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Reservoir simulation models are used by oil and gas companies in the development of new fields. Also, models are used in developed fields where production forecasts are needed to help make investment decisions. As building and maintaining a robust, reliable model of a field is often time-consuming and expensive, models are typically only constructed where large investment decisions are at stake. Improvements in simulation software have lowered the time to develop a model. Also, models can be run on personal computers rather than more expensive workstations.
For new fields, models may help development by identifying the number of wells required, the optimal completion of wells, the present and future needs for artificial lift, and the expected production of oil, water and gas.
For ongoing reservoir management, models may help in improved oil recovery by hydraulic fracturing. Highly deviated or horizontal wells can also be represented. Specialized software may be used in the design of hydraulic fracturing, then the improvements in productivity can be included in the field model. Also, future improvement in oil recovery with pressure maintenance by re-injection of produced gas or by water injection into an aquifer can be evaluated. Water flooding resulting in the improved displacement of oil is commonly evaluated using reservoir simulation.
The application of enhanced oil recovery (EOR) processes requires that the field possesses the necessary characteristics to make application successful. Model studies can assist in this evaluation. EOR processes include miscible displacement by natural gas, CO2, or nitrogen and chemical flooding (polymer, alkaline, surfactant, or a combination of these). Special features in simulation software is needed to represent these processes. In some miscible applications, the "smearing" of the flood front, also called numerical dispersion, may be a problem.
Reservoir simulation is used extensively to identify opportunities to increase oil production in heavy oil deposits. Oil recovery is improved by lowering the oil viscosity by injecting steam or hot water. Typical processes are steam soaks (steam is injected, then oil produced from the same well) and steam flooding (separate steam injectors and oil producers). These processes require simulators with special features to account for heat transfer to the fluids present and the formation, the subsequent property changes and heat losses outside of the formation.
A recent application of reservoir simulation is the modeling of coalbed methane (CBM) production. This application requires a specialized CBM simulator. In addition to the normal fractured (fissured) formation data, CBM simulation requires gas content data values at initial pressure, sorption isotherms, diffusion coefficient, and parameters to estimate the changes in absolute permeability as a function of pore-pressure depletion and gas desorption.
Traditional finite difference simulators dominate both theoretical and practical work in reservoir simulation. Conventional FD simulation is underpinned by three physical concepts: conservation of mass, isothermal fluid phase behavior, and the Darcy approximation of fluid flow through porous media. Thermal simulators (most commonly used for heavy crude oil applications) add conservation of energy to this list, allowing temperatures to change within the reservoir.
Numerical techniques and approaches that are common in modern simulators:
- Most modern FD simulation programs allow for construction of 3-D representations for use in either full-field or single-well models. 2-D approximations are also used in various conceptual models, such as cross-sections and 2-D radial grid models.
- Theoretically, finite difference models permit discretization of the reservoir using both structured and more complex unstructured grids to accurately represent the geometry of the reservoir. Local grid refinements (a finer grid embedded inside of a coarse grid) are also a feature provided by many simulators to more accurately represent the near wellbore multi-phase flow effects. This "refined meshing" near wellbores is extremely important when analyzing issues such as water and gas coning in reservoirs.
- Representation of faults and their transmissibilities are advanced features provided in many simulators. In these models, inter-cell flow transmissibilities must be computed for non-adjacent layers outside of conventional neighbor-to-neighbor connections.
- Natural fracture simulation (known as dual-porosity and dual-permeability) is an advanced feature which model hydrocarbons in tight matrix blocks. Flow occurs from the tight matrix blocks to the more permeable fracture networks that surround the blocks, and to the wells.
- A black oil simulator does not consider changes in composition of the hydrocarbons as the field is produced. The compositional model, is a more complex model, where the PVT properties of oil and gas phases have been fitted to an equation of state (EOS), as a mixture of components. The simulator then uses the fitted EOS equation to dynamically track the movement of both phases and components in field.
The simulation model computes the saturation change of three phases (oil, water and gas)and pressure of each phase in each cell at each time step. As a result of declining pressure as in a reservoir depletion study, gas will be liberated from the oil. If pressures increase as a result of water or gas injection, the gas is re-dissolved into the oil phase.
A simulation project of a developed field, usually requires "history matching" where historical field production and pressures are compared to calculated values. In recent years optimisation tools such as MEPO has helped to accelerate this process, as well as improve the quality of the match obtained. The model's parameters are adjusted until a reasonable match is achieved on a field basis and usually for all wells. Commonly, producing water cuts or water-oil ratios and gas-oil ratios are matched.
Other engineering approaches
Without FD models, recovery estimates and oil rates can also be calculated using numerous analytical techniques which include material balance equations (including Havlena-Odeh and Tarner method), fractional flow curve methods (1-D displacement by Buckley-Leverett, Deitz method for inclined structures, coning models), sweep efficiency estimation techniques for water floods and decline curve analysis. These methods were developed and used prior to traditional or "conventional" simulations tools as computationally inexpensive models based on simple homogeneous reservoir description. Analytical methods generally cannot capture all the details of the given reservoir or process, but are typically numerically fast and at times, sufficiently reliable. In modern reservoir engineering, they are generally used as screening or preliminary evaluation tools. Analytical methods are especially suitable for potential assets evaluation when the data are limited and the time is critical, or for broad studies as a pre-screening tool if a large number of processes and / or technologies are to be evaluated. The analytical methods are often developed and promoted in the academia or in-house, however commercial packages also exist.
- Black-oil equations
- Reservoir modeling
- Geologic modeling
- Petroleum engineering
- Computer simulation
- Seismic to Simulation
- Software for Reservoir Simulation
- Aziz, K. and Settari, A., Petroleum Reservoir Simulation, 1979, Applied Science Publishers.
- Ertekin, T, Abou-Kassem, J.H. and G.R. King, Basic Applied Reservoir Simulation, SPE Textbook Vol 10, 2001.
- Fanchi, J., Principles of Applied Reservoir Simulation, 3rd Edition, Elsevier GPP, 2006.
- Mattax, C.C. and Dalton, R. L, Reservoir Simulation, SPE Monograph Volume 13, 1990.
- Holstein, E. (Editor), Petroleum Engineering Handbook, Volume V(b), Chapt 17, Reservoir Engineering, 2007.
- Warner, H. (Editor), Petroleum Engineering Handbook,Volume VI, Chapter 6, Coalbed Methane, 2007.
- Carlson, M., Practical Reservoir Simulation, 2006, PennWell Corporation.
- R. E. Ewing, The Mathematics of Reservoir Simulation