Horizontal well fracturing pipeline optimization methods, devices, electronic equipment, and storage media

Abstract

This application provides a method, apparatus, electronic device, and storage medium for optimizing horizontal well fracturing pathways. It involves obtaining a three-dimensional geostress model based on a three-dimensional geological model and a one-dimensional geostress model; obtaining target well placement data based on the three-dimensional geostress model; and obtaining a target operational pathway based on the three-dimensional geostress model and the target well placement data. The target operational pathway characterizes the fracturing sequence for achieving the maximum estimated production of the target reservoir. By obtaining the three-dimensional geostress model from the three-dimensional geological model and the one-dimensional geostress model, and obtaining target well placement data determined by the stimulation volume of the target reservoir based on the three-dimensional geostress model, and then obtaining the target operational pathway determined by the maximum estimated production of the target reservoir based on the three-dimensional geostress model and the target well placement data, the maximum estimated production of the target reservoir can be obtained by sequentially fracturing the horizontal wells corresponding to the target well placement data according to the target operational pathway, thereby increasing oil and gas production.

Description

Technical Field

[0001] This application relates to the field of oil and gas field development technology, and in particular to a method, apparatus, electronic equipment and storage medium for optimizing horizontal well fracturing links. Background Technology

[0002] my country has large reserves of unconventional oil and gas resources, with a wide burial area and huge exploitation potential. However, unconventional reservoirs are characterized by low porosity, low permeability, and poor reservoir properties. They have virtually no self-flowing ability, and the oil layers have a large vertical span and multiple oil-bearing layers are developed in layers.

[0003] In the current oil and gas field development process, large-scale horizontal well fracturing technology is often used to increase the reservoir stimulation volume, thereby achieving efficient, economical and safe extraction.

[0004] However, in large-scale horizontal well integrated fracturing and production enhancement technology, the fracturing operation lacks a defined and perfect fracturing sequence, resulting in low oil and gas production. Summary of the Invention

[0005] This application provides a method, apparatus, electronic device, and storage medium for optimizing horizontal well fracturing pathways to solve the problem of low oil and gas production.

[0006] In a first aspect, this application provides a method for optimizing the fracturing sequence of horizontal wells, comprising: obtaining a three-dimensional geostress model based on a three-dimensional geological model and a one-dimensional geostress model, wherein the three-dimensional geostress model is used to determine the stress characteristics of the reservoir; obtaining target well placement data based on the three-dimensional geostress model, wherein the target well placement data characterizes the distribution characteristics of horizontal wells determined according to the stimulation volume of the target reservoir; and obtaining a target operational sequence based on the three-dimensional geostress model and the target well placement data, wherein the target operational sequence characterizes the fracturing order of each horizontal well corresponding to the target well placement data in order to achieve the maximum estimated production of the target reservoir.

[0007] In one possible implementation, obtaining the target well placement data based on the three-dimensional geostress model includes: obtaining candidate operation links based on initial well placement data and initial operation links, wherein the initial well placement data characterizes the distribution characteristics of horizontal wells preset for the target reservoir, and the candidate operation links are operation links applicable to the initial well placement data; and obtaining the target well placement data based on the three-dimensional geostress model and the candidate operation links.

[0008] In one possible implementation, obtaining the target well placement data based on the three-dimensional geostress model and the candidate operational links includes: obtaining a corresponding target volume estimation model based on the three-dimensional geostress model and the candidate operational links, wherein the volume estimation model is used to estimate the stimulation volume of the target reservoir based on the three-dimensional geostress model and the candidate operational links; and obtaining the target well placement data based on the target volume estimation model.

[0009] In one possible implementation, obtaining the target operation link based on the three-dimensional geostress model and the target well placement data includes: obtaining a corresponding target production prediction model based on the three-dimensional geostress model and the target well placement data, wherein the production prediction model is used to predict the production of the target reservoir based on the three-dimensional geostress model and the target well placement data; and obtaining the target operation link based on the target production prediction model.

[0010] In one possible implementation, the initial well placement data includes at least one first well placement data, and further includes: obtaining the initial well placement layer number and the initial well placement number; obtaining the number of well placement layers to be placed based on the initial well placement layer number and the number of completed well placement layers; obtaining the remaining well placement number based on the initial well placement number and the number of wells already placed; if the remaining well placement number meets the minimum well placement number required for the number of wells to be placed, then the first well placement data is obtained; if the remaining well placement number does not meet the minimum well placement number required for the number of wells to be placed, then the search is stopped, and the process returns to verify the number of well placement layers to be placed and the remaining well placement number corresponding to the next well placement data, until the verification is completed.

[0011] In one possible implementation, before obtaining the three-dimensional geostress model based on the three-dimensional geological model and the one-dimensional geostress model, the method includes: acquiring target block information, wherein the target block information characterizes the geological features of the target block; and obtaining the three-dimensional geological model and the one-dimensional geostress model based on the target block information.

[0012] In one possible implementation, the method further includes: obtaining updated target block information based on real-time logging data of the target block; and obtaining updated three-dimensional geological models and one-dimensional geostress models based on the updated target block information.

[0013] Secondly, this application provides a horizontal well fracturing pathway optimization device, comprising:

[0014] The processing module is used to obtain a three-dimensional geostress model based on a three-dimensional geological model and a one-dimensional geostress model. The three-dimensional geostress model is used to determine the stress characteristics of the reservoir.

[0015] The processing module is also used to obtain target well placement data based on the three-dimensional geostress model, wherein the target well placement data characterizes the distribution characteristics of horizontal wells determined based on the stimulation volume of the target reservoir;

[0016] The determination module is used to obtain the target operation sequence based on the three-dimensional geostress model and the target well layout data. The target operation sequence is used to characterize the fracturing order of each horizontal well corresponding to the target well layout data in order to achieve the maximum estimated production of the target reservoir.

[0017] In one possible implementation, when the processing module obtains the target well placement data based on the three-dimensional geostress model, it is specifically used to: obtain candidate operation links based on the initial well placement data and the initial operation link, wherein the initial well placement data characterizes the distribution characteristics of horizontal wells preset for the target reservoir, and the candidate operation links are operation links applicable to the initial well placement data; and obtain the target well placement data based on the three-dimensional geostress model and the candidate operation links.

[0018] In one possible implementation, when the processing module obtains the target well placement data based on the three-dimensional geostress model and the candidate operation links, it is specifically used to: obtain a corresponding target volume estimation model based on the three-dimensional geostress model and the candidate operation links, wherein the volume estimation model is used to estimate the stimulation volume of the target reservoir based on the three-dimensional geostress model and the candidate operation links; and obtain the target well placement data based on the target volume estimation model.

[0019] In one possible implementation, when the determining module obtains the target operation link based on the three-dimensional geostress model and the target well placement data, it is specifically used to: obtain a corresponding target production prediction model based on the three-dimensional geostress model and the target well placement data, wherein the production prediction model is used to predict the production of the target reservoir based on the three-dimensional geostress model and the target well placement data; and obtain the target operation link based on the target production prediction model.

[0020] In one possible implementation, the initial well placement data includes at least one first well placement data. The processing module is further configured to: obtain the initial well placement layer number and the initial well placement number; obtain the number of well placement layers to be placed based on the initial well placement layer number and the number of completed well placement layers; obtain the remaining well placement number based on the initial well placement number and the number of wells already placed; if the remaining well placement number meets the minimum well placement number required for the number of well placement layers to be placed, then the first well placement data is obtained; if the remaining well placement number does not meet the minimum well placement number required for the number of well placement layers to be placed, then the search is stopped, and the process returns to verify the number of well placement layers to be placed and the remaining well placement number corresponding to the next well placement data, until the verification is completed.

[0021] In one possible implementation, before obtaining the three-dimensional geostress model based on the three-dimensional geological model and the one-dimensional geostress model, the processing module is specifically used to: acquire target block information, wherein the target block information characterizes the geological features of the target block; and obtain the three-dimensional geological model and the one-dimensional geostress model based on the target block information.

[0022] In one possible implementation, the processing module is further configured to: obtain updated target block information based on real-time logging data of the target block; and obtain updated three-dimensional geological model and one-dimensional geostress model based on the updated target block information.

[0023] Thirdly, this application provides an electronic device, including: a processor, and a memory communicatively connected to the processor;

[0024] The memory stores computer-executed instructions;

[0025] The processor executes computer execution instructions stored in the memory to implement the horizontal well fracturing link optimization method as described in any of the first aspects of the embodiments of this application.

[0026] Fourthly, this application provides a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, are used to implement the horizontal well fracturing link optimization method as described in any of the first aspects of the embodiments of this application.

[0027] According to a fifth aspect of the embodiments of this application, this application provides a computer program product, including a computer program that, when executed by a processor, implements the horizontal well fracturing link optimization method as described in any of the first aspects above.

[0028] The horizontal well fracturing pathway optimization method, apparatus, electronic equipment, and storage medium provided in this application obtain a three-dimensional geostress model based on a three-dimensional geological model and a one-dimensional geostress model. This three-dimensional geostress model is used to determine the stress characteristics of the reservoir. Based on the three-dimensional geostress model, target well placement data is obtained, representing the distribution characteristics of horizontal wells determined according to the stimulation volume of the target reservoir. Based on the three-dimensional geostress model and the target well placement data, a target operational pathway is obtained, representing the fracturing sequence of each horizontal well corresponding to the target well placement data to achieve the maximum estimated production of the target reservoir. By obtaining the three-dimensional geostress model based on the three-dimensional geological model and the one-dimensional geostress model, obtaining the target well placement data determined by the stimulation volume of the target reservoir based on the three-dimensional geostress model, and then obtaining the target operational pathway determined by the maximum estimated production of the target reservoir based on the three-dimensional geostress model and the target well placement data, the maximum estimated production of the target reservoir can be obtained by fracturing each horizontal well corresponding to the target well placement data sequentially according to the target operational pathway, thus achieving an increase in oil and gas production. Attached Figure Description

[0029] 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.

[0030] Figure 1 This is an application scenario diagram of the horizontal well fracturing link optimization method provided in the embodiments of this application;

[0031] Figure 2 A flowchart illustrating a horizontal well fracturing link optimization method provided in one embodiment of this application;

[0032] Figure 3 for Figure 2 A schematic diagram of the modeling process for the three-dimensional geostress model in step S101 of the embodiment shown.

[0033] Figure 4 for Figure 2 A schematic diagram illustrating the specific implementation steps of modeling prior to step S101 in the illustrated embodiment;

[0034] Figure 5 for Figure 4 A schematic diagram of the modeling process of the three-dimensional geological model in step S1001 of the embodiment shown.

[0035] Figure 6 for Figure 2 A schematic diagram illustrating the distribution characteristics of a horizontal well in the illustrated embodiment;

[0036] Figure 7 for Figure 2A schematic diagram illustrating the specific implementation steps of step S102 in the illustrated embodiment;

[0037] Figure 8 for Figure 7 A schematic diagram of the fracturing sequence in the initial operation chain in step S1021 of the embodiment shown.

[0038] Figure 9 for Figure 7 A schematic diagram illustrating the specific implementation steps of step S1022 in the illustrated embodiment;

[0039] Figure 10 for Figure 2 A schematic diagram illustrating the specific implementation steps of step S103 in the illustrated embodiment;

[0040] Figure 11 A flowchart of a horizontal well fracturing link optimization method provided in another embodiment of this application;

[0041] Figure 12 This is a schematic diagram of the structure of a horizontal well fracturing link optimization device provided in one embodiment of this application;

[0042] Figure 13 A schematic diagram of an electronic device provided according to one embodiment of this application;

[0043] Figure 14 This is a block diagram illustrating a terminal device in an exemplary embodiment of this application.

[0044] 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

[0045] 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.

[0046] The technical solution of this application involves the collection, storage, use, processing, transmission, provision and disclosure of user personal information and data, which comply with the provisions of relevant laws and regulations and do not violate public order and good morals.

[0047] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties. Furthermore, the collection, use and processing of the relevant data must comply with the relevant laws, regulations and standards of the relevant countries and regions, and corresponding operation portals are provided for users to choose to authorize or refuse.

[0048] The application scenarios of the embodiments of this application are explained below:

[0049] Figure 1 This diagram illustrates an application scenario of the horizontal well fracturing link optimization method provided in this application. The horizontal well fracturing link optimization method provided in this application can be applied to scenarios where large-scale horizontal well fracturing is used to achieve oil and gas field development. For example, as shown... Figure 1 As shown, based on the oil and gas field to be developed, a corresponding three-dimensional geological model and a one-dimensional geostress model are obtained, and then a three-dimensional geostress model is obtained. On this basis, the distribution characteristics of horizontal wells determined by the stimulation volume of the target reservoir are obtained, i.e., the target well layout data, for example... Figure 1 The distribution of each horizontal well shown in the figure is then used to fracturing the horizontal wells in different fracturing sequences according to the three-dimensional geostress model and target well layout data. This fracturing sequence, i.e. the target operation link, is used to achieve the maximum estimated production of the target reservoir. By performing large-scale horizontal well fracturing according to the target operation link, the maximum estimated production can be obtained.

[0050] In the current oil and gas field development process, large-scale horizontal well fracturing technology is often used to increase the reservoir stimulation volume. However, the fracturing operation in large-scale horizontal well fracturing technology does not have a defined and perfect fracturing sequence, which leads to uneven expansion of artificial fractures, insufficient overall reservoir stimulation, and weak post-fracturing production stabilization capacity, resulting in low oil and gas production.

[0051] 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.

[0052] Figure 2 A flowchart of a horizontal well fracturing link optimization method provided in one embodiment of this application is shown below. Figure 2 As shown, the horizontal well fracturing link optimization method provided in this embodiment includes the following steps:

[0053] Step S101: Based on the three-dimensional geological model and the one-dimensional geostress model, a three-dimensional geostress model is obtained. The three-dimensional geostress model is used to determine the stress characteristics of the reservoir.

[0054] For example, a three-dimensional geological model is used to represent the spatial distribution of underground geological structures and properties. Based on the three-dimensional geological model, the spatial distribution characteristics of underground geological bodies can be obtained, such as the spatial location and thickness of different rock layers, ores and other geological bodies. Furthermore, the properties of underground geological bodies can be predicted, such as the mechanical properties of rocks.

[0055] For example, a one-dimensional geostress model is used to represent the variation of geostress in the vertical direction, which is determined by a combination of the elastic and mechanical parameters of the rock.

[0056] For example, a three-dimensional geostress model is used to determine the stress characteristics of a reservoir, including at least one of the following: vertical geostress, pore pressure, minimum horizontal geostress, and maximum horizontal geostress. Figure 3 for Figure 2 The schematic diagram of the modeling process of the three-dimensional geostress model in step S101 of the embodiment shown is as follows: Figure 3 As shown, a one-dimensional geostress model is obtained through rock elastic parameters and rock mechanical parameters. Quantitative reservoir data is obtained based on rock physical analysis. Three-dimensional stress modeling is performed on the three-dimensional geological model. Then, a mechanical mesh is constructed through finite element simulation, and a three-dimensional geostress model is obtained by combining the results.

[0057] For example, prior to step S101, it is necessary to perform three-dimensional geological modeling and one-dimensional geostress modeling on the oil and gas field to be developed. Figure 4 for Figure 2 The illustrated embodiment shows a schematic diagram of the specific implementation steps of modeling prior to step S101, as follows: Figure 4 As shown, the specific implementation steps of the modeling include:

[0058] Step S1001: Obtain target block information, which characterizes the geological features of the target block.

[0059] Step S1002: Based on the target block information, obtain a three-dimensional geological model and a one-dimensional geostress model.

[0060] For example, the target block information characterizes the geological features of the target block. According to the principle of model building, the more initial data, the more accurate the model. Therefore, the target block information includes at least one of the following data: reservoir structural information, original seismic data, seismic reference surface, stratigraphic and fault interpretation schemes, reservoir mechanics inversion results, well location coordinates of known wells in the block, geological stratification and conventional logging data, oil testing and production data, imaging logging data of known wells in the block, rock mechanics experimental data, microseismic data, existing fracturing operation curves and fracturing design data, and relevant research results of the study area and adjacent areas. Furthermore, based on the rock elastic parameters and rock mechanics parameters in the target block information, a one-dimensional geostress model can be obtained.

[0061] For example, to improve the modeling accuracy of a 3D geological model, a combination of deterministic and stochastic modeling is used to establish the model. For deterministic parameters, deterministic modeling is employed; for parameters with multiple influencing factors, a combination of deterministic and stochastic modeling is used. Simultaneously, inverted data volumes are used for constraints to reduce model uncertainty and improve the accuracy of the 3D geological model. In one possible implementation... Figure 5 for Figure 4 The illustrated embodiment shows a schematic diagram of the modeling process for the three-dimensional geological model in step S1001, as follows: Figure 5 As shown, based on the target block information obtained from comprehensive seismic and geological studies, structural interpretation, time-depth conversion, structural modeling, lithofacies modeling, and attribute modeling are performed sequentially to obtain a three-dimensional geological model. The process from lithofacies modeling to attribute modeling also includes facies control, which is to realize the modeling process from lithofacies modeling to attribute modeling by analyzing the distribution and evolution of geological facies.

[0062] In one possible implementation, to improve the accuracy of the three-dimensional geostress model, the three-dimensional geological model and the one-dimensional geostress model can be updated based on real-time logging data obtained during drilling in the target block. This updates the three-dimensional geostress model and improves its accuracy. More specifically, for example, updated target block information is obtained based on real-time logging data; updated three-dimensional geological and one-dimensional geostress models are obtained based on the updated target block information; and then the three-dimensional geostress model is updated based on the updated three-dimensional geological and one-dimensional geostress models.

[0063] In this embodiment, a three-dimensional geostress model is obtained by combining a three-dimensional geological model and a one-dimensional geostress model. This provides the reservoir stress characteristics for subsequent steps. The stress characteristics include at least one of the following: vertical geostress, pore pressure, minimum horizontal geostress, and maximum horizontal geostress. Before obtaining the three-dimensional geostress model from the three-dimensional geological model and the one-dimensional geostress model, an accurate three-dimensional geological model is obtained based on the target block information obtained from comprehensive seismic geological studies, using deterministic and stochastic modeling methods. A one-dimensional geostress model is then obtained by combining the rock elastic and rock mechanical parameters from the target block information, leading to the three-dimensional geostress model. Furthermore, during drilling in the target block, real-time logging data from the target block is used to update the three-dimensional geological model and the one-dimensional geostress model, thereby updating the three-dimensional geostress model to improve its accuracy.

[0064] Step S102: Based on the three-dimensional geostress model, the target well placement data is obtained. The target well placement data characterizes the distribution characteristics of horizontal wells determined according to the stimulation volume of the target reservoir.

[0065] For example, different distribution characteristics of horizontal wells result in different stimulated volumes after fracturing, leading to different oil and gas production rates. Target well placement data characterizes the distribution characteristics of horizontal wells determined based on the stimulated volume of the target reservoir; that is, it determines the target well placement data corresponding to the distribution characteristics of horizontal wells based on the stimulated volume of the target reservoir. More specifically, for example, Figure 6 for Figure 2 The illustrated embodiment is a schematic diagram of the distribution characteristics of a horizontal well, as shown below. Figure 6 As shown, in the three-dimensional geological model, two horizontal wells are arranged in the uppermost layer, two horizontal wells in the middle layer, and three horizontal wells in the lowermost layer. Based on the three-dimensional geostress model, the stress characteristics of the reservoir include at least one of the following: vertical geostress, pore pressure, minimum horizontal geostress, and maximum horizontal geostress. Under the same reservoir stress characteristics, the distribution characteristics of the horizontal wells corresponding to the second well layout data are as follows: Figure 1 The horizontal well layout shown corresponds to a modified volume size_1. The distribution characteristics of the horizontal wells corresponding to the third well layout data are as follows: Figure 6 The horizontal well layout shown corresponds to a stimulation volume size_2. If the stimulation volume size_2 is greater than the stimulation volume size_1, then the third well layout data is determined as the target well layout data. The stimulation volume of the target reservoir is positively correlated with the oil and gas production.

[0066] In one possible implementation, for the same distribution characteristics of horizontal wells, different fracturing sequences will also result in different stimulation volumes. Figure 7 for Figure 2 The schematic diagram of the specific implementation steps of step S102 in the illustrated embodiment is as follows: Figure 7 As shown, the specific implementation steps of step S102 include:

[0067] Step S1021: Based on the initial well layout data and the initial operation link, a candidate operation link is obtained. The initial well layout data characterizes the distribution characteristics of the horizontal wells preset for the target reservoir, and the candidate operation link is an operation link that is suitable for the initial well layout data.

[0068] For example, the initial operation chain includes sequential fracturing at the same layer, interlayer staggered zipper fracturing, and edge-center zipper fracturing; more specifically, for example, Figure 8 for Figure 7 The schematic diagram of the fracturing sequence in step S1021 of the illustrated embodiment shows that the horizontal wells are distributed in a "W"-shaped three-dimensional staggered pattern. Taking the distribution of horizontal wells in three layers as an example, as shown... Figure 8 As shown in Figure (a), sequential fracturing in the same layer proceeds as follows: fracturing from well 1 to well 2 to well 3 to well K (solid arrows), then fracturing from well K+1 to well K+2 to well K+3 to well U, and finally fracturing from well U+1 to well U+2 to well U+3 to well Z, thus completing the horizontal well fracturing task. Similarly, fracturing from well Z to well 1 (dashed arrows) can also complete the horizontal well fracturing task. Figure 8 As shown in Figure (b), interlayer staggered zipper fracturing involves completing the fracturing task of horizontal wells according to the fracturing sequence of solid arrows in the figure: from well 1 to well K+1 to well U+1 to well K+2 to well 2 to well K+3 to well U+2 to well Z to well U to well K. Correspondingly, the horizontal well fracturing task can also be completed by fracturing from well K to well 1 according to dashed arrows in the figure. Figure 8 As shown in Figure (c), edge-center zipper fracturing involves fracturing from well 1 to well K+1 to well U+1 to well K+2 to well 2 according to the solid arrows in the figure, and fracturing from well K to well U to well Z to well U+2 to well K+3 to well 2 according to the dashed arrows in the figure, in order to complete the fracturing task of horizontal wells. Furthermore, sequential fracturing within the same layer, interlayer staggered zipper fracturing, and edge-center zipper fracturing are further divided into single-stage fracturing methods and segmented fracturing methods, with corresponding different stimulation volumes.

[0069] For example, the initial well layout data characterizes the distribution characteristics of the horizontal wells preset for the target reservoir. For instance, for the target reservoir, taking a well layout layer of 3 layers and a well layout of 6, 10 distribution characteristics of horizontal wells can be obtained, namely 10 initial well layout data, as shown in Table 1.

[0070] Table 1

[0071] 1 1 1 4 2 1 2 3 3 1 3 2 4 1 4 1 5 2 1 3 6 2 2 2 7 2 3 1 8 3 1 2 9 3 2 1 10 4 1 1

[0072] For example, the candidate operation links are those applicable to the initial well layout data; that is, not all specific operation links in the initial operation links are applicable to the initial well layout data. More specifically, for example, the distribution characteristics of the horizontal wells corresponding to serial number 1 in Table 1 are not applicable to interlayer staggered zipper fracturing and edge-center zipper fracturing, while the distribution characteristics of the horizontal wells corresponding to serial number 3 in Table 1 are applicable to same-layer sequential fracturing, interlayer staggered zipper fracturing, and edge-center zipper fracturing. Further, the following definitions are made: whether same-layer sequential fracturing is used (1 for yes, 0 for no); whether interlayer alternating zipper fracturing is used (1 for yes, 0 for no); whether edge-center zipper fracturing is used (1 for yes, 0 for no); whether segmented fracturing is performed (1 for yes, 0 for no). Based on the above definitions, based on the 10 initial well layout data shown in Table 1, there are 10 candidate operation links as shown in Table 2. Table 2 does not list all candidate operation links and is only for illustration.

[0073] Table 2

[0074]

[0075] Table 2 (continued)

[0076]

[0077] Step S1022: Based on the three-dimensional geostress model and the candidate operation links, obtain the target well placement data.

[0078] For example, based on the reservoir stress characteristics obtained from the three-dimensional geostress model, including at least one of the following: vertical geostress, pore pressure, minimum horizontal geostress, and maximum horizontal geostress, under the same reservoir stress characteristics, combined with the candidate operational links, the corresponding target reservoir stimulation volume is obtained. Based on the size relationship of the target reservoir stimulation volumes, target well placement data corresponding to the distribution characteristics of horizontal wells is then obtained, determined according to the stimulation volumes of the target reservoirs. In one possible implementation, Figure 9 for Figure 7 The schematic diagram of the specific implementation steps of step S1022 in the embodiment shown is as follows: Figure 9 As shown, the specific implementation steps of step S1022 include:

[0079] Step S10221: Based on the three-dimensional geostress model and the candidate operation links, obtain the corresponding target volume estimation model. The volume estimation model is used to estimate the stimulation volume of the target reservoir based on the three-dimensional geostress model and the candidate operation links.

[0080] Step S10222: Obtain target well placement data based on the target volume prediction model.

[0081] For example, the volume estimation model is used to estimate the stimulation volume of a target reservoir based on a 3D geostress model and candidate operational links. More specifically, for example, the reservoir stress characteristics obtained through the 3D geostress model and candidate operational links are used as inputs to the volume estimation model. Based on the estimation logic, the corresponding estimated stimulation volume of the target reservoir can be obtained. Before using this volume estimation model, it needs to be trained and evaluated. For example, this volume estimation model is constructed using a random forest model based on five-fold cross-validation. More specifically, it includes two steps: First, based on the model's performance, computational resources, and data scale, the number of weak evaluators in the random forest model is optimized to avoid overfitting risk; then, five-fold cross-validation is performed using the maximum depth and maximum number of features of the random forest model to obtain the root mean square error (RMSE). The smaller the RMSE value, the more accurate the prediction result of the volume estimation model based on the random forest model. By adjusting the number of weak evaluators, the maximum depth, and the maximum number of features, the corresponding volume estimation model based on the random forest model is obtained. The specific training process will not be elaborated here.

[0082] For example, based on the three-dimensional geostress model and the candidate operation links, a corresponding target volume estimation model is obtained. Then, the reservoir stress characteristics obtained from the three-dimensional geostress model and the candidate operation links are input into the target volume estimation model to obtain the corresponding estimated target reservoir stimulation volume. Finally, target well placement data is obtained based on the size relationship of the estimated target reservoir stimulation volumes. In one possible implementation, the stimulation volume corresponding to the candidate operation links is estimated based on the target volume estimation model. Based on the comparison results of the stimulation volumes corresponding to the candidate operation links, the target operation links are determined. For example, the stimulation volumes corresponding to the candidate operation links shown in Table 2 are shown in Table 3.

[0083] Table 3

[0084]

[0085] For example, as shown in Table 3, the target well placement data is obtained based on the size relationship of the modification volume corresponding to the candidate operation links. More specifically, for example, in Table 3, the modification volume corresponding to serial number 1 and serial number 2 is much smaller than the modification volume corresponding to serial number 3 to serial number 10, and the modification volumes corresponding to serial number 3 to serial number 10 are not much different. Therefore, the initial well placement data corresponding to serial number 3 to serial number 10 is used as the target well placement data.

[0086] In this embodiment, candidate well placement routes suitable for the initial well placement data are obtained based on the initial well placement data and the initial work order. These routes are then combined with the reservoir stress characteristics obtained through a three-dimensional geostress model and input into a pre-trained and optimized target volume estimation model. This yields the stimulation volume of the target reservoir corresponding to the candidate well placement routes. Based on the size relationship of the stimulation volumes, the target well placement data is obtained, i.e., the distribution characteristics of horizontal wells determined based on the stimulation volumes of the target reservoirs. Since the stimulation volume of the target reservoir is positively correlated with oil and gas production, this embodiment's step of filtering the initial well placement data based on the stimulation volume of the target reservoir not only improves the accuracy of the final oil and gas production estimation but also enhances the processing efficiency of subsequent steps.

[0087] Step S103: Based on the three-dimensional geostress model and target well layout data, the target operation sequence is obtained. The target operation sequence is used to characterize the fracturing order of each horizontal well corresponding to the target well layout data in order to achieve the maximum estimated production of the target reservoir.

[0088] For example, the target operation sequence is used to characterize the fracturing order of each horizontal well corresponding to the target well placement data to achieve the maximum estimated production of the target reservoir. More specifically, the target well placement data is obtained based on the size relationship of the stimulated volumes of the target reservoir. Combined with the reservoir stress characteristics obtained through a three-dimensional geostress model, the production of the fracturing sequence corresponding to the target well placement data is estimated. The corresponding fracturing sequence is obtained based on the maximum estimated production, thus obtaining the target operation sequence. In one possible implementation, Figure 10 for Figure 2 The schematic diagram of the specific implementation steps of step S103 in the embodiment shown is as follows: Figure 10 As shown, the specific implementation steps of step S103 include:

[0089] Step S1031: Based on the three-dimensional geostress model and the target well layout data, obtain the corresponding target production prediction model. The production prediction model is used to predict the production of the target reservoir based on the three-dimensional geostress model and the target well layout data.

[0090] Step S1032: Obtain the target operation link based on the target output prediction model.

[0091] For example, the production prediction model is used to predict the production of a target reservoir based on a 3D geostress model and target well placement data. More specifically, for example, the stress characteristics of the reservoir obtained through the 3D geostress model and the operational chain determined by the target well placement data are used as inputs to the production prediction model. Based on the prediction logic, the corresponding predicted production of the target reservoir can be obtained. Before using this production prediction model, it needs to be trained and evaluated. For example, this production prediction model is constructed using a random forest model based on five-fold cross-validation. More specifically, it includes two steps: First, based on the model's performance, computational resources, and data scale, the number of weak evaluators in the random forest model is optimized to avoid overfitting risk; then, five-fold cross-validation is performed jointly with the maximum depth and maximum number of features of the random forest model to obtain the root mean square error (RMSE). The smaller the RMSE value, the more accurate the prediction result of the production prediction model based on the random forest model. By adjusting the number of weak evaluators, the maximum depth, and the maximum number of features, the corresponding production prediction model based on the random forest model is obtained. The specific training process will not be elaborated here.

[0092] For example, based on the three-dimensional geostress model and target well placement data, a corresponding target production prediction model is obtained. Then, the reservoir stress characteristics obtained from the three-dimensional geostress model and the operational sequence determined by the target well placement data are input into the target production prediction model to obtain the corresponding predicted production of the target reservoir. Finally, based on the maximum predicted production, the target operational sequence is obtained, i.e., the fracturing order for the maximum predicted production of the target reservoir is obtained. More specifically, for example, based on the size relationship of the stimulation volumes corresponding to the candidate operational sequences shown in Table 3, the initial well placement data corresponding to serial numbers 3 to 10 are used as target well placement data. Then, the operational sequence corresponding to the target well placement data and the reservoir stress characteristics obtained from the three-dimensional geostress model are input into the target production prediction model to obtain the predicted production corresponding to the operational sequence for each target well placement data, as shown in Table 4, where the serial numbers are consistent with those shown in Table 3.

[0093] Table 4

[0094]

[0095] For example, as shown in Table 4, based on the estimated production corresponding to the operation link corresponding to each target well placement data, the target operation link corresponding to the maximum estimated production is the fracturing sequence of the edge-center zipper fracturing method corresponding to serial number 10, which adopts segmented fracturing.

[0096] In this embodiment, a production prediction model is constructed based on a random forest model implemented with five-fold cross-validation. The stress characteristics of the reservoir obtained through the three-dimensional geostress model and the operational sequence determined by the target well data are input into the target production prediction model to obtain the predicted production corresponding to the operational sequence of each target well data. Then, the target operational sequence corresponding to the maximum predicted production is obtained. That is, by fracturing each horizontal well corresponding to the target well data in sequence according to the fracturing sequence corresponding to the target operational sequence, the maximum predicted production of the target reservoir can be obtained, thus realizing the improvement of oil and gas production.

[0097] In this embodiment, a three-dimensional geostress model is obtained based on a three-dimensional geological model and a one-dimensional geostress model. This three-dimensional geostress model is used to determine the stress characteristics of the reservoir. Based on the three-dimensional geostress model, target well placement data is obtained, which characterizes the distribution characteristics of horizontal wells determined according to the stimulation volume of the target reservoir. Based on the three-dimensional geostress model and the target well placement data, a target operational sequence is obtained. This target operational sequence characterizes the fracturing order of each horizontal well corresponding to the target well placement data to achieve the maximum estimated production of the target reservoir. By obtaining the three-dimensional geostress model from the three-dimensional geological model and the one-dimensional geostress model, obtaining the target well placement data determined by the stimulation volume of the target reservoir based on the three-dimensional geostress model, and then obtaining the target operational sequence determined by the maximum estimated production of the target reservoir based on the three-dimensional geostress model and the target well placement data, the maximum estimated production of the target reservoir can be obtained by fracturing each horizontal well corresponding to the target well placement data sequentially according to the target operational sequence, thus achieving an increase in oil and gas production.

[0098] Figure 11 A flowchart of a horizontal well fracturing link optimization method provided in another embodiment of this application is shown below. Figure 11 As shown, the horizontal well fracturing link optimization method provided in this embodiment is to... Figure 2 Based on the horizontal well fracturing link optimization method provided in the illustrated embodiment, the specific implementation steps for obtaining initial well placement data before step S1021 are as follows: The horizontal well fracturing link optimization method provided in this embodiment includes the following steps:

[0099] Step S201: Based on the three-dimensional geological model and the one-dimensional geostress model, a three-dimensional geostress model is obtained. The three-dimensional geostress model is used to determine the stress characteristics of the reservoir.

[0100] Step S202: Obtain the initial number of well layers and the initial number of wells.

[0101] Step S203: Based on the initial number of well layers and the number of completed well layers, obtain the number of well layers to be laid.

[0102] Step S204: Based on the initial number of wells and the number of wells already deployed, obtain the remaining number of wells.

[0103] For example, the number of well layers to be deployed is obtained based on the initial number of well layers and the number of well layers completed, and the remaining number of wells is obtained based on the initial number of well layers and the number of wells already deployed. More specifically, for example, if the initial number of well layers is 3 and the initial number of wells deployed is 6, the distribution characteristics of the horizontal wells corresponding to the first type of well deployment data data_1 are: 2 completed well layers, 1 layer to be deployed, 5 wells already deployed, and 1 remaining well; the distribution characteristics of the horizontal wells corresponding to the second type of well deployment data data_2 are: 2 completed well layers, 1 layer to be deployed, 6 wells already deployed, and 0 remaining wells.

[0104] Step S205: If the remaining number of wells meets the minimum number of wells required for the number of well layers to be laid out, then the first well layout data is obtained. The initial well layout data includes at least one first well layout data.

[0105] In step S206, if the remaining number of wells does not meet the minimum number of wells required for the number of wells to be placed, the search is stopped, and the process returns to step S203 to verify the number of wells to be placed and the remaining number of wells corresponding to the next well placement data, until the verification is completed.

[0106] For example, based on the development requirements of the target block, the initial number of well placement layers and the initial number of wells are obtained. Then, an enumeration combination algorithm is used to perform a depth-first search through recursive calls to obtain all the initial well placement data. More specifically, in each layer, the number of fracturing wells placed in the current layer is enumerated, and then the recursive search is implemented in the next layer. When the search reaches the last layer, if the sum of the number of wells placed equals the initial number of wells, it is determined as a first well placement data, i.e., the initial well placement data.

[0107] For example, since the enumeration method enumerates the values ​​sequentially from the set of all possible solutions in each layer, there may be instances in each layer where the remaining number of wells does not meet the minimum number of wells required for the layer to be laid. To avoid wasting computational resources and improve computational efficiency, it is necessary to determine whether the remaining number of wells meets the minimum number of wells required for the layer to be laid. More specifically, for example, based on the enumeration method, a pruning operation is introduced. If the remaining number of wells meets the minimum number of wells required for the layer to be laid, then the first well data is obtained, and the initial well data includes at least one first well data. If the remaining number of wells does not meet the minimum number of wells required for the layer to be laid, then the search stops, and the process returns to step S203 to verify the layer to be laid and the remaining number of wells corresponding to the next well data, until the verification is completed. Furthermore, a decision coefficient `judge` is defined. If the decision coefficient `judge` is greater than 0, the remaining number of wells meets the minimum number of wells required for the number of wells to be placed. If the decision coefficient `judge` is less than or equal to 0, the remaining number of wells does not meet the minimum number of wells required for the number of wells to be placed, and the search stops. The process returns to step S203 to verify the number of wells to be placed and the remaining number of wells corresponding to the next well placement data, until the verification is completed. The decision coefficient `judge` is obtained according to equation (1), where `remain` is the remaining number of wells, `total` is the initial number of well placement layers, and `finish` is the number of well placement layers completed.

[0108] judge=remain-(total-finish-1) (1)

[0109] In one possible implementation, the initial total number of well layers is 3, and the initial number of wells is 6. Based on the distribution characteristics of the horizontal wells corresponding to the first type of well placement data (data_1): the finished well layer count is 2, the layer to be placed is 1, the number of wells already placed is 5, and the remaining well count is 1. More specifically, for example, the first layer has 1 well placed, and the second layer has 4 wells placed. If the judgment coefficient (judge) is greater than 0, meaning the remaining well count (remain) satisfies the minimum number of wells required to reach the layer to be placed, then the first type of well placement data (data_1) is determined as the first well placement data, i.e., the initial well placement data. Based on the distribution characteristics of the horizontal wells corresponding to the second type of well placement data (data_2): the finished well layer count is 2, the layer to be placed is 1, the number of wells already placed is 6, and the remaining well count (remain) is 0. More specifically, for example... If the number of wells deployed in the first layer is 1 and the number of wells deployed in the second layer is 5, and the judgment coefficient is 0, then the remaining number of wells deployed does not meet the minimum number of wells required for the number of layers to be deployed. Therefore, the search stops and returns to step S203 to verify the number of layers to be deployed and the remaining number of wells for the next well deployment data. This process continues until verification is complete, resulting in 10 initial well deployment data sets as shown in Table 1. For example, the distribution characteristics of the horizontal wells corresponding to the next well deployment data set, data_3, are as follows: the number of completed well deployment layers is 1, the number of layers to be deployed is 2, the number of wells deployed is 2, and the remaining number of wells deployed is 4. More specifically, for example, if the number of wells deployed in the first layer is 2, and the judgment coefficient is greater than 0, then the remaining number of wells deployed satisfies the minimum number of wells required for the number of layers to be deployed. Therefore, well deployment data set data_3 is also the first well deployment data set, i.e., the initial well deployment data set.

[0110] In this embodiment, based on the enumeration method, a pruning operation is introduced. By judging whether the remaining number of wells meets the minimum number of wells required for the number of well layers to be laid, the calculation efficiency is improved, the initial well data is obtained quickly, and the waste of computing resources is avoided.

[0111] Step S207: Based on the initial well layout data and the initial operation link, a candidate operation link is obtained. The initial well layout data characterizes the distribution characteristics of the horizontal wells preset for the target reservoir, and the candidate operation link is an operation link that is suitable for the initial well layout data.

[0112] Step S208: Based on the three-dimensional geostress model and the candidate operation links, obtain the target well placement data.

[0113] Step S209: Based on the three-dimensional geostress model and target well layout data, the target operation sequence is obtained. The target operation sequence is used to characterize the fracturing order of each horizontal well corresponding to the target well layout data in order to achieve the maximum estimated production of the target reservoir.

[0114] In this embodiment, the implementation of step S201 is the same as that in this application. Figure 2 The implementation of step S101 in the illustrated embodiment is the same, and the implementation of steps S207-S208 is the same as that in this application. Figure 2 The implementation of steps S1021-S1022 in the illustrated embodiment is the same, and the implementation of step S209 is the same as in this application. Figure 2 The implementation of step S103 in the illustrated embodiment is the same, and will not be described in detail here.

[0115] Figure 12 This is a schematic diagram of the structure of a horizontal well fracturing link optimization device provided in one embodiment of this application, as shown below. Figure 12 As shown, the horizontal well fracturing link optimization device 3 provided in this embodiment includes:

[0116] Processing module 31 is used to obtain a three-dimensional geostress model based on the three-dimensional geological model and the one-dimensional geostress model. The three-dimensional geostress model is used to determine the stress characteristics of the reservoir.

[0117] Processing module 31 is also used to obtain target well placement data based on the three-dimensional geostress model. The target well placement data characterizes the distribution characteristics of horizontal wells determined based on the stimulation volume of the target reservoir.

[0118] The determination module 32 is used to obtain the target operation sequence based on the three-dimensional geostress model and the target well layout data. The target operation sequence is used to characterize the fracturing sequence of each horizontal well corresponding to the target well layout data in order to achieve the maximum estimated production of the target reservoir.

[0119] In one possible implementation, when the processing module 31 obtains the target well placement data based on the three-dimensional geostress model, it is specifically used to: obtain the candidate operation links based on the initial well placement data and the initial operation links, wherein the initial well placement data characterizes the distribution characteristics of the horizontal wells preset for the target reservoir, and the candidate operation links are operation links applicable to the initial well placement data; and obtain the target well placement data based on the three-dimensional geostress model and the candidate operation links.

[0120] In one possible implementation, when the processing module 31 obtains the target well placement data based on the three-dimensional geostress model and the candidate operation links, it is specifically used to: obtain the corresponding target volume estimation model based on the three-dimensional geostress model and the candidate operation links, the volume estimation model being used to estimate the stimulation volume of the target reservoir based on the three-dimensional geostress model and the candidate operation links; and obtain the target well placement data based on the target volume estimation model.

[0121] In one possible implementation, when determining the target operation link based on the three-dimensional geostress model and the target well placement data, the determining module 32 is specifically used to: obtain the corresponding target production prediction model based on the three-dimensional geostress model and the target well placement data, the production prediction model being used to predict the production of the target reservoir based on the three-dimensional geostress model and the target well placement data; and obtain the target operation link based on the target production prediction model.

[0122] In one possible implementation, the initial well placement data includes at least one first well placement data. The processing module 31 is further configured to: obtain the initial well placement layer number and the initial well placement number; obtain the number of well placement layers to be placed based on the initial well placement layer number and the number of completed well placement layers; obtain the remaining well placement number based on the initial well placement number and the number of wells already placed; if the remaining well placement number meets the minimum well placement number required for the number of well placement layers to be placed, then the first well placement data is obtained; if the remaining well placement number does not meet the minimum well placement number required for the number of well placement layers to be placed, then the search is stopped, and the process is returned to verify the number of well placement layers to be placed and the remaining well placement number corresponding to the next well placement data, until the verification is completed.

[0123] In one possible implementation, before the processing module 31 obtains the three-dimensional geostress model based on the three-dimensional geological model and the one-dimensional geostress model, it is specifically used to: acquire target block information, which characterizes the geological features of the target block; and obtain the three-dimensional geological model and the one-dimensional geostress model based on the target block information.

[0124] In one possible implementation, the processing module 31 is further configured to: obtain updated target block information based on real-time logging data of the target block; and obtain updated three-dimensional geological model and one-dimensional geostress model based on the updated target block information.

[0125] The processing module 31 and the determining module 32 are connected sequentially. The horizontal well fracturing link optimization device 3 provided in this embodiment can perform actions such as… Figures 2-11 The technical solutions of any of the method embodiments shown are similar in implementation principle and technical effect, and will not be described again here.

[0126] Figure 13 A schematic diagram of an electronic device provided in one embodiment of this application, as shown below. Figure 13 As shown, the electronic device 4 provided in this embodiment includes: a processor 41, and a memory 42 communicatively connected to the processor 41.

[0127] Among them, memory 42 stores computer-executed instructions;

[0128] The processor 41 executes computer execution instructions stored in the memory 42 to implement this application. Figures 2-11 The horizontal well fracturing link optimization method provided in any of the corresponding embodiments.

[0129] The memory 42 and the processor 41 are connected via a bus 43.

[0130] For relevant instructions, please refer to the corresponding text. Figures 2-11 The relevant descriptions and effects of the steps in the corresponding embodiments are understood, and will not be elaborated on here.

[0131] One embodiment of this application provides a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, are used to implement this application. Figures 2-11 The horizontal well fracturing link optimization method provided in any of the corresponding embodiments.

[0132] The computer-readable storage medium may be ROM, random access memory (RAM), CD-ROM, magnetic tape, floppy disk, and optical data storage device, etc.

[0133] One embodiment of this application provides a computer program product, including a computer program that, when executed by a processor, implements this application. Figures 2-11 The horizontal well fracturing link optimization method provided in any of the corresponding embodiments.

[0134] Figure 14 This is a block diagram illustrating an exemplary embodiment of the present application of a terminal device 800, which may be a mobile phone, computer, digital broadcasting terminal, messaging device, game console, tablet device, medical device, fitness device, personal digital assistant, etc.

[0135] The terminal device 800 may include one or more of the following components: processing component 802, memory 804, power supply component 806, multimedia component 808, audio component 810, input / output (I / O) interface 812, sensor component 814, and communication component 816.

[0136] Processing component 802 typically controls the overall operation of terminal device 800, such as operations associated with display, telephone calls, data communication, camera operation, and recording. Processing component 802 may include one or more processors 820 to execute instructions to complete all or part of the steps of the methods described above. Furthermore, processing component 802 may include one or more modules to facilitate interaction between processing component 802 and other components. For example, processing component 802 may include a multimedia module to facilitate interaction between multimedia component 808 and processing component 802.

[0137] Memory 804 is configured to store various types of data to support operation on terminal device 800. Examples of this data include instructions for any application or method operating on terminal device 800, contact data, phonebook data, messages, pictures, videos, etc. Memory 804 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk.

[0138] Power supply component 806 provides power to various components of terminal device 800. Power supply component 806 may include a power management system, one or more power supplies, and other components associated with generating, managing, and distributing power to terminal device 800.

[0139] Multimedia component 808 includes a screen that provides an output interface between terminal device 800 and the user. In some embodiments, the screen may include a liquid crystal display (LCD) and a touch panel (TP). If the screen includes a touch panel, the screen may be implemented as a touchscreen to receive input signals from the user. The touch panel includes one or more touch sensors to sense touches, swipes, and gestures on the touch panel. The touch sensors may sense not only the boundaries of touch or swipe actions but also the duration and pressure associated with the touch or swipe operation. In some embodiments, multimedia component 808 includes a front-facing camera and / or a rear-facing camera. When terminal device 800 is in an operating mode, such as a shooting mode or video mode, the front-facing camera and / or rear-facing camera may receive external multimedia data. Each front-facing camera and rear-facing camera may be a fixed optical lens system or have focal length and optical zoom capabilities.

[0140] Audio component 810 is configured to output and / or input audio signals. For example, audio component 810 includes a microphone (MIC) configured to receive external audio signals when terminal device 800 is in an operating mode, such as call mode, recording mode, and voice recognition mode. The received audio signals may be further stored in memory 804 or transmitted via communication component 816. In some embodiments, audio component 810 also includes a speaker for outputting audio signals.

[0141] I / O interface 812 provides an interface between processing component 802 and peripheral interface modules, such as keyboards, click wheels, buttons, etc. These buttons may include, but are not limited to, home buttons, volume buttons, power buttons, and lock buttons.

[0142] Sensor assembly 814 includes one or more sensors for providing status assessments of various aspects of terminal device 800. For example, sensor assembly 814 can detect the on / off state of terminal device 800, the relative positioning of components such as the display and keypad of terminal device 800, changes in the position of terminal device 800 or a component of terminal device 800, the presence or absence of user contact with terminal device 800, the orientation or acceleration / deceleration of terminal device 800, and temperature changes of terminal device 800. Sensor assembly 814 may include a proximity sensor configured to detect the presence of nearby objects without any physical contact. Sensor assembly 814 may also include a light sensor, such as a CMOS or CCD image sensor, for use in imaging applications. In some embodiments, sensor assembly 814 may also include an accelerometer, a gyroscope, a magnetometer, a pressure sensor, or a temperature sensor.

[0143] Communication component 816 is configured to facilitate wired or wireless communication between terminal device 800 and other devices. Terminal device 800 can access wireless networks based on communication standards, such as WiFi, 3G, 4G, 5G, or other standard communication networks, or combinations thereof. In one exemplary embodiment, communication component 816 receives broadcast signals or broadcast-related information from an external broadcast management system via a broadcast channel. In one exemplary embodiment, communication component 816 also includes a near-field communication (NFC) module to facilitate short-range communication. For example, the NFC module may be implemented based on radio frequency identification (RFID) technology, Infrared Data Association (IrDA) technology, ultra-wideband (UWB) technology, Bluetooth (BT) technology, and other technologies.

[0144] In an exemplary embodiment, the terminal device 800 may be implemented by one or more application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field-programmable gate arrays (FPGAs), controllers, microcontrollers, microprocessors, or other electronic components to perform the functions described in this application. Figures 2-11 The method provided in any of the corresponding embodiments.

[0145] In an exemplary embodiment, a non-transitory computer-readable storage medium including instructions is also provided, such as a memory 804 including instructions, which can be executed by a processor 820 of a terminal device 800 to perform the above-described method. For example, the non-transitory computer-readable storage medium may be a ROM, random access memory (RAM), CD-ROM, magnetic tape, floppy disk, and optical data storage device, etc.

[0146] This application also provides a non-transitory computer-readable storage medium, which, when the instructions in the storage medium are executed by the processor of a terminal device, enables the terminal device 800 to perform the above-described embodiments of this application. Figures 2-11 The method provided in any of the corresponding embodiments.

[0147] In the several embodiments provided in this application, it should be understood that the disclosed apparatus and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of modules is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple modules or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or modules may be electrical, mechanical, or other forms.

[0148] Other embodiments of this application will readily occur to those skilled in the art upon consideration of the specification and practice of the application disclosed herein. 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 techniques in the art not disclosed herein. The specification and examples are to be considered exemplary only, and the true scope and spirit of this application are indicated by the following claims.

[0149] It should be understood that this application is not limited to the precise structure described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of this application is limited only by the appended claims.

Claims

1. A method for optimizing the fracturing process in horizontal wells, characterized in that, The method includes: Based on the three-dimensional geological model and the one-dimensional geostress model, a three-dimensional geostress model is obtained, which is used to determine the stress characteristics of the reservoir. Based on the initial well placement data and the initial operation link, candidate operation links are obtained, wherein the initial well placement data characterizes the distribution characteristics of horizontal wells preset for the target reservoir, and the candidate operation links are operation links applicable to the initial well placement data; Based on the three-dimensional geostress model and the candidate operation links, a corresponding target volume estimation model is obtained. The volume estimation model is used to estimate the stimulation volume of the target reservoir based on the three-dimensional geostress model and the candidate operation links. Based on the target volume prediction model, target well placement data is obtained, which characterizes the distribution features of horizontal wells determined according to the stimulation volume of the target reservoir. Based on the three-dimensional geostress model and the target well placement data, a corresponding target production prediction model is obtained. The production prediction model is used to predict the production of the target reservoir based on the three-dimensional geostress model and the target well placement data. Based on the target production prediction model, a target operation sequence is obtained. The target operation sequence is used to characterize the fracturing order of each horizontal well corresponding to the target well layout data in order to achieve the maximum predicted production of the target reservoir.

2. The method according to claim 1, characterized in that, The initial well placement data includes at least one first well placement data point, and also includes: Obtain the initial number of well layers and the initial number of wells; Based on the initial number of well placement layers and the number of completed well placement layers, the number of well placement layers to be determined is obtained; Based on the initial number of wells and the number of wells already deployed, the remaining number of wells is obtained; If the remaining number of wells meets the minimum number of wells required for the number of well layers to be laid out, then the first well layout data is obtained; If the remaining number of wells does not meet the minimum number of wells required for the number of wells to be placed, the search stops, and the process returns to verify the number of wells to be placed and the remaining number of wells for the next well placement data until the verification is completed.

3. The method according to claim 1, characterized in that, Before obtaining the three-dimensional geostress model based on the three-dimensional geological model and the one-dimensional geostress model, the following steps are included: Obtain target block information, wherein the target block information characterizes the geological features of the target block; Based on the target block information, the three-dimensional geological model and the one-dimensional geostress model are obtained.

4. The method according to claim 3, characterized in that, Also includes: Based on the real-time logging data of the target block, the updated target block information is obtained; Based on the updated target block information, an updated three-dimensional geological model and a one-dimensional geostress model are obtained.

5. A horizontal well fracturing link optimization device, characterized in that, include: The processing module is used to obtain a three-dimensional geostress model based on a three-dimensional geological model and a one-dimensional geostress model. The three-dimensional geostress model is used to determine the stress characteristics of the reservoir. The processing module is further configured to: obtain candidate operation links based on initial well placement data and initial operation links, wherein the initial well placement data characterizes the distribution characteristics of horizontal wells preset for the target reservoir, and the candidate operation links are operation links applicable to the initial well placement data; obtain a corresponding target volume estimation model based on the three-dimensional geostress model and the candidate operation links, wherein the volume estimation model is used to estimate the stimulation volume of the target reservoir based on the three-dimensional geostress model and the candidate operation links; and obtain target well placement data based on the target volume estimation model, wherein the target well placement data characterizes the distribution characteristics of horizontal wells determined based on the stimulation volume of the target reservoir. The determination module is used to obtain a corresponding target production prediction model based on the three-dimensional geostress model and the target well layout data. The production prediction model is used to predict the production of the target reservoir based on the three-dimensional geostress model and the target well layout data. Based on the target production prediction model, a target operation sequence is obtained. The target operation sequence is used to characterize the fracturing order of each horizontal well corresponding to the target well layout data in order to achieve the maximum predicted production of the target reservoir.

6. An electronic device, 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 4.

7. 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 horizontal well fracturing link optimization method as described in any one of claims 1 to 4.

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