Company profile
QuickField.ai
The perfect analog for any greenfield.
- Industry
- Oil and Gas
- Employees
- 2
- Founded
- 2026
QuickField.ai company summary
QuickField.ai is a company in the Oil and Gas industry, founded in 2026. On LinkedIn the company has around 2 employees.
What technology does QuickField.ai use?
No technologies detected yet. Warmrank rechecks company websites on a rolling basis.
About QuickField.ai
Built on a large database of historical reservoirs, Quickfield uses machine learning to generate virtual analogs that predict recovery factors, production profiles at well level, and other key reservoir characteristics. Combined with the well-entry plan, this is used in engineering equations and subjected to Monte Carlo analysis to generate P10, P50, and P90 production scenarios, supporting faster, more consistent, and more transparent decisions. For exploration companies and development teams, Quickfield provides an unbiased, rapid empirical benchmark for concept selection, facility sizing, well phasing, and appraisal planning. Prospects can be screened, ranked, and compared not only by resource size and chance of success, but by expected production behavior, recovery potential, well count, and commercial development range. For subsurface consultants, Quickfield increases evaluation speed and repeatability. It enables rapid independent assessments, portfolio reviews, reserves and resources support, acquisition screening, lender due diligence, and expert benchmarking without relying solely on manually assembled analog sets. For farm-in, acquisition, and new-venture evaluation of discovered resources, 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. Build production scenarios and explore the potential of a greenfield asset in 4 quick steps: 1) Enter reservoir properties, a well entry plan, and development assumptions. 2) The algorithms will then build the perfect analog and base well production forecast. 3) Engineering equations then produce the reservoir forecasts and the Monte Carlo analysis. 4) You can fine-tune reservoir attributes and well plans to optimize the scenario.
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Frequently asked questions about QuickField.ai
What does QuickField.ai do?
Built on a large database of historical reservoirs, Quickfield uses machine learning to generate virtual analogs that predict recovery factors, production profiles at well level, and other key reservoir characteristics. Combined with the well-entry plan, this is used in engineering equations and subjected to Monte Carlo analysis to generate P10, P50, and P90 production scenarios, supporting faster, more consistent, and more transparent decisions. For exploration companies and development teams, Quickfield provides an unbiased, rapid empirical benchmark for concept selection, facility sizing, well phasing, and appraisal planning. Prospects can be screened, ranked, and compared not only by resource size and chance of success, but by expected production behavior, recovery potential, well count, and commercial development range. For subsurface consultants, Quickfield increases evaluation speed and repeatability. It enables rapid independent assessments, portfolio reviews, reserves and resources support, acquisition screening, lender due diligence, and expert benchmarking without relying solely on manually assembled analog sets. For farm-in, acquisition, and new-venture evaluation of discovered resources, 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. Build production scenarios and explore the potential of a greenfield asset in 4 quick steps: 1) Enter reservoir properties, a well entry plan, and development assumptions. 2) The algorithms will then build the perfect analog and base well production forecast. 3) Engineering equations then produce the reservoir forecasts and the Monte Carlo analysis. 4) You can fine-tune reservoir attributes and well plans to optimize the scenario.
How many employees does QuickField.ai have?
QuickField.ai has around 2 employees on LinkedIn.
When was QuickField.ai founded?
QuickField.ai was founded in 2026.
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