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A systematic and practical approach for analysing well test data of tight sandstone dry gas formations was developed that successfully models the near-wellbore effects post hydraulic fracture stimulation. First, 2D well test analytical models were used to investigate the derivative curve shapes that resulted from an actual field case; then deconvolution was applied to confirm the boundary of the well test data. 3D numerical models were then used to model and match the well test and deconvolution results that were obtained. All simulations used measured PVT properties and core data from the actual field dataset as input parameters. The analysis of the actual well test and comparison with the simulation results of the same test conducted on the simulation models confirmed that they resulted in the same derivative response. This analytical and numerical study has enabled the identification of the distance of the boundaries that compose the radial composite response in the well test analysis.

The application of a DFN in the finite-element grid was used to simulate the reservoir model, with the changes in the composite regions modelled as DFN anisotropy, as compared to the typical changes in grid properties, to obtain a radial composite model response. Thus it has been proved that the radial composite response is actually related to changes in the DFN that surrounds the well and the induced fracture. The investigation included simulation tests to evaluate the effect of the geomechanics on well test data and analysis (Fig. 7-1). The same technique was applied to the actual field data to investigate the radius of the region that is affected by the induced fracture and the main geomechanical properties that affect the DFN around the induced fracture.

Figure 7-1. Suggested workflow for well test analysis of tight sandstone naturally fractured formations.

The suggested workflow offers the opportunity to use well test results from tight sandstone reservoirs to design optimal (right-sized) hydraulic fracture stimulations that can connect with a pre-existing DFN when taking into consideration the scale-dependent rock framework properties

This thesis presents the first comprehensive study of this unique well test signature and subject. This study provides the following conclusions:

1. Tight sandstone reservoirs stimulated with induced hydraulic fracturing may often display a unique well test signature.

2. The data-mining process confirmed that this characteristic well test signature exists in several tight sandstone reservoirs post-fracturing and is associated with well test analysis results that show composite behaviour with multiple permeability regions around the wellbore. The well test response is similar to the composite behaviour seen in lean gas condensate wells, where there it is due to the existence of a condensate bank that is formed during the well test as the pressure drops below the dewpoint, thus causing different permeability regions around the wellbore. Since this well test

signature was reported from multiple locations in several locations worldwide with similar reservoir conditions (i.e., tight sandstone, stimulated by induced hydraulic fracture, dry gas), the recurrent signature is likely to be related to the effect of the induced fracture.

3. After investigation, factors that may cause the unique well test signature to be similar to that of a lean gas condensate reservoir (e.g., PVT, core data, geological setting, well production, and wellbore-related issues) are considered inapplicable to the subject case. 4. The typical linear and bilinear flow response that is seen in the early-time region of the

subject well test is due to the existence of a high-permeability streak intersecting the wellbore (i.e., induced hydraulic fracture). This was modelled and simulated as per the actual fluid mixture of proppant and gel to confirm the shape, half-length and width of the fracture. The proppant distribution in the fracture is of vital importance because it does affect the well test response. The manner in which the proppant is distributed within the fracture crack affects the interaction of the induced hydraulic fracture with the natural fracture network around it. The initial linear flow is a reflection of a high to moderate Cfd (dimensionless fracture conductivity)and causes pseudolinear flow due to

negligible Δp in the fracture plane. It was found that because the far part of the induced hydraulic fracture may have low concentration of proppant, the flow from the natural fracture network is enhanced, as it is reflecting flow from the narrow natural fractures into a wider region of open flow.

5. The characteristic derivative curves that identify multiple mobility zones that are noted after the bilinear and linear flow in the well test imply a change in storativity or a region of changed mobility, which confirms that the flow passes through different regions of natural fractures. If the natural fracture network was homogeneous and intact, then the well test response would be expected to match the initial well test derivative curve prior to the stimulation. However, the existence of the change of the storativity or mobility region implies that there is a change that has affected the natural fracture network in the region around the induced hydraulic fracture.

6. Well test analysis using typical analytical well test software and deconvolution confirmed the boundary conditions of the reservoir. Significant results were obtained initially from deconvolution, confirming the dual-porosity response, which is typical for formations with natural fractures. However, these software programs are not able to

model the natural fracture networks. Thus inadequate reservoir characterisation can be misleading when attempting to model naturally fractured formations using the typical analytical models. 3D numerical modelling allows the DFN network to be incorporated in the reservoir model.

7. The dimensions and properties of the induced hydraulic fracture are obtainable by proper modelling of the fracture shape as a 3D fracture geometry that intersects a DFN network. The proppant distribution within the fracture shape affects the fracture conductivity, and interaction with the DFN around the hydraulic fracture is affected by the same parameters.

8. Modelling of tight sandstone naturally fractured reservoirs should be performed with the use of a DFN model and finite-element simulation. The specific modelling of the DFN is sensitive to the properties of the fracture network in terms of the aperture, orientation, and shape factor (sigma). It has been proved that these factors affect the well test response significantly when compared to the previous traditional modelling techniques, utilising the dual-porosity method in which the sigma factor is the only parameter that communicates the interaction between the matrix and the fracture network.

9. The effect of geomechanics on the well test interpretation is significant because the flow in tight sandstone formations is directly correlated to the flow coming from the natural fracture network. The matrix is typically very tight, and the flow is a result of an efficiently connected fracture network, enabling passive flow to take place throughout the network and then connect to the wellbore through the induced fracture. The normal strain is the actual parameter that contributes to the connection and enhanced flow from the DFN, resulting in a well test result that matches the actual well test obtained from actual field data.

10. This study demonstrates that geomechanic effects impact the region around the induced hydraulic fracture. From 3D finite-element simulations utilising the two-way coupling technique with a geomechanical simulator, this impacted region was shown to occur at a distance equal to the half-length of the fracture in the same fracture orientation direction.

7.3 Comparison of Different Remedial Solutions to