Unconventional Well Optimization

Optimize unconventional well design and location quickly and easily with Data Physics driven fast full field models that match all your historical data and honors reservoir physics.

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Build and validate predictive models in a matter of days that match all your historical production and fracking data

Optimize well spacing, lateral length, frac stages, injection volume, pad/well location and other key design parameters

Optimize BHPs and choke settings during flowback to maximize production, NPV and recovery

Run probabilistic forecasts to estimate P10-P50-P90 production and recovery in minutes for any well, pad or full field

Build reliable models with little data via transfer and federated learning, and extrapolate beyond measurements

Fraceon combines physics based well/pad models and state-of-the-art machine learning techniques into a seamless full field model

The physical well models ensure that model predictions are always physically realistic and reliable

Through this combined modeling approach, Fraceon is able to integrate data that usually cannot be integrated directly into physical models

Fraceon provides an ensemble of models that all match your historical data to account for uncertainty and measurement errors

Fraceon is very fast and independent of interpretation bias, full field models can be run in minutes

Fraceon can run locally or on Tachyus Cloud, with no infrastructure footprint

Data can be exported easily to other visualization and analysis tools

Fraceon applies our trademark Data Physics models to create fast and accurate full field models honoring fractured well/pad physics, enabling robust forecasting and optimization.

How it works

In traditional unconventional modeling, various types of predictive models have been applied over the years for quantitative decision making. Such models range from the very simple analytical models (type-curves, etc.) to the very complex reservoir simulation models. Simulation models attempt to model detailed behavior of reservoir physics and integrate all kinds of measured data. However, many issues such as the significant time and effort required to build and calibrate these models, computational complexity, etc. generally make their practical application difficult.

Tachyus’ Data Physics is the amalgamation of the state-of-the-art in machine learning and reservoir physics. These models can be created as efficiently as machine learning models, integrate all kinds of data, and can be evaluated orders of magnitude faster than full scale simulation models, and since they reservoir physics, they have long term predictive capacity and provide physically realistic results. Data Physics based Fraceon is very fast and users can go from data preparation and modeling to decisions in a matter of days. Additionally, the models can be quickly updated with new data so that they always remain operationally useful.

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