Method and apparatus for determining morphological complexity of fracture network of shale gas well, and device, system, medium and product

Abstract

Provided in the present application are a method and apparatus for determining the morphological complexity of a fracture network of a shale gas well, and a device, a system, a medium and a product. The method comprises: acquiring first pump stop pressure curve characteristic data of a target shale gas well after network fracturing, and a plurality of pieces of second pump stop pressure curve characteristic data corresponding to a plurality of preset shale gas well fracture network entity models; determining, from among the plurality of pieces of second pump stop pressure curve characteristic data, target pump stop pressure curve characteristic data matching the first pump stop pressure curve characteristic data; and acquiring the morphological structure of a target fracture network in a fracture network entity model corresponding to the target pump stop pressure curve characteristic data, and on the basis of the morphological structure of the target fracture network, determining the morphological complexity of the fracture network of the target shale gas well. By means of the method of the present application, it is unnecessary to detect the morphological structure of a fracture network of a shale gas well on site, thereby avoiding a result error caused by on-site environmental factors; and the method has the advantages of a high accuracy, simple operations and ensured timeliness.

Description

Methods, devices, equipment, systems, media, and products for determining the morphological complexity of fracture networks in shale gas wells.

[0001] This application claims priority to Chinese Patent Application No. 2024104945530, filed on April 23, 2024, entitled “Method, Apparatus, Equipment, System, Medium and Product for Determining the Morphology Complexity of Fracture Networks in Shale Gas Wells”, the entire contents of which are incorporated herein by reference. Technical Field

[0002] This application relates to oil and gas extraction technology, and in particular to a method, apparatus, equipment, system, medium and product for determining the morphological complexity of fracture networks in shale gas wells. Background Technology

[0003] Hydraulic fracturing is a core technology for enhancing shale gas production. The complex fracture network formed by artificial hydraulic fractures and natural formation fractures is the main seepage channel for shale gas. Therefore, understanding the morphology and structure of the fracture network is crucial, and characterizing the fractures in the fracture network is an important means of evaluating the fracturing effect.

[0004] Existing technologies such as microseismic detection, inclinometer monitoring, and distributed optical fiber monitoring are used to detect and determine the fracture network morphology after hydraulic fracturing, which can obtain the geometric size and distribution of cracks in the fracture network.

[0005] However, these methods need to be tested in the actual field. Due to the complexity of the field conditions, such as rugged terrain and construction factors, the operation is difficult. Moreover, when detecting cracks, they are easily affected by various noises, which affects the final results. They are not only inaccurate but also have poor timeliness. Summary of the Invention

[0006] This application provides a method, apparatus, equipment, system, medium, and product for determining the morphological complexity of fracture networks in shale gas wells, in order to solve the problems of existing methods being difficult to implement, greatly affected by the field environment, having low accuracy, and poor timeliness.

[0007] Firstly, this application provides a method for determining the morphological complexity of fracture networks in shale gas wells, including:

[0008] In response to receiving a shale gas well fracture network determination request, the system acquires the first pump stop pressure curve feature data of the target shale gas well after fracture network fracturing and the second pump stop pressure curve feature data corresponding to multiple preset shale gas well fracture network entity models.

[0009] Determine the target pump stop pressure curve feature data that matches the first pump stop pressure curve feature data from a plurality of second pump stop pressure curve feature data;

[0010] Obtain the target fracture network morphology and structure in the entity model of the fracture network corresponding to the characteristic data of the target pump stop pressure curve, and determine the fracture network morphology complexity of the target shale gas well based on the target pressure fracture network morphology and structure.

[0011] In one possible design, determining the target pump stop pressure curve feature data that matches the first pump stop pressure curve feature data from a plurality of second pump stop pressure curve feature data includes:

[0012] Calculate the similarity of the curve shape between the first pump stop pressure curve feature data and each of the second pump stop pressure curve feature data;

[0013] The feature data of the second pump stop pressure curve corresponding to the maximum curve shape similarity is determined as the feature data of the target pump stop pressure curve.

[0014] In one possible design, determining the complexity of the hydraulic fracture network morphology of the target shale gas well based on the target pressure fracture network morphology includes:

[0015] Obtain the volume of branch cracks and main cracks in the target pressure fracture network structure;

[0016] Calculate the ratio of the branch fracture volume to the total fracture volume, where the total fracture volume is the sum of the branch fracture volume and the main fracture volume;

[0017] Based on the ratio results, the complexity of the fracture network morphology of the target shale gas well is determined.

[0018] In one possible design, before acquiring the characteristic data of the first shutdown pressure curve of the target shale gas well after fracture network fracturing and the characteristic data of the second shutdown pressure curve corresponding to multiple preset shale gas well fracture network entity models, the method further includes:

[0019] Determine the first dimensional parameters of the fracture network morphology structure of the plurality of preset shale gas wells;

[0020] Multiple solid models of the pressure fracture network are constructed based on multiple first size parameters;

[0021] Injection operations were performed on multiple hydraulic fracture network solid models to obtain the characteristic data of the second pump stop pressure curve corresponding to each hydraulic fracture network solid model.

[0022] The first dimensional parameter for determining the fracture network morphology of the plurality of preset shale gas wells includes:

[0023] Obtain attribute data and construction discharge data corresponding to multiple preset shale gas wells;

[0024] Multiple sets of attribute data and construction displacement data are sequentially input into a preset numerical simulation software, and the preset numerical simulation software is used to calculate and output multiple first dimension parameters.

[0025] The construction of multiple hydraulic fracture network solid models based on multiple first size parameters includes:

[0026] A similarity criterion algorithm is used to calculate the second size parameters corresponding to the multiple pressure fracture network entity models based on multiple first size parameters;

[0027] 3D printing technology is used to print multiple unit models in the solid model of the fracture network that meet the corresponding second size parameters. By combining multiple unit models, a solid model of the fracture network with different complexities that meet the corresponding second size parameters can be built. The unit models include: formation and wellbore connection unit model, formation unit model and cluster unit model.

[0028] One possible design also includes:

[0029] The similarity criterion algorithm is used to calculate the experimental flow data corresponding to the multiple pressure fracture network entity models based on the second size parameters and the corresponding construction flow data of the multiple pressure fracture network entity models;

[0030] The step of performing injection operations on multiple hydraulic fracture network solid models to obtain the characteristic data of the second pump stop pressure curve corresponding to each hydraulic fracture network solid model includes:

[0031] According to the corresponding experimental flow rate data, injection operations were performed on multiple hydraulic fracturing network solid models to obtain the characteristic data of the second pump stop pressure curve corresponding to each hydraulic fracturing network solid model.

[0032] Secondly, this application provides a device for determining the morphological complexity of fracture networks in shale gas wells, comprising:

[0033] The acquisition module is used to respond to the received shale gas well fracture network determination request, and acquire the first pump stop pressure curve feature data of the target shale gas well after fracture network fracturing and the second pump stop pressure curve feature data corresponding to multiple preset shale gas well fracture network entity models.

[0034] The determination module is used to determine, from a plurality of second pump stop pressure curve feature data, a target pump stop pressure curve feature data that matches the first pump stop pressure curve feature data;

[0035] The acquisition module is also used to acquire the target fracture network morphology and structure in the fracture network entity model corresponding to the target pump stop pressure curve feature data;

[0036] The determining module is also used to determine the complexity of the hydraulic fracture network morphology of the target shale gas well based on the target pressure fracture network morphology.

[0037] Thirdly, this application provides a device for determining the morphological complexity of fracture networks in shale gas wells, comprising: a processor, and a memory communicatively connected to the processor;

[0038] The memory stores computer-executed instructions;

[0039] The processor executes computer execution instructions stored in the memory to implement the method as described in any of the first aspects.

[0040] Fourthly, this application provides a system for determining the morphological complexity of a shale gas well fracture network, comprising: a solid model of the fracture network, a centrifugal pump, a water tank, a wellbore, a pressure gauge, and the morphological complexity determination equipment for a shale gas well fracture network as described in the third aspect.

[0041] One end of the centrifugal pump is connected to the water tank pipeline, and the other end of the centrifugal pump is connected to one end of the well shaft pipeline. A portion of the horizontal section of the well shaft is connected to any one of the hydraulic fracturing network solid models. The pressure gauge is installed on the pipeline near the well shaft.

[0042] The device for determining the morphological complexity of the fracture network in a shale gas well is communicatively connected to both the centrifugal pump and the pressure gauge.

[0043] Fifthly, this application provides a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, are used to implement the method as described in any of the first aspects.

[0044] In a sixth aspect, this application provides a computer program product, including a computer program that, when executed by a processor, implements the method described in the first aspect.

[0045] The method, apparatus, equipment, system, medium, and product for determining the morphological complexity of fracture networks in shale gas wells provided in this application, in response to receiving a request to determine the fracture network of a shale gas well, acquires the characteristic data of the first shutdown pressure curve of the target shale gas well after fracture network fracturing and the characteristic data of the second shutdown pressure curve corresponding to multiple preset shale gas well fracture network entity models; determines the characteristic data of the target shutdown pressure curve that matches the characteristic data of the first shutdown pressure curve from the multiple characteristic data of the second shutdown pressure curve; acquires the morphological structure of the target fracture network in the fracture network entity model corresponding to the characteristic data of the target shutdown pressure curve; and determines the morphological complexity of the fracture network of the target shale gas well based on the morphological structure of the target pressure fracture network. Because multiple pre-stored second shutdown pressure curve feature data corresponding to the pre-set shale gas well fracture network entity models are available, upon receiving a shale gas well fracture network determination request, the system can acquire the first shutdown pressure curve feature data of the target shale gas well after fracture network fracturing, as well as the second shutdown pressure curve feature data corresponding to the multiple pre-set shale gas well fracture network entity models. The shutdown pressure curve feature data is inherent in hydraulic fracturing technology, eliminating the need for on-site operations to obtain additional data. This not only saves costs but also avoids data errors caused by on-site environmental factors. Then, the system determines the target shutdown pressure curve feature data that matches the first shutdown pressure curve feature data from the multiple second shutdown pressure curve feature data. The method obtains the target fracture network morphology in the corresponding fracture network entity model. This is because the pressure fluctuation phenomenon after pump shutdown in shale gas fracture network fracturing is caused by the water hammer effect. The pressure fluctuation caused by the water hammer effect will be recorded on the construction curve. Its amplitude and attenuation rate are affected by the fracture morphology. Therefore, there is a correlation between the characteristic data of the pump shutdown pressure curve and the fracture network morphology. The fracture network morphology can be estimated by inversion from the characteristic data of the pump shutdown pressure curve. Thus, the fracture network morphology complexity of the target shale gas well can be determined based on the target fracture network morphology. Therefore, this method can quickly and easily determine the fracture network morphology complexity of the target shale gas well. It has the advantages of high accuracy, simple operation and guaranteed timeliness. Attached Figure Description

[0046] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0047] Figure 1 is an application scenario diagram of the method for determining the morphological complexity of fracture networks in shale gas wells provided in an embodiment of this application;

[0048] Figure 2 is a flowchart of a method for determining the morphological complexity of fracture networks in shale gas wells according to an embodiment of this application;

[0049] Figure 3 is a top view of a solid model of a hydraulic fracturing network provided in an embodiment of this application;

[0050] Figure 4 is a schematic diagram of the assembly of a formation / wellbore connection unit model provided in an embodiment of this application;

[0051] Figure 5 is a schematic diagram of the cluster unit model assembly provided in an embodiment of this application;

[0052] Figure 6 is a schematic diagram of the opening of a cluster unit model provided in an embodiment of this application;

[0053] Figure 7 is a flowchart of a method for determining the morphological complexity of fracture networks in shale gas wells according to another embodiment of this application;

[0054] Figure 8 is a schematic diagram of the structure of a device for determining the morphological complexity of fracture networks in shale gas wells according to an embodiment of this application;

[0055] Figure 9 is a schematic diagram of the structure of a shale gas well fracture network morphology complexity determination device provided in an embodiment of this application;

[0056] Figure 10 is a schematic diagram of the structure of a shale gas well fracture network morphology complexity determination system provided in an embodiment of this application.

[0057] The accompanying drawings illustrate specific embodiments of this application, which will be described in more detail below. These drawings and descriptions are not intended to limit the scope of the concept in any way, but rather to illustrate the concept of this application to those skilled in the art through reference to particular embodiments. Detailed Implementation

[0058] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this application as detailed in the appended claims.

[0059] To clearly understand the technical solution of this application, the solutions of the prior art will be described in detail first.

[0060] Currently, commonly used methods for detecting fracture network morphology include microseismic monitoring technology, inclinometer fracture monitoring technology, and distributed fiber optic monitoring technology. Microseismic monitoring technology uses detector arrays deployed in wells and on the surface to receive and record microseismic events generated or induced by hydraulic fracturing. These events are often related to the fracturing and fracture formation of underground rock formations. In-depth analysis of the waveforms and focal mechanisms of these microseismic events can reveal the morphology and connectivity information of the fracture network. Inclinometer fracture monitoring technology, before fracturing operations, inclinometers are deployed in the target well section or formation. During fracturing, high-pressure fluid is injected into the formation, causing rock fracturing and fracture formation. Simultaneously, the inclinometers deployed in the formation begin operating, accurately measuring and recording changes in tilt angle caused by formation deformation and transmitting the data in real time to the surface receiving station. Through data analysis and processing, key parameters such as fracture morphology, size, orientation, and connectivity can be revealed. Distributed fiber optic monitoring technology first deploys fiber optic sensors in the well. Through specific signal demodulation techniques, the physical signals captured by the sensors are converted into analyzable data. This collected data is then processed and analyzed to assess the morphology of the fractures. However, these methods require on-site testing, which is difficult due to complex conditions such as rugged terrain and construction factors. Furthermore, the methods are susceptible to noise interference during fracture detection, affecting the final results and resulting in both low accuracy and poor timeliness.

[0061] Therefore, when facing technical problems in existing technologies, in order to simplify the process of determining the fracture network morphology and structure of shale gas wells and avoid errors in results caused by field environmental factors, and because the pressure fluctuation phenomenon after pump shutdown in shale gas fracture network fracturing is caused by the water hammer effect—that is, after pump shutdown in a shale gas horizontal well hydraulic fracturing, the sudden change in flow rate causes the fluid in the wellbore to generate water hammer waves under inertial action, which propagate and reflect along the wellbore—the pressure fluctuations caused by the water hammer effect are recorded on the construction curve, and their amplitude and attenuation rate are affected by the fracture morphology and structure. Therefore, there is a correlation between the characteristic data of the pump shutdown pressure curve and the fracture network morphology and structure, and the fracture network morphology and structure can be estimated by inversion from the characteristic data of the pump shutdown pressure curve. Upon receiving a request to determine the fracture network of a shale gas well, the system can acquire the characteristic data of the first shutdown pressure curve of the target shale gas well after fracture network fracturing, as well as the characteristic data of the second shutdown pressure curve corresponding to multiple preset shale gas well fracture network entity models. The shutdown pressure curve characteristic data is inherent in hydraulic fracturing technology, eliminating the need for on-site operations to obtain additional data. This not only saves costs but also avoids data errors caused by on-site environmental factors. Then, the system determines the target shutdown pressure curve characteristic data that matches the first shutdown pressure curve characteristic data from the second shutdown pressure curve characteristic data corresponding to the multiple preset shale gas well fracture network entity models. Since the shutdown pressure curve characteristic data is correlated with the fracture network morphology, the corresponding target fracture network morphology can be obtained based on the target shutdown pressure curve characteristic data, thereby determining the morphological complexity of the target shale gas well's fracture network. This method can quickly and easily determine the morphological complexity of the target shale gas well's fracture network, offering advantages such as high accuracy, simple operation, and guaranteed timeliness.

[0062] Figure 1 illustrates an application scenario of the shale gas well fracture network morphology complexity determination method provided in an embodiment of this application. As shown in Figure 1, the application scenario corresponding to the shale gas well fracture network morphology complexity determination method provided in this embodiment includes: a terminal device 101, a server 102, and a server database 103. The server database 103 pre-stores feature data of the second pump-stop pressure curve corresponding to multiple preset shale gas well fracture network entity models. This data was obtained through injection operations on multiple fracture network entity models and is stored in the server database 103 according to the correspondence between the fracture network entity models and the second pump-stop pressure curve feature data. Specifically, after hydraulic fracturing of a shale gas well in the actual field and obtaining the pressure value and its corresponding time point after pump stoppage, the user sends a shale gas well fracture network determination request to the server through the terminal device 101. This request includes the pressure value obtained after pump stoppage and its corresponding time point.

[0063] Specifically, when server 102 receives a shale gas well fracture network determination request, it extracts feature data based on the pressure value and corresponding time point in the request to obtain the first shutdown pressure curve feature data of the target shale gas well after fracture network fracturing. It then retrieves the second shutdown pressure curve feature data corresponding to multiple pre-stored shale gas well fracture network entity models from server database 103. Next, server 102 determines the target shutdown pressure curve feature data that matches the first shutdown pressure curve feature data from the multiple second shutdown pressure curve feature data. Finally, server 102 obtains the target fracture network morphology structure in the fracture network entity model corresponding to the target shutdown pressure curve feature data and determines the fracture network morphology complexity of the target shale gas well based on the target pressure fracture network morphology structure.

[0064] The technical solution of this application and how the technical solution of this application solves the above-mentioned technical problems are described in detail below with specific embodiments. These specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described again in some embodiments. The embodiments of this application will now be described with reference to the accompanying drawings.

[0065] Figure 2 is a flowchart of a method for determining the morphological complexity of fractured networks in shale gas wells according to an embodiment of this application. As shown in Figure 2, the executing entity in this embodiment is a device for determining the morphological complexity of fractured networks in shale gas wells. This device can be implemented through a computer program, or through a medium storing a relevant computer program, such as a USB flash drive and / or optical disc; alternatively, it can be implemented through a physical device integrating or installing a relevant computer program, such as a chip or a device for determining the morphological complexity of fractured networks in shale gas wells. The method for determining the morphological complexity of fractured networks in shale gas wells provided in this embodiment includes the following steps:

[0066] S201, in response to receiving the shale gas well fracture network determination request, acquire the first pump stop pressure curve feature data of the target shale gas well after fracture network fracturing and the second pump stop pressure curve feature data corresponding to multiple preset shale gas well fracture network entity models.

[0067] The multiple pre-defined shale gas well fracture network physical models can be constructed by scaling down multiple fracture network size parameters of different real shale gas wells according to the obtained size parameters. The fracture network size parameters can include parameters such as fracture length, fracture height, and fracture width.

[0068] Optionally, fracturing parameters can be adjusted for the same actual shale gas well to obtain multiple fracturing network size parameters. These fracturing parameters can include parameters such as the number of fracturing segments and the number of clusters per segment.

[0069] Among them, the first pump shutdown pressure curve characteristic data is the pressure curve characteristic data generated after the pump is shut down when the target shale gas well is conducting on-site hydraulic fracturing network construction.

[0070] The second pump shutdown pressure curve characteristic data refers to the pressure curve characteristic data generated after pump shutdown when performing fluid injection operation on the preset shale gas well fracture network solid model. Fluid injection operation refers to injecting on-site construction fluid into the preset shale gas well fracture network solid model.

[0071] Specifically, when the shale gas well fracture network morphology complexity determination device receives the wellhead pressure value after the target shale gas well has undergone hydraulic fracturing and pump shutdown, it receives a shale gas well fracture network determination request. The device then extracts pressure curve feature data from the received wellhead pressure value. This extraction process includes using autocorrelation functions or Fourier transforms to determine the period, finding the maximum and minimum period signal values ​​within each period to determine the amplitude, or fitting an exponential decay model to derive the curve decay rate. This yields the first pump shutdown pressure curve feature data for the target shale gas well after fracture network fracturing. Finally, the device retrieves the second pump shutdown pressure curve feature data corresponding to multiple preset shale gas well fracture network entity models from the shale gas well fracture network morphology complexity determination device.

[0072] The wellhead pressure value includes the corresponding time point at which the pressure value was generated.

[0073] Accordingly, the device for determining the morphological complexity of fracture networks in shale gas wells is pre-programmed with a program or algorithm for extracting pressure curve feature data based on wellhead pressure values.

[0074] Understandably, after performing injection operations on multiple pre-defined shale gas well fracture network entity models and stopping the pump, multiple sets of wellhead pressure values ​​are obtained. These wellhead pressure values ​​need to be used to extract pressure curve feature data to obtain the second pump-stop pressure curve feature data corresponding to the multiple pre-defined shale gas well fracture network entity models. This data is then stored in the shale gas well fracture network morphology complexity determination device so that when a shale gas well fracture network determination request is received, the second pump-stop pressure curve feature data corresponding to the multiple pre-defined shale gas well fracture network entity models can be obtained.

[0075] S202, determine the target pump stop pressure curve feature data that matches the first pump stop pressure curve feature data from multiple second pump stop pressure curve feature data.

[0076] Among them, the target pump stop pressure curve feature data is the pump stop pressure curve feature data that best matches the first pump stop pressure curve feature data among multiple second pump stop pressure curve feature data.

[0077] Specifically, the first pump stop pressure curve feature data is sequentially compared with different second pump stop pressure curve feature data to calculate the curve shape similarity. If the curves can be fitted, the fitting parameters are compared. If two curves can be fitted with similar parameters, they are considered to be similar in shape. Thus, the target pump stop pressure curve feature data that matches the first pump stop pressure curve feature data is determined from multiple second pump stop pressure curve feature data.

[0078] It is understood that target pump stop pressure curve feature data that matches the first pump stop pressure curve feature data can also be determined from multiple second pump stop pressure curve feature data in other ways, and this embodiment does not limit this.

[0079] S203, obtain the target fracture network morphology and structure in the solid model of the fracture network corresponding to the characteristic data of the target pump stop pressure curve, and determine the fracture network morphology complexity of the target shale gas well based on the target pressure fracture network morphology and structure.

[0080] Among them, the target fracturing network morphology structure refers to the fracturing network morphology structure of the solid model of the fracturing network corresponding to the characteristic data of the target pump stop pressure curve. The fracturing network morphology structure may include the size parameters of the cracks, the distribution of the cracks, etc.

[0081] Specifically, after determining the characteristic data of the target pump shutdown pressure curve, the target fracture network morphology in the corresponding fracture network entity model is found based on the characteristic data of the target pump shutdown pressure curve. Then, the fracture distribution, including the number and location distribution of fractures, can be extracted from the target fracture network morphology, thereby determining the complexity of the fracture network morphology of the target shale gas well based on the fracture distribution.

[0082] Optionally, the complexity of the fracture network morphology of the target shale gas well can be determined based on the size parameters of the fractures in the fracture network morphology, or other methods can be used to determine the complexity of the fracture network morphology of the target shale gas well based on the target fracture network morphology. This embodiment does not limit this.

[0083] It is understandable that the target fracture network morphology and its corresponding shutdown pressure curve feature data of the fracture network entity model are pre-stored in the shale gas well fracture network morphology complexity determination device. This is used to find the target fracture network morphology in the corresponding fracture network entity model after the target shutdown pressure curve feature data is determined.

[0084] The method for determining the morphological complexity of fracture networks in shale gas wells provided in this embodiment, in response to a request to determine the fracture network of a shale gas well, acquires the characteristic data of the first shutdown pressure curve of the target shale gas well after fracture network fracturing and the characteristic data of the second shutdown pressure curve corresponding to multiple preset shale gas well fracture network entity models; determines the characteristic data of the target shutdown pressure curve that matches the characteristic data of the first shutdown pressure curve from the multiple second shutdown pressure curve characteristic data; acquires the morphological structure of the target fracture network in the fracture network entity model corresponding to the characteristic data of the target shutdown pressure curve; and determines the morphological complexity of the fracture network of the target shale gas well based on the morphological structure of the target pressure fracture network. Since the characteristic data of the second shutdown pressure curve corresponding to multiple preset shale gas well fracture network entity models are stored in advance, when a request to determine the fracture network of a shale gas well is received, the characteristic data of the first shutdown pressure curve of the target shale gas well after fracture network fracturing and the characteristic data of the second shutdown pressure curve corresponding to multiple preset shale gas well fracture network entity models can be acquired. The pump shutdown pressure curve characteristic data is inherent in hydraulic fracturing technology, eliminating the need for on-site operations to obtain additional data. This not only saves costs but also avoids data errors caused by on-site environmental factors. Then, from multiple second pump shutdown pressure curve characteristic data sets, the target pump shutdown pressure curve characteristic data matching the first pump shutdown pressure curve characteristic data is determined, and the corresponding target fracture network morphology in the fracture network entity model is obtained. This is because the pressure fluctuation phenomenon after pump shutdown in shale gas fracture network fracturing is caused by the water hammer effect. The pressure fluctuation caused by the water hammer effect is recorded on the construction curve, and its amplitude and attenuation rate are affected by the fracture morphology. Therefore, there is a correlation between the pump shutdown pressure curve characteristic data and the fracture network morphology. The fracture network morphology can be estimated through inversion from the pump shutdown pressure curve characteristic data. Thus, the fracture network morphology complexity of the target shale gas well can be determined based on the target fracture network morphology. Therefore, this method can simply and quickly determine the fracture network morphology complexity of the target shale gas well, with advantages such as high accuracy, simple operation, and guaranteed timeliness.

[0085] As an optional implementation, based on the above embodiments, a target pump stop pressure curve feature data that matches the first pump stop pressure curve feature data is determined from a plurality of second pump stop pressure curve feature data, including:

[0086] Calculate the similarity of the curve shape between the characteristic data of the first pump stop pressure curve and the characteristic data of each second pump stop pressure curve;

[0087] The feature data of the second pump stop pressure curve corresponding to the maximum curve shape similarity is determined as the feature data of the target pump stop pressure curve.

[0088] Specifically, corresponding curves can be generated based on the feature data of the first pump stop pressure curve and the feature data of each second pump stop pressure curve. Then, the curves are filtered to eliminate noise, smooth the curves, and retain edges and details. The processed first pump stop pressure curve and each second pump stop pressure curve are then compared for curve shape similarity. The maximum curve similarity is obtained, and the feature data of the second pump stop pressure curve corresponding to this similarity is the target pump stop pressure curve feature data.

[0089] The filtering process can smooth the curve by calculating the average value of the data, or by preprocessing the curve by setting other parameters, or by using other methods to eliminate noise, smooth the curve and preserve edges and details. This embodiment does not limit this.

[0090] The curve similarity calculation can be performed by selecting a point on the curve, calculating the distribution of other points relative to that point (i.e., shape context descriptors), and then comparing the shape context descriptors of the two curves to evaluate their similarity; or by treating the two curves as sets of points, calculating the maximum distance from a point in one set of points to the nearest point in the other set of points, and the smaller the distance, the higher the similarity of the two curves; or by calculating the curve shape similarity in other ways, which is not limited in this embodiment.

[0091] The method for determining the morphological complexity of fracture networks in shale gas wells provided in this embodiment identifies target shutdown pressure curve feature data that matches the first shutdown pressure curve feature data from multiple second shutdown pressure curve feature data. This includes: calculating the curve shape similarity between the first shutdown pressure curve feature data and each second shutdown pressure curve feature data; and determining the second shutdown pressure curve feature data corresponding to the maximum curve shape similarity as the target shutdown pressure curve feature data. By calculating the curve shape similarity between the first shutdown pressure curve feature data and each second shutdown pressure curve feature data to determine the target shutdown pressure curve feature data, the method can objectively and accurately determine the target shutdown pressure curve feature data that best matches the first shutdown pressure curve feature data based on curve shape similarity, avoiding errors from subjective judgment.

[0092] As an optional implementation, based on any of the above embodiments, the complexity of the hydraulic fracture network morphology of the target shale gas well is determined based on the target pressure fracture network morphology structure, including:

[0093] Obtain the volume of branch cracks and main cracks in the target pressure fracture network structure;

[0094] Calculate the ratio of the branch fracture volume to the total fracture volume, where the total fracture volume is the sum of the branch fracture volume and the main fracture volume;

[0095] Based on the ratio results, the complexity of the fracture network morphology of the target shale gas well is determined.

[0096] The hydraulic fracturing network includes main fractures and branch fractures, and the target hydraulic fracturing network morphology includes the length, width, and height of the main fractures and the length, width, and height of the branch fractures.

[0097] Specifically, the volumes of the main fractures and branch fractures can be calculated based on the length, width, and height of the main fractures and the branch fractures in the target fracture network structure to obtain the volumes of the branch fractures and main fractures in the target fracture network structure. Then, the volumes of the branch fractures and main fractures are summed to obtain the total fracture volume. The ratio of the branch fracture volume to the total fracture volume is then calculated. If the ratio is 0, it indicates that there are no branch fractures in the fracture network, thus determining that the fracture network structure of the target shale gas well is simple. Conversely, the closer the ratio is to 1, the more complex the fracture network structure of the target shale gas well.

[0098] It is understandable that complexity can also be represented by complexity levels. Therefore, multiple ratio ranges and complexity levels can be pre-configured. After determining the ratio result, it is determined which ratio range the result falls within, and the complexity level corresponding to that ratio range with the mapping relationship is determined as the fracture network morphology complexity of the target shale gas well.

[0099] The method for determining the morphological complexity of fracture networks in shale gas wells provided in this embodiment determines the morphological complexity of the fracture network in a target shale gas well based on the target pressure fracture network structure. This includes: obtaining the volume of branch fractures and the volume of main fractures in the target pressure fracture network structure; calculating the ratio of the branch fracture volume to the total fracture volume, where the total fracture volume is the sum of the branch fracture volume and the main fracture volume; and determining the morphological complexity of the fracture network in the target shale gas well based on the ratio result. Determining the morphological complexity of the fracture network in a target shale gas well by calculating the ratio of branch fracture volume to total fracture volume allows for an objective and quantitative assessment of the fracture network morphology. Compared to relying on subjective experience or vague descriptions, using ratio calculations can more accurately describe the complexity of the fracture network morphology and reduce errors from human judgment.

[0100] As an optional implementation, based on any of the above embodiments, before obtaining the characteristic data of the first shutdown pressure curve of the target shale gas well after fracture network fracturing and the characteristic data of the second shutdown pressure curve corresponding to multiple preset shale gas well fracture network entity models, the method further includes:

[0101] Determine the first dimensional parameters of the fracture network morphology structure of multiple preset shale gas wells;

[0102] Multiple solid models of the pressure fracture network are constructed based on multiple first-size parameters;

[0103] Injection operations were performed on multiple hydraulic fracture network solid models to obtain the characteristic data of the second pump stop pressure curve corresponding to each hydraulic fracture network solid model.

[0104] The first dimensional parameters for determining the fracture network morphology of multiple pre-defined shale gas wells are as follows:

[0105] Obtain attribute data and construction discharge data corresponding to multiple preset shale gas wells;

[0106] Multiple sets of attribute data and construction displacement data are sequentially input into the preset numerical simulation software, and the preset numerical simulation software is used to calculate and output multiple first dimension parameters;

[0107] Multiple solid models of the hydraulic fracture network are constructed based on multiple first-dimensional parameters, including:

[0108] A similarity criterion algorithm is used to calculate the second size parameters corresponding to multiple pressure fracture network solid models based on multiple first size parameters;

[0109] 3D printing technology is used to print various element models in the solid model of the fracture network that meet the corresponding second size parameters. By combining the various element models, a solid model of the fracture network with different complexities that meet the corresponding second size parameters can be built. The element models include: formation and wellbore connection element model, formation element model and cluster element model.

[0110] The first size parameter refers to the size parameters of the pre-selected shale gas well fracture network morphology, such as the length, width, and height of the fractures.

[0111] Specifically, the first dimensional parameters of the fracture network morphology of multiple pre-selected shale gas wells are determined according to a pre-selected method. Then, these first dimensional parameters are scaled proportionally to obtain the dimensional parameters of multiple fracture network solid models. Multiple fracture network solid models are then constructed according to these dimensional parameters. Finally, simulating the injection of fracturing fluid into shale gas wells during on-site hydraulic fracturing operations, the actual fracturing fluid is injected into each of the multiple fracture network solid models to make the experimental results more closely resemble the actual on-site results. The pressure values ​​after pump shutdown are recorded, and the characteristic data of the second pump shutdown pressure curve corresponding to each fracture network solid model are extracted from these values.

[0112] Among them, attribute data refers to data such as the length of the vertical section, the length of the horizontal section, the number of fracturing sections, and the number of clusters in each section of the shale gas well in the actual field.

[0113] Among them, the construction discharge data refers to the rate at which fracturing fluid is injected into the bottom layer during actual on-site hydraulic fracturing of shale gas wells.

[0114] The preset numerical simulation software is software used to calculate the first dimension parameters based on attribute data and construction discharge data, such as FracMan integrated geological engineering software or other numerical simulation software. This embodiment does not limit this software.

[0115] It should be noted that there are existing solutions in the industry for the FracMan integrated geological engineering software, which should be considered as exemplary. Their purpose is only to illustrate the feasibility of implementing the technical solution of this application, but it does not mean that the applicant has used or necessarily used the solution.

[0116] Specifically, based on the vertical and horizontal section lengths of multiple pre-defined shale gas wells obtained from actual field surveys, as well as pre-set fracturing parameters such as the number of fracturing sections and the number of clusters per section, along with the corresponding operational displacement data, these data are sequentially input into the pre-defined numerical simulation software according to the different shale gas wells. Numerical simulation calculations are then performed using the pre-set parameters, grid, boundary conditions, and initial conditions, outputting the first-dimensional parameters corresponding to different shale gas wells.

[0117] The second dimension parameter is the dimension parameter corresponding to the solid model of the pressure fracture network obtained after similarity criterion calculation based on the first dimension parameter, and may include parameters such as the length, width and height of the crack.

[0118] Specifically, the crack length in the first dimension parameter needs to be reduced according to a preset ratio, and then the similarity criterion algorithm is used for calculation. First, the hydraulic radius of the shale gas well in the actual site is calculated according to the first dimension parameter. The specific calculation formula of the hydraulic radius R is shown in Equation (1). Then, by setting the error threshold between the hydraulic radius of the shale gas well in the actual site and the hydraulic radius of the hydraulic fracture network entity model, the second dimension parameter of the hydraulic fracture network entity model is calculated. The corresponding second dimension parameter and the uniform outer contour dimension parameter are input into the 3D printer so that the printed outer contour dimension is uniform and the internal gap dimension meets the corresponding second dimension parameter. Multiple hydraulic fracture network entity models are manually built according to the second dimension parameter corresponding to each hydraulic fracture network entity model. During the building process, the number of different unit models can be controlled to build hydraulic fracture network entity models of different complexities. Figure 3 is a top view of one type of hydraulic fracture network solid model, which includes a formation and wellbore connection unit model 301, a formation unit model 302, a cluster unit model 303, and natural fractures 304 and artificial hydraulic fractures 305 constructed from the above three unit models.

[0119] The preset ratio can be 40:1, 20:1 or 10:1, etc. The specific ratio needs to be determined according to the actual situation, and this embodiment does not limit it.

[0120] Natural fractures refer to the fractures that exist in shale gas wells at the site before hydraulic fracturing.

[0121] It is understandable that the size of natural fractures can be obtained through field methods such as core observation and downhole television, and the size of natural fractures can be included in the first size parameter.

[0122] In equation (1): R is the hydraulic radius, h is the crack height, and wf is the crack width.

[0123] Among them, the formation-wellbore connection unit model, formation unit model, and cluster unit model are printed from a porous material to simulate the actual pore structure of the formation.

[0124] The formation / wellbore connection unit model and cluster unit model are not complete hexahedrons, but have a rounded corner to fit the circular horizontal section of the wellbore. Figure 4 shows a schematic diagram of the formation / wellbore connection unit model assembly, which includes a formation / wellbore connection unit model 401 and a rounded cutout 402. It can be understood that each formation / wellbore connection unit model 401 contains a rounded cutout 402. The formation / wellbore connection unit model and cluster unit model differ slightly in structure. The cluster unit model has perforations in the rounded section to simulate perforations during in-situ fracturing. These perforations provide a flow channel for fluid from the wellbore to enter the cluster unit model. Figure 5 shows a schematic diagram of the cluster unit model assembly, which includes a cluster unit model 501 and a perforation 502. Figure 6 shows a schematic diagram of the perforations in the cluster unit model, which includes a cluster unit model 601 and a perforation 602. Figure 6 is an enlarged schematic diagram of the perforation area in the cluster unit model in Figure 5. The formation / wellbore connection unit model and the cluster unit model can be arbitrarily combined to simulate different hydraulic fracturing section spacings under field conditions. The cluster unit model has several openings, the spacing of which can be arbitrarily adjusted to simulate different perforation spacings and perforation cluster numbers.

[0125] The method for determining the morphological complexity of fracture networks in shale gas wells provided in this embodiment, before obtaining the characteristic data of the first shutdown pressure curve of the target shale gas well after fracture network fracturing and the characteristic data of the second shutdown pressure curve corresponding to multiple preset shale gas well fracture network entity models, further includes: determining the first size parameters of the fracture network morphological structure of multiple preset shale gas wells; constructing multiple fracture network entity models based on the multiple first size parameters; performing fluid injection operations on the multiple fracture network entity models respectively to obtain the characteristic data of the second shutdown pressure curve corresponding to each fracture network entity model; determining the first size parameters of the fracture network morphological structure of multiple preset shale gas wells includes: obtaining the attribute data corresponding to the multiple preset shale gas wells and the application... The process involves inputting multiple sets of attribute data and construction displacement data into a pre-set numerical simulation software. The software calculates and outputs multiple first-dimensional parameters. Based on these first-dimensional parameters, multiple fracture network entity models are constructed. This includes using a similarity criterion algorithm to calculate the corresponding second-dimensional parameters for each fracture network entity model. 3D printing technology is used to print various element models that satisfy the corresponding second-dimensional parameters. Combining these element models allows for the creation of fracture network entity models with varying complexities to meet the corresponding second-dimensional parameters. These element models include formation-wellbore connection element models, formation element models, and cluster element models. Constructing fracture network entity models based on the first-dimensional parameters of the pre-set shale gas well fracture network morphology allows for accurate simulation of the fracture network morphology after actual field construction. This results in higher reliability of the final second shutdown pressure curve characteristic data. Furthermore, the construction of multiple fracture network entity models allows for the acquisition of multiple second shutdown pressure curve characteristic data, enabling the determination of different shale gas well fracture network morphological complexities. Numerical simulation calculations are performed using pre-set numerical simulation software to obtain the first-dimensional parameters, eliminating the need for on-site data acquisition and significantly reducing costs. Furthermore, the required first parameters can be obtained by adjusting the data input into the pre-set numerical simulation software. Similarity criteria are then applied to the first-dimensional parameters to calculate the second-dimensional parameters corresponding to the fracture network entity model. This allows for a more accurate simulation of the actual fracture network morphology and structure in the field, increasing the reliability of experimental data. By combining various unit models, fracture network entity models with different complexities corresponding to the second-dimensional parameters can be constructed, enriching the experimental data and providing solid data support for subsequently determining the complexity of the fracture network in shale gas wells in the field.

[0126] As an optional implementation, based on any of the above embodiments, it further includes:

[0127] The similarity criterion algorithm was used to calculate the experimental flow data corresponding to multiple pressure fracture network entity models based on the second size parameters and the corresponding construction flow data of multiple pressure fracture network entity models.

[0128] Injection operations were performed on multiple hydraulic fracturing network solid models to obtain the characteristic data of the second pump shutdown pressure curve corresponding to each hydraulic fracturing network solid model, including:

[0129] Injection operations were performed on multiple hydraulic fracturing network solid models according to the corresponding experimental flow data to obtain the characteristic data of the second pump stop pressure curve corresponding to each hydraulic fracturing network solid model.

[0130] Among them, the experimental flow rate data refers to the rate at which liquid is injected into the solid model of the pressure fracture network after similarity criterion calculation based on the second dimension parameters and the corresponding construction discharge data of the solid model of the pressure fracture network.

[0131] Specifically, when calculating the similarity criterion, after obtaining the second size parameter, the Reynolds number must be the same to obtain the experimental flow rate data. Reynolds number R e The specific calculation formula is shown in equation (2). First, the Reynolds number of the shale gas well in the actual field is calculated. The same liquid as the actual construction liquid is used for injection operation to ensure that the fluid density and fluid viscosity are the same. Then, the experimental flow rate data can be obtained according to the Reynolds number formula. The same liquid as the actual construction liquid is injected into multiple fracture network solid models according to the corresponding experimental flow rate data. When the liquid exits from the end of the fracture network solid model and the pressure value is stable, the injection is stopped, the fracture network solid model is closed, and the pressure value after the pump is stopped is collected. Thus, the characteristic data of the second pump stop pressure curve corresponding to each fracture network solid model is extracted from it. R e =w f ρv / μ (2)

[0132] In equation (2): R e ρ is the Reynolds number, v is the fluid density, v is the fluid velocity, and μ is the fluid viscosity.

[0133] The method for determining the morphological complexity of shale gas well fracture networks provided in this embodiment further includes: using a similarity criterion algorithm and calculating experimental flow data corresponding to multiple fracture network entity models based on multiple sets of first size parameters and construction displacement data; performing fluid injection operations on multiple fracture network entity models respectively to obtain the characteristic data of the second pump stop pressure curve corresponding to each fracture network entity model, including: performing fluid injection operations on multiple fracture network entity models respectively according to the corresponding experimental flow data to obtain the characteristic data of the second pump stop pressure curve corresponding to each fracture network entity model. The similarity criterion algorithm ensures that the fracture network entity models have similar flow characteristics to the actual shale gas wells during the simulation process, more accurately reflecting the fluid flow and fracture propagation during the actual fracturing process, thereby improving the accuracy of the simulation results; performing fluid injection operations on the fracture network entity models based on the calculated experimental flow data ensures that each model can be precisely injected according to its specific flow requirements.

[0134] Figure 7 is a flowchart of a method for determining the morphological complexity of a shale gas well fracture network according to another embodiment of this application. As shown in Figure 7, the method for determining the morphological complexity of a shale gas well fracture network provided in this embodiment includes how to obtain the feature data of the second pump stop pressure curve corresponding to multiple preset shale gas well fracture network entity models. The method for determining the morphological complexity of a shale gas well fracture network provided in this embodiment includes the following steps:

[0135] S701, obtain attribute data and construction discharge data corresponding to multiple preset shale gas wells.

[0136] S702 inputs multiple sets of attribute data and construction displacement data into the preset numerical simulation software in sequence, calculates and outputs multiple first dimension parameters.

[0137] S703, similarity criteria calculation is performed on multiple first-dimensional parameters to obtain the second-dimensional parameters corresponding to multiple hydraulic fracture network solid models.

[0138] S704 uses a similarity criterion algorithm and calculates the experimental flow data corresponding to multiple pressure cracking network entity models based on the second dimension parameters and corresponding construction flow data of multiple pressure cracking network entity models.

[0139] S705 utilizes 3D printing technology to print various element models in the solid model of the fracture network. The element models include: formation and wellbore connection element model, formation element model and cluster element model.

[0140] S706 allows for the arbitrary combination of various element models to construct multiple solid models of the pressure fracture network that satisfy the corresponding second size parameters.

[0141] S707 connects the solid model of the fracture network, centrifugal pump, water tank, wellbore, pressure gauge, and equipment for determining the morphological complexity of the shale gas well fracture network to build a system for determining the morphological complexity of the shale gas well fracture network.

[0142] S708, according to the corresponding experimental flow rate data, performs injection operations on multiple hydraulic fracturing network solid models respectively to obtain the characteristic data of the second pump stop pressure curve corresponding to each hydraulic fracturing network solid model.

[0143] S709, in response to receiving the shale gas well fracture network determination request, acquires the first pump stop pressure curve feature data of the target shale gas well after fracture network fracturing and the second pump stop pressure curve feature data corresponding to multiple preset shale gas well fracture network entity models.

[0144] S710, determine the target pump stop pressure curve feature data that matches the first pump stop pressure curve feature data from multiple second pump stop pressure curve feature data.

[0145] S711, obtain the target fracture network morphology and structure in the entity model of the fracture network corresponding to the characteristic data of the target pump stop pressure curve, and determine the fracture network morphology complexity of the target shale gas well based on the target pressure fracture network morphology and structure.

[0146] In this embodiment, the implementation method and technical effect of S701-S711 are similar to those of the corresponding solutions in the above embodiments, and will not be repeated here.

[0147] Figure 8 is a schematic diagram of the structure of a shale gas well fracture network morphology complexity determination device provided in an embodiment of this application. As shown in Figure 8, the shale gas well fracture network morphology complexity determination device provided in this embodiment is located in the shale gas well fracture network morphology complexity determination equipment. The shale gas well fracture network morphology complexity determination device 80 provided in this embodiment includes: an acquisition module 81 and a determination module 82.

[0148] The acquisition module 81 is used to, in response to a shale gas well fracture network determination request, acquire the first shutdown pressure curve feature data of the target shale gas well after fracture network fracturing and the second shutdown pressure curve feature data corresponding to multiple preset shale gas well fracture network entity models; the determination module 82 is used to determine the target shutdown pressure curve feature data that matches the first shutdown pressure curve feature data from the multiple second shutdown pressure curve feature data; the acquisition module 81 is also used to acquire the target fracture network morphology and structure in the fracture network entity model corresponding to the target shutdown pressure curve feature data; the determination module 82 is also used to determine the fracture network morphology complexity of the target shale gas well based on the target pressure fracture network morphology and structure.

[0149] The device for determining the morphological complexity of fracture networks in shale gas wells provided in this embodiment can execute the method embodiment shown in Figure 2. The specific implementation principle and technical effect are similar, and will not be described again here.

[0150] Optionally, the determining module 82, when determining the target pump stop pressure curve feature data that matches the first pump stop pressure curve feature data from multiple second pump stop pressure curve feature data, is specifically used to: calculate the curve shape similarity between the first pump stop pressure curve feature data and each second pump stop pressure curve feature data; and determine the second pump stop pressure curve feature data corresponding to the maximum curve shape similarity as the target pump stop pressure curve feature data.

[0151] Optionally, module 82, when determining the complexity of the fracture network morphology of the target shale gas well based on the target pressure fracture network morphology, is specifically used to: obtain the volume of branch fractures and the volume of main fractures in the target pressure fracture network morphology; calculate the ratio of the volume of branch fractures to the total fracture volume, where the total fracture volume is the sum of the volumes of branch fractures and main fractures; and determine the complexity of the fracture network morphology of the target shale gas well based on the ratio result.

[0152] Optionally, the shale gas well fracture network morphology complexity determination device provided in this embodiment also includes a construction module and a fluid injection module.

[0153] Accordingly, the determining module 82 is also used to determine the first size parameters of the fracture network morphology of multiple preset shale gas wells; the construction module is used to construct multiple fracture network entity models based on the multiple first size parameters and the construction displacement data of multiple preset shale gas wells; and the injection module is used to perform injection operations on the multiple fracture network entity models respectively to obtain the second pump stop pressure curve feature data corresponding to each fracture network entity model.

[0154] Accordingly, module 82, when determining the first dimension parameters of the fracture network morphology of multiple preset shale gas wells, is specifically used to: acquire the attribute data and construction displacement data corresponding to multiple preset shale gas wells; input multiple sets of attribute data and construction displacement data into the preset numerical simulation software in sequence, and use the preset numerical simulation software to calculate and output multiple first dimension parameters.

[0155] Accordingly, the construction module, when constructing multiple fracture network entity models based on multiple first-dimensional parameters and multiple preset shale gas well construction displacement data, is specifically used for: employing a similarity criterion algorithm and calculating the second-dimensional parameters corresponding to multiple fracture network entity models based on multiple sets of first-dimensional parameters and construction displacement data; using 3D printing technology to print multiple unit models in the fracture network entity models, so as to build multiple fracture network entity models that satisfy the second-dimensional parameters through the combination of multiple unit models. The unit models include: formation and wellbore connection unit models, formation unit models, and cluster unit models.

[0156] Optionally, the shale gas well fracture network morphology complexity determination device provided in this embodiment also includes a calculation module.

[0157] Accordingly, the calculation module is used to calculate the experimental flow data corresponding to multiple pressure cracking network entity models by employing a similarity criterion algorithm and based on multiple sets of first size parameters and construction flow data.

[0158] Accordingly, the injection module, when performing injection operations on multiple fracturing network entity models to obtain the characteristic data of the second pump stop pressure curve corresponding to each fracturing network entity model, is specifically used to: perform injection operations on multiple fracturing network entity models according to the corresponding experimental flow rate data to obtain the characteristic data of the second pump stop pressure curve corresponding to each fracturing network entity model.

[0159] It should be noted that the apparatus provided in this embodiment of the invention can implement all the method steps implemented in the above method embodiment and can achieve the same technical effect. Therefore, the parts and beneficial effects that are the same as those in the method embodiment will not be described in detail here.

[0160] Figure 9 is a schematic diagram of the structure of a shale gas well fracture network morphology complexity determination device provided in an embodiment of this application. As shown in Figure 9, the shale gas well fracture network morphology complexity determination device 90 provided in this embodiment includes: a processor 91 and a memory 92 that is communicatively connected to the processor.

[0161] The memory 92 stores computer-executed instructions; the processor 91 executes the computer-executed instructions stored in the memory 92 to implement the shale gas well fracture network morphology complexity determination method provided in any of the above embodiments. Related explanations can be understood by referring to the relevant descriptions and effects corresponding to the steps in the accompanying drawings, and will not be elaborated further here.

[0162] The program may include program code, which includes computer-executable instructions. Memory 92 may include high-speed RAM, and may also include non-volatile memory, such as at least one disk storage device.

[0163] In this embodiment, the memory 92 and the processor 91 are connected via a bus. The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. Buses can be categorized as address buses, data buses, control buses, etc. For ease of illustration, only one thick line is used in Figure 9, but this does not imply that there is only one bus or one type of bus.

[0164] Figure 10 shows a shale gas well fracture network morphology complexity determination system provided in an embodiment of this application. As shown in Figure 10, the shale gas well fracture network morphology complexity determination system 100 provided in this embodiment includes: a fracture network solid model 1001, a wellbore 1002, a pressure gauge 1003, a centrifugal pump 1004, a water tank 1005, and a shale gas well fracture network morphology complexity determination device 1006 as shown in Figure 9.

[0165] One end of the centrifugal pump 1004 is connected to the water tank 1005 through a pipeline. The water tank 1005 contains the actual fracturing fluid used in the construction. The other end of the centrifugal pump 1004 is connected to one end of the well barrel 1002 through a pipeline. A portion of the horizontal section of the well barrel 1002 is connected to any fracturing network solid model 1001. The pressure gauge 1003 is installed on the pipeline near the opening of the well barrel 1002.

[0166] Among them, the shale gas well fracture network morphology complexity determination device 1006 is communicatively connected to the centrifugal pump 1004 and the pressure gauge 1003.

[0167] The dimensions of the wellbore 1002 can be proportionally reduced according to the ratio of the vertical and horizontal sections of the actual shale gas well to obtain the dimensions of the wellbore 1002.

[0168] Understandably, experimental flow data is pre-set in the shale gas well fracture network morphology complexity determination device 1006. After the system is built, the shale gas well fracture network morphology complexity determination system 100 controls the centrifugal pump 1004 to open, thereby injecting the actual fracturing fluid in the water tank 1005 into the fracture network solid model 1001. When fluid exits from the end of the fracture network solid model 1001 and the wellhead pressure value displayed by the pressure gauge 1003 stabilizes, the centrifugal pump 1004 is controlled to close by the shale gas well fracture network morphology complexity determination device 1006, and the valve at the end of the fracture network solid model 1001 is manually closed. The shale gas well fracture network morphology complexity determination device 1006 records the wellhead pressure value displayed by the pressure gauge 1003 after the pump stops, until the pressure value stabilizes.

[0169] It should be noted that the apparatus provided in this embodiment of the invention can implement all the method steps implemented in the above method embodiment and can achieve the same technical effect. Therefore, the parts and beneficial effects that are the same as those in the method embodiment will not be described in detail here.

[0170] This application also provides a computer-readable storage medium storing computer-executable instructions. When executed by a processor, these instructions are used to implement the shale gas well fracture network morphology complexity determination method provided in any of the above embodiments. For example, the computer-readable storage medium may be a ROM, random access memory (RAM), CD-ROM, magnetic tape, floppy disk, or optical data storage device. Non-transitory computer-readable storage media may be any available medium or data storage device accessible to the processor, including but not limited to magnetic memory (e.g., floppy disk, hard disk, magnetic tape, magneto-optical disk (MO)), optical memory (e.g., CD, DVD, BD, HVD), and semiconductor memory (e.g., ROM, EPROM, EEPROM, NAND FLASH, SSD).

[0171] This application also provides a computer program product, including a computer program that, when executed by a processor, implements the method for determining the morphological complexity of fracture networks in shale gas wells provided in any of the above embodiments. It should be noted that, for the foregoing method embodiments, for the sake of simplicity, they are all described as a series of actions. However, those skilled in the art should understand that this application is not limited to the described order of actions, because according to this application, some steps can be performed in other orders or simultaneously. Furthermore, those skilled in the art should also understand that the embodiments described in the specification are all optional embodiments, and the actions and modules involved are not necessarily essential to this application.

[0172] It should be further noted that, although the various steps in the flowchart are shown in sequence as indicated by the arrows, these steps are not necessarily performed in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order restriction on the execution of these steps, and these steps may be performed in other orders. Moreover, at least a portion of the steps in the flowchart may include multiple sub-steps or multiple stages, and these sub-steps or stages are not necessarily performed at the same time, but may be performed at different times. The execution order of these sub-steps or stages is not necessarily to be performed in sequence, but may be performed in turn or alternately with other steps or at least a portion of the sub-steps or stages of other steps.

[0173] It should be understood that the above-described device embodiments are merely illustrative, and the device of the present application may also be implemented in other ways. For example, the division of units / modules in the above-described embodiments is merely a logical functional division, and actual implementations may employ other division methods. For example, multiple units, modules, or components may be combined or integrated into another system, or some features may be omitted or not implemented.

[0174] Furthermore, unless otherwise specified, the functional units / modules in the various embodiments of this application can be integrated into one unit / module, or each unit / module can exist physically separately, or two or more units / modules can be integrated together. The integrated units / modules described above can be implemented in hardware or as software program modules.

[0175] When integrated units / modules are implemented in hardware, the hardware can be digital circuits, analog circuits, etc. The physical implementation of the hardware structure includes, but is not limited to, transistors, memristors, etc. Unless otherwise specified, the processor can be any suitable hardware processor, such as a CPU, GPU, FPGA, DSP, and ASIC, etc. Unless otherwise specified, the storage unit can be any suitable magnetic or magneto-optical storage medium, such as Resistive Random Access Memory (RRAM), Dynamic Random Access Memory (DRAM), Static Random Access Memory (SRAM), Enhanced Dynamic Random Access Memory (EDRAM), High-Bandwidth Memory (HBM), Hybrid Memory Cube (HMC), etc.

[0176] If the integrated unit / module is implemented as a software program module and sold or used as an independent product, it can be stored in a computer-readable storage device (CMD). Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a memory and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this application. The aforementioned memory includes various media capable of storing program code, such as a USB flash drive, read-only memory (ROM), random access memory (RAM), portable hard drive, magnetic disk, or optical disk.

[0177] In the above embodiments, the descriptions of each embodiment have their own emphasis. Parts not described in detail in a particular embodiment can be referred to in the relevant descriptions of other embodiments. The technical features of the above embodiments can be combined arbitrarily. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as these combinations of technical features do not contradict each other, they should be considered within the scope of this specification. Those skilled in the art, upon considering the specification and practicing the invention disclosed herein, will readily conceive of other embodiments of this application. This application is intended to cover any variations, uses, or adaptations of this application that follow the general principles of this application and include common knowledge or customary technical means in the art not disclosed in this application. The specification and embodiments are considered exemplary only, and the true scope and spirit of this application are indicated by the following claims.

[0178] It should be understood that the present application is not limited to the exact structure described above and shown in the drawings, and that various modifications and changes may be made without departing from the scope thereof. The scope of the present application is limited only by the appended claims.

Claims

1. A method for determining the morphological complexity of fracture networks in shale gas wells, characterized in that, The method includes: In response to receiving a shale gas well fracture network determination request, the system acquires the first pump stop pressure curve feature data of the target shale gas well after fracture network fracturing and the second pump stop pressure curve feature data corresponding to multiple preset shale gas well fracture network entity models. Determine the target pump stop pressure curve feature data that matches the first pump stop pressure curve feature data from a plurality of second pump stop pressure curve feature data; Obtain the target fracture network morphology and structure in the entity model of the fracture network corresponding to the characteristic data of the target pump stop pressure curve, and determine the fracture network morphology complexity of the target shale gas well based on the target pressure fracture network morphology and structure.

2. The method according to claim 1, characterized in that, The step of determining the target pump stop pressure curve feature data that matches the first pump stop pressure curve feature data from a plurality of second pump stop pressure curve feature data includes: Calculate the similarity of the curve shape between the first pump stop pressure curve feature data and each of the second pump stop pressure curve feature data; The feature data of the second pump stop pressure curve corresponding to the maximum curve shape similarity is determined as the feature data of the target pump stop pressure curve.

3. The method according to claim 1 or 2, characterized in that, The determination of the complexity of the hydraulic fracture network morphology of the target shale gas well based on the target pressure fracture network morphology includes: Obtain the volume of branch cracks and main cracks in the target pressure fracture network structure; Calculate the ratio of the branch fracture volume to the total fracture volume, where the total fracture volume is the sum of the branch fracture volume and the main fracture volume; Based on the ratio results, the complexity of the fracture network morphology of the target shale gas well is determined.

4. The method according to any one of claims 1-3, characterized in that, Before obtaining the characteristic data of the first shutdown pressure curve of the target shale gas well after fracture network fracturing and the characteristic data of the second shutdown pressure curve corresponding to multiple preset shale gas well fracture network entity models, the process also includes: Determine the first dimensional parameters of the fracture network morphology structure of the plurality of preset shale gas wells; Multiple solid models of the pressure fracture network are constructed based on multiple first size parameters; Injection operations were performed on multiple hydraulic fracture network solid models to obtain the characteristic data of the second pump stop pressure curve corresponding to each hydraulic fracture network solid model. The first dimensional parameter for determining the fracture network morphology of the plurality of preset shale gas wells includes: Obtain attribute data and construction discharge data corresponding to multiple preset shale gas wells; Multiple sets of attribute data and construction displacement data are sequentially input into a preset numerical simulation software, and the preset numerical simulation software is used to calculate and output multiple first dimension parameters. The construction of multiple hydraulic fracture network solid models based on multiple first size parameters includes: A similarity criterion algorithm is used to calculate the second size parameters corresponding to the multiple pressure fracture network entity models based on multiple first size parameters; 3D printing technology is used to print multiple unit models in the solid model of the fracture network that meet the corresponding second size parameters. By combining multiple unit models, a solid model of the fracture network with different complexities that meet the corresponding second size parameters can be built. The unit models include: formation and wellbore connection unit model, formation unit model and cluster unit model.

5. The method according to claim 4, characterized in that, Also includes: The similarity criterion algorithm is used to calculate the experimental flow data corresponding to the multiple pressure fracture network entity models based on the second size parameters and the corresponding construction flow data of the multiple pressure fracture network entity models; The step of performing injection operations on multiple hydraulic fracture network solid models to obtain the characteristic data of the second pump stop pressure curve corresponding to each hydraulic fracture network solid model includes: According to the corresponding experimental flow rate data, injection operations were performed on multiple hydraulic fracturing network solid models to obtain the characteristic data of the second pump stop pressure curve corresponding to each hydraulic fracturing network solid model.

6. A device for determining the morphological complexity of fracture networks in shale gas wells, characterized in that, include: The acquisition module is used to respond to the received shale gas well fracture network determination request, and acquire the first pump stop pressure curve feature data of the target shale gas well after fracture network fracturing and the second pump stop pressure curve feature data corresponding to multiple preset shale gas well fracture network entity models. The determination module is used to determine, from a plurality of second pump stop pressure curve feature data, a target pump stop pressure curve feature data that matches the first pump stop pressure curve feature data; The acquisition module is also used to acquire the target fracture network morphology and structure in the fracture network entity model corresponding to the target pump stop pressure curve feature data; The determining module is also used to determine the complexity of the hydraulic fracture network morphology of the target shale gas well based on the target pressure fracture network morphology.

7. A device for determining the morphological complexity of fracture networks in shale gas wells, characterized in that, include: A processor, and a memory communicatively connected to the processor; The memory stores computer-executed instructions; The processor executes computer execution instructions stored in the memory to implement the method as described in any one of claims 1 to 5.

8. A system for determining the morphological complexity of fracture networks in shale gas wells, characterized in that, include: The solid model of the fracture network, centrifugal pump, water tank, wellbore, pressure gauge, and the equipment for determining the morphological complexity of the shale gas well fracture network as described in claim 7; One end of the centrifugal pump is connected to the water tank pipeline, and the other end of the centrifugal pump is connected to one end of the well shaft pipeline. A portion of the horizontal section of the well shaft is connected to any one of the hydraulic fracturing network solid models. The pressure gauge is installed on the pipeline near the well shaft. The device for determining the morphological complexity of the fracture network in a shale gas well is communicatively connected to both the centrifugal pump and the pressure gauge.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer-executable instructions, which, when executed by a processor, are used to implement the method as described in any one of claims 1 to 5.

10. A computer program product, characterized in that, Includes a computer program that, when executed by a processor, implements the method described in any one of claims 1 to 5.

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