{
"cells": [
{
"cell_type": "markdown",
"id": "f2eb1a06",
"metadata": {
"id": "f2eb1a06"
},
"source": "# Natrium Search Simulator — Polatlı Sodyum Sülfat Sahası Veri Analizi\n\n**Proje:** Quantum_Evaporite_Exploration / Natrium Search Simulator\n**Veri kaynağı:** Koyuncu Polatlı (Yeniköseler) Na₂SO₄ üretim kuyuları veri paketi (`KOYUNCU/` klasörü)\n**Amaç:** Sahadan gelen ham Excel/PPTX/fotoğraf paketini (1) temiz, analiz edilebilir tablolara dönüştürmek, (2) keşifsel analizle sahanın cevher yapısını anlamak ve (3) hibrit QML (PennyLane) sınıflandırıcı için özellik matrisini hazırlayıp klasik ML ile karşılaştırmalı ilk denemeyi yapmak.\n\n## Veri paketinde ne var?\n\n| Kaynak | İçerik | Bu notebook'ta |\n|---|---|---|\n| `KAVERNA SONDAJLARI.xlsx` | 19 üretim kuyusu (ÜRT-1…20, ÜRT-4 açılmadı): derinlik, casing, 4½\" ve 2⅜\" tubing konumları | `wells` |\n| `Polatlı Üretim Kuyuları Dikme Kesitler.xlsx` → `ÇÖZÜNEN CEVHER ORANI` | 19 kuyu × metre-metre karot bileşimi: Kil %, Kil taşı/Polihalit %, **Tenardit %**, Globerit içi kil/tenardit %, **Globerit toplam %** | `lith` (1.825 aralık) |\n| aynı dosya → `ÜRT-n` sayfaları | Aralık bazlı litoloji adı (GLOBERİT, GLOBERİT-TENARDİT, TENARDİT-KİL…), kuyu sıcaklığı, karot fotoğrafları | `dikme` (1.262 aralık, 15 kuyu) |\n| `Kopya sodyum sülfat analiz sonuçları revize.xlsx` | Kaverna brine analizleri (ÜRT-1/11/16): pH, Bomé, yoğunluk, Ca, Mg, SO₄, Na₂SO₄, Cl, NaCl | `brine` |\n| `ÜRT Kuyular Casing-Tubing Basınç Testler.xlsx` | Casing/tubing basınç testleri (5 kuyu) | `ptests` |\n| `Polatlı kuyu kaverna detayları.pptx` | Kaverna sirkülasyon performansı ve ideal tubing aralığı hesabı | `cavern` |\n| `POLATLI-ÜRT n/Karot Fotoğrafları` | 1.217 karot kutusu fotoğrafı (dosya adında derinlik aralığı) | `photos` (indeks) |\n| `KYC POLATLI-ZEMİN ETÜD ÇALIŞMA/` | Tesis zemin etüdü (SK-1…19 SPT/UD, sismik .rar, raporlar) — tesis inşaatına ait, cevher modeline girdi değil | sadece envanter |\n\n> **Not:** Kuyu koordinatları (X/Y) pakette yok (`SONDAJ NOKTALARII.kmz` yalnızca yol çizgisi içeriyor). Yanal/mekânsal modelleme için sahadan ÜRT kuyu başı koordinatları istenmeli — bkz. son bölüm.\n\n> **Çalıştırma notu:** Bu kopya, veri paketinin yalnızca tablo dosyalarıyla (fotoğrafsız) ayrı bir ortamda çalıştırıldı; bu yüzden §0 ve §1 çıktılarında dosya yolu/sayısı farklı görünür. Kendi bilgisayarınızda veya Colab'da yeniden çalıştırınca 1.286 dosya / 1,7 GB'lık tam paket okunur; analiz sonuçları değişmez."
},
{
"cell_type": "markdown",
"id": "c2cfdb02",
"metadata": {
"id": "c2cfdb02"
},
"source": "## 0. Kurulum ve yol yapılandırması\nNotebook hem yerel makinede (`Zoom/Natrium_Notebook/` içinde, veri `../KOYUNCU`) hem Google Colab'da (Drive'a yüklenmiş `KOYUNCU` klasörü) çalışır. 150 MB'lık orijinal kesit dosyası yoksa `data_slim/` içindeki yalnızca-veri kopyası kullanılır."
},
{
"cell_type": "code",
"execution_count": 2,
"id": "34b442af",
"metadata": {
"execution": {
"iopub.execute_input": "2026-11-03T19:59:15.282836Z",
"iopub.status.busy": "2026-11-03T19:59:15.282643Z",
"iopub.status.idle": "2026-11-03T19:59:15.806012Z",
"shell.execute_reply": "2026-11-03T19:59:15.804876Z"
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"colab": {
"base_uri": "https://localhost:8080/",
"height": 107
},
"id": "34b442af",
"executionInfo": {
"status": "error",
"timestamp": 1793737391277,
"user_tz": -180,
"elapsed": 58,
"user": {
"displayName": "Joseph Volkan ÖZCAN",
"userId": "11389530967736397480"
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},
"outputId": "a93fd1f7-09fe-4998-87a6-36b2964c65b4"
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"outputs": [
{
"output_type": "error",
"ename": "SyntaxError",
"evalue": "invalid syntax. Perhaps you forgot a comma? (2255374064.py, line 15)",
"traceback": [
"\u001b[0;36m File \u001b[0;32m\"/tmp/ipykernel_1010/2255374064.py\"\u001b[0;36m, line \u001b[0;32m15\u001b[0m\n\u001b[0;31m CANDIDATES = [Zoom/Natrium_Notebook\u001b[0m\n\u001b[0m ^\u001b[0m\n\u001b[0;31mSyntaxError\u001b[0m\u001b[0;31m:\u001b[0m invalid syntax. Perhaps you forgot a comma?\n"
]
}
],
"source": "import os, re, sys, warnings, glob, json\nimport numpy as np, pandas as pd\nimport matplotlib.pyplot as plt\nimport matplotlib as mpl\nwarnings.filterwarnings(\"ignore\")\npd.set_option(\"display.width\", 160); pd.set_option(\"display.max_columns\", 30)\n\n# ---- Colab? ----\nIN_COLAB = \"google.colab\" in sys.modules\nif IN_COLAB:\n from google.colab import drive\n drive.mount(\"/content/drive\")\n\n# ---- Veri klasörü adayları ----\nCANDIDATES = [Zoom/Natrium_Notebook\n \"../KOYUNCU\", # yerel: Zoom/Natrium_Notebook/ içinden\n \"./KOYUNCU\",\n \"/content/drive/MyDrive/KOYUNCU\", # Colab\n \"/content/drive/MyDrive/Zoom/KOYUNCU\",\n \"/content/KOYUNCU\",\n]\nDATA_DIR = next((p for p in CANDIDATES if os.path.isdir(p)), None)\nassert DATA_DIR, \"KOYUNCU veri klasörü bulunamadı — CANDIDATES listesine kendi yolunuzu ekleyin.\"\n\nNB_DIR = os.path.abspath(\".\")\nOUT_DIR = os.path.join(NB_DIR, \"processed\"); os.makedirs(OUT_DIR, exist_ok=True)\nFIG_DIR = os.path.join(NB_DIR, \"figures\"); os.makedirs(FIG_DIR, exist_ok=True)\n\nF_WELLS = f\"{DATA_DIR}/KAVERNA SONDAJLARI.xlsx\"\nF_BRINE = f\"{DATA_DIR}/Kopya sodyum sülfat analiz sonuçları revize (00000003).xlsx\"\nF_PTEST = f\"{DATA_DIR}/POLATLI-ÜRT 1/Casing Basınç Testi/ÜRT Kuyular Casing-Tubing Basınç Testler.xlsx\"\nF_PPTX = f\"{DATA_DIR}/Polatlı kuyu kaverna detayları.pptx\"\n_orig = f\"{DATA_DIR}/Polatlı Üretim Kuyuları Dikme Kesitler.xlsx\"\n_slim = os.path.join(NB_DIR, \"data_slim\", \"Dikme_Kesitler_slim.xlsx\")\nF_DIKME = _orig if os.path.exists(_orig) else _slim\nF_PHOTOS = os.path.join(NB_DIR, \"data_slim\", \"photo_index.csv\")\n\nprint(\"DATA_DIR :\", os.path.abspath(DATA_DIR))\nprint(\"Kesit dosyası:\", \"ORİJİNAL (150 MB)\" if F_DIKME==_orig else \"SLIM kopya\", \"->\", F_DIKME)\nprint(\"Çıktılar :\", OUT_DIR)\n\n# ---- Grafik stili ----\nPAL = {\"clay\":\"#8C7B6B\", \"claystone\":\"#B8A99A\", \"thenardite\":\"#2A9D8F\", \"glauberite\":\"#E9C46A\",\n \"polyhalite\":\"#E76F51\", \"accent\":\"#264653\", \"grey\":\"#9AA5B1\"}\nmpl.rcParams.update({\"figure.dpi\":110, \"axes.spines.top\":False, \"axes.spines.right\":False,\n \"axes.grid\":True, \"grid.alpha\":0.25, \"font.size\":10})"
},
{
"cell_type": "markdown",
"id": "9dff1442",
"metadata": {
"id": "9dff1442"
},
"source": "### Yardımcı fonksiyonlar\nSahadaki Excel'lerde sayılar Türkçe formatta (`164,50`), aralıklar `164,50/165,50`, `174/175`, `212,20-213,60`, `248/249,50` gibi karışık yazılmış; birkaç satırda tuş hatası var (`2601/262`). Aşağıdaki iki fonksiyon bunların tümünü sayıya çevirir."
},
{
"cell_type": "code",
"execution_count": null,
"id": "4e6f399a",
"metadata": {
"execution": {
"iopub.execute_input": "2026-11-03T19:59:15.808237Z",
"iopub.status.busy": "2026-11-03T19:59:15.807945Z",
"iopub.status.idle": "2026-11-03T19:59:15.817920Z",
"shell.execute_reply": "2026-11-03T19:59:15.816745Z"
},
"id": "4e6f399a",
"outputId": "6232352e-4076-4879-ca26-a9d311d48bc6"
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
" 164,50/165,50 -> (164.5, 165.5)\n",
" 174/175 -> (174.0, 175.0)\n",
" 212,20-213,60 -> (212.2, 213.6)\n",
" 248/249,50 -> (248.0, 249.5)\n",
" 2601/262 -> (260.1, 262.0)\n",
" 206,70m-207,90m) -> (206.7, 207.9)\n"
]
}
],
"source": "def to_float(x):\n if x is None: return np.nan\n if isinstance(x, (int, float, np.integer, np.floating)): return float(x)\n s = str(x).strip().replace(\"°C\", \"\").replace(\"m\", \"\").replace(\" \", \"\").replace(\",\", \".\")\n try: return float(s)\n except ValueError: return np.nan\n\ndef parse_interval(s):\n '''164,50/165,50 | 174/175 | 212,20-213,60 | 248/249,50 | 2601/262 -> (from_m, to_m)'''\n if s is None: return (np.nan, np.nan)\n s = str(s).replace(\"m\", \"\").replace(\"M\", \"\").replace(\"(\", \"\").replace(\")\", \"\").strip()\n parts = [p.strip().replace(\",\", \".\") for p in re.split(r\"[/\\-]\", s) if p.strip()]\n if len(parts) < 2: return (np.nan, np.nan)\n try: a, b = float(parts[0]), float(parts[1])\n except ValueError: return (np.nan, np.nan)\n if a > 1000: a /= 10 # '2601/262' tuş hatası\n if b > 1000: b /= 10\n return (a, b)\n\ndef well_no(s): return s.str.extract(r\"(\\d+)\")[0].astype(int)\n\n# hızlı test\nfor t in [\"164,50/165,50\",\"174/175\",\"212,20-213,60\",\"248/249,50\",\"2601/262\",\"206,70m-207,90m)\"]:\n print(f\"{t:>18} -> {parse_interval(t)}\")"
},
{
"cell_type": "markdown",
"id": "c0e8d7fb",
"metadata": {
"id": "c0e8d7fb"
},
"source": "## 1. Veri envanteri"
},
{
"cell_type": "code",
"execution_count": null,
"id": "b08cb342",
"metadata": {
"execution": {
"iopub.execute_input": "2026-11-03T19:59:15.819710Z",
"iopub.status.busy": "2026-11-03T19:59:15.819534Z",
"iopub.status.idle": "2026-11-03T19:59:15.838471Z",
"shell.execute_reply": "2026-11-03T19:59:15.837431Z"
},
"id": "b08cb342",
"outputId": "6034c5d9-e0d0-4236-efec-48adac49cbf4"
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Toplam 4 dosya, 0.01 GB\n"
]
},
{
"data": {
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" | 12 | \n",
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" 275.5 | \n",
" 180.15 | \n",
" 240.00 | \n",
" 250.28 | \n",
" 14 | \n",
" 10.28 | \n",
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" | 13 | \n",
" ÜRT-15 | \n",
" 277.0 | \n",
" 155.00 | \n",
" 260.01 | \n",
" 270.38 | \n",
" 15 | \n",
" 10.37 | \n",
"
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" | 14 | \n",
" ÜRT-16 | \n",
" 272.0 | \n",
" 162.00 | \n",
" 240.00 | \n",
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" 16 | \n",
" 8.00 | \n",
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" 17 | \n",
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"output_type": "display_data"
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],
"source": "fig, ax = plt.subplots(figsize=(12, 5))\nx = np.arange(len(wells))\nax.bar(x, wells.casing_m, color=PAL[\"grey\"], width=.6, label=\"Casing tabanı\")\nax.bar(x, wells.tubing_4_5_m - wells.casing_m, bottom=wells.casing_m, color=PAL[\"glauberite\"], width=.6, label=\"Casing → 4½\\\" tubing\")\nax.bar(x, wells.circ_interval_m, bottom=wells.tubing_4_5_m, color=PAL[\"thenardite\"], width=.6, label=\"Sirkülasyon aralığı (4½\\\"→2⅜\\\")\")\nax.bar(x, wells.depth_m - wells.tubing_2_3_8_m, bottom=wells.tubing_2_3_8_m, color=PAL[\"clay\"], width=.6, label=\"2⅜\\\" tubing → kuyu tabanı\")\nax.set_xticks(x); ax.set_xticklabels(wells.well, rotation=45, ha=\"right\"); ax.invert_yaxis()\nax.set_ylabel(\"Derinlik (m)\"); ax.set_title(\"Kuyu tasarımı: casing / tubing konumları (ÜRT-4 açılmadı)\")\nax.legend(loc=\"lower right\", fontsize=8, ncol=2); plt.tight_layout()\nplt.savefig(f\"{FIG_DIR}/01_kuyu_tasarimi.png\"); plt.show()"
},
{
"cell_type": "markdown",
"id": "c60eea10",
"metadata": {
"id": "c60eea10"
},
"source": "## 3. Litoloji: metre-metre karot bileşimi (`lith`)\n`ÇÖZÜNEN CEVHER ORANI` sayfası 19 kuyuyu yan yana bloklar hâlinde tutuyor (her blok 7 sütun, farklı satırlarda başlıyor, `ORTALAMA(%)` ile bitiyor). Blokları otomatik tespit edip tek bir *uzun* tabloya çeviriyoruz.\n\nSütun anlamları:\n- `clay_pct`, `claystone_pct` / `polyhalite_pct`, `thenardite_pct` → karotun toplam bileşimi (≈100)\n- `glauberite_total_pct` → karotta globerit olarak bulunan kısım; `glauberite_clay_pct` + `glauberite_thenardite_pct` onun içeriği"
},
{
"cell_type": "code",
"execution_count": null,
"id": "7867a05d",
"metadata": {
"execution": {
"iopub.execute_input": "2026-11-03T19:59:16.319095Z",
"iopub.status.busy": "2026-11-03T19:59:16.318882Z",
"iopub.status.idle": "2026-11-03T19:59:16.587170Z",
"shell.execute_reply": "2026-11-03T19:59:16.585757Z"
},
"id": "7867a05d",
"outputId": "e025f078-098f-4a77-d817-9e8b6ac2216a"
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"1825 aralık, 19 kuyu\n",
"Bileşim toplamı 100±5 dışında kalan satır: 3 (saha kayıt hataları — aşağıda listelenir)\n"
]
},
{
"data": {
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" NaN | \n",
" 40.0 | \n",
" 60.0 | \n",
" 40.0 | \n",
" 100.0 | \n",
" 1 | \n",
" 167.0 | \n",
" 1.0 | \n",
" 100.0 | \n",
"
\n",
" \n",
" | 3 | \n",
" ÜRT-1 | \n",
" 167.5 | \n",
" 168.5 | \n",
" 167,50/168,50 | \n",
" 50.0 | \n",
" NaN | \n",
" NaN | \n",
" 50.0 | \n",
" 50.0 | \n",
" 50.0 | \n",
" 100.0 | \n",
" 1 | \n",
" 168.0 | \n",
" 1.0 | \n",
" 100.0 | \n",
"
\n",
" \n",
" | 4 | \n",
" ÜRT-1 | \n",
" 168.5 | \n",
" 169.5 | \n",
" 168,50/169,50 | \n",
" 62.5 | \n",
" NaN | \n",
" NaN | \n",
" 37.5 | \n",
" 52.5 | \n",
" 17.5 | \n",
" 70.0 | \n",
" 1 | \n",
" 169.0 | \n",
" 1.0 | \n",
" 100.0 | \n",
"
\n",
" \n",
" | 5 | \n",
" ÜRT-1 | \n",
" 169.5 | \n",
" 170.5 | \n",
" 169,50/170,50 | \n",
" 75.0 | \n",
" NaN | \n",
" NaN | \n",
" 25.0 | \n",
" 75.0 | \n",
" 25.0 | \n",
" 100.0 | \n",
" 1 | \n",
" 170.0 | \n",
" 1.0 | \n",
" 100.0 | \n",
"
\n",
" \n",
" | 6 | \n",
" ÜRT-1 | \n",
" 170.5 | \n",
" 171.5 | \n",
" 170,50/171,50 | \n",
" 75.0 | \n",
" NaN | \n",
" NaN | \n",
" 25.0 | \n",
" 75.0 | \n",
" 25.0 | \n",
" 100.0 | \n",
" 1 | \n",
" 171.0 | \n",
" 1.0 | \n",
" 100.0 | \n",
"
\n",
" \n",
" | 7 | \n",
" ÜRT-1 | \n",
" 171.5 | \n",
" 172.5 | \n",
" 171,50/172,50 | \n",
" 70.0 | \n",
" NaN | \n",
" NaN | \n",
" 30.0 | \n",
" 70.0 | \n",
" 30.0 | \n",
" 100.0 | \n",
" 1 | \n",
" 172.0 | \n",
" 1.0 | \n",
" 100.0 | \n",
"
\n",
" \n",
"
\n",
"
\n",
"\n",
"
\n",
" \n",
" \n",
" | \n",
" well | \n",
" interval_label | \n",
" clay_pct | \n",
" claystone_pct | \n",
" polyhalite_pct | \n",
" thenardite_pct | \n",
" comp_sum | \n",
"
\n",
" \n",
" \n",
" \n",
" | 52 | \n",
" ÜRT-1 | \n",
" 220,50/221,60 | \n",
" 61.5 | \n",
" NaN | \n",
" NaN | \n",
" 48.5 | \n",
" 110.0 | \n",
"
\n",
" \n",
" | 835 | \n",
" ÜRT-11 | \n",
" 173,30/174,20 | \n",
" 14.0 | \n",
" NaN | \n",
" NaN | \n",
" 30.0 | \n",
" 44.0 | \n",
"
\n",
" \n",
" | 1727 | \n",
" ÜRT-20 | \n",
" 178/179 | \n",
" 36.0 | \n",
" NaN | \n",
" NaN | \n",
" 54.0 | \n",
" 90.0 | \n",
"
\n",
" \n",
"
\n",
"
\n",
"\n",
"
\n",
" \n",
" \n",
" | \n",
" n_intervals | \n",
" ore_top_m | \n",
" ore_base_m | \n",
" logged_m | \n",
" clay_mean | \n",
" thenardite_mean | \n",
" glauberite_mean | \n",
" thenardite_m | \n",
"
\n",
" \n",
" | well | \n",
" | \n",
" | \n",
" | \n",
" | \n",
" | \n",
" | \n",
" | \n",
" | \n",
"
\n",
" \n",
" \n",
" \n",
" | ÜRT-1 | \n",
" 77 | \n",
" 164.5 | \n",
" 247.0 | \n",
" 81.2 | \n",
" 58.27 | \n",
" 39.65 | \n",
" 66.01 | \n",
" 32.11 | \n",
"
\n",
" \n",
" | ÜRT-2 | \n",
" 95 | \n",
" 174.0 | \n",
" 269.0 | \n",
" 95.0 | \n",
" 55.25 | \n",
" 44.71 | \n",
" 93.74 | \n",
" 42.48 | \n",
"
\n",
" \n",
" | ÜRT-3 | \n",
" 86 | \n",
" 180.0 | \n",
" 267.3 | \n",
" 87.3 | \n",
" 62.45 | \n",
" 37.55 | \n",
" 95.52 | \n",
" 32.68 | \n",
"
\n",
" \n",
" | ÜRT-5 | \n",
" 83 | \n",
" 169.5 | \n",
" 255.0 | \n",
" 86.0 | \n",
" 65.64 | \n",
" 34.78 | \n",
" 96.94 | \n",
" 29.64 | \n",
"
\n",
" \n",
" | ÜRT-6 | \n",
" 91 | \n",
" 170.0 | \n",
" 262.0 | \n",
" 92.0 | \n",
" 58.59 | \n",
" 41.41 | \n",
" 96.13 | \n",
" 38.16 | \n",
"
\n",
" \n",
" | ÜRT-7 | \n",
" 96 | \n",
" 168.5 | \n",
" 264.8 | \n",
" 96.3 | \n",
" 57.81 | \n",
" 42.19 | \n",
" 95.51 | \n",
" 40.61 | \n",
"
\n",
" \n",
" | ÜRT-8 | \n",
" 67 | \n",
" 175.0 | \n",
" 250.0 | \n",
" 74.8 | \n",
" 56.87 | \n",
" 43.13 | \n",
" 91.35 | \n",
" 31.16 | \n",
"
\n",
" \n",
" | ÜRT-9 | \n",
" 111 | \n",
" 164.0 | \n",
" 275.5 | \n",
" 112.4 | \n",
" 64.91 | \n",
" 35.36 | \n",
" 91.38 | \n",
" 39.12 | \n",
"
\n",
" \n",
" | ÜRT-10 | \n",
" 121 | \n",
" 154.0 | \n",
" 275.5 | \n",
" 121.5 | \n",
" 62.26 | \n",
" 38.77 | \n",
" 91.95 | \n",
" 46.93 | \n",
"
\n",
" \n",
" | ÜRT-11 | \n",
" 104 | \n",
" 165.0 | \n",
" 269.5 | \n",
" 104.5 | \n",
" 44.00 | \n",
" 55.33 | \n",
" 87.74 | \n",
" 57.89 | \n",
"
\n",
" \n",
" | ÜRT-12 | \n",
" 98 | \n",
" 170.0 | \n",
" 268.0 | \n",
" 98.0 | \n",
" 59.47 | \n",
" 40.95 | \n",
" 94.73 | \n",
" 39.72 | \n",
"
\n",
" \n",
" | ÜRT-13 | \n",
" 92 | \n",
" 174.0 | \n",
" 268.5 | \n",
" 94.5 | \n",
" 59.94 | \n",
" 40.06 | \n",
" 93.12 | \n",
" 37.60 | \n",
"
\n",
" \n",
" | ÜRT-14 | \n",
" 67 | \n",
" 180.0 | \n",
" 253.8 | \n",
" 72.8 | \n",
" 58.66 | \n",
" 41.34 | \n",
" 96.56 | \n",
" 29.90 | \n",
"
\n",
" \n",
" | ÜRT-15 | \n",
" 127 | \n",
" 150.0 | \n",
" 277.0 | \n",
" 127.0 | \n",
" 60.17 | \n",
" 39.28 | \n",
" 96.77 | \n",
" 49.89 | \n",
"
\n",
" \n",
" | ÜRT-16 | \n",
" 87 | \n",
" 162.0 | \n",
" 249.5 | \n",
" 87.5 | \n",
" 46.58 | \n",
" 53.19 | \n",
" 82.21 | \n",
" 46.43 | \n",
"
\n",
" \n",
" | ÜRT-17 | \n",
" 107 | \n",
" 168.0 | \n",
" 275.0 | \n",
" 107.0 | \n",
" 58.38 | \n",
" 41.62 | \n",
" 91.78 | \n",
" 44.53 | \n",
"
\n",
" \n",
" | ÜRT-18 | \n",
" 96 | \n",
" 176.0 | \n",
" 272.0 | \n",
" 96.0 | \n",
" 54.06 | \n",
" 45.94 | \n",
" 94.66 | \n",
" 44.10 | \n",
"
\n",
" \n",
" | ÜRT-19 | \n",
" 102 | \n",
" 170.0 | \n",
" 272.0 | \n",
" 102.0 | \n",
" 55.23 | \n",
" 45.21 | \n",
" 92.45 | \n",
" 45.66 | \n",
"
\n",
" \n",
" | ÜRT-20 | \n",
" 118 | \n",
" 158.0 | \n",
" 276.0 | \n",
" 118.0 | \n",
" 57.55 | \n",
" 42.22 | \n",
" 89.74 | \n",
" 49.40 | \n",
"
\n",
" \n",
"
\n",
"
"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": "fig, axes = plt.subplots(1, 2, figsize=(14, 5), sharey=False)\npw = per_well.copy()\naxes[0].barh(pw.index, pw.thenardite_mean, color=PAL[\"thenardite\"], label=\"Tenardit %\")\naxes[0].barh(pw.index, pw.clay_mean, left=pw.thenardite_mean, color=PAL[\"clay\"], alpha=.6, label=\"Kil %\")\naxes[0].axvline(pw.thenardite_mean.mean(), ls=\"--\", color=PAL[\"accent\"]); axes[0].invert_yaxis()\naxes[0].set_title(\"Kuyu bazında ortalama karot bileşimi\"); axes[0].legend(fontsize=8); axes[0].set_xlabel(\"%\")\naxes[1].barh(pw.index, pw.thenardite_m, color=PAL[\"thenardite\"]); axes[1].invert_yaxis()\naxes[1].set_title(\"Kümülatif tenardit kalınlığı (m) = Σ kalınlık × tenardit%\"); axes[1].set_xlabel(\"m\")\nplt.tight_layout(); plt.savefig(f\"{FIG_DIR}/02_kuyu_ozet.png\"); plt.show()"
},
{
"cell_type": "markdown",
"id": "26a110e5",
"metadata": {
"id": "26a110e5"
},
"source": "### 3.1 Derinlik–kuyu tenardit haritası\nTüm kuyuları 2 m'lik derinlik dilimlerine oturtup tenardit yüzdesini ısı haritası olarak çiziyoruz. Bu, cevher zonunun kuyular arasında nasıl kaydığını (yapısal eğim / fasiyes değişimi) gösteren ilk \"pseudo-kesit\"tir."
},
{
"cell_type": "code",
"execution_count": null,
"id": "0a17f6ff",
"metadata": {
"execution": {
"iopub.execute_input": "2026-11-03T19:59:17.281239Z",
"iopub.status.busy": "2026-11-03T19:59:17.280987Z",
"iopub.status.idle": "2026-11-03T19:59:17.854287Z",
"shell.execute_reply": "2026-11-03T19:59:17.852759Z"
},
"id": "0a17f6ff",
"outputId": "f4b406ea-0a75-47dc-cdda-0b4bdee40a18"
},
"outputs": [
{
"data": {
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",
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": "BIN = 2.0\nlith[\"depth_bin\"] = (lith.depth_mid // BIN) * BIN\nheat = lith.pivot_table(index=\"depth_bin\", columns=\"well\", values=\"thenardite_pct\", aggfunc=\"mean\")\nheat = heat[sorted(heat.columns, key=lambda c: int(re.search(r\"\\d+\", c).group()))]\n\nfig, ax = plt.subplots(figsize=(13, 8))\nim = ax.imshow(heat.values, aspect=\"auto\", cmap=\"YlGnBu\", vmin=0, vmax=100,\n extent=[-0.5, len(heat.columns)-0.5, heat.index.max()+BIN, heat.index.min()])\nax.set_xticks(range(len(heat.columns))); ax.set_xticklabels(heat.columns, rotation=45, ha=\"right\")\nax.set_ylabel(\"Derinlik (m)\"); ax.set_title(\"Tenardit % — derinlik × kuyu (boş = karot kaydı yok)\")\n# sirkülasyon aralığını işaretle\nfor i, w in enumerate(heat.columns):\n r = wells[wells.well == w]\n if len(r):\n ax.plot([i-.4, i+.4], [r.tubing_4_5_m.iloc[0]]*2, color=\"red\", lw=1.5)\n ax.plot([i-.4, i+.4], [r.tubing_2_3_8_m.iloc[0]]*2, color=\"red\", lw=1.5)\nax.grid(False); plt.colorbar(im, ax=ax, label=\"Tenardit %\", shrink=.7)\nax.text(0.01, 0.01, \"kırmızı çizgiler: 4½\\\" ve 2⅜\\\" tubing konumu (sirkülasyon aralığı)\", transform=ax.transAxes, fontsize=8, color=\"red\")\nplt.tight_layout(); plt.savefig(f\"{FIG_DIR}/03_tenardit_heatmap.png\"); plt.show()"
},
{
"cell_type": "markdown",
"id": "1536304b",
"metadata": {
"id": "1536304b"
},
"source": "### 3.2 Tek kuyu profili\n`WELL` değişkenini değiştirip istediğiniz kuyuyu inceleyebilirsiniz. Varsayılan ÜRT-16: en hızlı Bomé artışı gösteren kaverna."
},
{
"cell_type": "code",
"execution_count": null,
"id": "ffd38587",
"metadata": {
"execution": {
"iopub.execute_input": "2026-11-03T19:59:17.856875Z",
"iopub.status.busy": "2026-11-03T19:59:17.856635Z",
"iopub.status.idle": "2026-11-03T19:59:18.295591Z",
"shell.execute_reply": "2026-11-03T19:59:18.293855Z"
},
"id": "ffd38587",
"outputId": "9a365b90-dc49-4378-93d4-b0c9b02d3480"
},
"outputs": [
{
"data": {
"image/png": 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",
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": "WELL = \"ÜRT-16\"\nd = lith[lith.well == WELL].sort_values(\"depth_from\")\nw = wells[wells.well == WELL].iloc[0]\nfig, ax = plt.subplots(figsize=(6, 10))\nax.barh(d.depth_mid, d.thenardite_pct, height=d.thickness_m, color=PAL[\"thenardite\"], label=\"Tenardit %\")\nax.barh(d.depth_mid, d.clay_pct, left=d.thenardite_pct, height=d.thickness_m, color=PAL[\"clay\"], alpha=.6, label=\"Kil %\")\nax.plot(d.glauberite_total_pct, d.depth_mid, color=PAL[\"glauberite\"], lw=2, label=\"Globerit toplam %\")\nfor y, lab in [(w.casing_m,\"casing\"),(w.tubing_4_5_m,'4½\" tubing'),(w.tubing_2_3_8_m,'2⅜\" tubing')]:\n ax.axhline(y, color=\"red\", ls=\"--\", lw=1); ax.text(101, y, lab, color=\"red\", fontsize=8, va=\"center\")\nax.invert_yaxis(); ax.set_xlim(0, 100); ax.set_xlabel(\"%\"); ax.set_ylabel(\"Derinlik (m)\")\nax.set_title(f\"{WELL} karot profili\"); ax.legend(loc=\"lower left\", fontsize=8)\nplt.tight_layout(); plt.savefig(f\"{FIG_DIR}/04_profil_{WELL}.png\"); plt.show()"
},
{
"cell_type": "markdown",
"id": "95c40089",
"metadata": {
"id": "95c40089"
},
"source": "## 4. Dikme kesit litoloji adları ve kuyu sıcaklığı (`dikme`)\n`ÜRT-n` sayfalarında her aralık için jeologun verdiği litoloji adı (GLOBERİT, GLOBERİT-TENARDİT, TENARDİT-KİL …) ve bazı kuyularda kuyu sıcaklığı var. Bunlar QML için **kategorik etiket** adayı."
},
{
"cell_type": "code",
"execution_count": null,
"id": "f174f4a4",
"metadata": {
"execution": {
"iopub.execute_input": "2026-11-03T19:59:18.298778Z",
"iopub.status.busy": "2026-11-03T19:59:18.298505Z",
"iopub.status.idle": "2026-11-03T19:59:18.428613Z",
"shell.execute_reply": "2026-11-03T19:59:18.427108Z"
},
"id": "f174f4a4",
"outputId": "4cdcc277-d8bf-4285-9976-1173751b0dc7"
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"1262 aralık, 15 kuyu (ÜRT-9/10/15/20 kesit sayfası yok)\n",
"lithology\n",
"GLOBERİT 953\n",
"GLOBERİT-TENARDİT 128\n",
"TENARDİT-KİL 91\n",
"TENARDİT-GLOBERİT 49\n",
"KİL-TENARDİT 17\n",
"GLOBERİT-KİL 5\n",
"KİL 3\n",
"TENARDİT 1\n",
"GLOBERİT-KİLTAŞI 1\n",
"GLOBERİT-GLOBERİT 1\n",
"SAF TENARDİT 1\n"
]
},
{
"data": {
"text/plain": [
"well\n",
"ÜRT-1 25.27\n",
"ÜRT-11 25.27\n",
"ÜRT-16 25.10\n",
"Name: temp_c, dtype: float64"
]
},
"execution_count": 12,
"metadata": {},
"output_type": "execute_result"
}
],
"source": "recs = []\nfor name in wb.sheetnames:\n if not name.upper().startswith(\"ÜRT\") or \"FOTOĞRAF\" in name.upper(): continue\n ws_ = wb[name]; well = name.replace(\" \", \"\").upper(); cur = None\n for row in ws_.iter_rows(values_only=True):\n row = list(row) + [None]*(14-len(row))\n lab = row[0]\n if isinstance(lab, str) and re.match(r\"^\\d\", lab.strip()):\n a, b = parse_interval(lab)\n cur = dict(well=well, depth_from=a, depth_to=b, interval_label=lab.strip(), lithology=None, temp_c=np.nan)\n recs.append(cur)\n lth = next((v for v in row[1:11] if isinstance(v, str) and re.search(r\"GLOBER|TENARD|KİL|POLİHAL|JİPS|ANHİDR|HALİT\", v.upper())), None)\n if lth and cur is not None and cur[\"lithology\"] is None: cur[\"lithology\"] = lth.strip().upper()\n t = row[11]\n if isinstance(t, str) and \"°C\" in t and cur is not None and np.isnan(cur[\"temp_c\"]): cur[\"temp_c\"] = to_float(t)\ndikme = pd.DataFrame(recs)\ndikme[\"well_no\"] = well_no(dikme.well)\ndikme = dikme.sort_values([\"well_no\",\"depth_from\"]).reset_index(drop=True)\n# litolojiyi 5 sınıfa indirge\ndef lith_class(s):\n if s is None or (isinstance(s,float) and np.isnan(s)): return None\n s = s.replace(\"GLOBERİT-GLOBERİT\",\"GLOBERİT\")\n if s in (\"GLOBERİT\",): return \"GLOBERİT\"\n if s.startswith(\"GLOBERİT-\"): return \"GLOBERİT-baskın\"\n if s.startswith(\"TENARDİT\") or s==\"SAF TENARDİT\": return \"TENARDİT-baskın\"\n if s.startswith(\"KİL\"): return \"KİL-baskın\"\n return \"DİĞER\"\ndikme[\"lith_class\"] = dikme.lithology.map(lith_class)\nprint(len(dikme), \"aralık,\", dikme.well.nunique(), \"kuyu (ÜRT-9/10/15/20 kesit sayfası yok)\")\nprint(dikme.lithology.value_counts().to_string())\ndikme.groupby(\"well\").temp_c.mean().dropna().round(2)"
},
{
"cell_type": "code",
"execution_count": null,
"id": "17874fc6",
"metadata": {
"execution": {
"iopub.execute_input": "2026-11-03T19:59:18.431075Z",
"iopub.status.busy": "2026-11-03T19:59:18.430838Z",
"iopub.status.idle": "2026-11-03T19:59:18.465459Z",
"shell.execute_reply": "2026-11-03T19:59:18.464099Z"
},
"id": "17874fc6",
"outputId": "4ae4b7f0-5ea9-4f0c-e3eb-4cebc1961506"
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Litoloji adı eşleşen aralık: 1236 / 1825\n"
]
},
{
"data": {
"text/html": [
"\n",
"\n",
"
\n",
" \n",
" \n",
" | \n",
" clay_pct | \n",
" thenardite_pct | \n",
" glauberite_total_pct | \n",
"
\n",
" \n",
" | \n",
" mean | \n",
" count | \n",
" mean | \n",
" count | \n",
" mean | \n",
" count | \n",
"
\n",
" \n",
" | lith_class | \n",
" | \n",
" | \n",
" | \n",
" | \n",
" | \n",
" | \n",
"
\n",
" \n",
" \n",
" \n",
" | GLOBERİT | \n",
" 62.5 | \n",
" 942 | \n",
" 37.5 | \n",
" 942 | \n",
" 99.7 | \n",
" 936 | \n",
"
\n",
" \n",
" | GLOBERİT-baskın | \n",
" 39.1 | \n",
" 134 | \n",
" 60.3 | \n",
" 134 | \n",
" 67.0 | \n",
" 134 | \n",
"
\n",
" \n",
" | KİL-baskın | \n",
" 72.8 | \n",
" 20 | \n",
" 32.1 | \n",
" 17 | \n",
" 85.0 | \n",
" 2 | \n",
"
\n",
" \n",
" | TENARDİT-baskın | \n",
" 26.3 | \n",
" 139 | \n",
" 73.9 | \n",
" 140 | \n",
" 47.5 | \n",
" 52 | \n",
"
\n",
" \n",
"
\n",
"
\n",
"\n",
"
\n",
" \n",
" \n",
" | \n",
" n | \n",
" first | \n",
" last | \n",
" bome_max | \n",
" na2so4_max_g_l | \n",
" pH_mean | \n",
"
\n",
" \n",
" | well | \n",
" | \n",
" | \n",
" | \n",
" | \n",
" | \n",
" | \n",
"
\n",
" \n",
" \n",
" \n",
" | KUYUSUYU | \n",
" 1 | \n",
" 2026-04-01 | \n",
" 2026-04-01 | \n",
" 1.18 | \n",
" NaN | \n",
" 7.60 | \n",
"
\n",
" \n",
" | ÜRT-1 | \n",
" 23 | \n",
" 2025-09-23 | \n",
" 2026-04-01 | \n",
" 23.15 | \n",
" 286.63 | \n",
" 8.12 | \n",
"
\n",
" \n",
" | ÜRT-11 | \n",
" 19 | \n",
" 2025-10-19 | \n",
" 2026-04-01 | \n",
" 25.00 | \n",
" 296.28 | \n",
" 7.92 | \n",
"
\n",
" \n",
" | ÜRT-16 | \n",
" 12 | \n",
" 2025-10-24 | \n",
" 2026-01-04 | \n",
" 26.15 | \n",
" 301.24 | \n",
" 8.28 | \n",
"
\n",
" \n",
"
\n",
"
"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": "fig, axes = plt.subplots(1, 3, figsize=(16, 4.5))\ncols = {\"ÜRT-1\":PAL[\"accent\"], \"ÜRT-11\":PAL[\"polyhalite\"], \"ÜRT-16\":PAL[\"thenardite\"]}\nfor wname, g in brine[brine.well.isin(cols)].groupby(\"well\"):\n axes[0].plot(g.date, g.bome, \"o-\", color=cols[wname], label=wname, ms=4)\n axes[1].plot(g.date, g.na2so4_g_l, \"o-\", color=cols[wname], label=wname, ms=4)\naxes[0].axhline(25, ls=\"--\", color=\"grey\"); axes[0].text(brine.date.min(), 25.5, \"hedef 24–25 °Bé\", fontsize=8, color=\"grey\")\naxes[0].set_title(\"Kaverna brine Bomé gelişimi\"); axes[0].set_ylabel(\"°Bé\"); axes[0].legend()\naxes[1].set_title(\"Na₂SO₄ konsantrasyonu\"); axes[1].set_ylabel(\"g/L\"); axes[1].legend()\nfor ax in axes[:2]: ax.tick_params(axis=\"x\", rotation=30)\n# Bomé – Na2SO4 kalibrasyonu\nok = brine.dropna(subset=[\"bome\",\"na2so4_g_l\"])\nk = np.polyfit(ok.bome, ok.na2so4_g_l, 1)\naxes[2].scatter(ok.bome, ok.na2so4_g_l, c=[cols.get(w, \"grey\") for w in ok.well], s=25)\nxx = np.linspace(ok.bome.min(), ok.bome.max(), 50); axes[2].plot(xx, np.polyval(k, xx), \"k--\", lw=1)\naxes[2].set_title(f\"Na₂SO₄ (g/L) ≈ {k[0]:.2f}·Bomé {k[1]:+.1f} (R²={np.corrcoef(ok.bome, ok.na2so4_g_l)[0,1]**2:.2f})\")\naxes[2].set_xlabel(\"°Bé\"); axes[2].set_ylabel(\"g/L\")\nplt.tight_layout(); plt.savefig(f\"{FIG_DIR}/05_brine.png\"); plt.show()"
},
{
"cell_type": "code",
"execution_count": null,
"id": "d2851466",
"metadata": {
"execution": {
"iopub.execute_input": "2026-11-03T19:59:19.169926Z",
"iopub.status.busy": "2026-11-03T19:59:19.169716Z",
"iopub.status.idle": "2026-11-03T19:59:19.730804Z",
"shell.execute_reply": "2026-11-03T19:59:19.729881Z"
},
"id": "d2851466",
"outputId": "47bda63a-149f-4bc6-8da5-1a10bd548b71"
},
"outputs": [
{
"data": {
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",
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": "# İyon dengesi görünümü: Ca/Mg safsızlıkları ve NaCl kirliliği Bomé ile nasıl değişiyor?\nfig, axes = plt.subplots(1, 2, figsize=(12, 4))\nfor wname, g in brine[brine.well.isin(cols)].groupby(\"well\"):\n axes[0].scatter(g.bome, g.ca_mg_l, color=cols[wname], label=f\"{wname} Ca\", s=22)\n axes[0].scatter(g.bome, g.mg_mg_l, color=cols[wname], marker=\"x\", label=f\"{wname} Mg\", s=22)\n axes[1].scatter(g.bome, g.nacl_wt_pct, color=cols[wname], label=wname, s=22)\naxes[0].set_xlabel(\"°Bé\"); axes[0].set_ylabel(\"mg/L\"); axes[0].set_title(\"Ca (●) ve Mg (×) vs Bomé\"); axes[0].legend(fontsize=7, ncol=3)\naxes[1].set_xlabel(\"°Bé\"); axes[1].set_ylabel(\"NaCl %wt\"); axes[1].set_title(\"NaCl kirliliği vs Bomé\"); axes[1].legend(fontsize=8)\nplt.tight_layout(); plt.savefig(f\"{FIG_DIR}/06_brine_iyonlar.png\"); plt.show()"
},
{
"cell_type": "markdown",
"id": "f8b50d69",
"metadata": {
"id": "f8b50d69"
},
"source": "## 6. Casing / tubing basınç testleri (`ptests`)\nHer test: başlangıç basıncı → bekleme → bitiş basıncı. Basınç düşüşü yüzdesi, kuyu sızdırmazlığının göstergesi (casing testlerinde düşük, tubing testlerinde yüksek düşüş normal: tubing kavernaya açık)."
},
{
"cell_type": "code",
"execution_count": null,
"id": "6e5faa0b",
"metadata": {
"execution": {
"iopub.execute_input": "2026-11-03T19:59:19.733527Z",
"iopub.status.busy": "2026-11-03T19:59:19.733217Z",
"iopub.status.idle": "2026-11-03T19:59:20.269407Z",
"shell.execute_reply": "2026-11-03T19:59:20.267901Z"
},
"id": "6e5faa0b",
"outputId": "b8f9b5b8-3615-4b6b-acdf-55afbab3fb88"
},
"outputs": [
{
"data": {
"image/png": 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zpf3369fP1Q04+eST3UOuR7UZlLUxfPhwV8tANSJE0xn0UOt/sF2xYoU99NBDJb6NgiZ6AEsOdDRp0sT9XqqpCdlSwEIPiU8++aR7aNcDt0yYMME9HJeXHmpPOukkV/NB03oaN27spiL4KSii2if+2iGiwEnLli3txRdfzPhxmuYhCgL4KeCgLA7/dCI9gA8ePDjl+ykQo4diP/1ZGRpeXY2KOuecc9y2VF2VOXPmuLfTvnH66aenDNikoywi9YtH76mAm6beKADn7U+SHFhQTZDk6T3KpFDfeNOgRAE5BUVysT9J7969bfny5a6d3v4kyjZRtoYyVTJJ1c8KnCiIoX0yuf+PO+44V2fFq5lz9913W8OGDe3TTz8t/hjVz9HUH723spIk3f6UrEePHi6Yo+/jn16kDBu16aijjirxPQEASEYmCACgStHouR6gBw0a5Gpe7Ljjji5t/uOPP7bffvvNdtttNzd9xaOHVwUC9Ht6wNIDmh7gk0fNNd1ho402cqPXGvlX3RAFEd544w3bYost3GtzQfUT9FCsII6mSShDQjVHFJQ57bTTyv0Rer2KUWo7KDDkPWx6+vbt677niSeeaC+88IJ16NDBZWWMGTPGTYXRA2UmGoXXg36vXr1cFsSFF17ogicKEmmKg6bhaJvoYV6ZLQrC+AMIHhX3fOqpp1z/aJvqv5oq0blzZ9e2XNB3u/POO90Df9OmTV0WgR7eNfVJgRYFncpD9Tr0Hvo+mjKlYqaa3qGgmld8U/uJto3qU6guhvYr/VeZPNo+fl27dnWZS8rcUUaFAnJ67++++85lguSCAhLqa+23muKl7f3777+7OjFqq/otE7VRAUIFkPRaZT/pdffff7+b3qNiv+rrevXqueDjBx984I4pBT5Ex5sCTipaqu2n/UHBOU0fu+qqq9x3FvW9sohUS0VZWfo8FelNpgCRAivavxXE0XsqCKV9RkEqtSW5qDAAAH5kggAAqhQFDR555BE30q0HS438q45H+/btXbBDWRX+qReqDaKpLBqJ1oOdHsg1mq0HLT1AasTa8/LLL7uHYD3U6qFaD6vKqHjnnXeKa2ioBoNep4dtjx7W9DCcTDVE9Lt6gPQoG0QPkkOHDnWZCgp8KDCQnMlRFk37UBaAghn+qTAeBUX0YK4pG3oo1kO3Hj71AKvP9zJl0lFgQVOJFCzSSjNeMUoFGPR6bXttJ43QP/DAA+57JH9XTSnSQ7ayJJSpo+CJAkyXXnqpa5v3gCzKMPGvIqNtpvfz6pz47bDDDiVqUojqUigbQdkLKhx73333uRoVNWvWLGtTuodqfZb2Fe0DaqPaqkwEZa1oO/gpqKRMHK1KoyCHfl/fUQVB/VN8FDhRQEBTk/Qe2vcUPND+6K/Vopoi/ho3ChaoPcoiSaZggvZ1P21/BcMUtPr3v//tAgYKMKmf/PtpKuojtUvbW33iFSbVNlYgQ7Vm9Pc6djSNSUE8f7BL7VFwRP9VlpEygpTtoiLDN9xwQ/FHaj9SfR5lmej39d6iwJG+qz+woX1UU44UgNHUNgWxtB8oqKepaf5jSa/1H+8eBfr0b16wBgBQOIq0OnDhfF0AAOJP0xeS6yTogVUPwsoIUXAE2Um1TUVFTPXAnTyto6pSFoeCTMqA8QffAAAoFGSCAAAQI1qhRiP5XuFW0XQCZRRoNFzTRJCdzz//3E1ZUtaGf+xHGSzKYlBGQKHQdDFNE0u3KhAAAFUdNUEAAIgR1YfQVAFNkdAUGqXyq/aIiouqkKZ/6VGUj7alanionoUyaVTgdu7cuW67avpRrupvxN1PP/1kixcvdtNWFi1aFPfmAgAQCqbDAAAQM8oCUZ0DFSrVSjWbbrqpq1OiugoIZs2aNa6eh+phqE6MakFoe6rAprcySVWnui1aLlf1M1TM1V/vBgCAQkEQBAAAAAAAFARqggAAAAAAgIJAEAQAAAAAABQEgiAAAAAAAKAgEAQxs1WrVtmvv/7q/gsAAAAAAKomgiBmrkr8Jpts4v5bCFavXm3z5s1z/42DOLUnTm0R2pMe2yazOG2fOLWF46ry7Df0FX1VEXE678SpLRxXHFcVEad9OU5t4biqfAiCAAAAAACAgkAQBAAAAAAAFASCIAAAAAAAoCAQBAEAAAAAAAWBIAgAAAAAACgIBEEAAAAAAEBBqFEQ3xIAAAAAgDIkEgmbN2+eLVu2zC3FWx56zfLly23JkiVWVFRUnpeEKm7tCap69epWu3Zta9iwYU63K0EQAAAAAEDBU/Dgt99+c8GMWrVquYfw8lDgQ78fhwCIxK09Qa1YscKWLl3qAkzNmjXL2fYlCAIAAAAAKHjKAFEApFGjRtagQYNybw8FT1atWmU1atTI2YN6RcStPRUxf/58mzt3ruubDTfcsCJvVYyaIAAAAACAgqcpMMroyCYAgnCpL9Qn6ptcIQgCAAAAACh4qgFS3ikwiI76pLz1WcqDIAgAAAAAACgIBEEAAAAAAEBBIAgCAAAAAAAKAqvDAAAAAKiQtkMGBnq9FiBtXqO2zVi1zFZn+Q5fn9ovy1cAgJEJAgAAAAAACgPTYQAAAAAAQFYOPvhgO+SQQ7J6TRwwHQYAAAAAgAwGDR2Vl+3T57geefnc8thxxx2tqKioPL8aKwRBAAAAAABAVq6++uqsfj8umA4DAAAAAEAVsmLFCrvyyittm222sUaNGtkBBxxgn376aYlv+Oqrr9phhx1mzZo1s+bNm9tFF11kq1atKv6d5cuX22WXXWZbbLGFNWzY0Lp3727ff/998b/37dvX+vX7X4HirbbaysaOHWuXXHKJtWzZ0rbccku78847S3xmIpGwAQMGWIcOHaxx48bWs2dPmzhxovvdJUuWRNIDBEEAAAAAAKhCjjrqKHv88cftnHPOsXvvvddWr15tXbt2tR9++MF9yzfffNMFRmrVqmX33XefnX/++TZkyBC79tpri7fCpZdeao888ohdddVV9uyzz9paa61lRx99tAuwyJw5c+z3338v/v0ff/zRrrnmGvee99xzj+29994usDJ69Oji39H7X3HFFe599HnrrruunXbaaTZt2jRbs2ZNJD3AdBgAAAAAAKqIt99+21555RWbPHmy7bTTTu5bqYjpxRdfbAsXLnR/3n777W3kyJHWo8f/ao78/PPPLpPj5ptvdr8zYcIE9+8nn3yy+3OXLl3ss88+s2rV0udS6H1vuukm9/v77ruvvfjiiy7j5MADD3Sffccdd1j//v3tvPPOc7+jQMyRRx5p3333XWRbnyAIAAAAAABVxHvvveemo6hwqad27douI8RTv359F+CYNWuWvfvuuy6LQ9khf/75Z/Hv7LHHHvbggw/a2muv7VaB2XXXXV0gJJOOHTsW/3P16tVt9913d58h33zzjf3zzz92+OGHl3gLBWhGjBgR2dZnOgwAAAAAAFWEpqg0aNAg47dRQKJ9+/bWokULV7dDtT5atWpV4jXK2tDPl19+aQcddJCrLaLpLploKoxfjRr/y7vwAiz16tUr8Tt169aNdMsTBAEAAAAAoIpQFsj06dNL1dhQXRCPVnZZZ511bO7cufbhhx+6+iE777xziS2gTI6zzz7bJk2aZAsWLHD1PW688UY3TSYIFVgVBVX8pkyZEuTtAiMIAgAAAABAFbH//vu7+huPPvpo8Tf65Zdf3Gosw4YNc3+nrIwmTZq4aTGycuVKV7/Do1ViVFz1ySefdH+lAqYnnnii+/+gq7i0bt3a1ShRMGXevHnuvRQAUWHWKFETBAAAAACAKkIZFypOetZZZ9mYMWPcdBMVStXUFxUiFRU7PeWUU1zARL8/btw4FyTxaBrLBhts4JbB1Xuopshrr73mCp/utddegbZUUVGRPfHEE3booYe6AIw+76+//nLL8F5++eWB3jMIgiAAAAAAAGTQ57j/raKSLJFIuMwJBQ70oB8H/fr1c0VMFcDQlJdbbrnFevbs6YqcykknneQCES+99JJb+vbhhx92/6YiqZ4HHnjA9txzT7fajKbSaCqM3kMBETnuuONK1Py4/vrrrUOHDiW+vrJJtG08bdq0cdNhtMrM/PnzrVOnTvbBBx+4f8606kwuEQQBAAAAAKCK2WWXXaxz585pv1X37t3dj59/RRkFJRTE0E8qWtrW74orrij1a8r68FM9EdUa0Uoznvfff9822mgjq1OnTiQ9EMsgiKrZPv300yk3gCJrF1xwQfG/zZw500W39F9FkbT+cFQRJAAAAAAAUD7KPFGtktNOO82aNWvmskxeffVVu/XWW8v3BjkQyyCIirR4BVv8fvvtN1dAxQuCTJ482c1h0hI7msc0cOBAF8l69tlnXUoPAAAAAACIBz2zb7fddjZq1Cj75JNPXCBEgRElM0QllkEQzRP66KOPSm0DFWHx0mY070rzmDTPSVVslVKjuUX6d0WWzjzzzKi2IQAAAAAAKAc9x+snX2IZBEll5MiR9vnnnxcv0TN+/Hj77rvvbMSIES4AIu3bt3fFWe6///6MQZDFixe7H8/s2bPd/6rYi3/t5KpK33HNmjWx+a5xak+c2uLtk/RVavRVZnHaPnFqC8dV5dlv6Cv6qiLidN6JU1vCPK7+ezeePb2umlmg1+f6vr1Q+iqoOG2fsNqigXaVX9B/s+H9fravC0vc2pML+k6ZjnkvJlAelSIIoi983XXXuYIs7dq1c99L1WSbNm1qbdu2LfE999lnH3vkkUds+fLlaafEDBgwwFWuTbZo0SK3/nFVp51n6dKlbrtms7OEJU7tiVNbvBsV+io1+iqzOG2fOLWF46ry7Df0FX1VEXE678SpLWEeV81r/He1iGwpANK4ei33sjVZvnjBggVZvoLjqiLitC+H1RY9Q9aqVavEaiblleugXEXFrT0VoUHhFStWZDzmGzZsWO6PqBRBEM0R+uqrr2zo0KHFX0z1QVRBNpmW+dHD/axZs2yzzTZLuSFUU6R3797F/6ZMkI4dO7raIvXr1y/3xqusdEAowrn++uvHJggSl/awbcq+OaCvUmPfSY9tw3EVFPsOx1VQcdp34tQWCas9M1YtC9RdXgbJzFXLbHWW75Dr+/awtk1QtCf6c+CSJUvcva6Wus2Gl3mhAeY4LJEbt/ZUlBY+Uc3PXB3z2fVuHnhZIEcffbRtvfXWxS1QlC7VzqnInejf06lbt677SaadNg6ZEVHQjhSn7xun9sSpLUJ70mPbZBan7ROntnBcVZ79hr6iryoiTuedOLUlrOMq2wCGnzJA9Pps3yOM+/ZC6KuKiNP2CaMtXgAjaCBDrwv62jDErT0Voe+Sq2NeGWixppofX3/9tV1zzTUl2qkqsn/88Ueptmt5XdG/AwAAAAAAeGIdBNHcH9XuOPbYY22rrbYq0WtaEnf69Ok2Z86cEn//wQcfWKNGjaxOnTr0MgAAAAAAKBbrIMjzzz/vVoC5+uqrS3VZjx493Jygu+66q/jf5s+fb48//rideuqppX4fAAAAAAAUttjWBFEWyA033OCWvG3dunWpXqpdu7b179/fTjvtNJs5c6a1atXKhg8f7v7+3HPPLexeBQAAAAAApcQ2E2TKlCmuEGpyLRC/Xr162ahRo9xfvfXWW3bAAQfYpEmTUq4aAwAAAAAACltsM0Hat2/vpsOURYEP/QAAAAAAAGQS20wQAAAAAAAQDS06onqc8+bNS/uBiUTCDjnkELvjjjuiaVQIYpsJAgAAAABAHLQdMjAvzfj61H6BPvfggw+2Cy+80Pbaa69yv/7333+3m266yU444QRr2LBhytcpCLJs2TJbsWJFud83bgiCAAAAAABQhbzxxhtukZFcq1atmr322mu5fttIMR0GAAAAAIAqQAuM7LPPPrZ69Wq79dZbrVu3brZ48WL79ttv3f8r28Pv2GOPtWHDhpX4u7/++sv69etnO+20kx155JH29ttvl/j3Pn362OOPP+7+Tu+n9/3xxx/d6q677rqrq9k5ceLEUlvz4Ycftn333de6dOli9913n73++ut2+OGHR77VyQQBAKAKGjT0v6unZSdhNauZrVyjVxVl91Iz63Ncj6xfAwAAcqdBgwZuKoxWT91hhx2sY8eOVqtWLRcIGTdunJvK4vfuu+/atttuW+Lv+vbtay1btrRTTjnFxo8fb3vvvbe99NJLdtBBB7nf++CDD6xJkybu//V+et/zzjvPWrRoYUcffbQ9++yzLhCjwMumm27qfu/888+3Bx980M455xxr3ry5PfPMMy6rZOrUqbn78uVEJggAAAAAAFXARhttZGeddZYLMChDQ/9fu3btrL7Z1ltvbUOHDrUzzzzTrdiqwMbFF1+c8T0UcLn//vtdkOO5556z5cuX2+jRo91rfvrpJ7v33nvtkUcesdtvv939zoQJE+yPP/7Iql25QhAEAAAAAAA4J554YoktoYyQ77//3ubPn592C+25557F/7bxxhtb27ZtbcaMGe7vPvzwQ6tevXqJGiXKTtFUm3wgCAIAAAAAAJzGjRuX2BLe1Jfffvst7RZKzjbRn7WSjMyePdvq169vNWqUrMax4YYb5mWLEwQBAAAAAKAKUyaGJC9tu3Tp0lLf+tdffy3xdzNnznR/3mSTTQJtoc0228xNfVm0aFGJ10+bNi3Q+1UUQRAAAAAAAKoQZV1olRePV6D0nXfeKf47reCycOHCUt968ODBxX+nbA6t6tKhQweXzRHE7rvvbnXr1rXLL7+8ODtERVOfeuqpIG9XYawOAwAAAJRD2yEDy/FbJWnstXmN2jZj1TJbnfWrzb4+tV+AVwEodDvuuKMNGDDApk+fbldccYU1bNjQrRqjQqlejY7Jkye7VWCSKTtEK8HstttubpUZrRAzZsyYwJtUK9YMGjTITjrpJPc+TZs2dcVSjzvuOBsxYkTg9w2KTBAAAAAAAKoQZVlodZgffviheBUWLV17zTXX2IIFC9wqMi+//LIdf/zx1r59e/fNN9hgA+vdu7cNGTLEBVFef/11V+RUy+hqmVzPYYcd5laDkfXWW8+9Jrm+hwIuWp7Xc8QRR9h3331nN954oyu0+sknn7hVaPKBTBAAAAAAADLIlJWlKSOrVq1yU1CKiopisR2bNWvmlqX1t2fttdd2WSF+119/ffEfVfNDGRty7bXXpv0e/td4WR7JrrrqqhJ/peyTFi1aWM+ePYv//quvvkqZiRI2giAAAAAAACAUChBdcMEFbondiy++2GWPjB071p544gl78MEHQ/nMTAiCAAAAAACAUChD5tVXX3VTce6++25bsmSJWzHm6aeftmOPPTaUz8yEIAgAAAAAAAiNVocZODD74tJhoDAqAAAAAAAoCARBAAAAAABAQWA6DAAAQB61HZJ9enB1M2teo7bNWLXMVgdoe6ZVDqJuT6a2AECUqlevbitWrIjyI1EOq1evtlq1apXjN8uHTBAAAAAAQMGrXbu2C4JoFRPEg/pCfaK+yRUyQQAAAAAABa9hw4a2fPlymzt3ri1cuNBlhpTXmjVrrFq1+OQYxK09QSgDRAGQOnXquL7Jlfj0EgAAAAAAeVJUVGTNmjVzD9zZTL9IJBLuYV3/jYO4tSco9YH6Qn2ivskVMkEAAAAAADBzD9sbbrhhVttCGQsLFiyw+vXrZ5U9Epa4tSduyAQBAAAAAAAFgSAIAAAAAAAoCARBAAAAAABAQYh1EGTVqlX20Ucf2cSJE23p0qVpO2TatGk2fvx4W7JkSUF0GgAAAAAAyF5sgyCTJk2yJk2a2C677GJdu3a1zTbbzEaPHl3iG/7555/WpUsX23LLLW2//fZzhWjuu+++7LcCAAAAAACo8mIZBPn111+tW7du1qtXLxfomDFjhvvzMcccY7Nnzy7ulOOOO87++OMP++GHH1wWyP3332/nnnuujRkzpsp3HAAAAAAAyE4sl8h96KGHbJtttrH+/fu7b1O3bl174IEHrHbt2vbzzz/bRhttZN9++62NHTvWxo0bZ1tssYX7vdNPP91effVVGzhwoB1wwAHZbQkAAAAAAFClxTII8sILL7iARiKRsK+++soWLVpk22+/vQ0ZMqS4M9566y1bf/317V//+leJDjr00EOtd+/etmbNGqtWLXWiy+LFi92Px8su0XrK+qnq9B21feLyXePUnji1RWhPemybzOK0feLUlsI6rhIVvJxl//pcX1cKZd+pHqCn9Brd5QR5rXccpBPkPSvSnlzvN2Ee51Fvm7L6Koiwjqsg20bitO+EtW2Coj3cBwYVt30nCtWrl/8sFMsgyMyZM10AY+utt7bp06fbihUrrEGDBvbkk0/avvvu67ahpsxssskmpQIdLVq0cAVVf//9d5cxksqAAQPs+uuvL/VPCrasu+66UfRRXumgUKFZBZmy2VnCEqf2xKkt3o0PfZUafZVZnLZPnNpSSMdVzYATXmsEfJ0sWLAgp5eKQtl3mteonfV2Uzc1rl7LvW5N1q/O3FdRtyfX+02Yx3nU26YyHVdBto1UZF/O9b5TKOecoOK0feLUljDPOUHFbftEoWHDhuX+mNgFQZSh8ddff9kll1ziprUoq0N/PuOMM1xNkG+++caaNm3qaoXUqVOn1BfV1BmZP39+2iDIBRdc4N7Xo0yQjh07Wr169Vxx1apOB0VRUZHLpIlLECQu7WHbZBan7ROntngXv7jsx3FrD32Vn+NqZZAn4/8X9LW5voYWyr4zY9WyrG89vPGumauWWZAc1kx9FXV7cr3fhHkOjHrbSK63T1jHVZBtIxXZlyvLtgkqrL4KKk7tiVNbwjznBBW37RM3sQuCeFNYDj74YBf4EAUnBg8ebI0aNXIrxJx22mlu5Zh33nmn1PZU8EP07+koUOIFS/wUEIhDUCAK2s5x+r5xak+c2iK0Jz22TWZx2j5xakvhHFdFAS4n/ikw2b8+jGtoIew7QYIYojiXXhvk9Zn6Ksj7VaQ9Yew3YR3nUW8bCWP7hHFcBd02cdt3wtg2FUF7uA8MKm77TpxUIOk1HOutt56L6rZp06bEB2iaigIbmgYjmgrzyy+/2N9//13i91Qwde21184qHQYAAAAAAFR9sQuCyH777edWffGbNm2aqw/Stm1b99cHHnigS/N5/vnni39NxT6ffvppO+yww6p+zwEAAAAAgKzEbjqM3HjjjS4TpGfPnm5KzB9//GGXXnqpbbXVVm71F1FWSK9evezss892wZBWrVq5pXW1moz+CwAAAAAA4BfLIMjmm29u48ePt759+9quu+5q66yzjlsV5t5777Vatf5bCV3uu+8+N/Xl8ssvt3nz5tk222xjY8eOdcvpAgAAAAAA+MUyCCKdO3e2L774wtX8qF27dqmlcEXFXu688073888//7iACAAAAAAAQCqxDYJ4lAVSHgRAAAAAAABAJrEsjAoAAAAAAJBrBEEAAAAAAEBBiP10GAAAAAAAotB2yMCsP6a6mTWvUdtmrFpmq7N89den9svyFagoMkEAAAAAAEBBIAgCAAAAAAAKQoWnw6xatcqmTJlin3zyif3222+2aNEia968ubVu3dpatWplm2++eUFsSAAAAABIhSkWQHwEDoJMmjTJBg8ebCNHjrSFCxe6b1SnTh3bZJNNbNasWcV/16FDBzv//PPtmGOOsbXWWis+3xwAAAAAABSUQNNhzj33XNt1113t/ffft4svvtjee+89mzt3ri1evNi+/vprW7Bggf3xxx82YcIE22uvvezyyy+3Fi1a2MyZMwtq4wIAAAAAgPgIlAmy44472ocffmgdO3ZM+00aNmxou+++u/u59dZbbfjw4VatWqCYCwAAAAAAQIUFCoL07Nkzqw+uWbOmnXDCCVm9BgAAAAAAIJcCBUEAAACAsAUpJinVzax5jdo2Y9UyW51lI78+tV+WrwAAVCahzE+ZOHGide7c2Zo1a2Z77LGHffrpp5VpmwAAAAAAgCoocCbItGnTrH79+tagQYNSm+Woo45yxVMVCHn11VfdVJhvvvmmCm4+AAAAAHETJIuoIhlEUlmyiIJsG6nI9qks2waFIXAmyM8//2zbbLONvfLKKyW21PLly93yuGeccYZ17drVzjzzTFaFAQAAAAAAeRc4CNKtWzcbPHiw9e7d204//XRbunSp+zJrrbWWHXzwwda+fXvbb7/9rFOnTnbcccfl/YsCAAAAAIDCFjgIIvvvv7999dVXLvNDQQ/VApGhQ4fafffd54IgQ4YMsYceeqiwtzIAAAAAAMi7wDVBPKoJMnz4cHv22WftsMMOs1NOOcVuvPFGlw0CAAAAAAAQFxXKBPE79thj7YsvvrAvv/zSdtxxR/v888/j8h0BAAAAAAAqFgQZMWKEC35oNZjHH3/cmjZtaq+99pqdddZZtueee9ott9xiq1dnuzo7AAAAAABA7gXOBHnnnXfcCjBbbrmltW3b1q666ip74YUXXAv195MnT7YxY8ZYly5dbOrUqblvOQAAAAAAQBYC1wT56KOP7Mgjj7QbbrjBfVwikbAPPvjADj/8cPfnLbbYwgVKbr/9duvVq1dx0VQAAAAAAIB8CBwE2XXXXe2mm26y2rVrW82aNe3JJ5+0QYMGlfgO1atXt8suu8xOPvnkfHw3AAAQE4OGjgrQkoTVrGa2co1eWpTV6/sc1yOr3wcAAIUh8HSYTp062bBhw2zJkiU2b948tyTuQQcdlHKrNWnSpDC2JgAAAAAAiK3AmSDSvXt39wMAAAAAABB3gTNBAAAAAAAAKpNAQZCLL77YFTydPXt2ub7rN998Y6eddlqoq8SsWrWqXG0BAAAAAACFKVAQpGXLlnbzzTfbJptsYvvtt5/dc8899t5779lvv/1mixcvdkGPl156yf1Ox44dbZtttnEBkwYNGpR7K2+77ba24YYblvpZvnx58XtoRZprr73WNt10U1t33XWtc+fObtUaAAAAAACAZIFqgpxxxhl23HHH2YgRI+yFF16wq6++2gU/kjVt2tQtmTt06FC3ZG55rV692qZMmWLnnXeeC2z4aSUaz0UXXWQPPfSQ3Xnnnda6dWt7+OGHbc8993RL9bZt27a8HwcAAAAAAApAoCCI1K1b10499VT3o4yMadOmuUwQrRaz8cYb25ZbbmnrrbdeoE04a9YsFwg59NBD3VK8qWhFmgceeMCtStOrVy/3K7vvvrvLPBkwYIA9+uijgT4bAAAAAABUTYGDIH5FRUUu6KGfXPjll1/c22i6jVfro0aNkk0dNWqU+51jjjmm+COrV69uJ554ol111VUZgyDKWvFnrni1TRR40U9Vp++4Zs2a2HzXOLUnTm0R2pMe2yazOG2fOLWlsI6rRAUvZ9m/PvM1NPv3Kym714dxPQ9rX64eoKf0Gs1pDvJa7zhIJ8h7VqQ9mfoqSFskTu2pSFvK6qsg4rQfF1JfBdmXK7LvVKbjKoiw9mNvn8xWWH0VVJjbJ64UCyivnARBcm3GjBnuLfv162evvPKK+0J77723y/xQlonod1q0aOFqgfhtvfXW9tdff9mff/5pG2ywQcqmKVPk+uuvL/VvixYtKvV+VZEOiqVLl7oMnmx2lrDEqT1xaot340NfpUZfZRan7ROnthTScVUzUNUvsxoBXycLFixIu2NG3Z5MbQkqrH25eY3aWTdJ3dS4ei33ujVZvzpzX0Xdnkx9FaQtUpHtk+v2VKQtZR1XQcRpPy6kvgqyL1dk38n1fhxmXwUR1n4sceqroMLcPnHVsGHDcjctlkEQFVA98MAD3VSYSy65xAU8rrzySuvWrZt98cUXVqtWLZszZ07KQqvel9eUmnRBkAsuuMB69+5dvJGUCaJpNPXq1bP69euXe+NVVjoolL2z/vrrxyYIEpf2sG0yi9P2iVNbhPakx7bJz3G1MsiT8f8L+tpM19Cg7ylBXhvG9TysfXnGqmVZ31J4410zVy2zIDmsmbZP1O3JdVukItsn1+2pSFsk1/tynPbjQuorjqvcPmOFtR9LnPoqqDC3T1UQyyBI9+7d3Y9nl112sfbt27ssD02DOeKII9wDvEbIk6kmSVkXDNUz0U8yZUXEITMiCtWqVYvV941Te+LUFqE96bFtMovT9olTWwrnuCoKcDnxTznJ/vWZr6HZv59VoD1hXc/D2JeDBDFEcS69NsjrM22fIO9XkfaE0Za4tSesvgoqTvtxofQVx1X5pyqUVxj7scSpryoirO1TFVQg6TVabdq0cavNaPldadasmf3666+utoWfskZ0MW3SpEm0DQQAAAAAALEWyyCIltS94YYbSmw41fnQijBeTZCuXbu6uh/vvPNOid976aWXrEuXLqGNAAEAAAAAgMopJ9NhRo4caW+++WbaLdC8eXO7+OKLy72Fateu7QqXNm7c2E444QRXwPP00093RUsPOOAA9z6aHqNASN++fe21115zwZEnnnjCteX5558v92cBAAAAAIDCEDgIMn78eBf4uOmmm2zmzJn28ccfl9hiy5cvt++//94FJ/z1PcrjsMMOs0svvdTOPvtst0KMlsndcMMNXXBDgRHP8OHDbb/99rNNN93U1llnHfv777/t5ptvtsMPP7w8HwMAAAAAAApI4CDIhAkT7LHHHrNrr73WzjnnHPeTTNNXDjroILfSS7ZuueUWO/PMM+3zzz93RVC33357F+jwU0BEwZcpU6a4+iBa4SWbpXEAAAAAAEDhCBwEue666+zqq6/OWHtDAYk+ffrYPffcY/vss0/WW1VZJF4NkHRU9VZTY/QDAAAAAACQTuDCqMq+ePLJJ8vcsipe+sMPP5T5ewAAAAAAAGEKnAkyZMgQe+SRR1zh0t9++839+K1evdq++uorV6NDNT4AAAAAAADyKXAQpH///nbJJZdYzZo17f7777c77rij1PeoUaOGqwdy22235fM7AgAAAAAABA+CKPjRpEkTtwmvuuoqt4qLX1FRkTVq1MgFQgAAAAAAAPItJxGKevXquR8AAAAAAIC4ClwYNdkHH3xgL774ovvrJUuWWI8ePVwmSM+ePe2vv/6K6/cHAAAAAAAFIidBkEmTJlnXrl1t7ty5brOpGOq7775rvXr1sjfffNOuv/56W7BggQ0cONC+/fbbAtm0AAAAAAAgTnIyHeb555+3fffd18444wz33fTniy++2C6//HLbaKON7K677rJatWrZ9OnT7eWXX3aBEQAAAAAAgCjlJBNE01022WQT124FOn766Sfbb7/93J+32mormzNnjn366ad200032eLFi6P8fgAAAAAAAE5OgiA77LCDjRw50k2Bue6666xp06bWvn17SyQS9sILL7gskVdeecU23XRTGz9+PJseAAAAAABELifTYU4++WR78sknbbfddrNq1arZkCFD3H8ffPBBGzRokI0aNar4i6233nqRf0kAAAAAAICcBEFq165t77zzjn322WfWsGFD22yzzdyW7datm8sO6dy5M1saAAAAAADkVU6CIFKjRg3baaedSnyZLbbYwv0AAAAAAADkW06CIFrt5YMPPkj7XbRCzKmnnprv7woAAAAAAApY4CDIJ598Yu+9956dc8459uGHH9rgwYNLbMbly5fb7Nmz3aoxqhVCEAQAAAAAAORT4NVhhg0bZldffbWtXLnSrrjiCvv5559L/MyaNcumTZvmskAUKAEAAAAAAMinwJkg/fv3t6uuuspq1qyZtv0tW7Z0GSC33Xabvfjii/n8nlXWoKH/W3mn/BJWs5rZyjV6RVH5X2ZmfY7rkdXvAwAAAAAQF4GDIDNmzLCvv/7aDjjggIzfRZkiU6ZMicv3BQAAAADERNshA7NuSXUza16jts1YtcxWZ/1qs69P7RfgVagqAgdB7rrrLhs0aJAtWrTIFi9ebAsXLiyxTVavXm1fffWV3XzzzbbHHntUle0FAAAAAAAqqcBBkBtuuMFOO+00Nx3m1ltvtTvuuCPlJth5553t9ttvr6SbBwAAAAAAVBWBgyD16tVzP3LeeefZMcccU2KbFBUVWbNmzaxx48ZVZVsBAAAAAIBKLHAQxG/jjTd2PwAAAAAAAHEVeIncZFOnTrU33njD/fXy5cvdVJn27dvbJZdcYitWrIjr9wcAAAAAAAUiJ0GQzz//3Lbbbjv77LPP3GbTkrjPPPOM7bDDDq54qmqG/P333zZs2DCbNWtWgWxaAAAAAAAQJzmZDvP0009bly5dXNaHPPvss3bBBRfYjTfeaFtvvbU9+uijtu6669q4cePsscces7Fjx8ZpGwAAAAAAgAKQk0yQBQsWWJs2bdzmmj17tn377bfWo0cP9+dtt93WfvrpJ5cZcs8999iff/5ZAJsVAAAAAADETU6CINtss42NGTPGpk2b5qbCNGzY0E2PEdUJ2WuvvezTTz+1Lbfc0kaMGJH1NtDqM0ceeaQtWbKk1Gv1/ieffLL7jCuuuIIgCwAAAAAASCknQZBevXpZrVq1XJBj4MCBLhhRo0YNGzJkiN1+++3Ws2fP4g9v0aJFVl2h6TPKIFHwJLnAqqbh7LfffrZs2TLbdddd7aWXXnL//eOPP7L6DAAAAAAAUPXlJAhSp04dmzx5so0aNco+/PBDO//8892W22mnnVxg4thjjw20JefOnWsXXXSRywJJphVoLrzwQld7RAVXr7/+eps4caLLFrn33nsDfR4AAAAAAKi6clIYVdZbbz076KCDSmwpTZPRT1AKprRr18769Oljzz//fIm3GT16tM2bN8/69etX/PeahnPSSSfZ4MGD7YYbbkj7sYsXL3Y/HtUxkdWrV7ufyiVRweZm9/owto/ec82aNaG8d7bi1BZvn4zLtolbe+irzOK0feLUlrjtx+G2J7vze2nZvz7zNSL79yspu9dXputV9WwvVmbuNRrJCvJab79LJ8h7VqQ9mfoqSFsqun1y3Z6KbJuy+iqIsM7J9NV/nyU4rlKL07Yp67gKsi9X5DivTNerOKtevfw9l5MgiLJAvvrqq7TbRMGJgw8+OKtt9tprr9kLL7xgX3zxhf3666+lXjt16lR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},
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},
{
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" tubing | \n",
" 1 | \n",
" 6.25 | \n",
" 18.00 | \n",
" 11.75 | \n",
" 65.3 | \n",
"
\n",
" \n",
" | 8 | \n",
" ÜRT-11 | \n",
" tubing | \n",
" 2 | \n",
" 13.75 | \n",
" 15.50 | \n",
" 1.75 | \n",
" 11.3 | \n",
"
\n",
" \n",
" | 9 | \n",
" ÜRT-11 | \n",
" tubing | \n",
" 3 | \n",
" 4.00 | \n",
" 16.00 | \n",
" 12.00 | \n",
" 75.0 | \n",
"
\n",
" \n",
" | 10 | \n",
" ÜRT-16 | \n",
" casing | \n",
" 1 | \n",
" 7.00 | \n",
" 10.40 | \n",
" 3.40 | \n",
" 32.7 | \n",
"
\n",
" \n",
" | 11 | \n",
" ÜRT-16 | \n",
" casing | \n",
" 2 | \n",
" 7.00 | \n",
" 10.00 | \n",
" 3.00 | \n",
" 30.0 | \n",
"
\n",
" \n",
" | 12 | \n",
" ÜRT-16 | \n",
" casing | \n",
" 3 | \n",
" 6.75 | \n",
" 10.00 | \n",
" 3.25 | \n",
" 32.5 | \n",
"
\n",
" \n",
" | 13 | \n",
" ÜRT-16 | \n",
" tubing | \n",
" 1 | \n",
" 5.00 | \n",
" 11.00 | \n",
" 6.00 | \n",
" 54.5 | \n",
"
\n",
" \n",
" | 14 | \n",
" ÜRT-16 | \n",
" tubing | \n",
" 2 | \n",
" 4.90 | \n",
" 11.25 | \n",
" 6.35 | \n",
" 56.4 | \n",
"
\n",
" \n",
" | 15 | \n",
" ÜRT-16 | \n",
" tubing | \n",
" 3 | \n",
" 5.00 | \n",
" 11.00 | \n",
" 6.00 | \n",
" 54.5 | \n",
"
\n",
" \n",
" | 16 | \n",
" ÜRT-17 | \n",
" casing | \n",
" 1 | \n",
" 8.50 | \n",
" 13.00 | \n",
" 4.50 | \n",
" 34.6 | \n",
"
\n",
" \n",
" | 17 | \n",
" ÜRT-17 | \n",
" casing | \n",
" 2 | \n",
" 9.50 | \n",
" 12.50 | \n",
" 3.00 | \n",
" 24.0 | \n",
"
\n",
" \n",
" | 18 | \n",
" ÜRT-17 | \n",
" casing | \n",
" 3 | \n",
" 12.00 | \n",
" 13.50 | \n",
" 1.50 | \n",
" 11.1 | \n",
"
\n",
" \n",
" | 19 | \n",
" ÜRT-17 | \n",
" tubing | \n",
" 1 | \n",
" 6.25 | \n",
" 11.00 | \n",
" 4.75 | \n",
" 43.2 | \n",
"
\n",
" \n",
" | 20 | \n",
" ÜRT-17 | \n",
" tubing | \n",
" 2 | \n",
" 4.50 | \n",
" 10.50 | \n",
" 6.00 | \n",
" 57.1 | \n",
"
\n",
" \n",
" | 21 | \n",
" ÜRT-17 | \n",
" tubing | \n",
" 3 | \n",
" 5.00 | \n",
" 8.00 | \n",
" 3.00 | \n",
" 37.5 | \n",
"
\n",
" \n",
" | 22 | \n",
" ÜRT-6 | \n",
" casing | \n",
" 1 | \n",
" 7.00 | \n",
" 11.50 | \n",
" 4.50 | \n",
" 39.1 | \n",
"
\n",
" \n",
" | 23 | \n",
" ÜRT-6 | \n",
" casing | \n",
" 2 | \n",
" 3.50 | \n",
" 10.50 | \n",
" 7.00 | \n",
" 66.7 | \n",
"
\n",
" \n",
" | 24 | \n",
" ÜRT-6 | \n",
" casing | \n",
" 3 | \n",
" 5.50 | \n",
" 11.50 | \n",
" 6.00 | \n",
" 52.2 | \n",
"
\n",
" \n",
"
\n",
"
\n",
"\n",
"
\n",
" \n",
" \n",
" | \n",
" well | \n",
" circ_days | \n",
" bome_2025_12_25 | \n",
" circ_interval_m | \n",
" circ_thenardite_pct | \n",
" circ_thenardite_pct_recomputed | \n",
" ideal_interval_m | \n",
"
\n",
" \n",
" \n",
" \n",
" | 0 | \n",
" ÜRT-1 | \n",
" 154.0 | \n",
" 19.0 | \n",
" 8.75 | \n",
" 29.19 | \n",
" 29.50 | \n",
" 14.09 | \n",
"
\n",
" \n",
" | 1 | \n",
" ÜRT-2 | \n",
" 0.0 | \n",
" 0.0 | \n",
" 9.00 | \n",
" 26.10 | \n",
" 26.11 | \n",
" 13.79 | \n",
"
\n",
" \n",
" | 2 | \n",
" ÜRT-3 | \n",
" 0.0 | \n",
" 0.0 | \n",
" 10.00 | \n",
" 33.00 | \n",
" 32.86 | \n",
" 11.82 | \n",
"
\n",
" \n",
" | 3 | \n",
" ÜRT-5 | \n",
" 0.0 | \n",
" 0.0 | \n",
" 10.00 | \n",
" 37.00 | \n",
" 37.00 | \n",
" 10.55 | \n",
"
\n",
" \n",
" | 4 | \n",
" ÜRT-6 | \n",
" 0.0 | \n",
" 0.0 | \n",
" 10.00 | \n",
" 30.00 | \n",
" 30.00 | \n",
" 13.55 | \n",
"
\n",
" \n",
" | 5 | \n",
" ÜRT-7 | \n",
" 0.0 | \n",
" 0.0 | \n",
" 10.00 | \n",
" 36.00 | \n",
" 35.97 | \n",
" 10.60 | \n",
"
\n",
" \n",
" | 6 | \n",
" ÜRT-8 | \n",
" 0.0 | \n",
" 0.0 | \n",
" 10.00 | \n",
" 21.50 | \n",
" 22.55 | \n",
" 16.06 | \n",
"
\n",
" \n",
" | 7 | \n",
" ÜRT-11 | \n",
" 76.0 | \n",
" 12.0 | \n",
" 8.00 | \n",
" 28.89 | \n",
" 28.89 | \n",
" 10.48 | \n",
"
\n",
" \n",
" | 8 | \n",
" ÜRT-12 | \n",
" 0.0 | \n",
" 0.0 | \n",
" 8.00 | \n",
" 31.25 | \n",
" 31.25 | \n",
" 12.67 | \n",
"
\n",
" \n",
" | 9 | \n",
" ÜRT-13 | \n",
" 0.0 | \n",
" 0.0 | \n",
" 11.00 | \n",
" 27.00 | \n",
" 27.73 | \n",
" 13.57 | \n",
"
\n",
" \n",
" | 10 | \n",
" ÜRT-14 | \n",
" 0.0 | \n",
" 0.0 | \n",
" 10.00 | \n",
" 31.00 | \n",
" 31.17 | \n",
" 12.01 | \n",
"
\n",
" \n",
" | 11 | \n",
" ÜRT-16 | \n",
" 69.0 | \n",
" 24.0 | \n",
" 8.00 | \n",
" 39.25 | \n",
" 39.56 | \n",
" 3.90 | \n",
"
\n",
" \n",
" | 12 | \n",
" ÜRT-17 | \n",
" 0.0 | \n",
" 0.0 | \n",
" 10.00 | \n",
" 26.80 | \n",
" 26.00 | \n",
" 14.04 | \n",
"
\n",
" \n",
" | 13 | \n",
" ÜRT-18 | \n",
" 0.0 | \n",
" 0.0 | \n",
" 10.00 | \n",
" 35.90 | \n",
" 36.50 | \n",
" 10.75 | \n",
"
\n",
" \n",
" | 14 | \n",
" ÜRT-19 | \n",
" 0.0 | \n",
" 0.0 | \n",
" 11.00 | \n",
" 33.60 | \n",
" 33.75 | \n",
" 11.68 | \n",
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\n",
" \n",
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\n",
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]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": "fig, ax = plt.subplots(figsize=(7, 5))\nok = cavern.dropna(subset=[\"circ_thenardite_pct_recomputed\"])\nax.scatter(ok.circ_thenardite_pct, ok.circ_thenardite_pct_recomputed, color=PAL[\"accent\"])\nfor _, r in ok.iterrows(): ax.annotate(r.well, (r.circ_thenardite_pct, r.circ_thenardite_pct_recomputed), fontsize=7, xytext=(3,3), textcoords=\"offset points\")\nlim = [15, 50]; ax.plot(lim, lim, \"k--\", lw=1); ax.set_xlim(lim); ax.set_ylim(lim)\nax.set_xlabel(\"Saha hesabı: sirkülasyon aralığı tenardit %\"); ax.set_ylabel(\"Bu notebook: kalınlık-ağırlıklı tenardit %\")\nax.set_title(\"Sirkülasyon aralığı tenardit % — saha vs yeniden hesap\"); plt.tight_layout(); plt.savefig(f\"{FIG_DIR}/08_kaverna_dogrulama.png\"); plt.show()"
},
{
"cell_type": "markdown",
"id": "88133d62",
"metadata": {
"id": "88133d62"
},
"source": "## 8. Karot fotoğraf indeksi (`photos`)\n1.217 fotoğraf; dosya adından kutu numarası ve derinlik aralığı çıkarılabilenler 423 adet (`S12 (48,30-52,40m).jpeg` gibi). Bu indeks ileride **görüntü tabanlı litoloji sınıflandırma** (CNN / quantum-kernel) için etiket eşlemesinin temelidir: `lith` tablosu ile derinlik üzerinden birleştirilir."
},
{
"cell_type": "code",
"execution_count": null,
"id": "e1e292a6",
"metadata": {
"execution": {
"iopub.execute_input": "2026-11-03T19:59:20.796841Z",
"iopub.status.busy": "2026-11-03T19:59:20.796607Z",
"iopub.status.idle": "2026-11-03T19:59:20.828827Z",
"shell.execute_reply": "2026-11-03T19:59:20.827239Z"
},
"id": "e1e292a6",
"outputId": "15f58af1-ff4d-4949-b9d3-b96962dada3d"
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"1217 fotoğraf; 423 tanesinde derinlik aralığı var\n"
]
},
{
"data": {
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" 0.000 | \n",
" 0.500 | \n",
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" \n",
" | Lojistik regresyon | \n",
" 0.752 | \n",
" 0.688 | \n",
" 0.573 | \n",
" 0.799 | \n",
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\n",
" \n",
" | Random forest | \n",
" 0.742 | \n",
" 0.703 | \n",
" 0.607 | \n",
" 0.819 | \n",
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" 0.732 | \n",
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" 0.690 | \n",
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" 0.762 | \n",
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