Engineering Intelligence
PEI is designed to apply intelligence to petroleum engineering workflows — connecting field evidence, engineering principles, analytical methods and professional judgement into a structured decision process.
The PEI principle
PEI is not intended to be a generic chatbot that simply answers petroleum engineering questions. Its intelligence is structured around the engineering process required to reach a defensible technical conclusion.
AI can provide computational and orchestration leverage. The engineering basis comes from physics, field evidence, recognised methods, technical references, validated calculations and professional judgement.
Engineering reasoning chain
PEI operating model
Engineering intelligence begins with understanding the problem and its context. PEI connects that context to relevant engineering knowledge and evidence, supports structured analysis, and carries the resulting technical reasoning toward a defensible engineering decision and appropriate action.
Define the asset, well, field, engineering problem, available data and decision that needs to be supported.
Bring together petroleum engineering knowledge, evidence, applicable principles, methods and technical analysis.
Interpret the analysis, assess uncertainty and limitations, compare alternatives and develop technically defensible recommendations.
Translate the recommendation into an appropriate engineering response, subject to professional review, execution controls and monitoring.
The engineering workflow
Each stage exists for a reason. PEI is intended to make the reasoning chain visible, repeatable and auditable rather than jumping directly from a question to an answer.
Identify the actual field or engineering problem, its objective, constraints, decision required and information needed to resolve it.
Outputs
Collect the relevant field data, technical records, measurements and authoritative engineering references. Assess data quality, completeness and consistency before analysis.
Outputs
Determine the petroleum engineering principles, physical mechanisms, recognised methods and applicable industry practices governing the problem.
Outputs
Apply the appropriate engineering workflow, equations, models and analytical methods to the available evidence.
Outputs
Test the analysis against independent calculations, alternative methods, historical behaviour, field observations and contradictory evidence where available.
Outputs
Identify data limitations, model uncertainty, assumptions, sensitivity to key parameters and areas where additional information is required.
Outputs
Translate the engineering findings into practical options, technical recommendations, risks, limitations and decision implications.
Outputs
The resulting engineering work remains subject to qualified professional review before it is used for consequential field, operational or development decisions.
Outputs
Engineering domains
PEI connects the engineering problem to the disciplines and workflows required to solve it. The same underlying principle may therefore lead into different analytical paths depending on the field problem.
Pressure behaviour, fluid flow, material balance, reservoir performance, well productivity and recovery decisions.
Well performance, inflow and outflow behaviour, artificial lift, production optimisation and operating constraints.
Well objectives, trajectories, pressure regimes, well integrity, completion design, stimulation and well delivery.
Logs, cores, petrophysical interpretation, fluid information and the evidence required to understand the reservoir.
Pressure and rate behaviour, permeability, skin, boundaries, connectivity and well performance.
Recovery diagnosis, reservoir and fluid screening, improved recovery opportunities, simulation and pilot evaluation.
Example engineering chain
Consider a production problem. PEI should be able to connect the observed field behaviour to the relevant engineering chain, rather than treating each calculation as an isolated answer.
The objective is not simply to produce an answer.
The objective is to establish why the answer is supported, what evidence it depends on, what uncertainty remains and what action the engineering evidence justifies.
Engineering assurance
It is designed to minimise preventable negligence.
Reservoirs, wells and field data contain uncertainty. Models have limitations and measurements are never perfect. PEI therefore treats uncertainty as part of engineering rather than pretending that every conclusion can be certain.
Design discipline
Connected to the asset lifecycle
The intelligence framework connects with the upstream lifecycle from exploration through reservoir characterisation, development, drilling, completion, testing, production, surveillance and improved recovery.