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End-to-end seismic interpretation workflow from SEG-Y loading through signal processing, rock physics, and visualization. Use when working with seismic data analysis pipelines.
デフォルトでは、最初にソースを確認する Prompt が選択されています。直接コマンドに切り替えるか、ローカルコピーをダウンロードすることもできます。
インストールを決める前に、SKILL.md と SkillsMP に表示されている付属ファイルをお読みください。
Codex または Claude でインストール この Prompt をコピーして Codex、Claude、または他のアシスタントに貼り付けると、Skill ページを確認してインストールできます。
直接コマンドでは確認用 Prompt が省略されます。実行前にソースを確認してください。
npx skills add https://github.com/SteadfastAsArt/geoscience-skills --skill seismic-interpretationコマンドは1行のまま表示されます。コピー前に横へスクロールして全体を確認してください。
ローカルで確認しますか？SkillsMP が現在取得できるファイルをダウンロードできます。
Spatial and spatiotemporal regression with GNNWR (Geographically Neural Network Weighted Regression). Use when Claude needs to: (1) Build spatially varying coefficient regression models, (2) Analyze geographic non-stationarity in spatial data, (3) Generate spatial coefficient maps for publication, (4) Run spatiotemporal regression with GTNNWR, (5) Scale geographically weighted regression to large datasets (N > 10k) with KNN mode, (6) Diagnose spatial model performance with F-tests, AIC, and residual maps.
Foundation skill for the geoscience skills library. Routes user intent to the correct domain skills, slash commands, and workflow skills. Loaded automatically at session start via SessionStart hook.
Geophysical equations and rock physics calculations for seismic analysis. Use when Claude needs to: (1) Calculate AVO responses (Zoeppritz, Shuey, Aki-Richards), (2) Perform Gassmann fluid substitution, (3) Generate seismic wavelets (Ricker, Ormsby), (4) Compute reflectivity and synthetic seismograms, (5) Calculate elastic moduli from velocities, (6) Apply Gardner/Castagna empirical relations, (7) Model rock physics effects.
SOC 職業分類に基づく
SKILL.md を表示中
| name | seismic-interpretation |
| skill_type | workflow |
| description | End-to-end seismic interpretation workflow from SEG-Y loading through signal processing, rock physics, and visualization. Use when working with seismic data analysis pipelines. |
| version | 1.0.0 |
| author | Geoscience Skills |
| license | MIT |
| tags | ["Seismic","Interpretation","SEG-Y","Rock Physics","Workflow","AVO","Processing"] |
| dependencies | ["segyio","obspy","bruges","pyvista"] |
| complements | ["segyio","obspy","bruges","disba","pyvista"] |
| workflow_role | processing |
End-to-end pipeline for seismic data analysis, from loading SEG-Y files through signal processing, rock physics modelling, and 3D visualization.
segyio obspy bruges disba pyvista
[SEG-Y I/O] --> [Signal Proc] --> [Rock Physics] --> [Dispersion] --> [3D Viz]
| | | | |
Load traces Filter/FFT AVO modelling Surface waves Volume render
Read headers Instrument resp Fluid sub Phase velocity Slice display
3D geometry Spectral anal Synthetics Inversion Horizon pick
| Question | If Yes | If No |
|---|---|---|
| Working with SEG-Y files? | Start with segyio | Use obspy for miniSEED/SAC |
| Need frequency filtering or spectral analysis? | Use obspy signal tools | Skip to rock physics |
| Performing AVO or fluid substitution? | Use bruges | Skip to visualization |
| Analysing surface waves (MASW/SASW)? | Use disba for dispersion | Skip disba |
| Need 3D volume rendering? | Use pyvista | Use matplotlib for 2D |
import segyio
import numpy as np
# Load and inspect SEG-Y
with segyio.open('survey.sgy', 'r', iline=189, xline=193) as f:
n_traces = f.tracecount
n_samples = len(f.samples)
dt = f.samples[1] - f.samples[0] # ms
cube = segyio.tools.cube(f) # (ilines, xlines, samples)
cdp_x = f.attributes(segyio.TraceField.CDP_X)[:]
cdp_y = f.attributes(segyio.TraceField.CDP_Y)[:]
from obspy import Trace, Stream
from obspy.signal.filter import bandpass
# Convert numpy trace to obspy for processing
tr = Trace(data=cube[50, 100, :].astype(np.float64))
tr.stats.sampling_rate = 1000.0 / dt # Hz
tr.stats.delta = dt / 1000.0 # seconds
# Bandpass filter
tr.filter('bandpass', freqmin=5, freqmax=80, corners=4, zerophase=True)
# Spectral analysis
from obspy.signal.tf_misfit import cwt
scalogram = cwt(tr.data, dt=tr.stats.delta, w0=6, fmin=1, fmax=100, nf=50)
from bruges.reflection import zoeppritz, shuey
from bruges.filters import ricker
from bruges.rockphysics import gassmann
from scipy.signal import convolve
# AVO modelling
theta = np.arange(0, 45, 1)
Rpp = zoeppritz(vp1, vs1, rho1, vp2, vs2, rho2, theta)
# Fluid substitution
vp_new, vs_new, rho_new = gassmann(
vp_sat, vs_sat, rho_sat,
k_mineral, rho_mineral,
k_brine, rho_brine,
k_oil, rho_oil,
porosity
)
# Synthetic seismogram
impedance = vp * rho
rc = np.diff(impedance) / (impedance[:-1] + impedance[1:])
_, wavelet = ricker(duration=0.128, dt=0.001, f=25)
synthetic = convolve(rc, wavelet, mode='same')
from disba import PhaseDispersion
# Define velocity model (thickness, Vp, Vs, density)
velocity_model = disba.PhaseDispersion(
thickness=[5, 10, 20, 0], # m (0 = half-space)
velocity_p=[300, 600, 1200, 2500],
velocity_s=[150, 300, 600, 1200],
density=[1.8, 1.9, 2.1, 2.4]
)
# Compute Rayleigh wave dispersion
pd = velocity_model(wave="rayleigh", mode=0, period=np.linspace(0.01, 1.0, 50))
import pyvista as pv
# Create structured grid from seismic cube
grid = pv.ImageData(dimensions=cube.shape)
grid.point_data['amplitude'] = cube.flatten(order='F')
# Volume rendering
plotter = pv.Plotter()
plotter.add_volume(grid, scalars='amplitude', cmap='seismic', opacity='sigmoid')
plotter.show()
# Inline slice
inline_slice = grid.slice(normal='x', origin=grid.center)
plotter = pv.Plotter()
plotter.add_mesh(inline_slice, scalars='amplitude', cmap='seismic')
plotter.show()
- [ ] Load SEG-Y with `segyio.open()`, check trace count and geometry
- [ ] Inspect text and binary headers for acquisition parameters
- [ ] Read trace headers to verify coordinates and fold
- [ ] Compute amplitude statistics (min, max, RMS) per trace
- [ ] Display representative inlines/crosslines with matplotlib
- [ ] Check for dead traces (zero or constant amplitude)
- [ ] Verify sample rate and recording length
- [ ] Load near and far angle stacks from SEG-Y (segyio)
- [ ] Extract well log Vp, Vs, density at target zone (lasio/welly)
- [ ] Compute AVO response with `bruges.reflection.zoeppritz()`
- [ ] Classify AVO anomaly (Class I-IV) from intercept and gradient
- [ ] Perform Gassmann fluid substitution for scenario modelling
- [ ] Generate synthetic seismogram and compare to seismic
- [ ] Create AVO crossplot (intercept vs gradient)
- [ ] Load shot gathers from SEG-Y (segyio)
- [ ] Apply f-k or phase-shift transform to extract dispersion image
- [ ] Pick fundamental mode dispersion curve
- [ ] Invert dispersion curve for 1D Vs profile using disba
- [ ] Repeat for multiple shot points
- [ ] Interpolate Vs profiles into 2D section (verde)
- [ ] Visualize with pyvista or matplotlib
- [ ] Load seismic section (segyio) and well logs (lasio)
- [ ] Compute acoustic impedance from Vp and density logs
- [ ] Generate reflectivity series from impedance
- [ ] Create Ricker wavelet at dominant frequency (bruges)
- [ ] Convolve reflectivity with wavelet for synthetic
- [ ] Extract seismic trace at well location
- [ ] Cross-correlate synthetic with seismic to find time shift
- [ ] Apply bulk shift and stretch/squeeze for best tie
Use the seismic interpretation workflow when:
Use individual domain skills when:
segyio alone)obspy alone)bruges alone)| Issue | Solution |
|---|---|
| SEG-Y geometry not detected | Specify iline= and xline= byte positions in segyio.open() |
| obspy Trace stats wrong | Set sampling_rate and delta correctly from SEG-Y sample interval |
| AVO angles unrealistic | Verify angle range matches acquisition (typically 0-40 degrees) |
| Synthetic does not tie | Check time-depth relationship and wavelet phase |
| Memory error on large cube | Load inline-by-inline instead of full cube |