Search

Summary Numerical flow models based on Discrete Fracture Methods (DFM) represent a fractured porous rock using an unstructured mesh where fractures are a subset of the elements faces. This allows for a high degree of geometric accuracy, but it also raises numerical challenges: the mesh must honor both small and large scale geometric features while keeping tractable and stable computations. For these reasons, we previously proposed a new geometric approximation method, which can be applied before meshing. The aim of this paper is to compare the flow impact of different geometric approximations of irregular and complex two-dimensional fracture networks. We present and validate a Control-Volume-Finite-Element DFM-based water flooding model and three fracture approximations strategies. The first strategy (A) projects fractures on the edges of an initial background mesh. The two others (B and C) rely on graph theory to analyze and modify a boundary representation of the fracture network according to minimal angles and mesh sizes criteria. Strategy B modifies the boundary representation using a contraction approach where flagged fracture elements (lines, extremities of intersections) are merged. Strategy C uses an expansion approach which moves the problematic fracture elements away one from another, hence preserving the model connectivity (we also present some adjustments as compared to the already published method). The approximation strategies A, B and C are applied to three reference data sets with respectively: two crossing fractures; highly connected fractures; anisotropic disconnected fractures. For each model, we compare the oil production and the saturation maps to the reference model. These tests show that the connectivity changes implied by the strategies A and B only have a small impact on the flow solution. Nonetheless, the expansion strategy C which preserves the fracture network topology provides the most accurate solution in all test cases.

International audience; Model updating is an important way forward to efficiently incorporate new information about the subsurface. Four local components are needed to address common needs: finding the subregion to be updated, updating the discrete model features (topology) locally or semi-globally, locally updating the feature geometry and locally updating the associated properties. We present a few existing strategies and highlight that topological and geometric editing are essential for geologically consistent and automatic or semi-automatic geomodel updates.

This paper proposes to improve the natural fracture network characterisation by analysis microseismic data. We use a 3D Hough transform to build fracture orientation and density maps describing discontinuities that cannot be described by other measurements. The stochastic Discrete fracture simulator combines geostatistical and pseudo-genetic approaches to generate models that honour both measures from field characterisation and hierarchical organisation that result from the fracturing process itself. We suggest that using realistic fracture network characterisation and introducing mechanical concepts in the DFN simulation process affect connectivity of DFNs, hence is essential for predictivity of reservoir flow models.

International audience

This paper discusses a novel workflow for history matching by perturbing the reservoir structural model constrained to prior geophysical and geological information. Our approach first models prior structural uncertainty related to geophysical processing and structural interpretations using geostatistical methods. Then, from the resulting large set of structural model realizations representing this prior structural uncertainty, the model realizations that match past production history are searched for using a stochastic search technique. In order to achieve an efficient search, the prior structural uncertainty models are embedded into a space defined with a “similarity distance”, i.e. a distance function which measures the similarity between any two reservoir geometry realizations. By choosing a proper distance function, production response from model realizations is spatially structured in this space, allowing a near-neighbor search such as the neighborhood algorithm (Sambridge, 1996). This workflow considers not only stochastically perturbed structural models around some reference interpretation, but also several structural scenarios with varying numbers and positions of fault blocks. A realistic case study is presented.

Building realistic facies models helps to improve reservoir description and performance. The proposed methodology is designed as an extensible framework for the integration of geological knowledge by combining the advantages of two well-tried mathematical technologies: (1) the discrete smooth interpolation, which provides an extensible framework for conditioned and constrained interpolations, and (2) the tau model, which allows the combination of partially redundant data. This presentation shows how sedimentological interpretations and sequence stratigraphy principles can be integrated in this framework to build geologically realistic facies realizations. The final facies model may be refined by accounting for diagenesis effects, which can be superimposed onto depositional facies thanks to our solution.

Whereas more and more reservoir studies use geostatistical simulations to represent petrophysical uncertainty, geological structures are often kept frozen in 3D reservoir modeling. Existing methods which eventually perturb geological structures act directly on the reservoir grid, hence are limited by current flow simulators. Instead, we use a flexible parametric model to stochastically perturb fault and horizon surfaces. We propose two methods to transfer this perturbation onto a volumetric model while maintaining its geometric consistency: - A new extension of simple constrained deformation is applied to a stratigraphic grid, which can then be used in mainstream flow simulators. - A method to perturb both the horizons and fault geometries in a geo-chronological model is also described. This clears the way to realistic structural uncertainty handling in new generation flow simulators.