Exploration Workflows
Exploration is the first phase of the upstream lifecycle - finding hydrocarbons beneath the earth's surface. Digital workflows have fundamentally changed how geoscientists acquire, process, and interpret subsurface data to identify promising prospects.
Digital Exploration Workflow
Seismic Data Acquisition
Modern seismic surveys use thousands of sensors (geophones or hydrophones) to record sound waves reflected from subsurface rock layers. Data is transmitted in real time to onshore processing centres via satellite or fibre.
Example: A marine seismic vessel tows 16 streamers, each 8 km long, recording data that is processed on a cloud HPC cluster within days instead of months.
Seismic Processing & Imaging
Raw seismic data is processed using algorithms that remove noise, correct for velocity variations, and produce high-resolution 3D images of the subsurface. Cloud computing has drastically reduced processing time.
Example: Full-waveform inversion (FWI) on AWS reduced a processing job from 6 weeks on an in-house cluster to 4 days in the cloud.
Interpretation & Prospect Evaluation
Geoscientists use interpretation software (Petrel, Kingdom, OpendTect) to map horizons, identify faults, and build geological models. AI-assisted interpretation can auto-pick faults and horizons, saving weeks of manual work.
Example: An ML model trained on interpreted seismic volumes auto-picks fault surfaces in a new survey with 90% accuracy, freeing geoscientists to focus on high-value analysis.
Risk Assessment & Decision Gate
Probabilistic tools calculate the chance of success (geological risk), estimate reserves (P10/P50/P90), and feed into economic models. Digital dashboards present these metrics to decision-makers in a clear, standardised format.
Example: A prospect evaluation dashboard shows GCoS, expected reserves, development cost estimates, and NPV side by side for 20 prospects, enabling portfolio ranking.
Key Tools in Digital Exploration
Petrel (Schlumberger/SLB)
Industry-standard platform for seismic interpretation, geological modelling, and reservoir simulation
Cloud HPC
AWS, Azure, and Google Cloud provide on-demand high-performance computing for seismic processing at scale
AI-Assisted Interpretation
Deep learning models for auto-fault detection, facies classification, and seismic attribute analysis
GIS & Spatial Analytics
Geographic information systems for mapping concessions, well locations, infrastructure, and environmental constraints