Enter reservoir properties
Add reservoir properties, a well entry plan, and development assumptions to define the base scenario.
Greenfield forecasting workbench · Oil & gas
The fully data-driven forecasting workbench that constructs the perfect analog for any greenfield — then carries it through the whole workflow to probabilistic production scenario analysis. Faster than manual methods at every step, and unbiased and explainable throughout: from building the analog to exploring hundreds of scenarios.
From an estimated geological resource to a probability distribution of extractable resources.
What is it
A rapid greenfield evaluation workbench that pairs smart machine-learning models with advanced reservoir-engineering calculations to deliver P10, P50, and P90 production forecasts and economic assessments in minutes.
Designed for use throughout the exploration and appraisal process, particularly when subsurface data are limited and fast, high-quality decisions are required.
Inside the application
How it works
Build production scenarios and explore the potential of a greenfield asset in 5 quick steps.
Add reservoir properties, a well entry plan, and development assumptions to define the base scenario.
The algorithms build a perfect virtual analog from hundreds of historical reservoirs, giving the recovery factor and the base well production forecast.
Engineering equations scale the analog into full-field production forecasts, which are then subjected to Monte Carlo analysis to generate the P10, P50, and P90 ranges.
Fine-tune reservoir attributes and well plans to explore many scenarios instantly and compare alternatives — the workbench recalculates in seconds.
Get economic forecasts based on the economic model and production data — turning field forecasts into NPV, cash flow, and investment insights.
Data foundation
QuickField is trained on open databases and public reports from oil and gas fields worldwide. For every field in our database you can inspect cumulative production history and the well operating model used to build analogs.
Basin and province coverage drawn from open geological and production databases — the foundation for matching analogs at regional scale.
Field inventories and production records compiled from public reports, so every analog is grounded in documented historical performance.
For each field in the database you can review cumulative production and the well operating model — the same building blocks used to construct your analog.
What you get
Assess a greenfield by generating a full set of probabilistic scenarios for the given reservoir conditions and well-entry plan — in about five minutes.
Inputs
A handful of petrophysical properties: porosity, permeability, reservoir pressure, oil and water viscosity, and oil saturation. The models read up to 24 features, but accuracy plateaus after about six key ones — consistent with empirical geology.
Outputs
Oil-well production curves, recovery factor, initial oil and water flow (Q0), and water cut — then Monte Carlo simulation for the P10, P50, and P90 distributions, with a sensitivity read on which attribute drives your uncertainty.
Over time
Use it for rapid early estimates while data is thin, then for tighter forecasts as the development plan progresses and more data becomes available. The more, and more accurate, the input, the sharper the forecast.
Who it is for
Three groups use QuickField to put a defensible number on a greenfield asset — each for a different decision.
01
Unlike labor intensive and inaccurate type-curve methods or expensive and subjective analog-based solutions, QuickField provides a rapid benchmark for concept selection, facility sizing, well phasing, and appraisal planning. Compare prospects by production behavior, recovery potential, well count, and economics.
02
A forecasting workbench that increases evaluation speed, objectivity, and repeatability — for rapid assessments, portfolio reviews, acquisition screening, lender due diligence, and expert benchmarking, without relying on manually assembled, expensive analog sets or time-consuming Excel-based Monte Carlo simulations.
03
QuickField enables rapid independent assessment where sufficient reservoir parameters are available but time is limited. It helps investors, operators, and consultants compare discoveries using consistent probabilistic production metrics, rather than relying only on volumetrics or manually selected analogs.
Under the hood
Every calculation step is transparent, auditable, and based on accepted methods — AI is used only to automate the steps engineers normally perform by hand. Four layers, each resting on the one below it.
Top layer
QuickField uses Monte Carlo simulation to quantify uncertainty in its production forecasts. Users can specify uncertainty ranges for reservoir properties and then run a set number of simulations to generate P10, P50, and P90 production profiles. This provides a probabilistic view of the outcome. Changing parameters recalculates new scenarios in seconds.
Layer 2
The application allows users to create synthetic reservoir models by entering key reservoir properties, such as permeability and viscosity. Users can then build well plans for these synthetic reservoirs, specifying the number, timing, and characteristics of new production and water injection wells. The model then calculates total liquids, water and oil over the lifetime of the field.
Layer 1
Rather than using traditional engineering decline-curve and water-cut growth formulas, historical field data is used to train machine-learning models that predict well-level production under specific reservoir conditions. The machine learning models essentially create "virtual analogs" for the given reservoir properties and use the well plans to generate full field production forecasts.
Bedrock
QuickField has built up a large database of historical production and petrophysical characteristics from various oil and gas fields. This serves as the foundation that enables the machine learning models to create virtual analogs. Users can also integrate their own private company data to further train the models for their specific assets.
Where it fits
QuickField replaces the classic, manual analog forecasting workflow with a fast, efficient, data-driven workbench — analog-based forecasting made fully data-driven, grounded in hundreds of reservoirs, and still lightning-fast. It doesn't replace full-physics reservoir simulation (Petrel and the like) or expert subsurface judgment; it removes the slow, manual analog work that comes before them, so you reach a defensible number in minutes, not weeks.
01
Thousands of engineering calculations, run for you, turn hundreds of historical reservoirs into a Monte Carlo probabilistic forecast — no manually assembled analog sets, no time-consuming spreadsheets.
02
A tornado chart shows exactly which reservoir parameter moves your P10–P90 range, so you know where the risk sits and where more data would pay off.
03
The economics module turns each production scenario into its monetary consequences, and recalculates any scenario you change in seconds.
Getting started
Companies typically take the first step by booking a demo using the public version of QuickField. Following a successful trial, it's possible to extend with the integration service, which updates the public model to a private model enriched with proprietary company data.
Get in touch
Tell us about the asset and where you are in the appraisal process — we'll show you what QuickField makes of it.
QuickField takes an estimated geological resource to a probability distribution of extractable resources.
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