SeisCapital

AI-enabled subsurface modelling platform that unifies seismic, technical, and commercial data to support faster, lower-risk capital allocation decisions in oil and gas exploration.

The Problem

“Disconnected subsurface and commercial data slows exploration investment decisions”

Organizations face these key challenges:

Seismic, well, reservoir, and commercial data are stored in disconnected systems

Prospect evaluations rely on manual spreadsheet consolidation

Technical and finance teams use inconsistent assumptions and versions

Scenario analysis is slow and difficult to repeat at portfolio scale

Impact When Solved

Cuts prospect evaluation cycle time from weeks to daysImproves consistency between technical and commercial assumptionsEnables portfolio ranking using risked value and uncertainty bandsReduces manual data reconciliation across seismic, wells, and economics

The Shift

Before AI~85% Manual

Human Does

•Gather seismic, well, reservoir, and commercial inputs from separate sources
•Reconcile assumptions and versions across technical and commercial teams
•Build static prospect evaluations and compare scenarios in spreadsheets
•Review opportunities in meetings and decide capital allocation priorities

Automation

•No meaningful AI support in the legacy workflow
•Limited automation for compiling prospect information
•Minimal assistance for comparing uncertainty across opportunities

With AI~75% Automated

Human Does

•Set evaluation assumptions, portfolio priorities, and decision criteria
•Review AI-ranked prospects and challenge key drivers and uncertainties
•Approve capital allocation, deferment, or further appraisal actions

AI Handles

•Unify seismic, well, reservoir, and commercial data into prospect views
•Generate probabilistic subsurface predictions, scorecards, and ranked opportunities
•Recompute risked economics and scenario comparisons as assumptions change
•Monitor new data and flag portfolio shifts, outliers, and decision triggers

Operating Intelligence

How SeisCapital runs once it is live

AI runs the first three steps autonomously.

Humans own every decision.

The system gets smarter each cycle.

Confidence94%

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

1AI

Assemble Context

Combine the relevant records, signals, and constraints.

instant

2AI

Analyze

Evaluate options, risk, and likely outcomes.

instant

3AI

Recommend

Present a ranked recommendation with supporting rationale.

instant

4Human checkpoint

Human Decision

A human accepts, edits, or rejects the recommendation.

hours to days

Authority gates · 1

The system must not approve capital allocation, drilling, appraisal, deferment, divestment, farm-down, or acquisition decisions without review by exploration and capital allocation leaders. [S1]

Why this step is human

The decision carries real-world consequences that require professional judgment and accountability.

5AI