In the oil industry, complex workflow is used to match or predict fluid production. The large uncertainty of the data can lead to large variability of the simulation results, notably because of the strongly heterogeneous nature of fluid flows. The particular case of naturally fractured reservoirs is well known to be especially difficult to match.This paper presents a method to improve an initial geological analysis, carried out in 2008, through the integration of hydrodynamic data in the fractured reservoir model. Dynamic data such as production information, production logging tools and well tests are used to determine fractures properties by calibrating the fluid flow or reservoir pressure measured at wells. The approach, applied to a real field case, respects both the statistical geological analysis and the dynamic analysis of the production history. Using this methodology the geological structural model based on static characterization are preserved and available.In the study we analysed uncertainties and, in respecting the initial geological model, we prove the presence of compartmentalization in the reservoir by matching 1 year of production and three well tests. Both analytical and numerical flow simulations were used at different scales for time and space: near the well and on the whole reservoir.
Low permeability reservoirs are currently being produced using horizontal wells and massive hydraulic fracturing operations. The design of stimulation jobs requires an integrated knowledge of the reservoir (lithology, mechanical properties, fracture properties, PVT, etc), needing calibration and scenario simulation capacities. Current tools permitting such a workflow exist, yet rarely fully integrated within a single package. In this paper we aim to show the advantages of using two new tools, presently developed as prototypes, namely an unstructured fracture model and a multiphysics coding platform designed to integrate all concepts currently under research pertaining to unconventional reservoirs. Characterization of unconventional reservoirs implies the conciliations of several scales, demanding the integration of a potentially large fracture information database. Within this "rich" database, today's models have difficulties integrating all this information. Thus, improving upon current Discrete Fracture Networks (DFN) would require many fractures to be accounted for (up to 500,000). Coupling of such DFN's to reservoir modeling packages often use up-scaling methods, resulting in models which in turn are simulated using extensions of classical dual continuum models. Current reservoir models do not integrate all physical pertinent phenomena though as being important for gas or multiphase production such as dynamic permeability varying with pressure, nonequilibrium effects, multicomponent adsorption models, diffusion effects or proper transfer functions between matrix and fractures. Using a realistic example inspired from field data, we show how the construction of a fracture model using a consistent Discrete and Deformable Fracture Networks (DDFN), tractable for multiphase flow reservoir simulations, can help describing a complex fracturing case. The use of a coding platform tailored to pertinent unconventional physics is discussed, through examples of developed multiphysics Geoscience applications. The example shows how the integration of the representation of a multistage operations through a DDFN model, using the joint characterization of a field natural fracture system and a propagating fracture network corresponding to the hydraulic fracturing process, calibrated on the BHP and microseismic cloud, is input as a specific unstructured dual discretization into a reservoir model. This explicit description of the fracture geometry is coupled to a non-discretized matrix refinement function accounting for matrix heterogeneities, well-adapted to the dynamic pressure behavior observed in such reservoirs. A generalized multiple interacting continua formulation (named "transient transfer influence function") is used within the matrix medium, allowing the simulation of a longer transition period, typical of many unconventional reservoirs, thus improving matrix contribution during hydraulic fracturing. Because the full process may include several hundred thousand fractures and approximately the same number of cells for the matrix medium, we show how run time performance is improved through a preconditioning technique which reduces the condition number of the matrix associated to the linear system, and speed up the iterative parallel linear solver convergence. The discussion of results obtained by using the integrated DDFN is extended to the potential use of an adapted computational platform which could be used for the inclusion of specific physics pertinent to unconventional reservoirs. This DDFN approach is able to computationally handle 100,000's of fractured coupled to a fluid flow simulator. The platform on which it was implemented could be extended to multiphysics problems, essential for unconventional resources.
Objectives/Scope The inherent complexity of unconventional resources, within the ever growing economic development of these, gave rise to many work-flows, in which both natural and hydraulic fractures are accounted for through the use of DFN (Discrete Fracture Network) models. Assessing the specific role of fractures in a multiphase flow context while inferring their mechanical behavior as well as their interaction leads to a better understanding of production characteristics from shale and tight reservoir. Methods, Procedures, Process A realistic reservoir case was considered for this study. A classical characterization methodology was used, integrating different scales, from seismic to core analysis. This characterization step, along with geomechanical considerations, such as brittleness leads to a statistical description of two fracture sets (natural and hydraulic), building a continuous DFN. This makes up our fracture model, geo-stochastically controlled. A simplified coupling method, for which two distinct mechanical laws (plastic-elastic) are applied, is used to describe the hydraulic fracturing process. Hydraulic fluid injection is simulated using an approximate fluid model (PAD + ‘Proppant’). Accounting for the pressure dependent fracture compressibility involves the inclusion of the dynamic behavior of fractures into the DDFN through the use of analytic and empirical fracture deformation models. Results and Observations The history-match of the BHP recorded during the stimulation and overall microseismic cloud, honors hydraulic fracturing characteristics such as injection rates and fluid properties, hence allowing the validation of both the characterization and geomechanical hypothesis formulated. This calibration was carried out on each hydraulically fractured stage, followed by an integration to the reservoir fluid flow simulator. Novel/Additive Information This paper describes a new method, called DDFN (Discrete and Deformable Fracture Network), applied at a large reservoir scale. The reservoir discretization method is computationally efficient, making it appropriate for any optimization of the hydraulic fracturing process. An additional characteristic of the DDFN approach is the by-passing of the up-scaling step, since the DDFN is included at the reservoir simulation scale directly, in the form of an unstructured grid, thus providing a more realistic representation of the overall fracture geometry. Examples of such simulation results performed using realistic data are shown. Discussion of the worth and limitations of the method is done. Planned Conclusion The application of this method to all stages makes up a realistic method, which could be used at reasonable speeds within any reservoir study. The main advantage of such a method is that it can be adapted to any characterization method. By nature modular, it could be linked to any workflow which provides a continuous fracture network made up of the interaction between natural and hydraulically induced fractures
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