Seismic Prospect Discovery

AI-powered seismic analysis and integration platform for enhancing imaging, automating interpretation, accelerating geological feature detection, and embedding Seismic workflows into enterprise exploration systems.

The Problem

SeisNova modernizes seismic interpretation and enterprise integration with AI

Organizations face these key challenges:

1

Poor seismic quality and difficult imaging in salt-affected areas

2

Slow manual fault picking and structural interpretation

3

Fragmented workflows across seismic tools and enterprise systems

4

Repeated data conversion, copying, and preprocessing before use

Impact When Solved

Accelerates seismic interpretation on large 3D datasetsImproves imaging of salt-related reflectors and complex structuresAutomates fault picking and geological feature detectionReduces repeated transcoding and preprocessing costs

The Shift

Before AI~85% Manual

Human Does

  • Gather seismic datasets from separate tools and prepare them for interpretation
  • Manually review seismic quality and request preprocessing or imaging updates
  • Interpret faults, horizons, and geological features across large 3D volumes
  • Compare analogues and subsurface findings using expert judgment and spreadsheets

Automation

  • Run limited rule-based preprocessing steps
  • Support basic batch imaging and data conversion jobs
  • Execute fixed API or embedded workflow calls between systems
With AI~75% Automated

Human Does

  • Set interpretation priorities and approve imaging and analysis objectives
  • Review AI-generated faults, features, and analogue rankings for subsurface decisions
  • Handle ambiguous geology, low-confidence outputs, and workflow exceptions

AI Handles

  • Enhance seismic quality and improve imaging for complex salt-related structures
  • Automate fault picking, feature detection, and multi-attribute interpretation support
  • Condition, transcode, and route seismic data through elastic processing workflows
  • Rank analogues and combine seismic outputs with enterprise context for decision support

Operating Intelligence

How Seismic Prospect Discovery runs once it is live

AI runs the first three steps autonomously.

Humans own every decision.

The system gets smarter each cycle.

Confidence82%
ArchetypeRecommend & Decide
Shape6-step converge
Human gates1
Autonomy
67%AI controls 4 of 6 steps

Who is in control at each step

Each column marks the operating owner for that step. AI-led actions sit above the divider, human decisions and feedback loops sit below it.

Loop shapeconverge

Step 1

Assemble Context

Step 2

Analyze

Step 3

Recommend

Step 4

Human Decision

Step 5

Execute

Step 6

Feedback

AI lead

Autonomous execution

1AI
2AI
3AI
5AI
gate

Human lead

Approval, override, feedback

4Human
6 Loop
AI-led step
Human-controlled step
Feedback loop
TL;DR

AI handles assembly, analysis, and execution. The human gate sits at the decision point. Every cycle refines future recommendations.

The Loop

6 steps

1 operating angles mapped

Operational Depth

Technologies

Technologies commonly used in Seismic Prospect Discovery implementations:

Key Players

Companies actively working on Seismic Prospect Discovery solutions:

Real-World Use Cases

Remote MCP-based AI orchestration for Seismic content workflows

This setup lets an external AI assistant securely plug into Seismic so it can look up content, react to events, and help users complete content-related tasks.

tool-using enterprise assistantproposed integration pattern documented by the vendor, indicating implementation-ready but not proof of broad end-user deployment in the source.
10.0

Wave resource data access for energy site assessment

A developer can call the Wave API to fetch ocean wave conditions and model outputs instead of collecting all measurements themselves.

retrieval and analytical data servingdeployed data-access workflow with public documentation and downloadable datasets.
10.0

AI-assisted capital allocation in subsurface modelling

AI helps combine underground technical data with business data so energy companies can decide more quickly where to spend money.

decision support and prioritizationproposed/deployed platform capability highlighted as product update
10.0

Pseudo-well generation to improve seismic inversion under sparse well control

When there are not enough real wells, the team creates approximate virtual wells from an initial impedance result and uses them to guide a better final inversion.

data augmentation for constrained inverse modelingpractical support technique demonstrated within the study’s geophysical workflow, not a standalone ai system.
10.0

Custom Seismic app and extension development

Developers can build apps that plug deeply into Seismic so teams can add custom features or connect Seismic to internal systems.

embedded application augmentationdeployed platform capability
10.0
+7 more use cases(sign up to see all)

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