",
        "  # calculate density\n",
        "  rhogas = []\n",
        "  for k in range(len(z_factor)):\n",
        "    rhogas_ = gas_density(temp, pressure[k], sg, z_factor[k])\n",
        "    rhogas.append(rhogas_)\n",
        "  \n",
        "  # plot density vs pressure\n",
        "  plt.plot(pressure, rhogas, color='blue')\n",
        "  plt.xlim(min(pressure), max(pressure))\n",
        "  plt.ylim(0, 35)\n",
        "  plt.title('Plot of Gas Density vs Pressure', size=15, pad=10)\n",
        "  plt.xlabel('Pressure (psig)')\n",
        "  plt.ylabel('Density (lbm/ft3)')\n",
        "\n",
        "  plt.grid()\n",
        "  plt.show()"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "MmanxGlzeIMM",
        "colab_type": "text"
      },
      "source": [
        "### Gas FVF - interactive"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Quh-M65g8kq8",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "@interact\n",
        "\n",
        "def interactive_gas_fvf(temp=(110, 572), sg=(0.57, 1.4), x_h2s=(0, 0.4), \n",
        "                        x_co2=(0, 0.4)):\n",
        "  \n",
        "  pressure = np.linspace(50, 5000, 451)\n",
        "\n",
        "  # calculate pseudoproperties using Sutton (1985), Wichert and Aziz (1972)\n",
        "  P_pc = []; P_pr = []\n",
        "  for i in range(len(pressure)):\n",
        "    P_pc_, T_pc_, P_pr_, T_pr = gas_pseudoprops(temp, pressure[i], sg, x_h2s, x_co2)\n",
        "    P_pc.append(P_pc_)\n",
        "    P_pr.append(P_pr_)\n",
        "\n",
        "  # calculate z-factor using Dranchuk-Aboukassem (1975)\n",
        "  z_factor = []\n",
        "  for j in range(len(P_pr)):\n",
        "    pseudo_rho, z_ = gas_zfactor(T_pr, P_pr[j])\n",
        "    z_factor.append(z_)\n",
        "  \n",
        "  # calculate gas FVF\n",
        "  Bg = []\n",
        "  for k in range(len(pressure)):\n",
        "    Bg_ = gas_fvf(z_factor[k], temp, pressure[k])\n",
        "    Bg.append(Bg_)\n",
        "  \n",
        "  # plot gas FVF vs pressure\n",
        "  plt.plot(pressure, Bg, color='purple')\n",
        "  plt.xlim(min(pressure), max(pressure))\n",
        "  plt.ylim(0, 0.6)\n",
        "  plt.title('Plot of Gas FVF vs Pressure', size=15, pad=10)\n",
        "  plt.xlabel('Pressure (psig)')\n",
        "  plt.ylabel('Gas FVF (res ft3/scf)')\n",
        "\n",
        "  plt.grid()\n",
        "  plt.show()  "
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "lxJz1senhfpx",
        "colab_type": "text"
      },
      "source": [
        "### Gas Isothermal Compressibility - interactive"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "qeh4JiV0hiId",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "@interact\n",
        "\n",
        "def interactive_gas_compressibility(temp=(110, 572), sg=(0.57, 1.4), \n",
        "                                    x_h2s=(0, 0.4), x_co2=(0, 0.4)):\n",
        "  \n",
        "  pressure = np.linspace(50, 5000, 451)\n",
        "\n",
        "  # calculate pseudoproperties using Sutton (1985), Wichert and Aziz (1972)\n",
        "  P_pc = []; P_pr = []\n",
        "  for i in range(len(pressure)):\n",
        "    P_pc_, T_pc_, P_pr_, T_pr = gas_pseudoprops(temp, pressure[i], sg, x_h2s, x_co2)\n",
        "    P_pc.append(P_pc_)\n",
        "    P_pr.append(P_pr_)\n",
        "\n",
        "  # calculate pseudo-reduced density and z-factor using Dranchuk-Aboukassem (1975)\n",
        "  pseudo_rho = []; z_factor = []\n",
        "  for j in range(len(P_pr)):\n",
        "    pseudo_rho_, z_ = gas_zfactor(T_pr, P_pr[j])\n",
        "    pseudo_rho.append(pseudo_rho_)\n",
        "    z_factor.append(z_)\n",
        "\n",
        "  # calculate isothermal compressibility using Trube (1957) and Mattar (1975)\n",
        "  cgas = []\n",
        "  for k in range(len(P_pr)):\n",
        "    cgas_ = gas_compressibility(T_pr, P_pr[k], pseudo_rho[k], z_factor[k], P_pc[k])\n",
        "    cgas.append(cgas_)\n",
        "  \n",
        "  # plot compressibility vs pressure\n",
        "  plt.plot(pressure, (np.array(cgas) * 1E+6), color='blue')\n",
        "  plt.xlim(min(pressure), max(pressure))\n",
        "  plt.title('Plot of Gas Compressibility vs Pressure', size=15, pad=10)\n",
        "  plt.xlabel('Pressure (psig)')\n",
        "  plt.ylabel('Compressibility (microsip)')\n",
        "\n",
        "  plt.grid()\n",
        "  plt.show()"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "bjgI5Vj6yK4K",
        "colab_type": "text"
      },
      "source": [
        "### Gas Viscosity - interactive"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "VlsTvbJW0fgW",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "@interact\n",
        "\n",
        "def interactive_gas_viscosity(temp=(110, 572), sg=(0.57, 1.4), x_h2s=(0, 0.4), \n",
        "                              x_co2=(0, 0.4)):\n",
        "  \n",
        "  pressure = np.linspace(50, 5000, 451)\n",
        "\n",
        "  # calculate pseudoproperties using Sutton (1985), Wichert and Aziz (1972)\n",
        "  P_pc = []; P_pr = []\n",
        "  for i in range(len(pressure)):\n",
        "    P_pc_, T_pc_, P_pr_, T_pr = gas_pseudoprops(temp, pressure[i], sg, x_h2s, x_co2)\n",
        "    P_pc.append(P_pc_)\n",
        "    P_pr.append(P_pr_)\n",
        "\n",
        "  # calculate z-factor using Dranchuk-Aboukassem (1975)\n",
        "  z_factor = []\n",
        "  for j in range(len(P_pr)):\n",
        "    pseudo_rho, z_ = gas_zfactor(T_pr, P_pr[j])\n",
        "    z_factor.append(z_)    \n",
        "  \n",
        "  # calculate density\n",
        "  rhogas = []\n",
        "  for k in range(len(z_factor)):\n",
        "    rhogas_ = gas_density(temp, pressure[k], sg, z_factor[k])\n",
        "    rhogas.append(rhogas_)\n",
        "  \n",
        "  # calculate viscosity using Lee et al (1966)\n",
        "  viscogas = []\n",
        "  for m in range(len(rhogas)):\n",
        "    viscogas_ = gas_mu(temp, rhogas[m], sg)\n",
        "    viscogas.append(viscogas_)\n",
        "  \n",
        "  # plot viscosity vs pressure\n",
        "  plt.plot(pressure, viscogas, color='black')\n",
        "  plt.xlim(min(pressure), max(pressure))\n",
        "  plt.ylim(0, 0.09)\n",
        "  plt.title('Plot of Gas Viscosity vs Pressure', size=15, pad=10)\n",
        "  plt.xlabel('Pressure (psig)')\n",
        "  plt.ylabel('Viscosity (cp)')\n",
        "\n",
        "  plt.grid()\n",
        "  plt.show()"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "gzYBZOp5SgmA",
        "colab_type": "text"
      },
      "source": [
        "## Oil\n",
        "\n",
        "Input to oil PVT are:\n",
        "\n",
        "* `pressure`: Pressure (psia)\n",
        "* `temp`: Temperature (°F)\n",
        "* `sg`: Specific gravity\n",
        "* `Rsb`: Solution gas-oil ratio at bubble-point pressure (scf/STB) (from PVT data)\n",
        "* `api`: Oil gravity (API)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "gVDMeaW6xq_B",
        "colab_type": "text"
      },
      "source": [
        "### PVT Calculator"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "YT_El5Shxsqw",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 276
        },
        "outputId": "9337521f-4c12-4626-febf-cb27c09295f7"
      },
      "source": [
        "\"\"\"\n",
        "INPUT\n",
        "\"\"\"\n",
        "\n",
        "pressure = 1900 # psi\n",
        "temp = 310 # Fahrenheit\n",
        "sg = 0.77 # specific gravity\n",
        "Rsb = 800 # solution gas-oil ratio at bubble-point pressure (scf/STB) (from PVT data)\n",
        "api = 38 # oil gravity (API)\n",
        "\n",
        "\"\"\"\n",
        "CALCULATOR\n",
        "\"\"\"\n",
        "\n",
        "# calculate bubble-point pressure using Vasquez and Beggs (1980)\n",
        "pbubble = oil_pbubble(Rsb, sg, api, temp)\n",
        "\n",
        "# calculate isothermal compressibility using Vazquez and Beggs (1980); McCain et al (1988)\n",
        "coil = oil_compressibility(pressure, pbubble, temp, api, Rsb, sg)\n",
        "\n",
        "# calculate FVF using Vazquez and Beggs (1980); Levitan and Murtha (1999)\n",
        "Bo = oil_fvf(pbubble, api, Rsb, sg, temp, pressure)\n",
        "\n",
        "# calculate gas-oil ratio using Vazquez and Beggs (1980)\n",
        "Rs = gasoilratio(pressure, pbubble, sg, api, temp, Rsb)\n",
        "\n",
        "# calculate gas-oil ratio using Vazquez and Beggs (1980); Beggs and Robinson (1975)\n",
        "viscooil = oil_mu(pressure, pbubble, sg, api, temp, Rsb)\n",
        "\n",
        "print('=== Oil PVT Correlation Calculator === \\n')\n",
        "print('Your Input:')\n",
        "print('Pressure: {} psia'.format(pressure))\n",
        "print('Temperature: {} °F'.format(temp))\n",
        "print('Specific Gravity: {}'.format(sg))\n",
        "print('Gas-oil ratio @ Bubble-point pressure: {} scf/STB'.format(Rsb))\n",
        "print('Oil gravity: {} API \\n'.format(api))\n",
        "\n",
        "print('PVT Output:')\n",
        "print('Bubble-point Pressure (Vasquez and Beggs, 1980): {} psi'.format(pbubble))\n",
        "print('Gas-oil ratio (Vasquez and Beggs, 1980): {} scf/STB'.format(Rs))\n",
        "print('FVF (Vazquez and Beggs, 1980; Levitan and Murtha, 1999): {} RB/STB'.format(Bo))\n",
        "print('Isothermal compressibility (Vasquez and Beggs, 1980): {} microsip'.format(coil * 1E+6))\n",
        "print('Viscosity (Vazquez and Beggs, 1980; Beggs and Robinson, 1975): {} cp'.format(viscooil))"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "=== Oil PVT Correlation Calculator === \n",
            "\n",
            "Your Input:\n",
            "Pressure: 1900 psia\n",
            "Temperature: 310 °F\n",
            "Specific Gravity: 0.77\n",
            "Gas-oil ratio @ Bubble-point pressure: 800 scf/STB\n",
            "Oil gravity: 38 API \n",
            "\n",
            "PVT Output:\n",
            "Bubble-point Pressure (Vasquez and Beggs, 1980): 3828.485471648363 psi\n",
            "Gas-oil ratio (Vasquez and Beggs, 1980): 348.27111660255684 scf/STB\n",
            "FVF (Vazquez and Beggs, 1980; Levitan and Murtha, 1999): 1.3041017875410919 RB/STB\n",
            "Isothermal compressibility (Vasquez and Beggs, 1980): 61.009423965846686 microsip\n",
            "Viscosity (Vazquez and Beggs, 1980; Beggs and Robinson, 1975): 0.36673292316547934 cp\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "dODZVJmLSjNT",
        "colab_type": "text"
      },
      "source": [
        "### Oil Bubble-point Pressure - interactive"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "zMiNDArzUDZs",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "@interact\n",
        "\n",
        "def interactive_oil_pbubble(Rsb=(20, 2070), sg=(0.56, 1.18), api=(16, 58)):\n",
        "  \n",
        "  temp = np.linspace(70, 295, 100)\n",
        "\n",
        "  # calculate bubble-point pressure using Vasquez and Beggs (1980)\n",
        "  pbubble = []\n",
        "  for i in range(len(temp)):\n",
        "    pb = oil_pbubble(Rsb, sg, api, temp[i])\n",
        "    pbubble.append(pb)\n",
        "  \n",
        "  # plot bubble-point pressure vs temperature\n",
        "  plt.plot(temp, pbubble, color='blue')\n",
        "  plt.xlim(min(temp), max(temp))\n",
        "  plt.ylim(50, 24000)\n",
        "  plt.title('Plot of Oil Bubble-point Pressure vs Temperature', size=15, pad=10)\n",
        "  plt.xlabel('Temperature (°F)')\n",
        "  plt.ylabel('Bubble-point Pressure (psia)')\n",
        "\n",
        "  plt.grid()\n",
        "  plt.show()"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "wpXZdqO7lcUU",
        "colab_type": "text"
      },
      "source": [
        "### Oil Isothermal Compressibility - interactive"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "jz4Zr6G9lf6f",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "@interact\n",
        "\n",
        "def interactive_oil_compressibility(Rsb=(20, 2070), sg=(0.56, 1.18), api=(16, 58),\n",
        "                                    temp=(70, 295)):\n",
        "  \n",
        "  pressure = np.linspace(50, 5000, 451)\n",
        "\n",
        "  # calculate bubble-point pressure using Vasquez and Beggs (1980)\n",
        "  pbubble = oil_pbubble(Rsb, sg, api, temp)\n",
        "\n",
        "  # calculate isothermal compressibility using Vazquez and Beggs (1980); McCain et al (1988)\n",
        "  coil = []\n",
        "  for i in range(len(pressure)):\n",
        "    coil_ = oil_compressibility(pressure[i], pbubble, temp, api, Rsb, sg)\n",
        "    coil.append(coil_)\n",
        "  \n",
        "  # plot oil FVF vs pressure \n",
        "  plt.plot(pressure, (np.array(coil) * 1E+06), color='green')\n",
        "  plt.xlim(min(pressure), max(pressure))\n",
        "  plt.ylim(0, 4000)\n",
        "  plt.title('Plot of Oil Compressibility vs Pressure', size=15, pad=10)\n",
        "  plt.xlabel('Pressure (psia)')\n",
        "  plt.ylabel('Oil compressibility (microsip)')\n",
        "\n",
        "  plt.grid()\n",
        "  plt.show()"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "FpGboG61bwAO",
        "colab_type": "text"
      },
      "source": [
        "### Oil FVF - interactive"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "hb-WEBDab6sm",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "@interact\n",
        "\n",
        "def interactive_oil_fvf(Rsb=(20, 2070), sg=(0.56, 1.18), api=(16, 58),\n",
        "                            temp=(70, 295)):\n",
        "  \n",
        "  pressure = np.linspace(50, 5000, 451)\n",
        "\n",
        "  # calculate bubble-point pressure using Vasquez and Beggs (1980)\n",
        "  pbubble = oil_pbubble(Rsb, sg, api, temp)\n",
        "\n",
        "  # calculate FVF using Vazquez and Beggs (1980); Levitan and Murtha (1999)\n",
        "  Bo = []\n",
        "  for i in range(len(pressure)):\n",
        "    Bo_ = oil_fvf(pbubble, api, Rsb, sg, temp, pressure[i])\n",
        "    Bo.append(Bo_)\n",
        "  \n",
        "  # plot oil FVF vs pressure \n",
        "  plt.plot(pressure, Bo, color='red')\n",
        "  plt.xlim(min(pressure), max(pressure))\n",
        "  plt.ylim(1, 1.5)\n",
        "  plt.title('Plot of Oil FVF vs Pressure', size=15, pad=10)\n",
        "  plt.xlabel('Pressure (psia)')\n",
        "  plt.ylabel('Oil FVF (RB/STB)')\n",
        "\n",
        "  plt.grid()\n",
        "  plt.show()"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "j1fuF0rplFQ1",
        "colab_type": "text"
      },
      "source": [
        "### Gas-Oil Ratio - interactive"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "CLc0v-KDqIHz",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 429,
          "referenced_widgets": [
            "fe45013bddf74ecabddeebb9a344dc32",
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            "2da6d1e9296c4a239040be2e9140909c",
            "d65a56f884874cf7803b45ec66e04510",
            "72149180cdac48d2a800358222434fed",
            "3c475e9de3f249da857c3b221e65015f",
            "863eae9ecc384dd897b4e4c97ea35ce9",
            "e8ca17d18f094489a32a520556ce22c6",
            "4bf49511382445e38f3dc1756aedaa67",
            "2fd2e175c17e40668c56ec78a6f1beaf",
            "38155c500507404b9d0ba22d3e7c05fe",
            "9f1cf57b84614fff81f450daa8ffd8d6",
            "7a715b51ad804b9d91d3ea019f314f9c",
            "96cec1ead46348118625e292259de658",
            "c70c9c9572314282b65990b91aab56b1"
          ]
        },
        "outputId": "1ecad3e4-9467-4628-9b89-da957ca315bf"
      },
      "source": [
        "@interact\n",
        "\n",
        "def interactive_oil_sgor(Rsb=(20, 2070), sg=(0.56, 1.18), api=(16, 58),\n",
        "                            temp=(70, 295)):\n",
        "  \n",
        "  pressure = np.linspace(50, 5000, 451)\n",
        "\n",
        "  # calculate bubble-point pressure using Vasquez and Beggs (1980)\n",
        "  pbubble = oil_pbubble(Rsb, sg, api, temp)\n",
        "\n",
        "  # calculate gas-oil ratio using Vazquez and Beggs (1980)\n",
        "  Rs = []\n",
        "  for i in range(len(pressure)):\n",
        "    Rs_ = gasoilratio(pressure[i], pbubble, sg, api, temp, Rsb)\n",
        "    Rs.append(Rs_)\n",
        "  \n",
        "  # plot oil FVF vs pressure \n",
        "  plt.plot(pressure, Rs, color='purple')\n",
        "  plt.xlim(min(pressure), max(pressure))\n",
        "  plt.ylim(0, 2000)\n",
        "  plt.title('Plot of Gas-Oil Ratio vs Pressure', size=15, pad=10)\n",
        "  plt.xlabel('Pressure (psia)')\n",
        "  plt.ylabel('Gas-Oil Ratio (scf/STB)')\n",
        "\n",
        "  plt.grid()\n",
        "  plt.show()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "fe45013bddf74ecabddeebb9a344dc32",
              "version_minor": 0,
              "version_major": 2
            },
            "text/plain": [
              "interactive(children=(IntSlider(value=1045, description='Rsb', max=2070, min=20), FloatSlider(value=0.87, desc…"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "4BV8QYZpr7TV",
        "colab_type": "text"
      },
      "source": [
        "### Oil Viscosity - interactive"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "dBNFhLPjvhhD",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "@interact\n",
        "\n",
        "def interactive_oil_visco(Rsb=(20, 2070), sg=(0.56, 1.18), api=(16, 58),\n",
        "                            temp=(70, 295)):\n",
        "  \n",
        "  pressure = np.linspace(50, 5000, 451)\n",
        "\n",
        "  # calculate bubble-point pressure using Vasquez and Beggs (1980)\n",
        "  pbubble = oil_pbubble(Rsb, sg, api, temp)\n",
        "\n",
        "  # calculate gas-oil ratio using Vazquez and Beggs (1980); Beggs and Robinson (1975)\n",
        "  visco = []\n",
        "  for i in range(len(pressure)):\n",
        "    visco_ = oil_mu(pressure[i], pbubble, sg, api, temp, Rsb)\n",
        "    visco.append(visco_)\n",
        "  \n",
        "  # plot oil FVF vs pressure \n",
        "  plt.plot(pressure, visco, color='green')\n",
        "  plt.xlim(min(pressure), max(pressure))\n",
        "  plt.ylim(0, 10)\n",
        "  plt.title('Plot of Oil Viscosity vs Pressure', size=15, pad=10)\n",
        "  plt.xlabel('Pressure (psia)')\n",
        "  plt.ylabel('Oil Viscosity (cp)')\n",
        "\n",
        "  plt.grid()\n",
        "  plt.show()"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "R5Xcr1f55qGd",
        "colab_type": "text"
      },
      "source": [
        "## Water\n",
        "\n",
        "Input to water PVT are:\n",
        "\n",
        "* `pressure`: Pressure (psia)\n",
        "* `temp`: Temperature (°F)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "m34h2Cyp7GdU",
        "colab_type": "text"
      },
      "source": [
        "### PVT Calculator"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "MxR2MEgK7JuT",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 138
        },
        "outputId": "132c5648-a7d6-45b4-c1a2-4aadbb4b29f6"
      },
      "source": [
        "\"\"\"\n",
        "INPUT\n",
        "\"\"\"\n",
        "\n",
        "pressure = 3000 # psi\n",
        "temp = 190 # Fahrenheit\n",
        "\n",
        "\"\"\"\n",
        "CALCULATOR\n",
        "\"\"\"\n",
        "\n",
        "# calculate water FVF using McCain et al (1989)\n",
        "Bw = waterfvf(temp, pressure)\n",
        "\n",
        "print('=== Water PVT Correlation Calculator === \\n')\n",
        "print('Your Input:')\n",
        "print('Pressure: {} psia'.format(pressure))\n",
        "print('Temperature: {} °F'.format(temp))\n",
        "\n",
        "print('PVT Output:')\n",
        "print('FVF (McCain et al, 1989): {} RB/STB'.format(Bw))"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "=== Water PVT Correlation Calculator === \n",
            "\n",
            "Your Input:\n",
            "Pressure: 3000 psia\n",
            "Temperature: 190 °F\n",
            "PVT Output:\n",
            "FVF (McCain et al, 1989): 1.0305404582765743 RB/STB\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "wExdDzvn5uzO",
        "colab_type": "text"
      },
      "source": [
        "### Water FVF - interactive"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "SJvMMDBd5zxg",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 333,
          "referenced_widgets": [
            "9ab0d0f6ccaf4be88e71e16b0b6588e6",
            "4ebbe5d37b5144a483827594f4d229b0",
            "aa580cfd2de14ca0946fa5f8f571e860",
            "773b22488edd47cbbae9495a5f934802",
            "29f590d06432486f8009f0cc9a218e93",
            "da15f5f895374e918c6d921047adb718",
            "c0424ebd85234b308bc779b83867a0e0"
          ]
        },
        "outputId": "5a05dd87-30d8-41e9-d4ee-a7d0df3e6a76"
      },
      "source": [
        "@interact\n",
        "\n",
        "def interactive_water_fvf(temp=(70, 295)):\n",
        "  \n",
        "  pressure = np.linspace(50, 5000, 451)\n",
        "\n",
        "  # calculate bubble-point pressure using Vasquez and Beggs (1980)\n",
        "  pbubble = oil_pbubble(Rsb, sg, api, temp)\n",
        "\n",
        "  # calculate water FVF using McCain et al (1989)\n",
        "  Bw = []\n",
        "  for i in range(len(pressure)):\n",
        "    Bw_ = waterfvf(temp, pressure[i])\n",
        "    Bw.append(Bw_)\n",
        "  \n",
        "  # plot oil FVF vs pressure \n",
        "  plt.plot(pressure, Bw, color='blue')\n",
        "  plt.xlim(min(pressure), max(pressure))\n",
        "  plt.ylim(0.98, 1.08)\n",
        "  plt.title('Plot of Water FVF vs Pressure', size=15, pad=10)\n",
        "  plt.xlabel('Pressure (psia)')\n",
        "  plt.ylabel('Water FVF (RB/STB)')\n",
        "\n",
        "  plt.grid()\n",
        "  plt.show()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "9ab0d0f6ccaf4be88e71e16b0b6588e6",
              "version_minor": 0,
              "version_major": 2
            },
            "text/plain": [
              "interactive(children=(IntSlider(value=182, description='temp', max=295, min=70), Output()), _dom_classes=('wid…"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    }
  ]
}