Refraction_3 / app.py
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import gradio as gr
import numpy as np
import matplotlib.pyplot as plt
# --- 輔助函數:產生 Ricker 震波 ---
def ricker_wavelet(t, f=25.0):
""" 產生一個 Ricker 震波 (墨西哥帽函數) """
t = t - 2.0 / f # 將震波峰值對齊時間點
p = (np.pi * f * t) ** 2
return (1 - 2 * p) * np.exp(-p)
# --- 核心計算與繪圖函數 ---
# 【*** FIX 1: Add scenario_name_val as a function parameter ***】
def plot_seismic_exploration(scenario_name_val, v1, v2, v3, h1, h2, x_max, num_receivers, gain):
"""
根據輸入的地層參數,計算並繪製所有探勘圖表。
"""
# === PART 1: 物理計算 (升級至三層模型) ===
valid_model = True
error_msg = ""
if v2 <= v1 or v3 <= v2:
valid_model = False
error_msg = "### ⚠️ 模型警告\n速度必須隨深度增加 (V3 > V2 > V1),折射波分析可能無效。"
# 計算關鍵物理量 (第一層介面)
t0_1 = (2 * h1) / v1
# 計算關鍵物理量 (第二層介面)
t0_2 = (2 * h1 / v1) + (2 * h2 / v2)
# === PART 2: 繪製地質模型圖 (新圖表) ===
fig0, ax0 = plt.subplots(figsize=(10, 2))
ax0.set_xlim(0, x_max)
ax0.set_ylim(-(h1 + h2) * 1.5, 5)
ax0.axhline(0, color='saddlebrown', linewidth=3)
ax0.axhline(-h1, color='gray', linestyle='--')
ax0.axhline(-(h1+h2), color='darkgray', linestyle='--')
ax0.fill_between([0, x_max], 0, -h1, color='sandybrown', alpha=0.6)
ax0.fill_between([0, x_max], -h1, -(h1+h2), color='darkkhaki', alpha=0.6)
ax0.fill_between([0, x_max], -(h1+h2), -(h1 + h2) * 1.5, color='dimgray', alpha=0.6)
ax0.text(x_max/2, -h1/2, f'Layer 1\nV1 = {v1:.0f} m/s\nh1 = {h1:.0f} m', ha='center', va='center', fontsize=9, color='black')
ax0.text(x_max/2, -h1-h2/2, f'Layer 2\nV2 = {v2:.0f} m/s\nh2 = {h2:.0f} m', ha='center', va='center', fontsize=9, color='black')
ax0.text(x_max/2, -(h1+h2)*1.25, f'Layer 3 (Basement)\nV3 = {v3:.0f} m/s', ha='center', va='center', fontsize=9, color='white')
ax0.set_title("Geological Model Cross-section")
ax0.set_ylabel("Depth (m)")
ax0.set_yticks([0, -h1, -(h1+h2)])
ax0.set_xticks([])
fig0.tight_layout(pad=1.1)
# === PART 3: 繪製 T-X 走時曲線圖 ===
x_continuous = np.linspace(0, x_max, 500)
# 反射波 (使用RMS速度近似)
v_rms_2 = np.sqrt((v1**2 * 2*h1/v1 + v2**2 * 2*h2/v2) / (2*h1/v1 + 2*h2/v2))
t_refl_1 = np.sqrt(t0_1**2 + (x_continuous / v1)**2)
t_refl_2 = np.sqrt(t0_2**2 + (x_continuous / v_rms_2)**2)
fig1, ax1 = plt.subplots(figsize=(10, 6))
ax1.plot(x_continuous, t_refl_1, 'm:', linewidth=2, label='Reflection 1 (from Layer 2)')
ax1.plot(x_continuous, t_refl_2, 'c:', linewidth=2, label='Reflection 2 (from Layer 3)')
# 折射波
if valid_model:
theta_c12 = np.arcsin(v1 / v2)
ti_12 = (2 * h1 * np.cos(theta_c12)) / v1
t_refr_12 = (x_continuous / v2) + ti_12
ax1.plot(x_continuous, t_refr_12, 'g--', label='Refraction (from Layer 2)')
ti_23 = 2 * h1 * np.sqrt(v3**2 - v1**2)/(v1*v3) + 2 * h2 * np.sqrt(v3**2 - v2**2)/(v2*v3)
t_refr_23 = (x_continuous / v3) + ti_23
ax1.plot(x_continuous, t_refr_23, 'y--', label='Refraction (from Layer 3)')
ax1.set_title("1. Travel-Time (T-X) Curve")
ax1.legend(fontsize='small')
ax1.grid(True)
ax1.set_xlim(0, x_max)
y_max = np.max(t_refl_2) * 1.1
ax1.set_ylim(0, y_max)
fig1.tight_layout(pad=1.1)
# === PART 4: 繪製視覺化震測剖面圖 ===
fig2, ax2 = plt.subplots(figsize=(10, 5))
receiver_x = np.linspace(0, x_max, int(num_receivers))
# 反射波到時
t_refl_1_rx = np.sqrt(t0_1**2 + (receiver_x / v1)**2)
t_refl_2_rx = np.sqrt(t0_2**2 + (receiver_x / v_rms_2)**2)
wavelet_duration = y_max / 10
wavelet_t = np.linspace(0, wavelet_duration, 100)
for i in range(int(num_receivers)):
# 繪製第一層反射
wavelet_amp_1 = ricker_wavelet(wavelet_t, f=40) * gain
x_trace_1 = receiver_x[i] + wavelet_amp_1
y_trace_1 = t_refl_1_rx[i] - wavelet_duration/2 + wavelet_t
ax2.plot(x_trace_1, y_trace_1, 'k-', linewidth=0.8)
ax2.fill_betweenx(y_trace_1, receiver_x[i], x_trace_1, where=(x_trace_1 > receiver_x[i]), color='black')
# 繪製第二層反射
wavelet_amp_2 = ricker_wavelet(wavelet_t, f=30) * gain * 0.8 # Deeper reflections are weaker
x_trace_2 = receiver_x[i] + wavelet_amp_2
y_trace_2 = t_refl_2_rx[i] - wavelet_duration/2 + wavelet_t
ax2.plot(x_trace_2, y_trace_2, 'b-', linewidth=0.8)
ax2.fill_betweenx(y_trace_2, receiver_x[i], x_trace_2, where=(x_trace_2 > receiver_x[i]), color='blue')
ax2.set_title(f"2. Visualized Seismic Profile ({int(num_receivers)} Traces)")
ax2.set_ylim(y_max, -y_max*0.05)
ax2.set_xlim(-x_max * 0.05, x_max * 1.05)
fig2.subplots_adjust(left=0.1, right=0.98, top=0.9, bottom=0.15)
# === PART 5: 準備探勘日誌 ===
log_md = f"""
### 📝 現場探勘日誌
**任務目標**: {scenario_name_val}
**儀器設定**: {int(num_receivers)} 個測站, 測線長度 {x_max} 公尺。
**初步分析**:
- **第一介面反射 (黑色震波)**: 雙程走時 (TWT) 約 **{t0_1*1000:.1f} ms**。
- **第二介面反射 (藍色震波)**: 雙程走時 (TWT) 約 **{t0_2*1000:.1f} ms**。
{error_msg}
"""
return fig0, fig1, fig2, log_md
# --- Gradio 介面與任務設定 ---
scenarios = {
"自訂模式 (Custom Mode)": {"v1": 800, "v2": 2500, "v3": 4500, "h1": 20, "h2": 50},
"尋找淺層地下水 (Find Groundwater)": {"v1": 500, "v2": 2200, "v3": 3500, "h1": 15, "h2": 40},
"桃園台地工程鑽探 (Taoyuan Engineering)": {"v1": 600, "v2": 1800, "v3": 3000, "h1": 10, "h2": 30},
"油氣田探勘 (Oil & Gas Prospecting)": {"v1": 1500, "v2": 2800, "v3": 4200, "h1": 100, "h2": 250},
}
def update_sliders(scenario_key):
params = scenarios[scenario_key]
return params['v1'], params['v2'], params['v3'], params['h1'], params['h2']
with gr.Blocks(theme=gr.themes.Soft()) as demo:
scenario_name = gr.State("自訂模式 (Custom Mode)")
gr.Markdown("# 地球物理探勘總部 🛰️")
with gr.Row():
with gr.Column(scale=1):
gr.Markdown("### 🎯 1. 選擇探勘任務")
scenario_dropdown = gr.Dropdown(list(scenarios.keys()), label="Select Mission", value="自訂模式 (Custom Mode)")
gr.Markdown("### ⚙️ 2. 微調地層參數")
v1_slider = gr.Slider(label="V1 (m/s)", minimum=300, maximum=5000, value=800, step=50)
h1_slider = gr.Slider(label="h1 (m)", minimum=5, maximum=500, value=20, step=5)
v2_slider = gr.Slider(label="V2 (m/s)", minimum=500, maximum=6000, value=2500, step=50)
h2_slider = gr.Slider(label="h2 (m)", minimum=10, maximum=1000, value=50, step=10)
v3_slider = gr.Slider(label="V3 (m/s)", minimum=1000, maximum=8000, value=4500, step=50)
gr.Markdown("### 📡 3. 設定儀器")
xmax_slider = gr.Slider(label="最大觀測距離 (m)", minimum=100, maximum=2000, value=500, step=50)
receivers_slider = gr.Slider(label="測站數量", minimum=10, maximum=200, value=50, step=5)
gain_slider = gr.Slider(label="剖面增益", minimum=1, maximum=20, value=4, step=1)
submit_btn = gr.Button("🚀 發射震波!", variant="primary")
with gr.Column(scale=2):
gr.Markdown("### 🗺️ 地質模型")
plot_output0 = gr.Plot(label="Geological Model")
gr.Markdown("### 📊 探勘數據")
plot_output1 = gr.Plot(label="走時-距離圖")
plot_output2 = gr.Plot(label="視覺化震測剖面圖")
with gr.Row():
log_output = gr.Markdown("### 📝 現場探勘日誌\n請選擇任務或調整參數,然後點擊「發射震波!」")
# --- 事件監聽 ---
scenario_dropdown.change(
fn=update_sliders,
inputs=scenario_dropdown,
outputs=[v1_slider, v2_slider, v3_slider, h1_slider, h2_slider]
)
scenario_dropdown.change(lambda x: x, inputs=scenario_dropdown, outputs=scenario_name)
# 【*** FIX 2: Add scenario_name to the inputs list ***】
submit_btn.click(
fn=plot_seismic_exploration,
inputs=[scenario_name, v1_slider, v2_slider, v3_slider, h1_slider, h2_slider, xmax_slider, receivers_slider, gain_slider],
outputs=[plot_output0, plot_output1, plot_output2, log_output]
)
gr.Markdown(
"""
---
### 🧠 總工程師的挑戰
1. **看見儲油構造**: 在「油氣田探勘」任務中,來自第二介面(藍色震波)的反射同相軸呈現一個向上彎曲的「背斜」形狀,這正是油氣最喜歡聚集的地方!你能透過微調 `h1` 和 `h2` 讓這個構造更明顯嗎?
2. **折射的極限**: 試著在自訂模式中,將 `V2` 調得比 `V1` 慢,看看走時圖和日誌會出現什麼警告?這在真實地質中稱為「低速帶」,是折射法的一大挑戰。
3. **解析度問題**: 將「測站數量」調到最低,再慢慢增加。你需要多少個測站,才能清楚地分辨出剖面圖中來自兩個不同介面的反射波?這就是探勘的「解析度」概念。
"""
)
gr.HTML("""
<footer style="text-align:center; margin-top: 30px; color:grey;">
<p>「創意的發揮是一種學習,過程中,每個人同時是學生也是老師。」</p>
<p>地球物理探勘總部 &copy; 2025 - 由 Gemini 根據課程文件與靈感生成</p>
</footer>
""")
if __name__ == "__main__":
demo.launch()