Hadi Farahani, PhD

Environmental + Data Intelligence

Environmental Data Analyst. I turn complex industrial monitoring data into decisions that hold up to audit, specializing in metrology, oil & gas analytics, and geospatial intelligence.

Currently building: OGE-01 Produced-Water Analytics (In Progress)

Connect on LinkedIn View GitHub
Synthetic concentration measurements with expanded uncertainty A line chart showing measured concentration over 24 months. The measured value ends at 96 mg/L, below the regulatory limit of 100 mg/L. However, the shaded uncertainty band (U = ±8) overlaps the limit, indicating a need for a formal decision rule. 120 100 80 60 40 20 Conc. (mg/L) 0 6 12 18 24 Monitoring Period (Months) Regulatory Limit (100 mg/L) Measured < limit, but U overlaps
Measured
Expanded Uncertainty (k=2)
Limit
SYNTHETIC Data · Seed 42 · Source CSV · sha256 3f9a…c1d2

Selected Work

OGE-01 PREVIEW
In Progress ENV Non-detects

Produced Water Quality Analytics

Problem: High variance in effluent quality masking treatment performance.
Method: Kaplan-Meier/ROS for left-censored data; stage-wise efficiency calculation.
Result: (Analysis in progress — data pipeline complete, awaiting final evaluation).

data: synthetic · n=240 · seed=42 Follow progress →
METHANE PREVIEW
Planned ENV Drift/CUSUM

Methane Emission Monitoring

Problem: Unreliable source prioritization due to sensor drift.
Method: CUSUM control charts for drift detection; Moran's I for spatial clustering; uncertainty-weighted ranking.
Result: (Project planned — methodology defined, notebook pending).

data: synthetic · n=120 · seed=42 View methodology →
OIL SPILL PREVIEW
Planned GEO Spatial Analysis

Oil Spill Risk Mapping

Problem: Lack of spatial risk context for emergency response planning.
Method: Combine open-source pipeline data with GIS proximity analysis and environmental sensitivity indices.
Result: (Project planned — methodology defined, GIS processing pending).

data: public (OSM) + synthetic risk indices View methodology →

How I Work

01. Validate

Establish data reliability before analysis.
Identify missing values, measurement anomalies, sensor drift, reporting limits, and data-quality issues.
Applied in: OGE-01 (In Progress)

02. Quantify Uncertainty

Understand the reliability of measured results.
Apply measurement uncertainty principles, statistical modelling, and uncertainty propagation to quantify the confidence associated with analytical results.
Applied in: OGE-01 (In Progress)

03. Decide

Translate analytical evidence into operational insight.
Identify abnormal conditions, prioritize environmental risks, evaluate decision thresholds, and communicate actionable findings.
Applied in: OGE-01 (In Progress)

Core Technical Stack

Programming & Data Analysis

Python Pandas NumPy SciPy

Geospatial & Earth Observation

QGIS GeoPandas Shapely

Databases & Reproducibility

SQLite Git Jupyter

Metrology & Methods

GUM (JCGM 100) Measurement Uncertainty Non-detect Analysis

Project Roadmap (35 Total)

A structured portfolio of industrial and environmental analytics. The projects below are currently in the pipeline. As each one is completed, the synthetic data, notebooks, and reproducible charts will be linked directly from this page.

Env Intel Lab (10 Projects)

  • OGE-01: Produced Water Analytics (In Progress)
  • OGE-02: Gas Flaring Performance
  • OGE-03: Methane Emission Monitoring
  • OGE-04: Drilling Waste Characterization
  • OGE-05: Oil Spill Risk Mapping
  • OGE-06: Groundwater Quality Trends
  • OGE-07: Industrial Air Quality
  • OGE-08: Climate Hazard Exposure
  • OGE-09: Oily Sludge Management
  • OGE-10: Microplastics & Emerging Pollutants

EnvIntel (25 Projects)

  • A Data Quality & Metrology (5)
  • B Industrial Operations (5)
  • C Geospatial & Earth Obs (5)
  • D Risk & Forecasting (5)
  • E Compliance & Governance (5)

*Individual EnvIntel notebooks will be published upon completion.

Let's build something defensible.

Open to collaboration and opportunities in environmental monitoring and compliance analytics.

Get in Touch