A method and apparatus for characterizing the fracture surface of a fracture system
By constructing a stratigraphic framework and a maximum likelihood seismic data volume, seismic attributes are extracted and cross-sections are cut, solving the problem of imprecise characterization of complex fault systems and achieving efficient and accurate cross-section characterization.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- Filing Date
- 2022-03-14
- Publication Date
- 2026-04-03
AI Technical Summary
Existing technologies are insufficient for efficiently and accurately characterizing the cross-sections of complex fault systems, especially since seismic interpreters struggle to precisely interpret each fault, resulting in inaccurate characterization.
By constructing a stratigraphic framework, a maximum likelihood seismic data volume is established based on the maximum likelihood method. Seismic attributes are extracted and converted into fracture sections. Finally, cross sections are cut under the stratigraphic framework, reducing manual intervention and improving the efficiency and accuracy of characterization.
It enables accurate characterization of cross-sections of complex fracture systems, reduces human influence, improves work efficiency, and ensures the accuracy of the cross-section system.
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Figure CN116794720B_ABST
Abstract
Description
Technical Field
[0001] This invention belongs to the field of oil and gas exploration technology, and more specifically, relates to a method and apparatus for cross-section characterization of a fracture system. Background Technology
[0002] Given the complex tectonic movements throughout geological history, resulting in intricate fault systems of varying scales, phases, levels, and directions, efficiently and accurately characterizing and refining fault surfaces while minimizing human intervention remains a challenging problem for the industry. Currently, fault surface characterization primarily relies on seismic interpreters manually interpreting faults, followed by geologists using relevant software to characterize these interpretations. However, this method is unsuitable for complex fault systems. For such systems, seismic interpreters struggle to precisely interpret each fault, hindering the accurate characterization of fault surfaces.
[0003] The present invention addresses the above-mentioned problems by providing a method and apparatus for characterizing the fracture surface of a fracture system. Summary of the Invention
[0004] In view of this, the purpose of the present invention is to provide a method and apparatus for characterizing the cross-section of a fracture system, which can minimize human intervention and accurately construct complex cross-section systems.
[0005] To achieve the above objectives, in one aspect, the present invention provides a method for characterizing the fracture surface of a fracture system, comprising:
[0006] Based on the stratigraphic data, a stratigraphic framework was constructed.
[0007] Based on seismic data, the maximum likelihood seismic data volume characterizing faults is established using the maximum likelihood method.
[0008] Based on the established maximum likelihood seismic data volume, seismic attributes are extracted from the maximum likelihood seismic data volume, and the seismic attributes are converted into crack slices;
[0009] Convert the cracked section into a cross-section;
[0010] Based on the geological grid, the cross section is cut to obtain the target cross section.
[0011] Preferably, the method for acquiring the layer data includes:
[0012] Acquire 3D seismic data volume;
[0013] Seismic profile tracing is performed on the layers of the three-dimensional seismic data volume;
[0014] Based on the reflection characteristics of the aforementioned strata on the seismic profile, the strata at the top and bottom surfaces are traced to obtain the original strata data;
[0015] The acquired raw layer data is processed to obtain the layer data of the top and bottom surfaces.
[0016] Preferably, the layer of the three-dimensional seismic data volume is obtained by lateral tracking of strong in-phase axes on the three-dimensional seismic data volume.
[0017] Preferably, the step of establishing a maximum likelihood seismic data volume characterizing a fault based on seismic data using the maximum likelihood method specifically includes: calculating the maximum likelihood attributes by scanning the fault dip and fault dip angle of a conventional seismic data volume to obtain the maximum likelihood seismic data volume.
[0018] Preferably, the maximum likelihood attribute is extracted and extraction parameters are set to obtain the cracked section.
[0019] Preferably, converting the crack segment into a cross-section includes: dividing the crack segment into two parts according to its size: micro-crack segments and medium-sized crack segments; deleting the micro-crack segments; merging some of the medium-sized crack segments; and converting the crack segment into a cross-section using software functions.
[0020] On the other hand, the present invention also provides a fracture surface characterization apparatus for a fracture system, comprising:
[0021] The stratigraphic framework module constructs a stratigraphic framework based on bedding plane data.
[0022] The seismic data volume module uses the maximum likelihood method to establish a maximum likelihood seismic data volume characterizing faults.
[0023] The crack slice module extracts seismic attributes from the established maximum likelihood seismic data volume and converts the seismic attributes into crack slices.
[0024] The cross-section module converts the crack plate into a cross-section;
[0025] The target section module cuts the section based on the stratigraphic grid to obtain the target section.
[0026] Preferably, the method for acquiring the layer data includes:
[0027] Acquire 3D seismic data volume;
[0028] Seismic profile tracing is performed on the layers of the three-dimensional seismic data volume;
[0029] Based on the reflection characteristics of the aforementioned strata on the seismic profile, the strata at the top and bottom surfaces are traced to obtain the original strata data;
[0030] The acquired raw layer data is processed to obtain the layer data of the top and bottom surfaces.
[0031] Preferably, the layer of the three-dimensional seismic data volume is obtained by lateral tracking of strong in-phase axes on the three-dimensional seismic data volume.
[0032] Preferably, the cross-section module is used to divide the crack segments into two parts according to their size: micro-crack segments and medium-sized crack segments. The micro-crack segments are deleted, some of the medium-sized crack segments are merged, and the cross-section is converted into a cross-section through software functions.
[0033] The beneficial effects of this invention are as follows:
[0034] This invention first constructs a stratigraphic framework using layer data; secondly, it establishes a maximum likelihood seismic data volume based on seismic data; based on the established maximum likelihood seismic data volume, it extracts seismic attributes from the maximum likelihood seismic data volume and converts these attributes into fracture slices; it then converts these fracture slices into cross-sections; finally, based on the stratigraphic framework, it cuts the cross-sections to obtain the target cross-section. This method enables more accurate characterization of cross-sections in complex fault systems, reduces human intervention, significantly improves work efficiency, minimizes the influence of subjective human factors, and ensures the accuracy of the cross-section system.
[0035] Other features and advantages of the present invention will be described in detail in the following detailed description section. Attached Figure Description
[0036] The above and other objects, features and advantages of the present invention will become more apparent from the more detailed description of exemplary embodiments of the invention in conjunction with the accompanying drawings, wherein the same reference numerals generally represent the same components in the exemplary embodiments of the invention.
[0037] Figure 1 A schematic flowchart of a fracture system section characterization method according to Embodiment 1 of the present invention is shown.
[0038] Figure 2 This is a maximum likelihood seismic data volume illustration of a fracture system cross-section characterization method according to Embodiment 1 of the present invention;
[0039] Figure 3 This is a schematic diagram of a discrete crack network model of a fracture system cross-section characterization method according to Embodiment 1 of the present invention;
[0040] Figure 4 This is a schematic diagram of a method for depicting the cross-section of a fracture system according to an embodiment of the present invention, which involves processing crack sections and converting them into a fault model.
[0041] Figure 5 This is a schematic diagram of the cross-section of a fracture system, as described in Embodiment 1 of the present invention, which is established by constructing a framework model of the converted fault. Detailed Implementation
[0042] To address the technical problem that seismic interpreters struggle to precisely interpret each fault in complex fracture systems, thus hindering the accurate characterization of fracture surfaces, this invention provides a method for characterizing fracture surfaces in fracture systems, comprising:
[0043] Based on the stratigraphic data, a stratigraphic framework was constructed.
[0044] Based on seismic data, the maximum likelihood seismic data volume characterizing faults is established using the maximum likelihood method.
[0045] Based on the established maximum likelihood seismic data volume, seismic attributes are extracted from the maximum likelihood seismic data volume, and the seismic attributes are converted into crack slices;
[0046] Convert the cracked section into a cross-section;
[0047] Based on the geological grid, the cross section is cut to obtain the target cross section.
[0048] This invention first constructs a stratigraphic framework using layer data; secondly, it establishes a maximum likelihood seismic data volume based on seismic data; based on the established maximum likelihood seismic data volume, it extracts seismic attributes from the maximum likelihood seismic data volume and converts these attributes into fracture slices; it then converts these fracture slices into cross-sections; finally, based on the stratigraphic framework, it cuts the cross-sections to obtain the target cross-section. This method enables more accurate characterization of cross-sections in complex fault systems, reduces human intervention, significantly improves work efficiency, minimizes the influence of subjective human factors, and ensures the accuracy of the cross-section system.
[0049] Specifically, the method for acquiring the layer data includes: acquiring a three-dimensional seismic data volume; performing seismic profile tracking on the layers of the three-dimensional seismic data volume; tracking the layers of the top and bottom surfaces based on the reflection characteristics of the layers on the seismic profile to acquire raw layer data; and processing the acquired raw layer data to acquire the layer data of the top and bottom surfaces.
[0050] Specifically, the layer of the three-dimensional seismic data volume is obtained by laterally tracing the strong in-phase axes on the three-dimensional seismic data volume.
[0051] It should be noted that, for the processed 3D seismic data volume, the layers are interpreted one by one based on seismic reflection characteristics through human-computer interaction. First, the layers are traced on the seismic profile. Layers exhibit strong reflection characteristics, high amplitude, and strong continuity on the seismic profile. The layers on the top and bottom surfaces of the section to be constructed are traced one by one to obtain the raw layer data. The acquired layer data is then imported using the "make surface" method in the software to finally obtain the top and bottom surface layer data.
[0052] Specifically, the step of establishing a maximum likelihood seismic data volume characterizing a fault based on seismic data using the maximum likelihood method includes: calculating the maximum likelihood attributes by scanning the fault dip and fault dip angle of a conventional seismic data volume, and obtaining the maximum likelihood seismic data volume.
[0053] It should be noted that the maximum likelihood seismic data volume is obtained by calculating the maximum likelihood attributes through scanning the fault dip and angle of the conventional seismic data volume. Here, the maximum likelihood seismic data volume uses a frequency of 15 Hz. The maximum likelihood data volume is then imported using software.
[0054] Specifically, the maximum likelihood attribute is extracted, and extraction parameters are set to obtain the crack slice.
[0055] It should be noted that the attributes of the maximum likelihood seismic data volume are extracted using the automtic fault extraction module in the software. The extraction parameters need to be set, with the extraction sampling distance set to 30 and the extraction sampling threshold set to all. The extracted data yields a discrete fracture network model.
[0056] Specifically, the fracture segments are divided into micro-fracture segments and small-to-medium-sized fracture segments according to their size. The micro-fracture segments are deleted, and some small-to-medium-sized fracture segments are merged. These segments are then converted into fault planes using software. Based on the stratigraphic framework, the fault planes are cut to obtain the target cross-section.
[0057] It should be noted that the discrete crack network model extracted in the previous steps is processed by deleting small-level cracks and merging small and medium-level cracks that have the same direction and are connected, according to actual needs. Finally, the processed cracks are converted into fault planes using the "convert to fault in fault model" function, and the converted fault planes are converted into "sticks" format cross-sections using the "convert to fault sticks" function.
[0058] A structural framework is established using the framework modeling method. The converted sticks format cross-sections are loaded into the fault framework, and appropriate boundaries are set. Then, the layer data of the top and bottom surfaces obtained in step S1 are imported through the model construction function to finally build the cross-section model.
[0059] The present invention also provides a fracture surface characterization device for a fracture system, comprising:
[0060] The stratigraphic framework module constructs a stratigraphic framework based on bedding plane data.
[0061] The seismic data volume module uses the maximum likelihood method to establish a maximum likelihood seismic data volume characterizing faults.
[0062] The crack slice module extracts seismic attributes from the established maximum likelihood seismic data volume and converts the seismic attributes into crack slices.
[0063] The cross-section module converts the crack plate into a cross-section;
[0064] The target section module cuts the section based on the stratigraphic grid to obtain the target section.
[0065] Specifically, the method for acquiring the layer data includes:
[0066] Acquire 3D seismic data volume;
[0067] Seismic profile tracing is performed on the layers of the three-dimensional seismic data volume;
[0068] Based on the reflection characteristics of the aforementioned strata on the seismic profile, the strata at the top and bottom surfaces are traced to obtain the original strata data;
[0069] The acquired raw layer data is processed to obtain the layer data of the top and bottom surfaces.
[0070] Specifically, the layer of the three-dimensional seismic data volume is obtained by laterally tracing the strong in-phase axes on the three-dimensional seismic data volume.
[0071] Specifically, the cross-section module is used to divide the crack segments into two parts, micro crack segments and medium-sized crack segments, according to their size. The micro crack segments are deleted, some medium-sized crack segments are merged, and the cross-section is converted into a cross-section through software functions.
[0072] This invention first constructs a stratigraphic framework using layer data; secondly, it establishes a maximum likelihood seismic data volume based on seismic data; based on the established maximum likelihood seismic data volume, it extracts seismic attributes from the maximum likelihood seismic data volume and converts these attributes into fracture slices; it then converts these fracture slices into cross-sections; finally, based on the stratigraphic framework, it cuts the cross-sections to obtain the target cross-section. This method enables more accurate characterization of cross-sections in complex fault systems, reduces human intervention, significantly improves work efficiency, minimizes the influence of subjective human factors, and ensures the accuracy of the cross-section system.
[0073] To illustrate this technical solution in detail, the present invention will be described in more detail through the following exemplary embodiments.
[0074] Example 1
[0075] refer to Figure 1 This invention provides a method for characterizing the fracture surface of a fracture system, the specific steps of which include:
[0076] S1: Construct a stratigraphic framework based on layer data;
[0077] S2: Based on seismic data, the maximum likelihood seismic data volume characterizing the fault is established using the maximum likelihood method;
[0078] S3: Based on the established maximum likelihood seismic data volume, extract the seismic attributes from the maximum likelihood seismic data volume and convert the seismic attributes into crack slices;
[0079] S4: Convert the cracked section into a cross-section;
[0080] S5: Based on the geological grid, the cross section is cut to obtain the target cross section.
[0081] The following is a detailed explanation of each of the above steps.
[0082] S1: Construct a stratigraphic framework based on the layer data.
[0083] Specifically, the method for acquiring the layer data includes: acquiring a three-dimensional seismic data volume; performing seismic profile tracking on the layers of the three-dimensional seismic data volume; tracking the layers of the top and bottom surfaces based on the reflection characteristics of the layers on the seismic profile to acquire raw layer data; and processing the acquired raw layer data to acquire the layer data of the top and bottom surfaces.
[0084] Furthermore, the layer position of the three-dimensional seismic data volume is obtained by laterally tracking the strong in-phase axes on the three-dimensional seismic data volume.
[0085] Specifically, for the processed 3D seismic data volume, the layers are interpreted one by one based on seismic reflection characteristics through human-computer interaction. First, the layers are traced on the seismic profile. Layers exhibit strong reflection characteristics, high amplitude, and strong continuity on the seismic profile. The layers on the top and bottom surfaces of the section to be constructed are traced one by one to obtain the raw layer data. The acquired layer data is then imported using the "make surface" method in the software to finally obtain the bedding plane data for the top and bottom surfaces.
[0086] S2: Based on seismic data, the maximum likelihood seismic data volume characterizing the fault is established using the maximum likelihood method.
[0087] Furthermore, the maximum likelihood seismic data volume is obtained by scanning the fault dip and fault dip angle of the conventional seismic data volume to calculate the maximum likelihood attribute.
[0088] Specifically, the maximum likelihood attributes are calculated by scanning the fault dip and angle of conventional seismic data volumes to obtain the maximum likelihood seismic data volume. Here, the maximum likelihood seismic data volume uses a frequency of 45 Hz. The maximum likelihood data volume is then imported using software, such as... Figure 2 As shown.
[0089] S3: Based on the established maximum likelihood seismic data volume, extract the seismic attributes from the maximum likelihood seismic data volume and convert the seismic attributes into crack slices.
[0090] Furthermore, the maximum likelihood attribute is extracted, and extraction parameters are set to obtain the crack fragments.
[0091] Specifically, the attributes of the maximum likelihood seismic data volume are extracted using the automtic fault extraction module in the software. Extraction parameters need to be set, with the extraction sampling distance set to 30 and the extraction sampling threshold set to all. The extracted result is a discrete fracture network model, such as... Figure 3 As shown.
[0092] S4: Convert the cracked section into a cross-section.
[0093] Furthermore, the crack segments are divided into two parts according to their size: micro-crack segments and medium-sized crack segments. The micro-crack segments are deleted, and some medium-sized crack segments are merged. The crack segments are then converted into fault planes using software functions.
[0094] Specifically, depending on different needs, small cross-sections with the same orientation can be merged to form cross-sections of different scales. More specifically, the discrete crack network model extracted in step S3 is processed, and according to actual needs, small-level cracks are deleted, while small-to-medium-level cracks with the same orientation and connected are merged. Finally, the processed cracks are converted into fault planes using the "convert to fault in fault model" function, and the converted fault planes are then converted into sticks format cross-sections using the "convert to fault sticks" function, such as... Figure 4 As shown.
[0095] S5: Based on the geological grid, the cross section is cut to obtain the target cross section.
[0096] Specifically, cross-sections transformed from seismic data volumes are cut under the constraints of a stratigraphic framework using a VM (Virtual Machine Model) construction method. This ultimately creates a cross-section model. More specifically, a structural framework is built using a framework modeling method. The strips-formatted cross-sections converted in step S4 are loaded into the fault framework, appropriate boundaries are set, and then the top and bottom bedding plane data obtained in step S1 are imported using the model construction function to finally create the cross-section model, as shown below. Figure 5 As shown.
[0097] This invention first constructs a stratigraphic framework using layer data; secondly, it establishes a maximum likelihood seismic data volume based on seismic data; based on the established maximum likelihood seismic data volume, it extracts seismic attributes from the maximum likelihood seismic data volume and converts these attributes into fracture slices; it then converts these fracture slices into cross-sections; finally, based on the stratigraphic framework, it cuts the cross-sections to obtain the target cross-section. This method enables more accurate characterization of cross-sections in complex fault systems, reduces human intervention, significantly improves work efficiency, minimizes the influence of subjective human factors, and ensures the accuracy of the cross-section system.
[0098] Furthermore, this invention changes the previous situation where cross-section characterization required manual assistance from seismic interpreters, minimizing human intervention and ensuring the objectivity of complex cross-section characterization. Finally, this method accurately characterizes small- to medium-scale fracture systems, providing a highly reliable basis for oilfield production and development, well location deployment, and other work.
[0099] Example 2
[0100] This invention provides a fracture surface characterization device for a fracture system, comprising:
[0101] The stratigraphic framework module constructs a stratigraphic framework based on bedding plane data.
[0102] The seismic data volume module, based on seismic data, uses the maximum likelihood method to establish a maximum likelihood seismic data volume characterizing faults;
[0103] The crack slice module extracts seismic attributes from the established maximum likelihood seismic data volume and converts the seismic attributes into crack slices.
[0104] The cross-section module converts the crack plate into a cross-section;
[0105] The target section module cuts the section based on the stratigraphic grid to obtain the target section.
[0106] Specifically, the method for acquiring the layer data includes:
[0107] Acquire 3D seismic data volume;
[0108] Seismic profile tracing is performed on the layers of the three-dimensional seismic data volume;
[0109] Based on the reflection characteristics of the aforementioned strata on the seismic profile, the strata at the top and bottom surfaces are traced to obtain the original strata data;
[0110] The acquired raw layer data is processed to obtain the layer data of the top and bottom surfaces.
[0111] Specifically, the layer of the three-dimensional seismic data volume is obtained by laterally tracing the strong in-phase axes on the three-dimensional seismic data volume.
[0112] Specifically, the cross-section module is used to divide the crack segments into two parts, micro crack segments and medium-sized crack segments, according to their size. The micro crack segments are deleted, some medium-sized crack segments are merged, and the cross-section is converted into a cross-section through software functions.
[0113] The various embodiments of the present invention have been described above. These descriptions are exemplary and not exhaustive, nor are they limited to the disclosed embodiments. Many modifications and variations will be apparent to those skilled in the art without departing from the scope and spirit of the described embodiments.
Claims
1. A method for characterizing the fracture surface of a fracture system, characterized in that, include: Based on the stratigraphic data, a stratigraphic framework was constructed. Based on seismic data, the maximum likelihood seismic data volume characterizing faults is established using the maximum likelihood method. Based on the established maximum likelihood seismic data volume, seismic attributes are extracted from the maximum likelihood seismic data volume, and the seismic attributes are converted into crack slices; Convert the cracked section into a cross-section; Based on the geological grid, the cross section is cut to obtain the target cross section.
2. The method for characterizing the fracture surface of a fracture system according to claim 1, characterized in that, The methods for obtaining the layer data include: Acquire 3D seismic data volume; Seismic profile tracing is performed on the layers of the three-dimensional seismic data volume; Based on the reflection characteristics of the aforementioned strata on the seismic profile, the strata at the top and bottom surfaces are traced to obtain the original strata data; The acquired raw layer data is processed to obtain the layer data of the top and bottom surfaces.
3. The method for characterizing the fracture surface of a fracture system according to claim 2, characterized in that, The layer position of the three-dimensional seismic data volume is obtained by lateral tracking of the strong in-phase axes on the three-dimensional seismic data volume.
4. The method for characterizing the fracture surface of a fracture system according to claim 1, characterized in that, The establishment of the maximum likelihood seismic data volume characterizing faults based on seismic data and using the maximum likelihood method specifically includes: The maximum likelihood seismic data volume is obtained by scanning the fault dip and fault dip angle of a conventional seismic data volume to calculate the maximum likelihood attribute.
5. The method for characterizing the fracture surface of a fracture system according to claim 4, characterized in that, The maximum likelihood attribute is extracted, and the extraction parameters are set to obtain the crack slice.
6. The method for characterizing the fracture surface of a fracture system according to claim 5, characterized in that, The step of converting the crack segment into a cross-section includes: dividing the crack segment into two parts according to its size: micro-crack segments and medium-sized crack segments; deleting the micro-crack segments; merging some of the medium-sized crack segments; and converting the crack segment into a cross-section using software functions.
7. A fracture surface characterization device for a fracture system, characterized in that, include: The stratigraphic framework module constructs a stratigraphic framework based on bedding plane data. The seismic data volume module uses the maximum likelihood method to establish a maximum likelihood seismic data volume characterizing faults. The crack slice module extracts seismic attributes from the established maximum likelihood seismic data volume and converts the seismic attributes into crack slices. The cross-section module converts the crack plate into a cross-section; The target section module cuts the section based on the stratigraphic grid to obtain the target section.
8. The apparatus according to claim 7, characterized in that, The methods for obtaining the layer data include: Acquire 3D seismic data volume; Seismic profile tracing is performed on the layers of the three-dimensional seismic data volume; Based on the reflection characteristics of the aforementioned strata on the seismic profile, the strata at the top and bottom surfaces are traced to obtain the original strata data; The acquired raw layer data is processed to obtain the layer data of the top and bottom surfaces.
9. The apparatus according to claim 8, characterized in that, The layer position of the three-dimensional seismic data volume is obtained by lateral tracking of the strong in-phase axes on the three-dimensional seismic data volume.
10. The apparatus according to claim 7, characterized in that, The cross-section module is used to divide the crack segments into two parts according to their size: micro crack segments and medium-sized crack segments. The micro crack segments are deleted, some medium-sized crack segments are merged, and the cross-section is converted into a cross-section through software functions.
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