Modeling tight gas reservoirs

To evaluate a layered, tight gas reservoir and design the well completion, the operator must use both a reservoir model and a hydraulic fracture propagation model. The data required to run both models are similar and can be divided into two groups. One group consists of data that can be "controlled." The second group reflects data that must be measured or estimated but cannot be controlled.

The primary data that can be controlled by the engineer are the well completion details and the fracture treatment details, such as:

• Fluid volume
• Injection rate

The data that must be measured or estimated by the design engineer are:

• Formation depth
• Formation permeability
• In-situ stresses in the pay zone
• In-situ stresses in the surrounding layers
• Formation modulus
• Reservoir pressure
• Formation porosity
• Formation compressibility
• Thickness of the reservoir

There are actually three thicknesses that are important to the design engineer:

• The gross thickness of the reservoir
• The net thickness of the gas producing interval
• The permeable thickness that accepts fluid loss during the hydraulic fracture treatment

Data for reservoir simulation models

The data required to run a reservoir model depends on the type of model one chooses to use. The engineer can use (listed in order of simplest to most complex):

• Semisteady-state flow equations
• Materials balance methods
• Single-layer analytical solutions
• Multilayered analytical solutions
• Numerical reservoir simulation models

As one might expect, the amount and complexity of the data required to use these models increases as the complexity of the model increases.

Interestingly, most of the data required to run a reservoir simulation model are also required to run a 3D hydraulic fracture propagation model. Table 1 lists the data required to run both the reservoir model and the fracture treatment design model. Because a typical tight gas reservoir is a layered formation, it is necessary to determine values of reservoir properties, such as permeability, net pay, porosity, and water saturation on a layer-by-layer basis. Many problems can be solved using a single-layer model; however, in other cases, better completions are achieved by developing multilayer models of the reservoir.

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  Table 1—Sources of Data for Both Reservoir Model and Fracture Model

Hydraulic fracture propagation models

The fracture propagation model requires information on the rock mechanical properties, such as:

• In-situ stress
• Modulus
• Poisson’s ratio

The data on the fracture fluid properties and the propping agent properties is also required.

The most critical data for the design of a fracture treatment are, roughly in order of importance:

• The in-situ stress profile
• Formation permeability
• Fluid loss characteristics
• Total fluid volume pumped
• Propping agent type and amount
• Pad volume size
• Fracture fluid viscosity
• Injection rate
• Formation modulus

The design engineer should focus his/her time on the most important parameters. In hydraulic fracture treatment design, by far the two most important parameters are:

• The in-situ stress profile and the permeability profile of the zone to be stimulated
• The layers of rock above and below the target zone that affect fracture height growth

In new fields or reservoirs, most operating companies are normally willing to spend money to run logs, cut cores, and run well tests to determine important factors such as the in-situ stress and the permeability of the reservoir layers. By using such data, along with fracture treatment records and production records, accurate data sets for a given reservoir in a given field can normally be compiled. These data sets can be used on subsequent wells to optimize the fracture treatment designs. It is normally not practical to cut cores and run well tests on every well. Thus, the data obtained from cores and well tests from a few wells must be correlated to log parameters, so the logs on subsequent wells can be used to compile accurate data.

Vertical profiles

To use either a multilayered reservoir model or a pseudo-three-dimensional (P3D) hydraulic fracture propagation model, the data must be entered by reservoir layer. Fig. 1 illustrates the profiles of important input data required by either the reservoir or the P3D model. For the situation in Fig. 1, the well is completed and the fracture treatment is initiated in the sandstone reservoir. The fracture typically grows up and down until a barrier is reached to prevent vertical fracture growth. In many cases, thick marine shales, which tend to have in-situ stresses that are higher than the sandstones, are barriers to vertical fracture growth. In other cases, coal seams prevent fractures from growing vertically. Many coal seams are highly cleated, and when the fracture fluid enters the coal seam, it remains contained within the coal seam.

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  Fig. 1—Profiles of input data.

The data used to design a fracture treatment can be obtained from a number of sources, such as:

• Drilling records
• Completion records
• Well files
• Openhole logs
• Cores and core analyses
• Well tests
• Production data
• Geologic records
• Other public records, such as publications

In addition, service companies provide data on their fluids, additives, and propping agents.

Economic models

To design the optimum well completion and fracture-treatment design in a tight gas reservoir, detailed economic calculations must be conducted. The first decision is usually to determine if there is enough net gas pay, porosity, and permeability to justify setting casing after the well reaches total depth. Once casing is set, engineering and economic calculations are required to determine the optimum completion method and the optimum fracture-treatment design. The data required to run an economic model are given in Table 2.

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  Table 2—Sources of Data for an Economic Model

Essentially, one must determine the net cash flow for a variety of completion scenarios. The net cash flow can then be evaluated using a number of ways to determine the optimum completion design. The data required to run an economics model is specific to each situation. Many factors can vary widely among leases in the same field and, especially, in different geologic basins in different countries or even continents, such as

• Gas prices
• Operating costs
• Royalty payments
• Taxes

Hence, it is extremely important to gather the appropriate economic data and performed detailed economic calculations to design the optimum well completion.

Noteworthy papers in OnePetro

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External links

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See also

Tight gas reservoirs

Hydraulic fracturing in tight gas reservoirs

Reserves estimation in tight gas reservoirs

Statistical data correlations in tight gas reservoirs

Tight gas drilling and completion

Log analyses in tight gas reservoirs

Core analyses in tight gas reservoirs

Permeability estimation in tight gas reservoirs

PEH:Tight_Gas_Reservoirs