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KEY FEATURES

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Powered by the Nexus® engine, all types of models, grids (structured or unstructured), and recovery mechanisms can be modeled at any asset level (wells, reservoir, multiple reservoirs, surface network) to analyze and optimize asset performance—in both the short term to maximize production and in the long term for further field development.

Built-in streamline analysis computations are based on full-physics of the simulation, without the need for separate streamline simulation software. Streamlines can be used to determine sweep efficiency, compute flow between production-injection pairs, and increase understanding of hydrocarbon recovery mechanisms.

Surface network and subsurface equations are solved simultaneously, via Newton-level implicit coupling, for a more accurate representation of the asset to improve robustness and performance. Surface facilities extend into wellbores, providing accurate flow within the most complex wellbores; and branched wellbores, inflow control valves, and inflow control devices can be easily created in the model.

Automated procedures perform well management functions by adjusting settings, such as valve positions, and making decisions based on the operating conditions encountered in the simulation. They allow the simulation to mimic complex, real-time decisions, and have access to network data to modify network-operating parameters, as needed.

Several independent reservoirs can be combined into one model if they have a common surface network. Maintaining the integrity of individual models, the multi-reservoir case uses the same reservoir input as individual cases in addition to any shared facilities. Interdependencies can be identified and the complete multi-reservoir network configuration can be modified to ensure optimal overall production.

The reservoir management suite includes automated workflows for calibration and fine-tuning of the asset models, using historical data to improve the forecasting accuracy of the model, using the latest history matching and optimization techniques. This reduces manual cumbersome modifications and enables engineers to focus more on high-value tasks and analysis of results.

Network models can be de-coupled from the subsurface, and simulated separately, to perform quick production analysis and capacity management in the short term. Inflow Performance Relationship (IPR) curves can also be generated for network-only models, and all types of facilities can be modeled (pipes, valves, chokes, compressors, pumps, etc.).

A sensitivity analysis module included in Full-Scale Asset Simulation identifies which parameters are impacting the results of simulations the most and should be considered in the engineering study. The design matrix of factorial analysis allows efficient exploration of multiple scenarios, while tornado charts provide a visually appealing summary of the sensitivity  analysis results.

The scope of scenarios can be expanded, with unlimited compute capability available on demand, to analyze and design the best plan to maximize recovery. With the infrastructure available to handle models of all sizes, there is no need for upscaling or coarsening to run simulations.

Full-Scale Asset Simulation extends the conventional dual porosity model to support virtually any number of porosity types, superimposed in the same physical domain. This feature helps to more accurately model heterogeneous reservoirs with hybrid transport mechanisms. It is used to simulate complicated fluid transport in fractured carbonate reservoirs or unconventional plays where the interplay of transport among porosity types can be determinant.

The ability to model highly complex giant fields provides a competitive edge. Giant fields can include thousands of wells and network connections, millions of grid blocks, complex compositional fluids and recovery mechanisms, and multiple reservoirs. The combination and interaction of these features, including multiple flow paths per well, cannot be handled by most simulators.

The reservoir management suite includes a module to build proxy flow models based on the latest machine learning algorithms such as deep neural network, long short-term memory network, or advanced convolutional neural network. This significantly reduces the computational time required and reduces the cost of performing near real time updates for the selected engineering workflows. It also preserves the prediction accuracy of the petroleum reservoir behavior.

The surface facilities algorithms extend into wellbores, providing accurate determination of flow within even the most complex wellbores. Branched wellbores, multi-lateral wells, tubing-and-annulus configurations, and downhole control devices such as Inflow Control Devices (ICD) and Inflow Control Valves (ICV) can easily be created in a Nexus® model. The well’s interaction with the reservoir is accurately determined due to the implicit coupling of the surface facilities model with the reservoir model.


ADVANCED ASSET SIMULATION

Powered by the Nexus® engine, all types of models, grids (structured or unstructured), and recovery mechanisms can be modeled at any asset level (wells, reservoir, multiple reservoirs, surface network) to analyze and optimize asset performance—in both the short term to maximize production and in the long term for further field development.

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