Modules

Our technology allows for direct connection, and automated updating and analysis, of production data allowing for rapid performance evaluation of conventional and unconventional reservoirs.

 

Using Machine Learning data science, analyses are automated allowing the user to focus more on the interpretation and decision making, as opposed to data and model management.


 

Our team is continuously developing new technology  for cloud based reservoir description, production analysis, and gas/oil rate forecasting with a focus on extending applications into Water and Carbon applications. 


 

Visit our "Coming Soon" page for additional updates.

 
GAZ: Gas Modelling
  • Traditional (and emerging) gas diagnostics for reservoir evaluation, stimulation analysis, resource estimation and more

  • Flowing material balance

  • Blasingame, Beta, NPI, and other common type-curves

  • Our approach is unique in that it uses Machine Learning to find the best solution for OGIP

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SPAD: Decline Analysis
  • Traditional (and emerging) decline models performance prediction for recoverable oil and gas

  • Inclusion of the “Buba” diagnostic for real-time tracking of OGIP

  • Inclusion of the Stretched Exponential and Power Law models for unconventional gas

  • Our approach is unique in that it uses Machine Learning and sophisticated nonlinear methods to find the best solution for OGIP

  • Our unconventional models contain new and modern diagnostics for improving match parameters

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LINIYA:  Wellbore Modelling

​Our multiphase wellbore system is unique in that it can provide detailed production diagnostics, including:

  • Hydrate evaluation

  • Liquid lift identification​

Our system is unique in that it can be tied directly to a SCADA system (via IIOT or similar) for real-time identification of production problems and remedies (such as the impact of inhibitors).

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SHIFER: Unconventional Gas Diagnostics
  • Shale and Coal Seam Gas diagnostics

  • Coal Seam Gas typecurves

  • Shale fracture analysis

 

Our approach is unique in that it uses Machine Learning and sophisticated nonlinear methods to find the best solution for OGIP.

Our unconventional models contain new and modern diagnostics for improving match parameters.

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KOLDUN: Monte Carlo Simulation
  • Advanced Monte-Carlo simulation for volumetrics and production forecasting

  • Our system allows for conventional and unconventional resources including coal seam gas

Our system is unique in that it goes beyond traditional probabilistic decline and provides physics based forecasts accounting for petrophysical, geophysical, and operation changes such as stimulation and compression

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