Borehole Intelligence & Automated Petrography

Introduction

The foundational act of the field intelligence chain.

Understanding what is in the reservoir at the scale of individual rock grains, pore throats, and mineral assemblages is the foundational act of the entire field development and production intelligence chain. Every reservoir model, every field development plan, every completion and stimulation decision, every production optimisation strategy draws its validity from the quality of that foundational understanding.

This product addresses that foundational need directly. It replaces the manual, specialist-dependent, periodically-produced characterisation workflow with an AI-driven, continuously-executable intelligence system. The characterisation intelligence it generates is governed, quantified, and integrated into the Energy Operating System's data foundation — the raw material from which TARGET's broader asset lifecycle portfolio builds its reservoir models, optimises its development programmes, and governs its investment decisions.

The Strategic Position

The energy industry spends enormously to generate subsurface characterisation data, then loses most of its value to the speed and consistency limits of the manual workflows that process it. This product eliminates that loss: what took weeks now takes minutes, what depended on individual specialist judgment now runs on a consistent, quantified, AI-driven framework, and what once sat in a static report now flows as a live, governed data asset into the organisation's intelligence infrastructure.

The Workflow It Disrupts

Built to close the gap — not to make the old way faster.

A cascade of specialist-dependent, time-consuming processes designed for a world where computation was expensive and human expertise was the primary analytical asset.

3–5/day

Petrography throughput

Samples analysed per specialist — and results vary lab to lab.

25–35m/wk

Core described

Static logs that can't update without redoing the work by hand.

Weekslate

Insight lags the decision

Answers land after the choices that needed them are made.

Gaps

Filled by assumption

Guesses that compound through every downstream model and plan.

The shift: not a faster version of this workflow — a full replacement, architecturally impossible before AI-driven image intelligence reached today's maturity.

What the Product Delivers

A coherent end-to-end characterisation system

The capabilities are not a collection of analytical tools. They are one system — each component feeding the next, and all outputs flowing as governed data assets into the Energy OS foundation.

Precision at Scale

Automated Petrography

An AI-driven engine processes thin section images from carbonate and clastic reservoirs and returns fully quantified characterisation in minutes per sample, at pixel-level precision — lithology, texture, pore types, cement, grain mineralogy, pore-throat measurements, and AI-computed permeability.

The advantage is structural, not incremental: results that are quantified, reproducible, and consistent across every sample regardless of programme volume.

80%+

Analysis cycle reduced

90%+

Analyst time saved / sample

Automated Petrography — AI-derived component maps and quantified abundances

Eliminating the MICP Constraint

AI-Generated Pore System Characterisation

Mercury Injection Capillary Pressure has governed pore-throat distributions, capillary pressure curves, and rock typing for decades — but it is expensive, slow, environmentally restricted, and sparse by necessity.

The product eliminates that constraint. Using the same deep-learning infrastructure, it projects MICP-equivalent characterisation directly from thin section images — capillary pressure curves, pore-throat radius distributions, and saturation profiles — in minutes per sample, across every thin section in the programme, without physical mercury.

100%

Thin-section coverage

Mercury, zero lab handling

AI-Generated Pore System — capillary pressure curve and pore-throat histograms

Living Digital Description

From Core Photograph to Living Digital Description

A conventional core description is a static log — produced over days or weeks, frozen at creation, and disconnected from the log and petrographic data that belong beside it.

The product converts core box photographs into dynamic, azimuthal digital descriptions — a live, multi-scale, depth-synchronised data asset rather than a static image. Reservoir rock typing becomes one consistent system across every scale.

40–60%

Less time & cost to describe

360°

Azimuthal coverage

Integrated Reservoir Rock Typing — continuous RRT from core and log data

One Environment for All Subsurface Data

Multi-Scale Integration & Core Data Management

One depth-synchronised environment brings together thin sections, core plugs, photographs, open-hole logs, borehole imaging, and rock-type classifications — ending the tool-switching that has long fragmented interpretation.

A geoscientist moves fluidly from pore scale to log scale without leaving the environment. AI digitisation revives decades of legacy paper, film, and analogue records into searchable digital assets, and a governed 360° repository covers every core data type.

Synchronised environment

360°

Governed data coverage

Multi-Scale Wellbore Visualisation — integrated depth display

Platform Position & Competitive Differentiation

A difference in commercial value that is not one of degree. It is one of kind.

Built natively on the Energy Operating System, the product's AI capabilities draw on a domain-specific corpus of carbonate and clastic thin section imagery accumulated across live deployments in the world's most geologically complex producing fields. That training corpus is not a feature of the product — it is the competitive moat.

Workflow scope

End-to-end: from raw thin section image through petrography, pore system characterisation, core description, rock typing, and multi-scale visualisation — one product, one system, one governed data output.

Reservoir coverage

Both carbonate and clastic reservoir types in dedicated analytical modules — an end-to-end solution that most point tools do not offer within a single environment.

Speed of insight

Minutes to hours for characterisation that conventional workflows take weeks to months to deliver — enabling real-time decision support during active drilling and development programmes.

Data asset integration

All outputs flow as governed data assets into the Energy OS foundation — immediately available to reservoir models, other products in the portfolio, and agentic agents; not locked in standalone reports.

Training corpus depth

AI models trained on domain-specific imagery from twenty years of live deployments across the world's most geologically complex producing fields — a corpus that no new entrant can replicate.

Platform inheritance

Sovereign deployment, governed data foundation, audit trail, and continuous model improvement from the full Energy OS deployment base — capabilities no standalone characterisation product can provide.