kucherenko/petropowers/exploration

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Guide AI agents through oil & gas exploration workflow.

Install

npx vskill@latest install kucherenko/petropowers/exploration

SKILL.md

Skill: Exploration Pipeline

Guide AI agents through oil & gas exploration workflow.

Purpose

Support geoscientists in discovering hydrocarbon prospects through seismic interpretation, well log analysis, and risk assessment.

Roles

  • Geologist - Subsurface structure, stratigraphy, depositional systems
  • Geophysicist - Seismic acquisition, processing, interpretation
  • Petrophysicist - Well log analysis, formation evaluation
  • Seismic Interpreter - Horizon picking, fault mapping, attribute analysis

Data Types

DataFormatSkill Reference
Seismic volumesSEG-Ypetropowers:oil-gas-cross-cutting/segy-operations
Well logsLASpetropowers:oil-gas-cross-cutting/well-log-analysis
Geological modelsRESQML, proprietaryCustom parsing needed
Core samplesPhotos, reportsUnstructured analysis
Satellite/gravityGeoTIFF, gridsGeospatial tools

Workflow

Phase 1: Seismic Data Review
  1. Load SEG-Y data
  2. Check data quality (signal-to-noise, fold, bin spacing)
  3. Generate quicklook visualizations
  4. Identify key reflectors
Phase 2: Seismic Interpretation
  1. Pick horizons (key stratigraphic surfaces)
  2. Map faults and structural features
  3. Generate attribute volumes (coherence, amplitude, frequency)
  4. Identify direct hydrocarbon indicators (DHIs)
Phase 3: Well Log Correlation
  1. Load well logs
  2. Perform formation evaluation
  • Porosity calculation
  • Water saturation
  • Lithology identification
  1. Tie wells to seismic (synthetic seismogram)
  2. Correlate formations across wells
Phase 4: Prospect Identification
  1. Integrate seismic and well data
  2. Map reservoir extent
  3. Define structural/stratigraphic traps
  4. Estimate reservoir properties
  5. Calculate volumetrics (STOIIP/GIIP)
Phase 5: Risk Assessment
  1. Geological chance of success (Pg)
  • Trap adequacy
  • Reservoir presence
  • Seal integrity
  • Source maturity
  • Timing/migration
  1. Volume uncertainty (P10/P50/P90)
  2. Economic evaluation (NPV, IRR)
  3. Risk-adjusted prospect ranking

Domain Tasks

These tasks are handled by this skill:

  • Seismic interpretation: "Pick the base Cretaceous horizon"
  • Log analysis: "Calculate porosity from the density log"
  • Prospect evaluation: "Estimate STOIIP for this structure"
  • Risk assessment: "Calculate probability of success"

Software Tasks

These tasks invoke petropowers:oil-gas-delegation:

  • Seismic visualization web application
  • Prospect database system
  • Automated report generation
  • Real-time drilling dashboard

Quality Checklist

Before finalizing interpretation:

  • [ ] Seismic quality reviewed (phase/Amplitude vs Offset, migration)
  • [ ] Well ties validated
  • [ ] Horizons consistent across dataset
  • [ ] Faults mapped with appropriate throw
  • [ ] Attribute analysis supports interpretation
  • [ ] Volumetrics within credible ranges
  • [ ] Risk factors documented

Safety Considerations

Exploration data informs drilling decisions:

  • Inaccurate interpretation can lead to dry holes (financial risk)
  • Over-pressured zones must be identified
  • Shallow hazards (gas clouds, water flows) must be mapped
  • Well planning uses exploration data for casing design

Example Workflows

Seismic Quicklook
python
import segyio
import numpy as np
with segyio.open('seismic.sgy', 'r') as segyfile:
data = segyio.tools.cube(segyfile)
print(f"Shape: {data.shape}")
print(f"Amplitude range: {data.min():.0f} to {data.max():.0f}")
print(f"Inlines: {segyfile.ilines.min()}-{segyfile.ilines.max()}")
print(f"Crosslines: {segyfile.xlines.min()}-{segyfile.xlines.max()}")
Formation Evaluation
python
import lasio
import numpy as np
log = lasio.read('well.las')
df = log.df()
# Porosity from density
phi = (2.65 - df['RHOB']) / (2.65 - 1.0)
# Water saturation (Archie)
Rw = 0.1 # formation water resistivity
Sw = np.sqrt((Rw) / (phi**2 * df['RT']))
# Net pay (simplified)
net_pay = ((phi > 0.10) & (Sw < 0.6)).sum() * 0.5 # ft per sample
print(f"Net pay: {net_pay:.0f} ft")
print(f"Average porosity: {phi[phi > 0.10].mean():.1%}")
print(f"Average Sw: {Sw[Sw < 1].mean():.1%}")
Volumetrics
python
# Simplified STOIIP calculation
area = 500 # acres
thickness = 50 # ft
porosity = 0.20
water_saturation = 0.25
formation_volume_factor = 1.2
# STOIIP = 7758 * A * h * phi * (1-Sw) / Bo
stoiip = 7758 * area * thickness * porosity * (1 - water_saturation) / formation_volume_factor
print(f"STOIIP: {stoiip:,.0f} bbl")
print(f"STOIIP: {stoiip/1e6:.1f} MMbbl")

References

  • Industry standards: SEG-Y format, LAS specifications
  • Interpretation software: Petrel, Kingdom, Kingdom, DecisionSpace
  • Seismic attributes: Chopra & Marfurt (2007)
  • Risk quantification: Rose (2001), "Risk Analysis and Management of Petroleum Exploration Ventures"

Security

  • Security scanPassed, 90 of 100Pattern checks on the skill's files.
  • Model reviewPassed

Quality evaluation

  • Task evaluationNot runNo evaluation yet. Run one in Skill Studio.

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