• 专利附录
  • 专利说明
  • 权利要求
  • 类似技术
  • 同族专利
  • 引用文献
  • 法律状态
  • 优先权
    • 专利摘要:
    One embodiment of a geomodelling method includes: (a) obtaining a model (210) of a subsurface region (200) having a reservoir, the model (210) including a discrete fracture network; (b) determining an aperture map for each fracture (302, 304) in the discrete fracture network, each aperture map having aperture values based at least in part on a lateral dimension of the fracture (302, 304); (c) for each of a plurality of cells (212) in the model (210): (cl) identifying a portion of the discrete fracture network contained within the given cell (212); (c2) deriving a fracture permeability from aperture cards for the identified portion; and (c3) calculating a fracture porosity from aperture cards for the identified portion; and (d) displaying the fracture porosity and fracture permeability as a function of position throughout the subsurface region (200).
    公开号:FR3034556A1
    申请号:FR1651681
    申请日:2016-02-29
    公开日:2016-10-07
    发明作者:Yogendra Narayan Pandey；Genbao Shi；Jeffrey Marc Yarus；Veronica Liceras
    申请人:Landmark Graphics Corp；
    IPC主号:
    专利说明:

    [0001] 1 Background Seismology is used for exploration, archaeological studies, and engineering projects that require geological information. Exploration seismology provides data that, when used in conjunction with other geophysical, borehole, and geological data available, can provide information about the structure and distribution of rock types and their contents. Such information greatly helps research geothermal reservoirs, water, and mineral deposits such as hydrocarbons and ores. Most companies rely on exploration seismology to select sites in which to explore exploration oil wells. Traditional seismology uses artificially generated seismic waves to map structures within a subsurface region. Seismic waves propagate from a source to the earth and are reflected from the boundaries between subsurface structures. Surface receivers detect and record reflected seismic waves for later analysis. Typically, the recorded signals from each shot (i.e., each source start) are processed to form a partial image based on the depth of the subsurface. The partial images are overlapped and added ("stacked") to form a volumetric image of the subsurface boundaries that delimit the layers of the formation and other structures. The properties of each layer or other structure are then determined from a variety of sources including additional seismic signal processing, direct measurement via borehole ratios and cores, and interpretation by professional geologists. .
    [0002] The resulting geological model has great value for identifying subsurface features of interest (including reservoirs), evaluating development strategies, and optimizing the execution of these strategies. Among the 10 common uses of such models is the determination of the production potential of various wells drilled in and around hydrocarbon reservoirs. These determinations typically involve the simulation of fluid flows from the wellbore formation matrix to estimate rates and volumes of hydrocarbon production. For such simulations, the porosity and permeability values of the formation are particularly interesting depending on the position throughout the region containing the reservoir. One factor that potentially complicates many formations (particularly the increasingly important role played by shale) is the presence of natural fractures that may serve as fluid flow paths or dominant storage mechanisms, or for less alter, effective porosity and / or permeability of the matrix material. Fractures tend to be two-dimensional in nature, having a thickness ("opening") which is much smaller than their lateral dimensions (length and width), and as such they require special handling when dealing with simulations. which typically consider a coarse volumetric block as a fundamental unit. One approach approached by the literature is the use of a volumetric block model augmented by a discrete fracture network (DFN) for "Discrete Fracture 5 Network". DFN represents fractures in the form of two-dimensional surfaces incorporated in the volumetric block model. Often, fractures are presumed to be flat rectangles, although some representations may represent mosaic surface fractures that may be irregularly shaped and may be curved or wavy (i.e. non-planar). . In any case, the existing literature seems to provide each fracture with an assumed opening (often derived from a statistical distribution) that is constant across the entire surface of the fracture, with different fractures having aperture values. different or randomly varying across the fracture surface without any physical correlation. These 20 approaches neglect some of the physical realities of fracture geometry, introducing unavoidable inaccuracies on the models and results derived from this approach.
    [0003] According to one or more embodiments of the present disclosure, a geomodelling method comprises: obtaining a model of a subsurface region comprising a reservoir, the model including a discrete fracture network; determining an aperture map for each fracture in the discrete fracture network, each aperture map having aperture values based at least in part on a lateral dimension of the fracture; for each of a plurality of cells in the model: identifying a portion of the discrete fracture network contained within the given cell; deriving a fracture permeability from opening cards for the identified portion; and calculating a fracture porosity from aperture cards for the identified portion; and displaying fracture porosity and fracture permeability as a function of position throughout the subsurface region. According to one or more embodiments of the present disclosure, said calculation includes: converting each aperture card into a localized fracture porosity map; and integrating localized fracture porosity map values for the identified portion of the discrete fracture network. According to one or more embodiments of the present disclosure, said derivation includes: transforming each aperture card into a localized fracture permeability map; the application of directional component weightings to localized fracture permeability map values; and aggregating weighted localized fracture permeability map values for the identified portion of the discrete fracture network.
    [0004] According to one or more embodiments of the present disclosure, the method further comprises estimating a producible reservoir volume based at least in part on a spatial dependence of the fracture porosity. According to one or more embodiments of the present disclosure, the method further comprises estimating a reservoir production rate based at least in part on a spatial dependence of the fracture permeability. According to one or more embodiments of the present disclosure, the determination includes the use of a length-correlated geostatistical technique to associate an aperture value with each face of a mosaic representation of the fracture. . According to one or more embodiment (s) of the present disclosure, the geostatistical technique comprises at least one of: kriging, sequential Gaussian simulation, and co-simulation.
    [0005] According to one or more embodiments of the present disclosure, the determination includes the use of a geometric technique to assign a length-correlated aperture value to each face of a mosaic representation of the fracture. .
    [0006] According to one or more embodiments of the present disclosure, the geometric technique assigns aperture values to provide the fracture with an elliptical section. According to one or more embodiments of the present disclosure, the model further includes matrix porosity and matrix permeability values for each cell.
    [0007] According to one or more embodiments of the present disclosure, a geomodelling system comprises: nonvolatile information storage including a model of a subsurface region, the model including a discrete fracture network; a memory including modeling software; and one or more processors coupled to the memory 10 for executing the modeling software, the software causing the one or more processors to derive spatially dependent fracture porosity values and spatially dependent fracture permeability tensor values from the network discrete fractures by: determining an opening map for each fracture in the discrete fracture network, each aperture map having aperture values that are based at least in part on a short dimension of the gap; fracture; for each of a plurality of cells in the model: identifying a portion of the discrete fracture network contained within the given cell; derivation of fracture permeability from opening maps for fractures in this portion; and calculating fracture porosity from the opening cards for fractures in that portion; and wherein the software further causes the one or more processors to display or store fracture permeability and fracture porosity as a function of position throughout the subsurface region. According to one or more embodiments of the present disclosure, said calculation includes: converting each aperture card into a localized fracture porosity map; and integrating localized fracture porosity map values for the identified portion of the discrete fracture network. According to one or more embodiment (s) of the present disclosure, said derivation includes: transforming each aperture card into a localized fracture permeability map; Applying directional component weightings to localized fracture permeability map values; and aggregating weighted localized fracture permeability map values for the identified portion of the discrete fracture network. According to one or more embodiments of the present disclosure, the system further comprises estimating a producible reservoir volume based at least in part on a spatial dependence of the fracture porosity. According to one or more embodiments of the present disclosure, the system further comprises estimating a reservoir production rate based at least in part on a spatial dependence of the fracture permeability. According to one or more embodiments of the present disclosure, the determination includes the use of a geostatistical technique correlated with length to associate an aperture value with each face of a tiled representation of the present invention. fracture. According to one or more embodiment (s) of the present disclosure, the geostatistical technique 5 comprises at least one of: kriging, sequential Gaussian simulation, and co-simulation. According to one or more embodiments of the present disclosure, the determination includes the use of a geometric technique to assign a length-correlated aperture value to each face of a mosaic representation of the fracture. . According to one or more embodiments of the present disclosure, the geometric technique assigns aperture values to provide the fracture with an elliptical section. According to one or more embodiment (s) of the present disclosure, the model further includes values of matrix porosity and matrix permeability for each cell.
    [0008] Brief Description of the Drawings Accordingly, the drawings and the following description disclose geological modeling systems and methods which employ an aperture mapping correlated with the size of the fracture and which further employ the opening maps as basis of determination of porosity tensors and localized fracture permeability. In the drawings: FIG. 1 is a block diagram of an illustrative geological modeling system. Figure 2A is an isometric view of an illustrative subsurface region. Figure 2B is an isometric view of an illustrative volumetric model showing the subsurface region. Figure 3A is a detail view of a model cell including a portion of a discrete fracture network. Figure 3B is a flattened representation of a fracture. Figure 4 is a flow chart of an illustrative geological modeling process. Figure 5A is a mosaic representation of a fracture. Figure 5B is a view of the flattened representation with superposed bins. Figure 5C is the flattened representation including mosaics associated with individual skips. Figure 6 is a mapping of mosaic coordinates associated with aperture values.
    [0009] It should be understood, however, that the specific embodiments given in the drawings and in their detailed description do not limit the disclosure, but rather that they give the person skilled in the art the foundation on which to discern the shapes, equivalents and alternative modifications which are encompassed with the embodiments given by the scope of the appended claims. DETAILED DESCRIPTION The disclosed systems and methods are best understood in an illustrative context. We begin here with a brief discussion of the material that commonly integrates the tools of the profession of geological modeling. Fig. 1 shows a computer system including a personal workstation 102. The workstation 102 may be in the form of a desktop computer having a user interface (eg, keyboard, mouse, and display) that allows the workstation to communicate. user to interact with the system, enter instructions and view answers. In this way, the user is able to load seismic data into the system, configure and control the data processing to obtain and store geological models, subject these models to additional processing for refining, and use these models for evaluation. production strategies through the simulation of potential production operations.
    [0010] Generally, the workstation 102 lacks sufficient internal resources to perform such processing in a timely manner. A local area network (LAN) 104 couples the workstation 102 to one or more multiprocessor computers 106, which themselves are coupled via a storage area network (SAN) 108 to one or more shared storage units 110. The LAN 104 provides high speed communication between the multiprocessor computers 106 and the personal workstation 102. The LAN 104 may take the form of an Ethernet network. The multiprocessor computer (s) 106 provides parallel processing capability to enable timely processing of the seismic and geological model data. Each computer 106 includes multiple processors 112, a distributed memory 114, an internal bus 116, a SAN interface 118, and a LAN interface 120. Each processor 112 operates on allocated tasks to solve part of the global problem and contribute at least some of the overall results. Each processor 112 is associated with a distributed memory module 114 which stores application software and a raw data set for use of the processor. The internal bus 116 provides interprocessor communication and communication with the SAN or LAN networks via the corresponding interfaces 118, 120. Communication between processors in different computers 106 may be provided by LAN 104 or via a mailbox mechanism on storage devices 110. SAN 108 provides low latency access to shared storage devices 110. The SAN 108 may take the form of, for example, a Fibrechannel 15 or Infiniband network. Shared storage units 110 may be large standalone information storage units that employ magnetic disk type media for nonvolatile data storage. To improve the speed and reliability of data access, the shared storage units 110 may be configured as a redundant disk array ("RAID"). It is the software that configures the various parts of the computer system to co-ordinate and operate collectively as a geological modeling system ("geo-modeling"). One or more proprietary or commercially available software packages may be installed in the computer system to provide the desired functionality. Scripts, workflows, or other user-created programming mechanisms may be employed to customize the operation of the software and to automate certain operations such as those outlined below for aperture mapping correlated with size. fracture and localized porosity and permeability determinations. Examples of commercially available software that support the use of such user programming include Paradigm's GOCAD software, which supports the use of TCL ("Bol Command Language") or CLI ("Command Language Interface"). And Schlumberger's Petrel software, which includes a process manager 10 for creating workflows. Both packages support the use of plug-ins ("plug-ins" in English) that can be licensed in traditional programming languages such as C ++. Nevertheless, the implementation of the following methods is not limited to any specific software language or execution environment. Figure 2a is a representation of a subsurface region of interest 200 having formation beds 202 and other subsurface structures, potentially including a naturally fractured reservoir. Various wells 204 may be provided or already in existence for production from the reservoir. To evaluate the effectiveness of the well placement and other customizable parameters of the reservoir development and production strategy, the subsurface region of interest 200 is represented by a geologic model 210 that is squared or otherwise divided into cells. 212. Each cell is assigned a value representative of a seismic attribute and / or other forming properties (eg, porosity, permeability), allowing the model 210 to represent the spatial variation of these properties throughout the region. interest. Typically, the model 3034556 13 is initially based on seismic attributes such as reflectivity, acoustic impedance, acoustic velocity, and density, and acquires additional parameter values since additional data and processing make it possible to refine the model. The uniform grided data format lends itself to computer analysis and visual rendering at each stage of processing. To allow the model 10 to be developed and refined within a reasonable time, and to make it useful for fluid flow simulations, it is necessary to limit the number of cells 212. Generally, this restriction causes the cells to have sizes of the order of 10 meters or more. While it is not unusual for fractures to have lateral dimensions of this scale, their openings are typically of the order of a few millimeters (or fractions of a millimeter) rendering them essentially invisible despite their influence on permeability and the porosity of the formation. Figure 3a shows an illustrative cell having internal fractures 302, 304, shown as two-dimensional surfaces. The fractures 302, 304 are just the portion of the fractures represented by a discrete fracture network component ("DFN") of the geomodel 210, the portion that intersects the illustrated volumetric cell. To allow flexion and curvature of the fractures, each fracture is represented by a mosaic, for example a triangular mesh representation of the fracture 304 as shown in FIG. 3b. Other surface representation techniques are known and suitable for use in disclosed systems and methods, including rectangular and hexagonal meshes, irregular mosaics, and scatter plot representations. In view of the foregoing context, FIG. 4 shows a flowchart of an illustrative geomodeling process employing aperture mapping correlated with fracture size. It begins with block 402 where the geomodeling system obtains information about formation properties in the region of interest (including fractures), for example by accessing databases containing seismic survey data and borehole reports. In many cases, detailed fracture maps are not available. In such cases, the fracture distribution can be statistically characterized and the statistical parameters employed to generate (via stochastic propagation through estimated stress fields) discrete fracture networks simulated in the region of interest. At block 404, the geomodeling system processes the measurement data to derive a volumetric model of the region of interest, including a DFN. DFN has a two-dimensional representation of each fracture as a surface (potentially curved or wavy). If it is not already normalized to a suitable form, this representation is normalized by the system at block 406. In the embodiment envisaged, the normalized representation is a flat, triangular mesh representation of the fracture, obtained by projecting the DFN representation at 30 triangular mesh of the fracture on a plane. In the embodiment envisaged, the plane is defined by a first straight line between the vertices farthest from the representation DFN, and a second straight line perpendicular to the vertex farthest from the first straight line. Other projections are also envisaged, like non-projected two-dimensional representations (for example parametric representations).
    [0011] In block 408, the system orients the normalized representation within the plane to place a long dimension of the representation parallel to the x-axis. It is possible to use the first straight line from the previous block as x axis. Nevertheless, the embodiment 10 envisaged orients the x-axis parallel to the larger of the two characteristic dimensions called direction length (Ldirection) and dip length (Lpendage). Other orientation techniques are also adequate, as long as the x-axis is generally aligned with the longest lateral dimension of the fracture as shown in Figure 5a. The origin of the coordinate axes is placed in the center of the fracture representation, which can be calculated as the average of the x coordinates and the average of the y coordinates.
    [0012] Also at block 408, the system defines skips along the x axis. The size of the bucket is preferably chosen to be approximately equal to the characteristic width of the faces of the mosaic so that the buckets actually divide the representation into columns approximately the width of a tile. In Figure 5b, the buckets are shown with a size equal to the average edge length. These alignment and tipping operations allow the system to account for anisotropic rock properties that cause natural fractures to deviate from idealized circular or rectangular fracture forms.
    [0013] In block 410, the system processes the standard representation of each fault to associate each face with a corresponding skip. In the embodiment contemplated, the centers of the face (the average of the three vertices defining each face) are used for this purpose, attributing each face to the bucket which includes the center of the face. Figure 5c uses cross-hatching to show the faces assigned to the buckets 532, 534, and 536.
    [0014] Once each face has an assigned bucket, the system determines the width of the fracture in each bucket. FIG. 6 illustrates the width W of the fracture in the bucket 534. The width can be calculated as the difference between the maximum and minimum coordinate values y of the vertices of the faces in the bucket 534. Alternative width measurements are also envisaged. , including the maximum distance between centers of face in the bucket 534. In block 412, the system generates an aperture card 20 by assigning a localized aperture value to each face of the fracture representation. In at least some contemplated embodiments, this task is performed geometrically, while in other contemplated embodiments, this task is performed statistically to correlate the values of the fracture to the size of the fracture. In one of the geometrical embodiments, the system models the fracture section as an ellipse as shown in FIG. 6. The major axis of the ellipse extends from the top edge of the fracture to its bottom edge (and thus has a length equal to the width W of the fracture). Note that the ellipse is usually not centered on the x axis. For example, the ellipse for the 173 faces in the skip 536 (Figure 5c) would be almost entirely below the x-axis. The minor axis of the ellipse is sized according to the width of the fracture in accordance with a correlation relation such that: b max = F VVK Where b max is the length of the minor axis in millimeters, F is a constant, W is the width of the fracture in millimeters, k is an exponent between 0.5 and 2, and the fraction is a scaling factor to account for the difference between average fracture aperture and maximum aperture. The correlation relationship parameters are selected by the user based on his experience, core measurements, or borehole reports. Additional information on fracture size / opening correlation relationships can be found in the literature, including, for example, S. P. Neuman, "Multiscale relationships between fracture length, aperture, density and permeability", Geophysical Research Letters, vol. 35, No. 22, p. L22402, 2008; and S. L. Philipp, F. Afsar and A. Gudmundsson, "Effects of Mechanical Layering on Hydrofracture Location and Fluid Transport in Tanks", Frontiers in Earth Science, vol. 1, No. 4, 2013.
    [0015] To determine the aperture value for each face in the representation of the fracture, the center of the face is taken as the representative point of the entire face. With yi representing the y-axis coordinate of the center of the face for the face j adjusted for the shift between the center of the ellipse and the x-axis, and W and bmax, i representing the lengths of the minor and major axes 3034556 18 of the ellipse in the bucket i, the aperture value for the face j is Namely, the aperture value for the face 5 corresponds to the width of the ellipse at the coordinate y of the center of its face as shown in Figure 6. This approach to the generation of localized aperture values provides elliptic fracture apertures in a deterministic pattern.
    [0016] Another contemplated system assigns localized aperture values using a geostatistical technique such as sequential Gaussian simulation (SGS), rotational band simulation, or multivariate simulation versions of these methods. This approach allows the creation of multiple solutions (realizations) that are of equal probability, which measures the potential uncertainty in the model. These techniques use a random path through all the centers of the faces in the fracture. By constraining the opening values at the fracture boundaries to a value of zero, these techniques "walk" on the random paths, attributing to each face an aperture value derived from a probability distribution with the parameter values. desired mean, variance, and spatial co-variance. These parameter values may be derived from measurements of existing fracture openings in cores or studies in the literature (or their variograms), derived from simulated fracture propagations, or specified by the user. Probability distribution parameter values that describe fracture openings can be correlated to fracture width, average aperture size, fracture position (horizontal and vertical), fracture density, and others. descriptive variables.
    [0017] In block 414, the system calculates a localized permeability value for each face j. Assuming a laminar flow, the flow permeability along the fracture is: However, when the flow direction is not aligned with the fracture, the localized permeability value changes in accordance with the angle α between the flow vector and the normal to the elliptical opening opening on the encompassing face j (Figure 6) = = cos' a 15 12 (See TDv Golf-Racht, Fundamentals of fractured reservoir engineering TD van Golf-Racht, Elsevier Amsterdam, New York, 1982, pages 147 to 157). This latter expression is used by the system 20 in determining the directionally dependent components of the permeability tensor at block 416. Alternatively, the directional dependency may be neglected (i.e., the system assumes that the direction flow is always oriented along the fracture) to obtain a scalar permeability value for each face. At block 416, the system cuts the network of discrete fractures with volumetric cells from the geomodel. The system integrates on the fracture faces within each given cell to derive a total permeability tensor or scalar value for that cell. The system also integrates on the fracture faces to obtain the total face volume (the volume of each face j is the product of the opening bj with the face area Ai). This integral, when divided by the cell volume V'i'i 'gives the porosity of the fracture: (rif = A; b; / Vceime jccelidle This equation can also be seen as the expression of a localized porosity value for each face j of the representation of the fracture: Aibi Vceime In this way (that is to say the association of localized porosity and permeability values with the faces of the fracture representations), system 15 converts a fracture opening map into a fracture porosity map and a fracture permeability map.These maps can be viewed or, as previously discussed, aggregated to obtain values for the cells of the model. volumetric.
    [0018] In block 418, the system takes the fracture permeability and porosity values of the volumetric cell fractures, together with any other significant sources of permeability and porosity (such as matrix material pores), and uses them. to evaluate any reservoir in the region of interest. Such an evaluation typically involves a determination of the fluid saturations (including hydrocarbon percentages of which the formation fluid is composed), a determination of hydrocarbon volume or density in situ, and fluid flow simulations. to determine the volume and rate of hydrocarbon producible for various well configurations. For flow simulations for Type I tanks, where fractures are the primary source of hydrocarbon storage capacity and serve as primary flow paths, it may be sufficient to consider only the fracture properties at performing an evaluation. Nevertheless, in Type II tanks, matrix porosity dominates hydrocarbon storage, and in Type III reservoirs the matrix provides the primary flow paths. Thus, evaluations for type II and type III reservoirs must necessarily consider the matrix properties in addition to the fracture properties. Simulations often employ a finite volume (or finite element) approach in 3D (or hybrid 2.5D) to solve flow equations for matrix and fractures separately, supplemented by equations modeling the transfer of fluids between matrix and fractures. These simulations may involve a finer scale mesh with an unstructured grid that gives a very high resolution in the region close to the fracture. Alternatively, the properties of the fracture and the matrix can be combined with an equivalent representation in a relatively coarse grid or on an upper scale. The results of fluid flow simulations and other evaluation operations can be visually represented on a computer screen for the user to study and manipulate. Typically, the user will identify potential problems based on these visual representations and will take additional steps to address these problems. Such additional operations may include finer grain simulations, alternative sink configurations, potential pacing treatments, and any other optimization that may appear to be justified based on available resources. As mentioned previously, it is envisaged that the operations shown in FIG. 4 can be implemented as software, which can be stored in a computer memory, in long-term storage media, and in portable information storage media. It should be noted that the illustrative method of FIG. 4 is provided for explanation only. In practice, the various operations shown in Figure 4 can be performed in different orders and are not necessarily sequential. For example, geomodel processing can substantially benefit from parallelism. In some embodiments of the method of processing, data from different portions of the model can be processed independently. In other embodiments, the operations can be "channeled" so that operations on individual faults occur in the displayed sequence despite the simultaneous application of different operations to different faults. Additional operations may be added to the illustrative method and / or more of the operations shown may be omitted. Many other modifications, equivalents, and alternatives will be apparent to those skilled in the art once the above disclosure is fully appreciated.
    [0019] For example, the correlation between the size and the opening of the fracture may take forms other than the law of powers given above. The elliptical shape used for geometric determination of localized aperture values may be replaced by other shapes, including oval, tear, and mystical almond. Rectangular and trapezoidal shapes are also contemplated. The mesh may be formed of any form of generic geometric polygon. It is further contemplated that the allocated apertures may be given a time dependence which itself introduces a time dependence on the values of the porosity and the permeability of the localized fracture. This time dependence can be used to capture the effects of drainage and reservoir subsidence. The following claims are intended to be interpreted to encompass all of these modifications, equivalents, and alternatives, if applicable.
    权利要求:
    Claims (20)
    [0001]
    REVENDICATIONS1. A method of geomodelling, characterized in that it comprises: obtaining a model (210) of a subsurface region (200) comprising a reservoir, the model including a discrete fracture network; determining an aperture map for each fracture (302, 304) in the discrete fracture network, each aperture map having aperture values based at least in part on a lateral dimension of the fracture (302, 304); for each of a plurality of cells (212) in the model (210): identifying a portion of the discrete fracture network contained within the given cell (212); derivation of fracture permeability from opening cards for the identified portion; And calculating fracture porosity from aperture cards for the identified portion; and displaying fracture porosity and fracture permeability as a function of position throughout the subsurface region (200).
    [0002]
    The method of claim 1, wherein said calculating includes: converting each aperture card into a localized fracture porosity map; and integrating localized fracture porosity map values for the identified portion of the discrete fracture network. 3034556 25
    [0003]
    The method of claim 1 or 2, wherein said derivation includes: transforming each aperture card into a localized fracture permeability map; the application of directional component weightings to localized fracture permeability map values; and aggregating weighted localized fracture permeability map values for the identified portion of the discrete fracture network.
    [0004]
    The method of any one of claims 1 to 3, further comprising estimating a producible reservoir volume based at least in part on a spatial dependence of the fracture porosity.
    [0005]
    The method of any one of claims 1 to 4, further comprising estimating a reservoir generation rate based at least in part on a spatial dependence of the fracture permeability.
    [0006]
    The method of any one of claims 1 to 5, wherein the determining includes using a length-correlated geostatistical technique to associate an aperture value with each face of a mosaic representation of the fracture. (302, 304).
    [0007]
    The method of claim 6, wherein the geostatistical technique comprises at least one of: kriging, sequential Gaussian simulation, and co-simulation.
    [0008]
    The method of any one of claims 1 to 5, wherein the determining includes using a geometric technique to assign a length-correlated aperture value to each face of a mosaic representation of the fracture (302, 304). 10
    [0009]
    The method of claim 8, wherein the geometric technique assigns aperture values to provide the fracture (302, 304) with an elliptical section. 15
    [0010]
    The method of any one of claims 1 to 9, wherein the model (210) further includes matrix porosity and matrix permeability values for each cell (212). 20
    [0011]
    A geomodeling system, characterized in that it comprises: nonvolatile information storage including a model (210) of a subsurface region (200), the model (210) including a discrete fracture network; a memory (114) including modeling software; and one or more processors (112) coupled to the memory (114) for executing the modeling software, the software causing the one or more processors (112) to derive spatially dependent fracture porosity values and tensor values of 3034556 27 spatially dependent fracture permeability from the discrete fracture network by: determining an opening map for each fracture (302, 304) in the discrete fracture network, each aperture card having d-values; which are based at least in part on a short dimension of the fracture (302, 304); for each of a plurality of cells (212) in the model (210): identifying a portion of the discrete fracture network contained within the given cell (212); deriving a fracture permeability from opening cards for fractures (302, 304) in this portion; and calculating a fracture porosity from the opening cards for fractures (302, 304) in that portion; and in that the software further causes the one or more processors (112) to display or store fracture permeability and fracture porosity as a function of position throughout the subsurface region (200). 25
    [0012]
    The system of claim 11, wherein said calculating includes: converting each aperture card into a localized fracture porosity map; and integrating localized fracture porosity map values for the identified portion of the discrete fracture network. 3034556 28
    [0013]
    The system of claim 11 or 12, wherein said derivation includes: transforming each aperture card into a localized fracture permeability map; The application of directional component weightings to localized fracture permeability map values; and aggregating weighted localized fracture permeability map values for the identified portion of the discrete fracture network.
    [0014]
    The system of any one of claims 11 to 13, further comprising estimating a producible reservoir volume based at least in part on a spatial dependence of the fracture porosity.
    [0015]
    The system of any one of claims 11 to 14, further comprising estimating a reservoir generation rate based at least in part on a spatial dependence of the fracture permeability.
    [0016]
    The system of any one of claims 11 to 15, wherein the determining includes using a length correlated geostatistical technique to associate an aperture value with each face of a tiled representation of the fracture (302, 304). 30
    [0017]
    The system of claim 16, wherein the geostatistical technique comprises at least one of: kriging, sequential Gaussian simulation, and co-simulation.
    [0018]
    The system of any one of claims 11 to 15, wherein the determining includes using a geometric technique to assign a length-correlated aperture value to each face of a mosaic representation of the fracture (302, 304). 10
    [0019]
    The system of claim 18, wherein the geometric technique assigns aperture values to provide the fracture (302, 304) with an elliptical section.
    [0020]
    The system of any one of claims 11 to 19, wherein the model (210) further includes matrix porosity and matrix permeability values for each cell (212). 15 20
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    同族专利:
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    CA2978699A1|2016-10-13|
    WO2016163984A1|2016-10-13|
    US20170038489A1|2017-02-09|
    AR103835A1|2017-06-07|
    GB201714240D0|2017-10-18|
    AU2015390914A1|2017-09-21|
    GB2552603A|2018-01-31|
    NO20171435A1|2017-09-05|
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    优先权:
    申请号 | 申请日 | 专利标题
    PCT/US2015/024544|WO2016163984A1|2015-04-06|2015-04-06|Fracture-size-correlated aperture mapping for localized porosity and permeability determination|
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