{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "d2c53f49-cf24-48a3-bb8e-571867849c14",
   "metadata": {},
   "source": [
    "# Example large diameter well\n",
    "## Experimental and for radial flow only"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "ed2bfa2a-5ffc-48bc-8224-66edf4410140",
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "from scipy.special import k0\n",
    "\n",
    "import timflow.steady as tfs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "0c7a38da-e288-4fb4-9d73-5cfea442d38c",
   "metadata": {},
   "outputs": [],
   "source": [
    "rw = 5\n",
    "ml = tfs.Model3D(kaq=10, z=np.arange(20, -1, -2), kzoverkh=50)\n",
    "w = tfs.well.LargeDiameterWell(ml, Qw=100, layers=[0, 1, 2, 3, 4], rw=rw)\n",
    "rf = tfs.Constant(ml, 100, 0, 20)\n",
    "ml.solve()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "dc1a5d30-8a1a-46d6-bfd4-67e9a360dc4c",
   "metadata": {},
   "outputs": [],
   "source": [
    "xg = np.linspace(rw, 50, 100)\n",
    "h = ml.headalongline(xg, 0)\n",
    "for i in range(10):\n",
    "    plt.plot(xg, h[i])\n",
    "plt.xlim(0, 50)\n",
    "plt.xticks(np.arange(0, 51, 5))\n",
    "plt.grid()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "ef53616a-88a3-4722-84e2-92727e5399a1",
   "metadata": {},
   "outputs": [],
   "source": [
    "qx = ml.disvec(rw, 0)[0]\n",
    "print(qx * 2 * np.pi * rw)\n",
    "print(np.sum(qx * 2 * np.pi * rw))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "8ced6e89-e8fd-4a7b-8b77-ca5e610581e9",
   "metadata": {},
   "outputs": [],
   "source": [
    "ml.head(rw, 0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "801170e6-538e-4400-81fe-817734bc04e7",
   "metadata": {},
   "outputs": [],
   "source": [
    "k0(5 / ml.aq.lab[1:])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "8a558620-5871-44ee-9d3a-9a21f4d4b6e0",
   "metadata": {},
   "outputs": [],
   "source": [
    "ml.aq.eigvec"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}