Coiled tubing mechanically controlled dual packer drag fracturing device and fracturing method

Abstract

The present application relates to the technical field of oilfield reservoir reconstruction, and particularly relates to a coiled tubing mechanical control type double-seal drag fracturing equipment and a fracturing method. The method comprises the following steps: taking a reference layer section as a reference, analyzing temperature changes of each sampling position in a target layer section in a target period to obtain a plurality of temperature difference data, and performing local peak point detection on the temperature difference data to determine a plurality of temperature difference local peak data; then, in the plurality of temperature difference local peak data, analyzing a peak height, a peak width and a fracturing balance time of each temperature difference local peak data to determine a probability that each temperature difference local peak data indicates a main fracture, and then identifying a target sampling position indicating the main fracture according to the probability; finally, determining whether to stop fracturing operation of the target layer section according to temperature changes of a plurality of target sampling positions and a number of the plurality of target sampling positions. The present application can output a fracturing operation detection result with high timeliness, avoid unnecessary consumption of fracturing fluid, and reduce the exploitation cost of low-permeability and tight reservoirs.

Description

Technical Field

[0001] This invention relates to the technical field of oilfield reservoir stimulation, specifically to a coiled tubing mechanically controlled double-seal drag fracturing device and fracturing method. Background Technology

[0002] Applications have revealed that due to the stress distribution in low-permeability tight reservoirs and the mutual interference of fracture networks, common oil well monitoring methods such as tracers, microseismic analysis, and pressure curve analysis have a lag in sensing the propagation of multiple fracture clusters during fracturing. This can easily lead to excessive injection of fracturing fluid, resulting in unnecessary consumption of fracturing fluid and increased extraction costs.

[0003] In other words, the timeliness of existing technologies in monitoring the fracturing effect of low-permeability tight reservoirs is relatively low. Summary of the Invention

[0004] The purpose of this invention is to provide a coiled tubing mechanically controlled double-seal drag fracturing device and fracturing method to solve the technical problem of low timeliness in monitoring the fracturing effect of low-permeability tight reservoirs in the prior art.

[0005] In a first aspect, one embodiment of the present invention provides a coiled tubing mechanically controlled dual-seal drag fracturing method, the method comprising:

[0006] Using the benchmark layer as a reference, the temperature changes at each sampling location in the target layer within the target period are analyzed to obtain multiple temperature difference data. The benchmark layer and the target layer are adjacent and located in the same depth range. The multiple temperature difference data correspond one-to-one with multiple sampling locations in the target layer.

[0007] Local peak detection is performed on the multiple temperature difference data to determine multiple local temperature difference peak data;

[0008] In the multiple local temperature difference peak data, the peak feature information of each local temperature difference peak data is analyzed to obtain the main fracture index of each local temperature difference peak data. The peak feature information includes a first feature indicating the peak height of the corresponding local temperature difference peak data, a second feature indicating the peak width of the corresponding local temperature difference peak data, and a third feature indicating the fracturing balance time of the corresponding local temperature difference peak data. The main fracture index is used to characterize the probability that the corresponding local temperature difference peak data indicates a main fracture.

[0009] Based on the main fracture index of each local temperature difference peak data, the target sampling location indicating the main fracture is identified among all sampling locations included in the target segment.

[0010] The target operation result is determined based on the temperature changes at multiple target sampling locations within the target period and the number of multiple target sampling locations. The target operation result is used to indicate whether the fracturing operation in the target section has been stopped.

[0011] In some embodiments, the step of analyzing the temperature changes at each sampling location within the target segment during the target period, using a reference segment as a reference, to obtain multiple temperature difference data includes:

[0012] At the end of the target period, the average temperature value of all sampling locations within the reference layer is calculated to obtain the reference temperature;

[0013] Within the target period, the differences between the average temperature at multiple sampling locations in the target layer and the reference temperature are analyzed to obtain multiple temperature difference data.

[0014] In some embodiments, the step of obtaining the third feature of each temperature difference local peak data in a plurality of temperature difference local peak data includes:

[0015] In the multiple local temperature difference peak data, the temperature change after each temperature sampling time within the target period is analyzed at the sampling position indicated by each local temperature difference peak data, and multiple fracturing balance indices associated with each local temperature difference peak data are determined. Among them, the multiple fracturing balance indices associated with each local temperature difference peak data correspond one-to-one with the multiple temperature sampling times in the target period.

[0016] Among the multiple fracturing equilibrium indices associated with each local temperature difference peak data, the temperature sampling time corresponding to the largest fracturing equilibrium index is determined as the corresponding fracturing equilibrium time, so as to obtain the fracturing equilibrium time corresponding to each local temperature difference peak data.

[0017] The third characteristic of each temperature difference local peak data is determined based on the first time difference between the fracturing equilibrium time corresponding to each local peak data and the start time of the target cycle.

[0018] In some embodiments, the step of analyzing the temperature change after each temperature sampling time within a target period at the sampling location indicated by each local temperature difference peak data, and determining multiple fracturing balance indices associated with each local temperature difference peak data, includes:

[0019] Multiple backward temperature sequences associated with each local peak temperature difference are obtained. Each backward temperature sequence corresponds one-to-one with multiple temperature sampling times within the target period. The backward temperature sequence includes multiple temperature values ​​collected from the corresponding sampling position from the corresponding temperature sampling time to the end of the target period.

[0020] In the multiple local temperature difference peak data, the degree of dispersion of each backward temperature sequence associated with each local temperature difference peak data is analyzed to obtain multiple temperature dispersion coefficients associated with each local temperature difference peak data.

[0021] At multiple temperature sampling moments within the target period, the second time difference between each temperature sampling moment and the end of the target period is analyzed to determine the time-domain coefficient of each temperature sampling moment. The time-domain coefficient and the corresponding second time difference are negatively correlated.

[0022] Among the multiple temperature dispersion coefficients associated with each local temperature difference peak data, each fracturing balance index associated with each local temperature difference peak data is determined based on each temperature dispersion coefficient associated with each local temperature difference peak data and its corresponding time domain coefficient.

[0023] In some embodiments, the main crack index is positively correlated with the first feature, the main crack index is positively correlated with the second feature, and the main crack index is positively correlated with the third feature.

[0024] In some embodiments, the step of identifying a target sampling location indicating a main fracture among all sampling locations included in the target segment based on the main fracture index of each local temperature difference peak data includes:

[0025] The average value of the main crack index of the multiple local temperature difference peak data is calculated to obtain the index mean.

[0026] Among the multiple local temperature difference peak data, the sampling location indicated by the local temperature difference peak data where the main crack index is greater than the average value of the index is determined as the target sampling location.

[0027] In some embodiments, the step of determining the target operation result based on the temperature changes at multiple target sampling locations within a target period and the number of multiple target sampling locations includes:

[0028] The temperature rise at each target sampling location after the corresponding fracturing equilibrium moment is analyzed to obtain the fracture saturation index at each target sampling location;

[0029] The calculation weight of each target sampling location is determined based on the fracturing balance index corresponding to each target sampling location.

[0030] Based on the calculation weight of each target sampling location, the crack saturation index of multiple target sampling locations is weighted and calculated to obtain the pumping saturation index;

[0031] The target operation result is determined based on the pump saturation index and the number of multiple target sampling locations.

[0032] In some embodiments, the step of determining the calculation weight of each target sampling location based on the fracturing balance index corresponding to each target sampling location includes:

[0033] Calculate the sum of the fracturing balance indices corresponding to multiple target sampling locations to obtain the cumulative index value;

[0034] Calculate the ratio of the fracturing balance index to the cumulative index value corresponding to each target sampling location to obtain the calculation weight of each target sampling location.

[0035] In some embodiments, the output probability of the first operation result is positively correlated with the number of multiple target sampling locations, and the output probability of the first operation result is positively correlated with the pump saturation index, wherein the first operation result is a target operation result indicating the cessation of fracturing operations in the target segment.

[0036] Secondly, another embodiment of the present invention provides a coiled tubing mechanically controlled dual-seal drag fracturing device, the device comprising:

[0037] The data acquisition module is used to analyze the temperature changes at each sampling location in the target layer within the target period, with the reference layer as a reference, and obtain multiple temperature difference data. The reference layer and the target layer are adjacent and in the same depth range, and the multiple temperature difference data correspond one-to-one with multiple sampling locations in the target layer.

[0038] The peak detection module is used to perform local peak detection on the multiple temperature difference data to determine the multiple local peak data of temperature difference.

[0039] The feature analysis module is used to analyze the peak feature information of each local temperature difference peak data in the multiple local temperature difference peak data to obtain the main fracture index of each local temperature difference peak data. The peak feature information includes a first feature indicating the peak height of the corresponding local temperature difference peak data, a second feature indicating the peak width of the corresponding local temperature difference peak data, and a third feature indicating the fracturing balance time of the corresponding local temperature difference peak data. The main fracture index is used to characterize the probability that the corresponding local temperature difference peak data indicates a main fracture.

[0040] The main fracture identification module is used to identify the target sampling location indicating the main fracture among all sampling locations included in the target layer based on the main fracture index of each local temperature difference peak data.

[0041] The operation result detection module is used to determine the target operation result based on the temperature change of multiple target sampling locations within the target period and the number of multiple target sampling locations. The target operation result is used to indicate whether the fracturing operation in the target section has been stopped.

[0042] Thirdly, in another embodiment of the present invention, an electronic device is provided, including a processor, a memory, and a computer program stored in the memory and executable on the processor, wherein the computer program, when executed by the processor, implements the steps of the method described in the first aspect.

[0043] Fourthly, in another embodiment of the present invention, a computer-readable storage medium is provided, on which a computer program is stored, which, when executed by a processor, implements the steps of the method described in the first aspect.

[0044] The present invention has the following beneficial effects:

[0045] This invention uses adjacent layers within the same depth range as a reference to analyze temperature changes at various points in the target layer undergoing fracturing operations within the target period. This yields multiple temperature difference data points to accurately quantify the magnitude of temperature changes at each point in the target layer. Then, through local peak detection, multiple local temperature difference peaks corresponding to the fracture region are identified from these data points. Further analysis of the peak height, peak width, and time taken to reach fracturing equilibrium at each local peak data point determines the probability that the sampling location indicated by each local peak data point corresponds to the main fracture region. Based on this, several target sampling locations corresponding to the main fracture region are identified from the multiple sampling locations in the corresponding fracture region. By combining the temperature changes at each target sampling location with the total number of target sampling locations, it is determined whether fracturing operations in the target layer should be stopped. This enables timely monitoring of the fracturing effect in low-permeability tight reservoirs. Especially when the fracturing effect in the target layer meets expectations, the injection of fracturing fluid can be stopped promptly to avoid unnecessary consumption of fracturing fluid and reduce the exploitation cost of low-permeability tight reservoirs. Attached Figure Description

[0046] To more clearly illustrate the technical solutions and advantages in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0047] Figure 1 This is a schematic diagram of the structure of a coiled tubing mechanically controlled double-seal drag fracturing construction equipment provided in an embodiment of the present invention;

[0048] Figure 2 This is a schematic flowchart of a coiled tubing mechanically controlled double-seal drag fracturing method provided in an embodiment of the present invention;

[0049] Figure 3 This is a schematic diagram of the structure of a coiled tubing mechanically controlled double-seal drag fracturing device provided in an embodiment of the present invention;

[0050] Figure 4 This is a schematic diagram of an electronic device provided in an embodiment of the present invention. Detailed Implementation

[0051] To further illustrate the technical means and effects adopted by the present invention to achieve its intended purpose, the following, in conjunction with the accompanying drawings and preferred embodiments, details the specific implementation, structure, features, and effects of a coiled tubing mechanically controlled double-seal drag fracturing device and fracturing method proposed according to the present invention. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. Furthermore, specific features, structures, or characteristics in one or more embodiments can be combined in any suitable form.

[0052] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains.

[0053] The following description, in conjunction with the accompanying drawings, details the specific scheme of the coiled tubing mechanically controlled double-seal drag fracturing equipment and fracturing method provided by the present invention.

[0054] For low-permeability tight reservoirs, if the dual-seal drag technology is used for staged fracturing, the corresponding packers need to be set and unsealed multiple times. After a certain stage of fracturing, a pressure difference will appear between the upper and lower parts of the packer, which will interfere with the unsealing operation of the packer. In severe cases, it may even lead to damage to the device and cause the construction to be interrupted.

[0055] Based on this, embodiments of the present invention provide a coiled tubing mechanically controlled double-seal drag fracturing construction device, such as... Figure 1 As shown, Figure 1 Number 1 indicates continuous tubing, number 2 indicates safety joint, number 3 indicates pressure relief valve, number 4 indicates hydraulic anchor, number 5 indicates top packer, number 6 indicates sandblaster, number 7 indicates balance valve, number 8 indicates bottom packer, and number 9 indicates positioning elastic stabilizer.

[0056] The safety joint is fixed to the upper and lower ends of the continuous tubing and the upper end of the pressure relief valve by threads, respectively. The hydraulic anchor is fixed to the lower end of the pressure relief valve and the upper end of the top packer by threads, respectively. The sandblaster is fixed to the lower end of the top packer and the upper end of the balance valve by threads, respectively. The top and lower ends of the top packer are fixed to the lower end of the balance valve and the upper end of the positioning elastic stabilizer by threads, respectively.

[0057] The top packer and the bottom packer are used in combination and in conjunction, and both are set and released mechanically by lifting and lowering the tubing string.

[0058] The top packer is equipped with a pressure relief valve with a pressure relief function. The opening and closing of the pressure relief valve is controlled by mechanically raising and lowering the tubing column.

[0059] The bottom packer is equipped with a pressure relief valve at its upper end. The opening and closing of the pressure relief valve is controlled mechanically by raising and lowering the tubing column.

[0060] When using the above-mentioned coiled tubing mechanically controlled double-sealed drag fracturing equipment, the coiled tubing must first be lowered to the predetermined position of the horizontal well in the low-permeability tight reservoir of the oilfield. During the tubing string lowering process, the positioning elastic stabilizer is used to achieve accurate positioning. Then, by raising and lowering the tubing string, the bottom packer and the top packer are set in sequence. At the same time, the pressure relief valve and the balance valve are closed. Afterwards, fracturing fluid is pumped through the coiled tubing using a surface pump truck. Under the action of the oil-casing pressure difference, the hydraulic anchor is anchored to the inner wall of the casing. The sandblasting device serves as a communication channel with the formation to verify the sealing of the top packer and the bottom packer.

[0061] After that, the horizontal well section of the low-permeability tight reservoir in the oilfield between the top packer and the bottom packer was taken as the target section for fracturing operations. There are multiple clusters of fractures in the target section. During the fracturing operation, fracturing fluid carrying proppant was sprayed out through the nozzle of the sand jetting device and entered the target section to carry out fracturing operations on the multiple clusters of fractures in the target section.

[0062] After fracturing is completed, the tubing string is pulled up, the pressure relief valve is opened, and a connection between the oil and casing is established. The oil and casing pressures are balanced, and the hydraulic anchor is not anchored to the casing. The tubing string is pulled up further, the top packer is released, and the balance valve 7 is opened at the same time. The oil and casing pressures are balanced again, the bottom packer is released, and the tubing string is dragged up to the next horizontal well fracturing section (which can be understood as a new target section) through precise positioning by the positioning elastic centralizer. The above process is repeated until all sections of the low-permeability tight horizontal well (also known as a low-permeability tight reservoir) have been fracturing.

[0063] In the above process, the use of a balancing valve can balance the pressure difference between the packer and the surrounding area after the packer has completed fracturing of a certain section, ensuring the smooth execution of subsequent packer unsealing operations and guaranteeing the continuity of construction in low-permeability tight horizontal wells.

[0064] However, it should be noted that during fracturing operations on multiple clusters of fractures in the target layer, it is difficult to accurately monitor the fracturing effect of the multiple clusters of fractures in the target layer based on commonly used oil well monitoring methods such as tracers, microseismic analysis, and pressure curve analysis, which can easily lead to unnecessary waste of fracturing fluid.

[0065] Based on this, the present invention further provides a coiled tubing mechanically controlled double-seal drag fracturing method to adapt to the aforementioned coiled tubing mechanically controlled double-seal drag fracturing construction equipment, thereby minimizing unnecessary consumption of fracturing fluid, specifically as follows: Figure 2 As shown, the method includes:

[0066] Step S1: Using the benchmark layer as a reference, analyze the temperature changes at each sampling location in the target layer within the target period to obtain multiple temperature difference data.

[0067] Among them, the reference layer and the target layer are adjacent and in the same depth range, and multiple temperature difference data correspond one-to-one with multiple sampling locations in the target layer.

[0068] The aforementioned target segment can be understood as the segment in which fracturing operations are being carried out in multiple segments (different segments are in different depth ranges) included in a low-permeability tight horizontal well (i.e., the aforementioned target segment).

[0069] In application, if the boundary between a low-permeability tight horizontal well and a vertical well is set as the origin in the horizontal direction, and the distance between each location and the origin in the horizontal direction is defined as the coordinate value of each location in the horizontal direction, then the coordinate value range corresponding to the target layer is: The coordinate range corresponding to the benchmark segment is: .

[0070] In this invention, a distributed optical fiber system (DTS) is installed outside the sleeve to sense temperature data at various locations in the target layer and at various locations in the reference layer. The distributed optical fiber system is uniformly distributed with multiple sampling positions along the horizontal direction, with an interval of 0.25 meters between adjacent sampling positions. The distributed optical fiber system performs periodic sampling, with a time interval of 30 seconds between two adjacent sampling operations.

[0071] In practical applications, other devices with temperature detection functions can also be selected to periodically collect temperature data at various locations in the target layer and at various locations in the reference layer.

[0072] In this invention, fracturing is carried out intermittently on multiple clusters of fractures in the target layer. After each set construction time (i.e., one construction cycle), the fracturing effect of the target layer is tested, and the decision to continue the next construction is made based on the test results. The aforementioned target cycle can be understood as any one of the multiple construction cycles associated with the target layer.

[0073] The duration of the above-mentioned construction cycle can be between 2 minutes and 15 minutes. The shorter the construction cycle, the more timely the monitoring of the fracturing effect of the target layer. In this invention, the duration of the construction cycle is set to 5 minutes based on experience.

[0074] Specifically, the steps of analyzing the temperature changes at each sampling location within the target segment during the target period, using a baseline segment as a reference, to obtain multiple temperature difference data, include:

[0075] At the end of the target period, the average temperature value of all sampling locations within the reference layer is calculated to obtain the reference temperature;

[0076] Within the target period, the differences between the average temperature at multiple sampling locations in the target layer and the reference temperature are analyzed to obtain multiple temperature difference data.

[0077] During the fracturing operation of multiple clusters of fractures in the target section, low-temperature fracturing fluid (compared to the original temperature of the reservoir) continuously enters the fractures and is filtered out from the fractures into the reservoir. During its flow, heat conduction and heat convection effects occur, which continuously cool the wellbore, fractures and surrounding formations. Therefore, the area where the fractures in the target section are located will be in an exothermic state.

[0078] In the above settings, by obtaining the reference temperature, a suitable temperature threshold is dynamically determined based on the actual temperature conditions exhibited by the target layer within the target period. This effectively ensures the accuracy of the temperature difference data obtained in subsequent calculations.

[0079] Analyzing the difference between the average temperature at the sampling location and the reference temperature can effectively suppress the interference of extreme noise. Based on the overall temperature trend at each sampling location, the temperature drop at each sampling location within the target period can be accurately quantified, further ensuring the accuracy of the calculated temperature difference data.

[0080] In this invention, the average value of multiple temperature values ​​at each sampling location within the target period is determined as the corresponding average temperature value, and the difference between the reference temperature and the average temperature value at each sampling location is determined as the corresponding temperature difference data.

[0081] Step S2: Perform local peak detection on the multiple temperature difference data to determine multiple local peak data of temperature difference.

[0082] As mentioned earlier, the larger the temperature difference data, the more significant the temperature drop at the corresponding sampling location, which means that the probability of the corresponding sampling location indicating the location / region of a crack is greater.

[0083] The present invention, through the measure of local peak detection, can initially identify sampling locations with a high probability of indicating crack areas from multiple sampling locations included in the target layer, so as to carry out targeted analysis and processing in the future. This can reduce the amount of data to be processed in the future while avoiding interference from sampling locations that are not crack locations, and improve the overall processing efficiency of the solution.

[0084] The aforementioned local peak detection aims to identify the temperature difference data with corresponding local maxima (the value of the corresponding temperature difference data is greater than the value of the previous temperature difference data and greater than the value of the next temperature difference data) from multiple temperature difference data (arranged in order of horizontal coordinate values) and determine them as local temperature difference peak data.

[0085] In one example, the present invention uses the AMPD peak finding algorithm to complete the above-mentioned local peak detection operation.

[0086] Step S3: Analyze the peak characteristic information of each temperature difference local peak data in the multiple temperature difference local peak data to obtain the main crack index of each temperature difference local peak data.

[0087] Among them, the peak feature information includes a first feature indicating the peak height of the corresponding local temperature difference peak data, a second feature indicating the peak width of the corresponding local temperature difference peak data, and a third feature indicating the fracturing balance time of the corresponding local temperature difference peak data. The main fracture index is used to characterize the probability that the corresponding local temperature difference peak data indicates a main fracture (a large-volume fracture designed to provide an efficient channel for oil and gas to flow from the far end of the reservoir to the wellbore).

[0088] It should be noted that in the fracturing operation, the concept opposite to the main fracture is the secondary fracture (small-volume fracture, which usually cannot provide a channel for oil and gas to flow from the far end of the reservoir to the wellbore, or can only provide an inefficient channel for oil and gas to flow from the far end of the reservoir to the wellbore), such as branch fractures and micro fractures.

[0089] The primary fracture can hold more fracturing fluid (compared to the secondary fracture) during fracturing operations, resulting in a more significant temperature drop and a longer duration of the temperature drop process.

[0090] The value of the first feature mentioned above is specifically the value of the local peak data of the corresponding temperature difference, and the value of the second feature mentioned above is specifically the half-width at half-maximum of the local peak data of the corresponding temperature difference (referring to the length of the line segment formed by extending to both sides and first intersecting with the data curve in the data curve corresponding to multiple temperature difference data).

[0091] In this invention, the fracturing equilibrium time should be understood as the time from the start of the target cycle until the corresponding fracture is fully filled with fracturing fluid and the temperature drops sharply to reach equilibrium (the temperature drops slowly, remains unchanged, or shows a slow upward trend).

[0092] The larger the main crack index, the higher the probability that the corresponding local temperature difference peak data indicates a main crack.

[0093] It should be understood that the main crack index is positively correlated with the first feature, the main crack index is positively correlated with the second feature, and the main crack index is positively correlated with the third feature.

[0094] In this invention, the positive correlation trend should be understood as follows: for two related values, as one value increases, the probability of the other value increasing will also increase accordingly.

[0095] The higher the value of the local temperature difference peak data, the greater the temperature drop at the corresponding sampling location, and the more fracturing fluid the corresponding sampling location is in contact with. Therefore, the higher the probability that the corresponding sampling location indicates the main fracture of the fracturing operation.

[0096] The larger the half-width at half-maximum (WHM) of the local temperature difference peak data, the longer the temperature drop process at the corresponding sampling location lasts, and the more fracturing fluid the corresponding sampling location comes into contact with. Therefore, the probability that the corresponding sampling location indicates the main fracture of the fracturing operation is also higher.

[0097] The longer the fracturing equilibrium takes, the longer it takes for the corresponding sampling location to go from a sudden temperature drop to temperature equilibrium. This also indicates that the volume of the fracture area indicated by the corresponding sampling location is larger. Therefore, the probability that the corresponding sampling location indicates the main fracture of the fracturing operation is also higher.

[0098] In one example, the first, second, and third features of each local temperature difference peak data can be processed based on a trained neural network model to obtain the main crack index of each local temperature difference peak data.

[0099] In another example, the Topsis superior-inferiority distance algorithm can also be used to process the first, second, and third features of each local temperature difference peak data to obtain the main crack index of each local temperature difference peak data.

[0100] Specifically, the steps for obtaining the third feature of each local temperature difference peak data in multiple local temperature difference peak data include:

[0101] In the multiple local temperature difference peak data, the temperature change after each temperature sampling time within the target period is analyzed at the sampling position indicated by each local temperature difference peak data, and multiple fracturing balance indices associated with each local temperature difference peak data are determined. Among them, the multiple fracturing balance indices associated with each local temperature difference peak data correspond one-to-one with the multiple temperature sampling times in the target period.

[0102] Among the multiple fracturing equilibrium indices associated with each local temperature difference peak data, the temperature sampling time corresponding to the largest fracturing equilibrium index is determined as the corresponding fracturing equilibrium time, so as to obtain the fracturing equilibrium time corresponding to each local temperature difference peak data.

[0103] The third characteristic of each temperature difference local peak data is determined based on the first time difference between the fracturing equilibrium time corresponding to each local peak data and the start time of the target cycle.

[0104] The fracturing equilibrium index mentioned above indicates the confidence level of determining the corresponding temperature sampling time as the fracturing equilibrium time (the moment when temperature equilibrium is reached) at the corresponding sampling location. The higher the fracturing equilibrium index, the more reliable it is to determine the corresponding temperature sampling time as the fracturing equilibrium time at the corresponding sampling location.

[0105] The steps of analyzing the temperature change after each temperature sampling time within the target period at the sampling location indicated by each local temperature difference peak data point, and determining the multiple fracturing balance indices associated with each local temperature difference peak data point, include:

[0106] Multiple backward temperature sequences associated with each local peak temperature difference are obtained. Each backward temperature sequence corresponds one-to-one with multiple temperature sampling times within the target period. The backward temperature sequence includes multiple temperature values ​​collected from the corresponding sampling position from the corresponding temperature sampling time to the end of the target period.

[0107] In the multiple local temperature difference peak data, the degree of dispersion of each backward temperature sequence associated with each local temperature difference peak data is analyzed to obtain multiple temperature dispersion coefficients associated with each local temperature difference peak data.

[0108] At multiple temperature sampling moments within the target period, the second time difference between each temperature sampling moment and the end of the target period is analyzed to determine the time-domain coefficient of each temperature sampling moment. The time-domain coefficient and the corresponding second time difference are negatively correlated.

[0109] Among the multiple temperature dispersion coefficients associated with each local temperature difference peak data, each fracturing balance index associated with each local temperature difference peak data is determined based on each temperature dispersion coefficient associated with each local temperature difference peak data and its corresponding time domain coefficient.

[0110] For the sampling locations of each indicated fracture region, the overall temperature change after the fracturing equilibrium moment is relatively stable. Therefore, the smaller the temperature dispersion coefficient, the more it indicates that the corresponding temperature sampling moment is the fracturing equilibrium moment of the corresponding sampling location.

[0111] However, it should be noted that the overall temperature change at the sampling location remains stable after the fracturing equilibrium moment, and the later the time, the more stable the overall temperature change at the sampling location. By configuring the time domain coefficient, a higher calculation coefficient can be configured for the temperature sampling moments earlier in time, which can effectively suppress the fracturing equilibrium index at temperature sampling moments after the actual fracturing equilibrium moment, so as to ensure the accuracy and reliability of the fracturing equilibrium index determined for each temperature sampling moment.

[0112] The temperature dispersion coefficient can be the standard deviation of the corresponding backward temperature sequence.

[0113] For example, the first The local temperature difference peak data is in the first Fracturing balance index at each temperature sampling time It can be represented as:

[0114] =

[0115] in, Indicates the start time of the target period. Indicates the end time of the target period. Indicates the first period within the target period At each temperature sampling time, Indicates the first The local temperature difference peak data is in the first The standard deviation of the backward temperature sequence associated with each temperature sampling time. Indicates the first The local temperature difference peak data is in the first The backward temperature sequence associated with each temperature sampling time.

[0116] It should be noted that in the above formula, if the calculated standard deviation is 0, it is determined that the fracturing balance index of the corresponding sampling location at the corresponding temperature sampling time is abnormal, and the corresponding temperature sampling time is removed from the candidate queue of the fracturing balance time of the corresponding sampling location.

[0117] Step S4: Based on the main fracture index of each local temperature difference peak data, identify the target sampling location indicating the main fracture among all sampling locations included in the target layer.

[0118] In some implementations, the main crack index of all local temperature difference peak data can be normalized (scaled to the 0-1 range), and the location indicated by the local temperature difference peak data where the main crack index (after normalization) is greater than or equal to the normalization threshold (e.g., 0.7) can be determined as the target sampling location.

[0119] In other embodiments, the step of identifying the target sampling location indicating the main fracture among all sampling locations included in the target segment based on the main fracture index of each local temperature difference peak data includes:

[0120] The average value of the main crack index of the multiple local temperature difference peak data is calculated to obtain the index mean.

[0121] Among the multiple local temperature difference peak data, the sampling location indicated by the local temperature difference peak data where the main crack index is greater than the average value of the index is determined as the target sampling location.

[0122] Step S5: Determine the target operation result based on the temperature changes of multiple target sampling locations within the target period and the number of multiple target sampling locations.

[0123] The target operation result is used to indicate whether fracturing operations in the target layer have been stopped.

[0124] As mentioned earlier, the target sampling location is highly likely to indicate the location of the main fracture in the target segment. During the fracturing operation, the number of main fractures and temperature changes will indicate the fracturing effect of the target segment. Generally speaking, the more main fractures there are and the more the actual temperature change matches the reference temperature change (the temperature change of the main fractures in other segments where fracturing operations have been stopped), the more the fracturing operation should be stopped.

[0125] In one example, a data sequence indicating the temperature changes of multiple target sampling locations within a target period, along with the number of multiple target sampling locations, can be concatenated to form model input data. This data is then fed into a pre-trained binary classification model (such as a support vector machine (SVM) model) to obtain the detection results output by the binary classification model. Based on the detection results, it can be determined whether to stop the fracturing operation on the target layer.

[0126] The binary classification model aims to output a first value or a second value based on the input data. The first value indicates that the fracturing operation on the target segment should be stopped, while the second value indicates that the fracturing operation on the target segment should continue.

[0127] As can be seen, this invention uses adjacent layers within the same depth range as a reference to analyze the temperature changes at various points in the target layer undergoing fracturing operations within the target period. This yields multiple temperature difference data points used to accurately quantify the temperature change amplitude at various points in the target layer. Then, through local peak detection, multiple local temperature difference peaks corresponding to the fracture region are identified from these multiple temperature difference data points. Further analysis is then performed on the peak height, peak width, and time taken for each local temperature difference peak to reach fracturing equilibrium at the corresponding sampling location. This determines the probability that the sampling location indicated by each local temperature difference peak corresponds to the main fracture region. Based on this, several target sampling locations corresponding to the main fracture region are identified from the multiple sampling locations in the corresponding fracture region. By combining the temperature changes at each target sampling location and the total number of target sampling locations, it is determined whether fracturing operations in the target layer should be stopped. This enables timely monitoring of the fracturing effect in low-permeability tight reservoirs. Especially when the fracturing effect in the target layer is found to be in line with expectations, the injection of fracturing fluid can be stopped promptly to avoid unnecessary consumption of fracturing fluid and reduce the exploitation cost of low-permeability tight reservoirs.

[0128] In some implementations, the step of determining the target operation result based on the temperature changes at multiple target sampling locations within a target period and the number of multiple target sampling locations includes:

[0129] The temperature rise at each target sampling location after the corresponding fracturing equilibrium moment is analyzed to obtain the fracture saturation index at each target sampling location;

[0130] The calculation weight of each target sampling location is determined based on the fracturing balance index corresponding to each target sampling location.

[0131] Based on the calculation weight of each target sampling location, the crack saturation index of multiple target sampling locations is weighted and calculated to obtain the pumping saturation index;

[0132] The target operation result is determined based on the pump saturation index and the number of multiple target sampling locations. The output probability of the first operation result is positively correlated with the number of multiple target sampling locations and positively correlated with the pump saturation index. The first operation result is the target operation result that indicates the cessation of fracturing operations in the target segment.

[0133] The step of determining the calculation weight of each target sampling location based on the fracturing balance index corresponding to each target sampling location includes:

[0134] Calculate the sum of the fracturing balance indices corresponding to multiple target sampling locations to obtain the cumulative index value;

[0135] Calculate the ratio of the fracturing balance index to the cumulative index value corresponding to each target sampling location to obtain the calculation weight of each target sampling location.

[0136] It should be understood that when the main fracture is fully filled, the fracturing operation in the target segment can be considered to have achieved the expected operational goal. However, in actual operation, the fracturing process will generate micro-fracture propagation. The full filling of the propagating micro-fractures and secondary fractures at the end of the fracturing fluid flow path usually causes unnecessary fracturing fluid consumption. Therefore, measures to assess whether to stop the operation based on the temperature changes at various locations in the target segment usually output fracturing operation detection results with low timeliness (aiming to indicate whether to stop the fracturing operation). This invention, through the aforementioned process, first identifies target sampling locations with a high probability of indicating the main fracture from sampling locations at various locations in the target segment. Then, it determines the filling degree of the corresponding main fracture by analyzing the fracture saturation index of each target sampling location. Combined with the number of target sampling locations, it indirectly calculates the number of main fractures. By combining the above two methods, it avoids the interference of propagating micro-fractures and secondary fractures at the end of the fracturing fluid flow path, and outputs target operation results with high timeliness.

[0137] It should be understood that the higher the temperature rise at the target sampling location after the corresponding fracturing equilibrium moment, the higher the degree of filling of the main fracture indicated by the target sampling location, and therefore the higher the fracture saturation index at the target sampling location.

[0138] In one example, a straight line can be fitted to multiple sampling temperatures at the target sampling location after the corresponding fracturing equilibrium time (using the least squares method), and the slope of the fitted line can be determined as the fracture saturation index of the corresponding target sampling location.

[0139] In this example, if the fracture saturation index at a target sampling location is calculated to be negative, the target operation result indicating that fracturing operations should continue in the target segment is directly output.

[0140] The fracturing balance index indirectly reflects the volume of the corresponding main fracture. The larger the volume of the main fracture, the more important it is in the fracturing operation assessment process. Therefore, a larger calculation weight should be assigned to ensure the accuracy of the calculated pump saturation index.

[0141] The above-mentioned pump saturation index is used to represent the overall degree of filling of the main fracture in the target layer.

[0142] In this embodiment, the pump saturation index and the number of multiple target sampling locations can be processed by a decision model to obtain the target operation result. The decision model can also be a support vector machine (SVM) model. For a description of the decision model, please refer to the previous description of the binary classification model (the model inputs of the two are different, but the model output settings are the same). To avoid repetition, it will not be repeated here.

[0143] In one embodiment, the present invention also provides a coiled tubing mechanically controlled dual-seal drag fracturing device, such as... Figure 3 As shown, the device 200 includes:

[0144] The data acquisition module 201 is used to analyze the temperature changes at each sampling location in the target layer within the target period, with the reference layer as a reference, and obtain multiple temperature difference data. The reference layer and the target layer are adjacent and in the same depth range, and the multiple temperature difference data correspond one-to-one with multiple sampling locations in the target layer.

[0145] Peak detection module 202 is used to perform local peak detection on the multiple temperature difference data to determine multiple local peak data of temperature difference.

[0146] The feature analysis module 203 is used to analyze the peak feature information of each temperature difference local peak data in the multiple temperature difference local peak data to obtain the main fracture index of each temperature difference local peak data. The peak feature information includes a first feature indicating the peak height of the corresponding temperature difference local peak data, a second feature indicating the peak width of the corresponding temperature difference local peak data, and a third feature indicating the fracturing balance time of the corresponding temperature difference local peak data. The main fracture index is used to characterize the probability that the corresponding temperature difference local peak data indicates a main fracture.

[0147] The main fracture identification module 204 is used to identify the target sampling location indicating the main fracture among all sampling locations included in the target segment based on the main fracture index of each local temperature difference peak data.

[0148] The operation result detection module 205 is used to determine the target operation result based on the temperature change of multiple target sampling locations within the target period and the number of multiple target sampling locations. The target operation result is used to indicate whether the fracturing operation of the target layer has been stopped.

[0149] It should be noted that the equipment provided in the above embodiments is only an example of the division of the above functional modules. In actual applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the computer equipment can be divided into different functional modules to complete all or part of the functions described above. In addition, the coiled tubing mechanically controlled double-seal drag fracturing equipment and the coiled tubing mechanically controlled double-seal drag fracturing method embodiment provided in the above embodiments belong to the same concept, and their specific implementation process can be found in the method embodiment, which will not be repeated here.

[0150] This invention also provides an electronic device. Please refer to [link to relevant documentation]. Figure 4 The electronic device may include a processor 301, a memory 302, and a program 3021 stored in the memory 302 and capable of running on the processor 301.

[0151] When program 3021 is executed by processor 301, it can achieve the following: Figure 2 Any steps in the corresponding method embodiments and the achievement of the same beneficial effects will not be repeated here.

[0152] Those skilled in the art will understand that all or part of the steps of the methods described in the above embodiments can be implemented by hardware related to program instructions, and the program can be stored in a readable medium.

[0153] This invention also provides a readable storage medium storing a computer program, which, when executed by a processor, can perform the above-described functions. Figure 2Any step in the corresponding method embodiment can achieve the same technical effect, and will not be repeated here to avoid repetition.

[0154] The computer-readable storage medium of this invention can be any combination of one or more computer-readable media. The computer-readable medium can be a computer-readable signal medium or a computer-readable storage medium. For example, a computer-readable storage medium can be an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of computer-readable storage media (a non-exhaustive list) include: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In this document, a computer-readable storage medium can be any tangible medium that contains or stores a program that can be used by or in conjunction with an instruction execution system, apparatus, or device.

[0155] Computer-readable signal media may include data signals propagated in baseband or as part of a carrier wave, carrying computer-readable program code. Such propagated data signals may take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. Computer-readable signal media may also be any computer-readable medium other than computer-readable storage media, capable of sending, propagating, or transmitting programs for use by or in connection with an instruction execution system, apparatus, or device.

[0156] The program code contained on the storage medium can be transmitted using any suitable medium, including but not limited to wireless, wire, optical fiber, RF, etc., or any suitable combination thereof.

[0157] Computer program code for performing the operations of this invention can be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, and C++, as well as conventional procedural programming languages ​​such as "C" or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or terminal. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network—including a local area network (LAN) or a wide area network (WAN)—or can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0158] This invention also provides a computer program product that, when run on a computer, causes the computer to perform the aforementioned steps to implement the coiled tubing mechanical control dual-seal drag fracturing method provided in the above embodiments.

[0159] It should be noted that the order of the above embodiments of the present invention is merely for descriptive purposes and does not represent the superiority or inferiority of the embodiments. The processes depicted in the accompanying drawings do not necessarily require a specific or sequential order to achieve the desired result. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0160] The various embodiments in this specification are described in a progressive manner. The same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on describing the differences from other embodiments.

Claims

1. A coiled tubing mechanically controlled double-seal drag fracturing method, characterized in that, The method includes: Using the benchmark layer as a reference, the temperature changes at each sampling location in the target layer within the target period are analyzed to obtain multiple temperature difference data. The benchmark layer and the target layer are adjacent and located in the same depth range. The multiple temperature difference data correspond one-to-one with multiple sampling locations in the target layer. Local peak detection is performed on the multiple temperature difference data to determine multiple local temperature difference peak data; In the multiple local temperature difference peak data, the peak feature information of each local temperature difference peak data is analyzed to obtain the main fracture index of each local temperature difference peak data. The peak feature information includes a first feature indicating the peak height of the corresponding local temperature difference peak data, a second feature indicating the peak width of the corresponding local temperature difference peak data, and a third feature indicating the fracturing balance time of the corresponding local temperature difference peak data. The main fracture index is used to characterize the probability that the corresponding local temperature difference peak data indicates a main fracture. Based on the main fracture index of each local temperature difference peak data, the target sampling location indicating the main fracture is identified among all sampling locations included in the target segment. The target operation result is determined based on the temperature changes at multiple target sampling locations within the target period and the number of multiple target sampling locations. The target operation result is used to indicate whether the fracturing operation in the target section has been stopped. The steps involved in analyzing the temperature changes at various sampling locations within the target segment during the target period, using a baseline segment as a reference, to obtain multiple temperature difference data include: At the end of the target period, the average temperature value of all sampling locations within the reference layer is calculated to obtain the reference temperature; Within the target period, the differences between the average temperature at multiple sampling locations in the target layer and the reference temperature are analyzed to obtain multiple temperature difference data. The steps for obtaining the third feature of each local temperature difference peak data point in the multiple local temperature difference peak data points include: In the multiple local temperature difference peak data, the temperature change after each temperature sampling time within the target period is analyzed at the sampling position indicated by each local temperature difference peak data, and multiple fracturing balance indices associated with each local temperature difference peak data are determined. Among them, the multiple fracturing balance indices associated with each local temperature difference peak data correspond one-to-one with the multiple temperature sampling times in the target period. Among the multiple fracturing equilibrium indices associated with each local temperature difference peak data, the temperature sampling time corresponding to the largest fracturing equilibrium index is determined as the corresponding fracturing equilibrium time, so as to obtain the fracturing equilibrium time corresponding to each local temperature difference peak data. The third characteristic of each temperature difference local peak data is determined based on the first time difference between the fracturing equilibrium time corresponding to each local peak data and the start time of the target cycle.

2. The coiled tubing mechanically controlled double-seal drag fracturing method according to claim 1, characterized in that, The steps for analyzing the temperature change at each temperature sampling time within the target period for the sampling location indicated by each local temperature difference peak data point, and determining the multiple fracturing balance indices associated with each local temperature difference peak data point, include: Multiple backward temperature sequences associated with each local peak temperature difference are obtained. Each backward temperature sequence corresponds one-to-one with multiple temperature sampling times within the target period. The backward temperature sequence includes multiple temperature values ​​collected from the corresponding sampling position from the corresponding temperature sampling time to the end of the target period. In the multiple local temperature difference peak data, the degree of dispersion of each backward temperature sequence associated with each local temperature difference peak data is analyzed to obtain multiple temperature dispersion coefficients associated with each local temperature difference peak data. At multiple temperature sampling moments within the target period, the second time difference between each temperature sampling moment and the end of the target period is analyzed to determine the time-domain coefficient of each temperature sampling moment. The time-domain coefficient and the corresponding second time difference are negatively correlated. Among the multiple temperature dispersion coefficients associated with each local temperature difference peak data, each fracturing balance index associated with each local temperature difference peak data is determined based on each temperature dispersion coefficient associated with each local temperature difference peak data and its corresponding time domain coefficient.

3. The coiled tubing mechanically controlled double-seal drag fracturing method according to claim 1, characterized in that, The main crack index shows a positive correlation with the first feature, the main crack index shows a positive correlation with the second feature, and the main crack index shows a positive correlation with the third feature.

4. The coiled tubing mechanically controlled double-seal drag fracturing method according to claim 1, characterized in that, The steps for identifying the target sampling location indicating the main fracture among all sampling locations included in the target segment, based on the main fracture index of each local temperature difference peak data, include: The average value of the main crack index of the multiple local temperature difference peak data is calculated to obtain the index mean. Among the multiple local temperature difference peak data, the sampling location indicated by the local temperature difference peak data where the main crack index is greater than the average value of the index is determined as the target sampling location.

5. The coiled tubing mechanically controlled double-seal drag fracturing method according to claim 1, characterized in that, The steps for determining the target operation result based on the temperature changes at multiple target sampling locations within the target period and the number of target sampling locations include: The temperature rise at each target sampling location after the corresponding fracturing equilibrium moment is analyzed to obtain the fracture saturation index at each target sampling location; The calculation weight of each target sampling location is determined based on the fracturing balance index corresponding to each target sampling location. Based on the calculation weight of each target sampling location, the crack saturation index of multiple target sampling locations is weighted and calculated to obtain the pumping saturation index; The target operation result is determined based on the pump saturation index and the number of multiple target sampling locations.

6. The coiled tubing mechanically controlled double-seal drag fracturing method according to claim 5, characterized in that, The steps for determining the calculation weight of each target sampling location based on the fracturing balance index corresponding to each target sampling location include: Calculate the sum of the fracturing balance indices corresponding to multiple target sampling locations to obtain the cumulative index value; Calculate the ratio of the fracturing balance index to the cumulative index value corresponding to each target sampling location to obtain the calculation weight of each target sampling location.

7. The coiled tubing mechanically controlled double-seal drag fracturing method according to claim 5, characterized in that, The output probability of the first operation result is positively correlated with the number of multiple target sampling locations, and the output probability of the first operation result is positively correlated with the pump saturation index. The first operation result is the target operation result that indicates the cessation of fracturing operations in the target segment.

8. A coiled tubing mechanically controlled double-seal drag fracturing device, characterized in that, The equipment for performing the coiled tubing mechanically controlled double-seal drag fracturing method according to any one of claims 1-7, the equipment comprising: The data acquisition module is used to analyze the temperature changes at each sampling location in the target layer within the target period, with the reference layer as a reference, and obtain multiple temperature difference data. The reference layer and the target layer are adjacent and in the same depth range, and the multiple temperature difference data correspond one-to-one with multiple sampling locations in the target layer. The peak detection module is used to perform local peak detection on the multiple temperature difference data to determine the multiple local peak data of temperature difference. The feature analysis module is used to analyze the peak feature information of each local temperature difference peak data in the multiple local temperature difference peak data to obtain the main fracture index of each local temperature difference peak data. The peak feature information includes a first feature indicating the peak height of the corresponding local temperature difference peak data, a second feature indicating the peak width of the corresponding local temperature difference peak data, and a third feature indicating the fracturing balance time of the corresponding local temperature difference peak data. The main fracture index is used to characterize the probability that the corresponding local temperature difference peak data indicates a main fracture. The main fracture identification module is used to identify the target sampling location indicating the main fracture among all sampling locations included in the target layer based on the main fracture index of each local temperature difference peak data. The operation result detection module is used to determine the target operation result based on the temperature change of multiple target sampling locations within the target period and the number of multiple target sampling locations. The target operation result is used to indicate whether the fracturing operation in the target section has been stopped.

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