CN113963112A - Method and device for generating discrete fracture network - Google Patents
Method and device for generating discrete fracture network Download PDFInfo
- Publication number
- CN113963112A CN113963112A CN202111214856.5A CN202111214856A CN113963112A CN 113963112 A CN113963112 A CN 113963112A CN 202111214856 A CN202111214856 A CN 202111214856A CN 113963112 A CN113963112 A CN 113963112A
- Authority
- CN
- China
- Prior art keywords
- crack
- cluster
- fracture
- root
- cracks
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
- 238000000034 method Methods 0.000 title claims abstract description 49
- 238000009826 distribution Methods 0.000 claims description 17
- 230000000977 initiatory effect Effects 0.000 claims description 3
- 230000000694 effects Effects 0.000 abstract description 4
- VNWKTOKETHGBQD-UHFFFAOYSA-N methane Chemical compound C VNWKTOKETHGBQD-UHFFFAOYSA-N 0.000 description 10
- 239000007789 gas Substances 0.000 description 7
- 238000007689 inspection Methods 0.000 description 5
- 239000003345 natural gas Substances 0.000 description 5
- 230000008569 process Effects 0.000 description 5
- 239000003245 coal Substances 0.000 description 3
- 238000010586 diagram Methods 0.000 description 3
- 238000005516 engineering process Methods 0.000 description 3
- 238000004891 communication Methods 0.000 description 2
- 239000012530 fluid Substances 0.000 description 2
- 230000006870 function Effects 0.000 description 2
- 230000001788 irregular Effects 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 239000003208 petroleum Substances 0.000 description 2
- 239000003209 petroleum derivative Substances 0.000 description 2
- 239000003079 shale oil Substances 0.000 description 2
- 239000004215 Carbon black (E152) Substances 0.000 description 1
- 238000003491 array Methods 0.000 description 1
- 238000004134 energy conservation Methods 0.000 description 1
- 229930195733 hydrocarbon Natural products 0.000 description 1
- 150000002430 hydrocarbons Chemical class 0.000 description 1
- 230000007774 longterm Effects 0.000 description 1
- 239000011159 matrix material Substances 0.000 description 1
- 238000005065 mining Methods 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
- 230000035699 permeability Effects 0.000 description 1
- 230000009467 reduction Effects 0.000 description 1
- 230000007723 transport mechanism Effects 0.000 description 1
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T17/00—Three dimensional [3D] modelling, e.g. data description of 3D objects
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
- G06Q50/02—Agriculture; Fishing; Forestry; Mining
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Business, Economics & Management (AREA)
- General Physics & Mathematics (AREA)
- Marine Sciences & Fisheries (AREA)
- Human Resources & Organizations (AREA)
- Health & Medical Sciences (AREA)
- Economics (AREA)
- General Health & Medical Sciences (AREA)
- Tourism & Hospitality (AREA)
- Marketing (AREA)
- Primary Health Care (AREA)
- Animal Husbandry (AREA)
- Mining & Mineral Resources (AREA)
- Agronomy & Crop Science (AREA)
- General Business, Economics & Management (AREA)
- Strategic Management (AREA)
- Life Sciences & Earth Sciences (AREA)
- Computer Graphics (AREA)
- Geometry (AREA)
- Software Systems (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
- Investigating Strength Of Materials By Application Of Mechanical Stress (AREA)
Abstract
The embodiment of the application discloses a method and a device for generating a discrete fracture network, wherein the method comprises the following steps: carrying out block division on the area generating the random fracture network to form a plurality of blocks; circularly executing the following steps until a preset stop condition is met: and generating random cracks, recording the cracks according to the blocks, and determining corresponding crack clusters. By the scheme of the embodiment, the discrete fracture network model is quickly and accurately established, and the established discrete fracture network model is low in complexity and good in anti-interference effect.
Description
Technical Field
The embodiment of the application relates to the exploration, development and utilization technology of tectonic geology, geothermy, petroleum and natural gas, in particular to a method and a device for generating a discrete fracture network.
Background
The existing energy structure of China still takes coal as the main part, in 2020, the coal accounts for 56 percent, and the petroleum and the natural gas account for 20 percent and 8 percent respectively. Under the international environment of energy conservation and emission reduction, China further reduces the consumption proportion of coal and increases the investment and development of petroleum and natural gas, particularly natural gas. At present, the external dependence of petroleum in China is close to 70%, and the external dependence of natural gas exceeds 40%, so that the exploration and development of oil and gas resources are related to national energy safety. With the long-term development of conventional oil and gas fields, the high water content stage is generally entered, and the oil and gas yield is difficult to break through. The development of unconventional oil and gas reservoirs, such as compact oil and gas reservoirs, shale oil and gas reservoirs and the like, is becoming more and more important.
Fractures are crucial in the development of unconventional hydrocarbon reservoirs. Taking shale oil and gas reservoirs as examples, the shale reservoir matrix permeability is extremely low, and the yield is extremely low in a conventional mining mode. At present, a mature method is to drill a long horizontal well to perform multi-section hydraulic fracturing, and the fracturing fracture interacts with a natural fracture to form a complex fracture network so as to provide a high-permeability channel for underground fluid seepage. Natural fractures are therefore particularly important in creating reservoir modification volumes, whereas the geometry and specific distribution of subsurface fractures cannot be accurately obtained under existing technical conditions. The discrete fracture network is the only method that can establish a large-scale fracture system at present. The discrete fracture network refers to representing complex fractures by using simple geometric figures, such as straight line segments representing two-dimensional fractures and ellipses or polygons representing three-dimensional fractures. The specific form of the crack, such as roughness, tortuosity and the like, is ignored, but the topological structure of the crack network is preserved. The discrete fracture network model thus established may be used to study the effect of the fracture system on the subsurface fluid seepage.
The connectivity of the discrete fracture network is a key for determining the seepage capability of the fracture network, so that the inspection of the clusters in the fracture network is a key step for judging the good or bad connectivity of the fracture. The algorithm commonly used to examine clusters is the Hoshen-Kopelman algorithm, which is highly complex and is O (N)2lnN), checking for discrete fracture network clusters with large numbers of fractures is inefficient.
Disclosure of Invention
The embodiment of the application provides a method and a device for generating a discrete fracture network, which can be used for quickly and accurately establishing a discrete fracture network model, and the established discrete fracture network model has low complexity and good anti-interference effect.
The embodiment of the application provides a method for generating a discrete fracture network, which can comprise the following steps:
carrying out block division on the area generating the random fracture network to form a plurality of blocks;
circularly executing the following steps until a preset stop condition is met: and generating random cracks, recording the cracks according to the blocks, and determining corresponding crack clusters.
In an exemplary embodiment of the present application, the generating random fractures may include: generating random cracks according to preset statistical distribution;
the statistical distribution typically includes: the length of the crack conforms to power law distribution, the direction of the crack conforms to Fisher distribution, and the position of the crack conforms to Poisson distribution.
In an exemplary embodiment of the present application, after forming a plurality of blocks, before recording the crack according to the blocks, the method may further include: marking each block, and allocating a first array for recording crack numbers in the block to each block;
each fracture possesses a fracture number which increases from 1 in the order of fracture initiation; the recording the crack according to the block may include:
when the length of the generated crack is smaller than the size of the area, setting a temporary integer type second array to record the serial number of the block to which the crack belongs; and recording the crack number corresponding to the crack in a first array corresponding to each block to which the crack belongs; determining all blocks in a rectangular or square area related to the track of the crack as the blocks to which the crack belongs;
and when the length of the generated crack is larger than the size of the area, recording the crack number corresponding to the crack into a preset long crack record array.
In an exemplary embodiment of the present application, the determining the corresponding fracture cluster may include:
when the generated crack is a first crack, forming a first crack cluster by the first crack, and taking the first crack as a root crack of the first crack cluster;
detecting whether the generated fracture intersects at least one generated fracture when the generated fracture is not the first fracture;
when the fracture intersects with one generated fracture, adding the fracture into a fracture cluster to which the intersected generated fracture belongs; when the crack intersects with a plurality of generated cracks, detecting whether the intersected plurality of generated cracks belong to the same crack cluster; adding the generated cracks into the same crack cluster to which the generated cracks belong when the generated cracks belong to the same crack cluster; when the intersected multiple generated cracks do not belong to the same crack cluster, unifying all the crack clusters to which the intersected multiple generated cracks belong into one crack cluster, and adding the cracks into the unified crack cluster;
and when the crack does not intersect with any generated crack, forming a new crack cluster by the crack, and taking the crack as a root crack of the new crack cluster.
In an exemplary embodiment of the present application, each fracture may also have a root node number;
after determining the respective fracture cluster, the method may further comprise: determining a root node number of the crack;
the determining the root node number of the crack may include:
determining a first generated crack in a crack cluster as a root crack of the crack cluster;
for a root crack in a crack cluster, taking the opposite number of the crack in the crack cluster as the root node number of the root crack;
and for other fractures in one fracture cluster except the root fracture, taking the fracture number of the root fracture in the fracture cluster as the root node numbers of the other fractures.
In an exemplary embodiment of the present application, each fracture also has a cluster number; the cluster number is the number of the crack cluster to which the crack belongs, namely the crack number of the root crack in the crack cluster to which the crack belongs;
to determine a fracture cluster corresponding to any fracture, the method may further comprise: and finding the cluster number of any crack through a recursive algorithm.
In an exemplary embodiment of the present application, the finding a cluster number of any crack by a recursive algorithm may include: for any of the fractures, the following operations are performed:
61. checking the root node number of the current crack; when the root node number of the current crack is less than 0, entering step 62; entering step 63 when the root node number of the current crack is the crack number of another crack;
62. determining the cracks with the root node number smaller than 0 as root cracks, and taking the crack numbers of the root cracks as cluster numbers of the current cracks; stopping searching the cluster number;
63. the other fracture is taken as the current fracture and returns to step 61.
In an exemplary embodiment of the present application, the method may further include: when a new crack is added into any crack cluster, updating the root node number of the root crack in the crack cluster;
when any plurality of crack clusters are unified into the same crack cluster, the root cracks in the unified crack clusters are determined, and the root node number and the cluster number of each crack in the unified crack clusters are updated.
In an exemplary embodiment of the present application, the updating the root node number of the root fracture in the fracture cluster may include:
modifying the root node number of the root crack in the crack cluster into the opposite number of the total number of cracks currently contained in the crack cluster;
the determining root cracks in the unified crack cluster, and updating the root node number and the cluster number of each crack in the unified crack cluster may include:
taking root cracks of the crack clusters with the maximum number of cracks corresponding to the plurality of crack clusters before being unified as root cracks of the unified crack clusters;
updating the root node number of the root crack in the unified crack cluster into the opposite number of the total number of all cracks contained in the unified crack cluster; updating the root node numbers of other cracks except the root crack in the unified crack cluster into the crack numbers of the root crack;
keeping the cluster number of the root crack in the unified crack cluster unchanged, and updating the cluster numbers of other cracks into the crack numbers of the root crack.
In an exemplary embodiment of the present application, the stop condition may include: up to a given number of fractures, or clusters of fractures formed throughout the area where the random fracture network was generated.
The embodiment of the application also provides a device for generating a discrete fracture network, which may include a processor and a computer-readable storage medium, where instructions are stored in the computer-readable storage medium, and when the instructions are executed by the processor, the generation of the discrete fracture network is implemented.
Compared with the related art, the embodiment of the application can comprise the following steps: carrying out block division on the area generating the random fracture network to form a plurality of blocks; circularly executing the following steps until a preset stop condition is met: and generating random cracks, recording the cracks according to the blocks, and determining corresponding crack clusters. By the scheme of the embodiment, the discrete fracture network model is quickly and accurately established, and the established discrete fracture network model is low in complexity and good in anti-interference effect.
Additional features and advantages of the application will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by the practice of the application. Other advantages of the present application may be realized and attained by the instrumentalities and combinations particularly pointed out in the specification and the drawings.
Drawings
The accompanying drawings are included to provide an understanding of the present disclosure and are incorporated in and constitute a part of this specification, illustrate embodiments of the disclosure and together with the examples serve to explain the principles of the disclosure and not to limit the disclosure.
FIG. 1 is a flow chart of a method for generating a discrete fracture network according to an embodiment of the present disclosure;
FIG. 2 is a schematic diagram of a method for generating a discrete fracture network according to an embodiment of the present disclosure;
FIG. 3 is a schematic view of a fracture network for creating a discrete fracture according to an embodiment of the present application;
FIG. 4 is a schematic view of a fracture network for creating two discrete fractures in accordance with an embodiment of the present disclosure;
FIG. 5 is a schematic view of a fracture network for producing nine discrete fractures in accordance with an embodiment of the present application;
FIG. 6 is a schematic view of a fracture network reaching a stop condition according to an embodiment of the present application;
FIG. 7 is a schematic diagram of a three-dimensional discrete fracture network according to an embodiment of the present application;
fig. 8 is a block diagram of a device for generating a discrete fracture network according to an embodiment of the present disclosure.
Detailed Description
The present application describes embodiments, but the description is illustrative rather than limiting and it will be apparent to those of ordinary skill in the art that many more embodiments and implementations are possible within the scope of the embodiments described herein. Although many possible combinations of features are shown in the drawings and discussed in the detailed description, many other combinations of the disclosed features are possible. Any feature or element of any embodiment may be used in combination with or instead of any other feature or element in any other embodiment, unless expressly limited otherwise.
The present application includes and contemplates combinations of features and elements known to those of ordinary skill in the art. The embodiments, features and elements disclosed in this application may also be combined with any conventional features or elements to form a unique inventive concept as defined by the claims. Any feature or element of any embodiment may also be combined with features or elements from other inventive aspects to form yet another unique inventive aspect, as defined by the claims. Thus, it should be understood that any of the features shown and/or discussed in this application may be implemented alone or in any suitable combination. Accordingly, the embodiments are not limited except as by the appended claims and their equivalents. Furthermore, various modifications and changes may be made within the scope of the appended claims.
Further, in describing representative embodiments, the specification may have presented the method and/or process as a particular sequence of steps. However, to the extent that the method or process does not rely on the particular order of steps set forth herein, the method or process should not be limited to the particular sequence of steps described. Other orders of steps are possible as will be understood by those of ordinary skill in the art. Therefore, the particular order of the steps set forth in the specification should not be construed as limitations on the claims. Further, the claims directed to the method and/or process should not be limited to the performance of their steps in the order written, and one skilled in the art can readily appreciate that the sequences may be varied and still remain within the spirit and scope of the embodiments of the present application.
The embodiment of the application provides a method for generating a discrete fracture network, which, as shown in fig. 1 and fig. 2, may include steps S101 to S102:
s101, carrying out block division on an area for generating a random fracture network to form a plurality of blocks;
s102, circularly executing the following steps until a preset stop condition is met: and generating random cracks, recording the cracks according to the blocks, and determining corresponding crack clusters.
In the exemplary embodiment of the application, an improved discrete fracture network generation method is provided, which can quickly generate a discrete fracture network, can perform inspection on fracture clusters in the discrete fracture network, can quickly and accurately mark all fracture clusters in the discrete fracture network, and can analyze fracture connectivity according to an inspection result. The cluster inspection method has a complexity close to o (n) and is applicable to two-dimensional and three-dimensional fracture networks.
In an exemplary embodiment of the present application, the area where the random fracture network is generated may be first block-divided to form a plurality of blocks. The area can be a square area or a rectangular area, and block division of the area is facilitated.
In an exemplary embodiment of the present application, after forming a plurality of blocks, before recording the crack according to the blocks, the method may further include: each block is marked and assigned a first array for recording the crack numbers in the block.
In an exemplary embodiment of the present application, each block may be numbered according to row-first or column-first, and each block is assigned an integer-type array (such as the first array described above) to record the crack number in the block.
In an exemplary embodiment of the present application, as shown in fig. 3, the area may be a square area, the area may be divided into 25 small blocks, and each small block may be regarded as one block. The method of the embodiment of the application is also suitable for the irregular area, and the divided small area can be an irregular figure without influencing the implementation of the method of the embodiment of the application.
In an exemplary embodiment of the present application, the generating random fractures may include: generating random cracks according to preset statistical distribution;
the statistical distribution typically includes: the length of the crack conforms to power law distribution, the direction of the crack conforms to Fisher distribution, and the position of the crack conforms to Poisson distribution. Other statistical distributions are possible.
In an exemplary embodiment of the present application, each fracture possesses a fracture number that increases from 1 in the order of fracture initiation; the recording the crack according to the block may include:
when the length of the generated crack is smaller than the size of the area, setting a temporary integer type second array to record the serial number of the block to which the crack belongs; and recording the crack number corresponding to the crack in a first array corresponding to each block to which the crack belongs; determining all blocks in a rectangular or square area related to the track of the crack as the blocks to which the crack belongs;
and when the length of the generated crack is larger than the size of the area, recording the crack number corresponding to the crack into a preset long crack record array.
In an exemplary embodiment of the present application, a random crack may be generated, and if the crack length is less than or equal to the region length, the crack may be regarded as a short crack, and the block to which the crack belongs is recorded and stored in a temporary array (such as the second array described above); recording the crack number of the crack in the corresponding block array (such as the first array); if the crack length is larger than the region length, the crack can be used as a long crack, the search of the affiliated block is not carried out, and the crack number of the crack is recorded in a long crack record array.
In an exemplary embodiment of the present application, each crack may have a crack number, a root node number, and a cluster number, and all of the root node numbers and the cluster numbers may be stored in corresponding arrays.
In an exemplary embodiment of the present application, the crack numbers are incremented from 1 in the order of generation. For a root crack in a crack cluster, the root node number is the opposite number of the number of cracks in the crack cluster, and can be used for recording the total number of cracks in the crack cluster; the root node number is, for other fractures in the fracture cluster, the fracture number of the root fracture in the fracture cluster. The cluster number is the number of the fracture cluster to which the fracture belongs, and is the fracture number of the root fracture in the fracture cluster to which the fracture belongs. The number of the initial root nodes of all cracks is-1, which represents that the initial root nodes of all cracks individually form a crack cluster, and the number of the cracks in the crack cluster is 1.
In an exemplary embodiment of the present application, as shown in fig. 3, for example, the length of the crack 1 is smaller than the area length, so that all the blocks to which the crack belongs are recorded, which may include blocks 2, 3, 7, 8, 12, 13, 17, 18 (gray blocks). For the convenience of the programming process, all the blocks in the rectangular or square area to which the track of each crack relates are set as the blocks to which the crack belongs (for example, the blocks may be the blocks to which a geometric figure composed of two right-angled triangles whose hypotenuses are the straight lines connecting two ends of the track of the crack), and whether the track of each block with cracks exists is not examined, such as the tracks of the blocks 17 and 8 without cracks exist therein. That is, 1 is the crack number of the crack 1, and indicates that the crack 1 is the first random crack to be generated. The root node number of the crack at this time is-1, which means that the crack alone forms a crack cluster, the cluster number of the crack cluster is 1, and the number of cracks in the crack cluster is 1. And the crack 1 is the root crack of the crack cluster.
In an exemplary embodiment of the present application, the determining the corresponding fracture cluster may include:
when the generated crack is a first crack, forming a first crack cluster by the first crack, and taking the first crack as a root crack of the first crack cluster;
detecting whether the generated fracture intersects at least one generated fracture when the generated fracture is not the first fracture;
when the fracture intersects with one generated fracture, adding the fracture into a fracture cluster to which the intersected generated fracture belongs; when the crack intersects with a plurality of generated cracks, detecting whether the intersected plurality of generated cracks belong to the same crack cluster; adding the generated cracks into the same crack cluster to which the generated cracks belong when the generated cracks belong to the same crack cluster; when the intersected multiple generated cracks do not belong to the same crack cluster, unifying all the crack clusters to which the intersected multiple generated cracks belong into one crack cluster, and adding the cracks into the unified crack cluster;
and when the crack does not intersect with any generated crack, forming a new crack cluster by the crack, and taking the crack as a root crack of the new crack cluster.
In an exemplary embodiment of the present application, after determining the respective fracture cluster, the method may further include: determining a root node number of the crack;
the determining the root node number of the crack may include:
determining a first generated crack in a crack cluster as a root crack of the crack cluster;
when the randomly generated cracks are root cracks in a crack cluster, taking the opposite number of the number (total number) of the cracks in the crack cluster as the root node number of the root cracks;
when the randomly generated cracks are other cracks in one crack cluster except the root crack, the crack number of the root crack in the crack cluster is used as the root node number of the crack (i.e. other cracks not root cracks).
In an exemplary embodiment of the present application, to determine a fracture cluster corresponding to any fracture, the method may further include: and finding the cluster number of any crack through a recursive algorithm.
In an exemplary embodiment of the present application, the finding a cluster number of the any crack by a recursive algorithm includes: for any of the fractures, the following operations are performed:
A. checking the root node number of the current crack; entering step B when the root node number of the current crack is less than 0; when the root node number of the current crack is the crack number of another crack, entering the step C;
B. determining the cracks with the root node number smaller than 0 as root cracks, and taking the crack numbers of the root cracks as cluster numbers of the current cracks; stopping searching the cluster number;
C. and taking the other crack as the current crack, and returning to the step A.
In an exemplary embodiment of the present application, the method may further include: when a new crack is added into any crack cluster, updating the root node number of the root crack in the crack cluster;
when any plurality of crack clusters are unified into one crack cluster, determining root cracks in the unified crack cluster, and updating the root node number and the cluster number of each crack in the unified crack cluster.
In an exemplary embodiment of the present application, the updating the root node number of the root fracture in the fracture cluster may include:
modifying the root node number of the root crack in the crack cluster into the opposite number of the total number of cracks currently contained in the crack cluster;
the determining root cracks in the unified crack cluster, and updating the root node number and the cluster number of each crack in the unified crack cluster may include:
taking root cracks of the crack clusters with the maximum number of cracks corresponding to the plurality of crack clusters before being unified as root cracks of the unified crack clusters;
updating the root node number of the root crack in the unified crack cluster into the opposite number of the total number of all cracks contained in the unified crack cluster; updating the root node numbers of other cracks except the root crack in the unified crack cluster into the crack numbers of the root crack;
keeping the cluster number of the root crack in the unified crack cluster unchanged, and updating the cluster numbers of other cracks into the crack numbers of the root crack.
In the exemplary embodiments of the present application, the above-described scheme will be described in detail below.
In the exemplary embodiment of the present application, after a crack is randomly generated, the crack cluster may be determined according to an intersection relationship between the crack and the generated crack, and a root node number and a cluster number of the crack are determined according to the intersection relationship. Specifically, the intersection relationship between the crack and the generated crack may be determined according to whether the crack is a short crack or a long crack.
In an exemplary embodiment of the present application, when the crack is a short crack, the intersection relationship between the short crack sharing at least one block with the short crack and all long cracks may be checked, that is, the intersection relationship between the short crack recorded in the first array and all long cracks recorded in the long crack array, which correspond to all blocks recorded in the second array, and the current crack is checked; when the crack is a long crack, the intersection relationship between the long crack and all other cracks except the long crack can be checked; and the number of all intersecting fractures is recorded.
In an exemplary embodiment of the present application, determining the root node number and the cluster number of the crack according to the intersection relationship, and updating the root node number and the cluster number of the crack cluster where the intersected generated crack is located may include:
when the crack (i.e. the current crack) intersects with one generated crack, determining the cluster number of the intersected generated crack (i.e. the intersected crack), and setting the cluster number of the crack as the cluster number of the intersected generated crack; setting the root node number of the crack as the crack number of the root crack of the cluster to which the intersected generated crack belongs; and the number value of the root node of the root crack of the crack cluster to which the intersected generated crack belongs is reduced by one;
when the crack (i.e. the current crack) intersects with a plurality of generated cracks, finding cluster numbers corresponding to all the intersected generated cracks, and deleting repeated cluster numbers in the cluster numbers; and for each remaining nonrepeating cluster number, checking whether the cluster number of all cracks generated at present has a situation of being repeated with the cluster number, if the cluster number of all cracks generated at present has a situation of being repeated with the cluster number, setting the root node number and the cluster number corresponding to the crack having the repeated situation as the cluster number of one crack cluster containing the largest number of cracks in the corresponding cluster in the intersected generated cracks (namely the cluster number of one crack cluster containing the smallest root node number value of the root crack in all the remaining nonrepeating clusters), and changing the cluster number of the crack (namely the current crack) into the cluster number of one crack cluster containing the largest number of cracks in the corresponding cluster in the intersected generated cracks. And adding the root node number values of all root cracks of all the crack clusters corresponding to the intersected generated cracks, subtracting one from the added value, recording the number as the root node number of the root crack of the new crack cluster, and setting the root node number of the current crack as the crack number of the root crack. Wherein the root fracture of the new fracture cluster is the root fracture of the fracture cluster containing the largest number of fractures in all the remaining non-repeating clusters. If only one non-repeated cluster number exists, the generated cracks intersected with the current cracks belong to a crack cluster, and the root cracks are the original root cracks of the crack cluster; if the number of all non-repeated clusters is multiple, the generated cracks intersected with the current cracks belong to multiple different crack clusters, the multiple different crack clusters are unified into a new crack cluster, and the root cracks of the new crack cluster are the root cracks of one crack cluster with the largest number of cracks in the multiple different crack clusters.
In an exemplary embodiment of the present application, as shown in fig. 4, a crack 2 is newly added, the crack number is 2, the initial root node number is-1, and the cluster number is 2. The block to which the crack belongs is represented by a wave block. At this time, the cracks 2 are subjected to the collective inspection. First, a short crack sharing at least one block with the crack 2 is found, and the crack 1 shares the blocks 7, 8, 12, 13, 17 and 18 with the crack 2, so that the intersection relationship of the crack 1 and the crack 2 is checked. And intersecting the crack 2 with the crack 1, searching the root node number of the crack 1, wherein the root node number is-1, the crack 1 is shown as the root crack of the cluster 1, the cluster number and the crack number are both 1, changing the root node number of the crack 2 from-1 to the crack number of the crack 1, reducing the root node number of the crack 1 by one, changing the root node number of the crack 1 from-1 to-2, and indicating that the number of the cracks of the cluster changed at this time is 2. The cluster number of crack 2 is changed to the crack number of crack 1, which is 1.
In the exemplary embodiment of the present application, as shown in fig. 5, if a crack 9 intersects three cracks, corresponding cluster numbers of the three cracks are found, where two crack clusters are numbered 1, one crack cluster is numbered 2, and if repeated cluster numbers are removed, only two cluster numbers are found, which are 1 and 2 respectively. All generated cracks are checked, 8 cracks are shown in the figure, and if the cluster numbers of all generated cracks are 1 or 2, the cluster numbers are all changed to 1, that is, in this embodiment, the cluster numbers corresponding to all cracks in the crack cluster 2 are all changed to 1, and the root node numbers are also changed to 1. And changing the number value of the root crack of the crack cluster 1, namely the number value of the root node of the crack 1 into the original value, adding the number value of the root node of the root crack of the crack cluster 2, and subtracting one to obtain-9. The root node number of the crack 9 is changed to 1 (root crack, i.e., the crack number of the crack 1), and the cluster number is changed to 1. There is only one fracture cluster in the fracture network at this time, and there are 9 fractures in the fracture cluster.
In an exemplary embodiment of the present application, the stop condition may include: up to a given number of fractures, or clusters of fractures formed throughout the area where the random fracture network was generated.
In an exemplary embodiment of the present application, the number of cracks may be continuously increased according to the foregoing embodiment until a preset stop condition is satisfied.
In an exemplary embodiment of the present application, as shown in fig. 6, there are three fracture clusters in the fracture network, wherein the largest fracture cluster 3 connects four sides of the area (i.e., the formed fracture cluster penetrates through the area where the random fracture network is generated), and this condition may be set as a stop condition, and then the generation of new fractures is stopped.
FIG. 7 illustrates the generation of a three-dimensional discrete fracture network using the method of the present application, wherein the fracture clusters throughout the region are dark in color and the other local fracture clusters are light in color.
In the exemplary embodiment of the application, 150.000 cracks are generated by using the scheme of the embodiment of the application, and the crack clustering determination is carried out, so that only 47 seconds (two-dimensional cracks) and 30 seconds (three-dimensional cracks) are consumed, the generation time of a discrete crack network is greatly reduced, and the working efficiency is improved.
The embodiment of the present application further provides a device 1 for generating a discrete fracture network, as shown in fig. 8, which may include a processor 11 and a computer-readable storage medium 12, where the computer-readable storage medium 12 stores instructions, and when the instructions are executed by the processor 11, the generation of the discrete fracture network is implemented.
In the exemplary embodiment of the present application, any of the foregoing methods for generating a discrete fracture network is applicable to the apparatus embodiment, and details thereof are not repeated here.
It will be understood by those of ordinary skill in the art that all or some of the steps of the methods, systems, functional modules/units in the devices disclosed above may be implemented as software, firmware, hardware, and suitable combinations thereof. In a hardware implementation, the division between functional modules/units mentioned in the above description does not necessarily correspond to the division of physical components; for example, one physical component may have multiple functions, or one function or step may be performed by several physical components in cooperation. Some or all of the components may be implemented as software executed by a processor, such as a digital signal processor or microprocessor, or as hardware, or as an integrated circuit, such as an application specific integrated circuit. Such software may be distributed on computer readable media, which may include computer storage media (or non-transitory media) and communication media (or transitory media). The term computer storage media includes volatile and nonvolatile, removable and non-removable media implemented in any method or technology for storage of information such as computer readable instructions, data structures, program modules or other data, as is well known to those of ordinary skill in the art. Computer storage media includes, but is not limited to, RAM, ROM, EEPROM, flash memory or other memory technology, CD-ROM, Digital Versatile Disks (DVD) or other optical disk storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other medium which can be used to store the desired information and which can accessed by a computer. In addition, communication media typically embodies computer readable instructions, data structures, program modules or other data in a modulated data signal such as a carrier wave or other transport mechanism and includes any information delivery media as known to those skilled in the art.
Claims (10)
1. A method of generating a discrete fracture network, comprising:
carrying out block division on the area generating the random fracture network to form a plurality of blocks;
circularly executing the following steps until a preset stop condition is met: and generating random cracks, recording the cracks according to the blocks, and determining corresponding crack clusters.
2. The method of generating a discrete fracture network of claim 1, wherein the generating random fractures comprises: generating random cracks according to preset statistical distribution;
the statistical distribution includes: the length of the crack conforms to power law distribution, the direction of the crack conforms to Fisher distribution, and the position of the crack conforms to Poisson distribution.
3. The method of generating a discrete fracture network of claim 1,
after forming a plurality of blocks, prior to recording the crack from the blocks, the method further comprises: marking each block, and allocating a first array for recording crack numbers in the block to each block;
each fracture possesses a fracture number which increases from 1 in the order of fracture initiation; the recording the crack according to the block includes:
when the length of the generated crack is smaller than or equal to the size of the area, setting a temporary integer type second array to record the serial number of the block to which the crack belongs; and recording the crack number corresponding to the crack in a first array corresponding to each block to which the crack belongs; determining all blocks in a rectangular or square area related to the track of the crack as the blocks to which the crack belongs;
and when the length of the generated crack is larger than the size of the area, recording the crack number corresponding to the crack into a preset long crack record array.
4. The method of generating a discrete fracture network of any of claims 1-3, wherein the determining the corresponding fracture clusters comprises:
when the generated crack is a first crack, forming a first crack cluster by the first crack, and taking the first crack as a root crack of the first crack cluster;
detecting whether the generated fracture intersects at least one generated fracture when the generated fracture is not the first fracture;
when the fracture intersects with one generated fracture, adding the fracture into a fracture cluster to which the intersected generated fracture belongs; when the crack intersects with a plurality of generated cracks, detecting whether the intersected plurality of generated cracks belong to the same crack cluster; adding the generated cracks into the same crack cluster to which the generated cracks belong when the generated cracks belong to the same crack cluster; when the intersected multiple generated cracks do not belong to the same crack cluster, unifying all the crack clusters to which the intersected multiple generated cracks belong into one crack cluster, and adding the cracks into the unified crack cluster;
and when the crack does not intersect with any generated crack, forming a new crack cluster by the crack, and taking the crack as a root crack of the new crack cluster.
5. The method of generating a discrete fracture network of claim 4, wherein each fracture further has a root node number;
after determining the respective fracture cluster, the method further comprises: determining a root node number of the crack;
the determining a root node number for the fracture includes:
determining a first generated crack in a crack cluster as a root crack of the crack cluster;
for a root crack in a crack cluster, taking the opposite number of the crack in the crack cluster as the root node number of the root crack;
and for other fractures in one fracture cluster except the root fracture, taking the fracture number of the root fracture in the fracture cluster as the root node numbers of the other fractures.
6. The method of generating a discrete fracture network of claim 5, wherein each fracture further has a cluster number; the cluster number is the number of the crack cluster to which the crack belongs, and is the crack number of the root crack in the crack cluster to which the crack belongs;
to determine a corresponding fracture cluster for any of the fractures, the method further comprises: finding the cluster number of any crack through a recursive algorithm;
the finding the cluster number of any crack through a recursive algorithm comprises: for any of the fractures, the following operations are performed:
61. checking the root node number of the current crack; when the root node number of the current crack is less than 0, entering step 62; entering step 63 when the root node number of the current crack is the crack number of another crack;
62. determining the cracks with the root node number smaller than 0 as root cracks, and taking the crack numbers of the root cracks as cluster numbers of the current cracks; stopping searching the cluster number;
63. the other fracture is taken as the current fracture and returns to step 61.
7. The method of generating a discrete fracture network of claim 6, further comprising: when a new crack is added into any crack cluster, updating the root node number of the root crack in the crack cluster;
when any plurality of crack clusters are unified into one crack cluster, determining root cracks in the unified crack cluster, and updating the root node number and the cluster number of each crack in the unified crack cluster.
8. The method for generating a discrete fracture network according to claim 7, wherein the updating the root node number of the root fracture in the fracture cluster comprises:
modifying the root node number of the root crack in the crack cluster into the opposite number of the total number of cracks currently contained in the crack cluster;
the determining root cracks in the unified crack clusters, and updating the root node number and the cluster number of each crack in the unified crack clusters includes:
taking root cracks of the crack clusters with the maximum number of cracks corresponding to the plurality of crack clusters before being unified as root cracks of the unified crack clusters;
updating the root node number of the root crack in the unified crack cluster into the opposite number of the total number of all cracks contained in the unified crack cluster; updating the root node numbers of other cracks except the root crack in the unified crack cluster into the crack numbers of the root crack;
keeping the cluster number of the root crack in the unified crack cluster unchanged, and updating the cluster numbers of other cracks into the crack numbers of the root crack.
9. A method of generating a discrete fracture network according to any of claims 1-3, wherein the stopping conditions comprise: up to a given number of fractures, or clusters of fractures formed throughout the area where the random fracture network was generated.
10. An apparatus for generating a discrete fracture network, comprising a processor and a computer-readable storage medium having instructions stored therein, which when executed by the processor, enable generation of the discrete fracture network of any of claims 1-9.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111214856.5A CN113963112B (en) | 2021-10-19 | 2021-10-19 | Discrete fracture network generation method and device |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111214856.5A CN113963112B (en) | 2021-10-19 | 2021-10-19 | Discrete fracture network generation method and device |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN113963112A true CN113963112A (en) | 2022-01-21 |
| CN113963112B CN113963112B (en) | 2024-09-03 |
Family
ID=79465132
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202111214856.5A Active CN113963112B (en) | 2021-10-19 | 2021-10-19 | Discrete fracture network generation method and device |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN113963112B (en) |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| GB201009387D0 (en) * | 2009-06-05 | 2010-07-21 | Logined Bv | Fracture network characterization method |
| CN105279790A (en) * | 2014-06-13 | 2016-01-27 | 中国石油化工股份有限公司 | Fracture network 3D digital core modeling method |
| US20170074770A1 (en) * | 2015-09-15 | 2017-03-16 | IFP Energies Nouvelles | Method for characterizing the fracture network of a fractured reservoir and method for exploiting it |
| CN109100790A (en) * | 2018-09-25 | 2018-12-28 | 中国石油天然气股份有限公司 | Artificial crack simulation method and device |
| CN111077053A (en) * | 2019-12-19 | 2020-04-28 | 昆明理工大学 | Fracture type porous medium seepage analysis visualization method |
-
2021
- 2021-10-19 CN CN202111214856.5A patent/CN113963112B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| GB201009387D0 (en) * | 2009-06-05 | 2010-07-21 | Logined Bv | Fracture network characterization method |
| CN105279790A (en) * | 2014-06-13 | 2016-01-27 | 中国石油化工股份有限公司 | Fracture network 3D digital core modeling method |
| US20170074770A1 (en) * | 2015-09-15 | 2017-03-16 | IFP Energies Nouvelles | Method for characterizing the fracture network of a fractured reservoir and method for exploiting it |
| CN109100790A (en) * | 2018-09-25 | 2018-12-28 | 中国石油天然气股份有限公司 | Artificial crack simulation method and device |
| CN111077053A (en) * | 2019-12-19 | 2020-04-28 | 昆明理工大学 | Fracture type porous medium seepage analysis visualization method |
Non-Patent Citations (2)
| Title |
|---|
| 冯伟;冯煜;: "基于离散裂缝网络的储层裂缝建模技术", 内蒙古石油化工, no. 02, 30 January 2015 (2015-01-30), pages 1 - 2 * |
| 郑松青;姚志良;: "离散裂缝网络随机建模方法", 石油天然气学报, no. 04, 15 August 2009 (2009-08-15) * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN113963112B (en) | 2024-09-03 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN105134191B (en) | Method for evaluating reserves of tight oil well | |
| CN102609982B (en) | Topology discovery method of space geological data based on unstructured mode | |
| CN108898670B (en) | Three-dimensional geological modeling method based on entity and profile | |
| CN110442834B (en) | Method, device, computer equipment and readable storage medium for constructing logging curve | |
| CN110991885A (en) | Method for evaluating easiness of developing of regional bedding rock slope | |
| CN115937467B (en) | Method and system for dividing random three-dimensional fracture in upscale model grid | |
| CN108952676B (en) | Shale gas reservoir heterogeneity evaluation method and device | |
| CN105631078A (en) | Numerical value simulation method for adaptive medium of natural fractured reservoir | |
| US10627542B2 (en) | Hybrid approach to assisted history matching in large reservoirs | |
| CN111144117A (en) | Knowledge graph Chinese address disambiguation method | |
| US11112514B2 (en) | Systems and methods for computed resource hydrocarbon reservoir simulation and development | |
| CN105447292A (en) | Oil gas wildcat screening method | |
| CN110197013B (en) | Riverbed bedrock surface modeling method based on Morphing | |
| CA2975437C (en) | Selecting potential well locations in a reservoir grid model | |
| CN113963112B (en) | Discrete fracture network generation method and device | |
| CN105068141A (en) | Method and device for determining karst reservoir distribution of fracture system | |
| CN107013207B (en) | Method for acquiring underground well position information of complex fault block oil reservoir sand body | |
| CN113268846B (en) | Method, device, terminal and storage medium for determining water control strategy with water-gas reservoir | |
| CN112561220B (en) | Method, device, equipment and readable storage medium for identifying abnormal well in production well | |
| CN109254330B (en) | Identification method and device for fractured segments of igneous rock reservoir | |
| CN110442950B (en) | Multi-factor fusion residual oil distribution prediction graph compiling method | |
| CN118273695A (en) | Shale oil horizontal well fracturing layering method and device | |
| Shi et al. | A Simulation Model With Unstructured Grid Provides Better Predictions of Water Movement in Heavily Fractured Reservoir–A Case Study at Onshore Abu Dhabi | |
| US20230237225A1 (en) | Machine learning based reservoir modeling | |
| CN116861716A (en) | Numerical simulation method and system for fracture-cavity type carbonate rock triple medium |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |