Tool enables estimation of fluid behavior and properties and is now available for use
Aware of what is most advanced in the Oil and Gas sector, ESSS O&G has just launched a solution for engineers to obtain a reliable representation of the behavior of Fluids and Simulation Environment (RF-DAP PHASE). O software allows engineers a reliable representation of the PVT behavior of fluids. RF-DAP FASE predicts phase equilibria and estimates the physical, thermodynamic and transport properties of complex hydrocarbons and aqueous mixtures.
Vinicius Girardi, Business Development Manager at ESSS O&G, explains how the ESSS team created innovative forecasting capabilities in RF-DAP FASE. “To calculate the phase equilibrium and properties of fluids, for example, we developed modern and robust algorithms using automatic differentiation and machine learning approaches,” he says.
Innovation was a keyword throughout the development of the software. “Our solution innovates for the O&G industry with a p21 that connects the simulator to a central fluid database”, adds Giardi.
“Because it is deployed on servers or in a cloud, it democratizes access across the enterprise and can benefit from robust servers to deliver analytics with low computational time. As the RF-DAP FASE is directly linked to a central fluid database, fluid composition and other experimental data can be read directly from it and simulation results can be stored back, all in a transparent and optimized”, he adds.
Another focus of the ESSS team was an intuitive and easy-to-use interface. The goal was to ensure that a user had an amazing experience using RF-DAP FASE without the need to do extensive training or consult complex user guides.
How it works
The ESSS O&G solution performs fluid characterization based on an equation of state (EoS) model. It simulates phase equilibria through flash calculations, up to three coexisting phases. Users can also combine fluid properties with experimental data through robust regression algorithms.
The models are implemented under the Helmholtz free energy framework and all derivatives are computed using automatic differentiation. Without losing numerical precision, this approach circumvents errors caused by erroneous manual derivations of complex analytical expressions or code implementation.
Machine learning algorithms are used to identify the phases after calculating the phase equilibria over a set of specified pressure and temperature conditions. Each phase is grouped as a continuous surface in the property space. This technique replaces an older, rule-based approach that needed to consider different types of mixtures at the same time. The automated approach simplifies the implementation of these rules and can be used in blends with never-before-seen behavior.
where to use the software:
- Forecasting flow assurance issues;
- Process design and optimization;
- Reservoir characterization.
PVT analysis provides insight into reservoir exploration and recovery strategies that can significantly improve a project's cash flow and economic valuation.
How to compare simulations of PVT experiments with experimental data
The properties of typical PVT experiments (CCE, DL and Separator Tests) can also be calculated. By comparing these simulations of PVT experiments with experimental data, it is possible to see that, although the characterization procedure provides good estimates for both the composition and properties of the mixture, the contribution of the heaviest components still represents the biggest source of errors.
When PVT data is available, RF-DAP PHASE can adjust the model to match experimental values using robust regression algorithms in order to obtain a representative model of a given fluid. The Peneloux volume displacement constant, binary interaction parameters, and correlation coefficients used to estimate the properties of the heaviest fraction are adjusted using a multi-stage optimization procedure.
The free trial is available on the website of ESSS O&G.
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