Plugging agent design method, device and equipment and storage medium

Abstract

The invention discloses a plugging agent design method, device and equipment and a storage medium, and relates to the technical field of oil field drilling plugging, and the method comprises the steps: obtaining well logging data of a drilled well in a target area, and processing the well logging data to obtain a target crack exponential function; collecting fracture parameters of fractures of all scales of drilled wells in the target area, and determining a corresponding normal distribution function based on the fracture parameters and the target fracture exponential function; acquiring a percentage setting instruction, and determining a crack opening interval range of the target crack based on the percentage setting instruction and the normal distribution function; a plurality of fractured leakage layer plugging agent formulas are generated according to the fracture opening degree interval range and the ideal filling theory, a pressure-bearing plugging experiment is carried out to obtain a corresponding pressure-bearing experiment result, and a target fractured leakage layer plugging agent formula is determined from the fractured leakage layer plugging agent formulas according to the pressure-bearing experiment result to obtain a target plugging agent. Therefore, the plugging agent which can form effective residence and is high in pressure bearing capacity of a plugging layer can be generated.

Description

Technical Field

[0001] This invention relates to the field of oilfield drilling and plugging technology, and particularly to a plugging agent design method, apparatus, equipment and storage medium. Background Technology

[0002] Lost drilling fluid (WSF) is one of the most common and complex downhole problems during drilling. The consequences of WSF include: costly loss of drilling fluid, non-operational time, wellbore instability, and in some cases, blowouts, which can be more serious than the WSF itself. Based on the formation in which the loss occurs, WSF is generally classified into three types: permeable WSF, fractured WSF, and cavernous WSF. Fractured WSF is the most common and difficult to resolve. It not only leads to significant waste of drilling fluid and increases drilling costs but also prolongs the well construction period, severely hindering the exploration and development of oil and gas resources.

[0003] Currently used plugging agent formulations for fractured wells are often based on trial and error, lacking scientific basis and quantitative analysis, remaining at a relatively one-sided, intuitive stage. Furthermore, different construction sites have different formation compositions and fracture types, requiring different plugging formulations. For deep fractured well leakage problems under various conditions, relying solely on experience is insufficient to achieve good plugging results. Therefore, it is necessary to address how to develop plugging agents tailored to the characteristics of fractures to improve the efficiency and success rate of on-site plugging. Summary of the Invention

[0004] In view of this, the purpose of this invention is to provide a method, apparatus, equipment, and storage medium for designing a sealing agent, capable of generating a sealing agent that can form an effective retention layer with high pressure resistance. The specific solution is as follows:

[0005] In a first aspect, this application discloses a method for designing a sealing agent, comprising:

[0006] Obtain logging data from drilled wells within the target area, and process the logging data using the fracture indicator parameter method to obtain the target fracture exponential function;

[0007] Collect fracture parameters of fractures at various scales in the drilled wells within the target area, and determine the normal distribution function corresponding to the fracture aperture in the area based on the fracture parameters and the target fracture exponential function;

[0008] Obtain the percentage setting instruction, and determine the crack aperture range of the target crack based on the percentage setting instruction and the normal distribution function;

[0009] Several formulas for sealing agents to plug cracked layers are generated based on the crack aperture range and the ideal filling theory.

[0010] Pressure testing was conducted on the several cracked leakage plugging agent formulations to obtain the pressure test results corresponding to each cracked leakage plugging agent formulation. Based on the pressure test results, a target cracked leakage plugging agent formulation was determined from the several cracked leakage plugging agent formulations to obtain the target plugging agent.

[0011] Optionally, the step of acquiring well logging data from drilled wells within the target area and processing the well logging data using the fracture indicator parameter method to obtain the target fracture exponential function includes:

[0012] Extract each target data from the well logging data of the drilled wells within the target area, and determine the fracture composite index and fractal dimension of the well logging curve corresponding to each target data.

[0013] The comprehensive crack index and the fractal dimension are substituted into the preset crack index calculation formula to determine the target crack index function.

[0014] Optionally, the step of extracting target data from the well logging data of drilled wells within the acquired target area, and determining the fracture composite index and fractal dimension of the well logging curve corresponding to each target data; and substituting the fracture composite index and the fractal dimension into a preset fracture index calculation formula to determine the target fracture index function includes:

[0015] Target data is extracted from the logging data of drilled wells within the target area, and data cleaning and normalization operations are performed to obtain the fracture composite index of each logging curve.

[0016] The first weight value is determined based on the degree of fracture response corresponding to each of the aforementioned logging curves;

[0017] The fractal dimension of each target data is calculated using the rescaled range analysis method, and the corresponding second weight value is determined based on the fractal dimension.

[0018] Substitute the fracture composite index, the first weight value, the fractal dimension, and the second weight value into the preset fracture index calculation formula to obtain the fracture index function corresponding to each well logging curve;

[0019] The crack exponential function is integrated based on a preset formula to obtain the target crack exponential function.

[0020] Optionally, the step of collecting fracture parameters of fractures at various scales from drilled wells within the target area, and determining the normal distribution function corresponding to the fracture aperture in the area based on the fracture parameters and the target fracture exponential function, includes:

[0021] Collect fracture parameters corresponding to fractures of various scales that have been drilled in the target area, and construct a corresponding fractured formation porosity and fracture aperture model based on the fracture parameters and the target fracture exponential function, and determine the corresponding normal distribution function based on the fractured formation porosity and fracture aperture model.

[0022] Optionally, the step of generating several crack-related leakage plugging agent formulations based on the crack aperture range and ideal filling theory includes:

[0023] Empirical rules for determining the particle size of the plugging agent are based on the crack aperture range and the ideal filling theory.

[0024] Based on the empirical rules for particle size, a particle size range is determined, and several crack-forming agent formulations are generated within the particle size range.

[0025] Optionally, the step of determining the particle size range based on the empirical rules for particle size, and generating several crack-related leakage plugging agent formulations within the particle size range, includes:

[0026] The particle size range is determined based on the empirical rules for particle size, and a target sealing material is selected from the preset sealing materials within the particle size range; the preset sealing materials include bridging materials, filler materials, fiber materials, and deformable materials;

[0027] The material mixing ratio corresponding to the target sealing material is determined based on the material properties of the target sealing material, and several crack leakage plugging agent formulations are generated based on the material mixing ratio.

[0028] Optional. The step of conducting pressure-bearing sealing tests on the plurality of cracked leakage plugging agent formulations to obtain the pressure-bearing test results corresponding to each cracked leakage plugging agent formulation includes:

[0029] The target sealing material is prepared according to the preset sealing grout preparation method and the material mixing ratio to prepare the subsequent sealing agent;

[0030] Based on the crack opening range, a target crack plate is selected, and a pressure-bearing sealing test is conducted on the prepared sealing agent using the target crack plate to obtain the pressure-bearing test results corresponding to each cracked leakage layer sealing agent formulation.

[0031] Secondly, this application discloses a sealing agent design device, comprising:

[0032] The data processing module is used to acquire well logging data of drilled wells in the target area and process the well logging data using the fracture indicator parameter method to obtain the target fracture exponential function.

[0033] The function generation module is used to collect fracture parameters of fractures at various scales in the drilled wells within the target area, and to determine the normal distribution function corresponding to the fracture aperture in the area based on the fracture parameters and the target fracture exponential function.

[0034] The interval determination module is used to obtain the percentage setting instruction and determine the crack aperture interval range of the target crack based on the percentage setting instruction and the normal distribution function;

[0035] The formulation production module is used to generate several formulations of crack-related leakage plugging agents based on the crack opening range and the ideal filling theory.

[0036] The pressure-bearing leakage sealing test module is used to conduct pressure-bearing leakage sealing tests on the plurality of cracked leakage sealing agent formulations to obtain the pressure-bearing test results corresponding to each cracked leakage sealing agent formulation, and to determine the target cracked leakage sealing agent formulation from the plurality of cracked leakage sealing agent formulations based on the pressure-bearing test results to obtain the target sealing agent.

[0037] Thirdly, this application discloses an electronic device, including:

[0038] Memory, used to store computer programs;

[0039] A processor for executing the computer program to implement the aforementioned plugging agent design method.

[0040] Fourthly, this application discloses a computer-readable storage medium for storing a computer program, which, when executed by a processor, implements the aforementioned plugging agent design method.

[0041] As can be seen, the following steps are taken: acquiring logging data from drilled wells within the target area; processing the logging data using the fracture indicator parameter method to obtain the target fracture exponential function; collecting fracture parameters of fractures at various scales from drilled wells within the target area; determining the normal distribution function corresponding to the fracture aperture in the area based on the fracture parameters and the target fracture exponential function; obtaining percentage setting instructions; determining the fracture aperture range of the target fracture based on the percentage setting instructions and the normal distribution function; generating several fracture-related leakage plugging agent formulations based on the fracture aperture range and ideal filling theory; conducting pressure-bearing plugging experiments on the several fracture-related leakage plugging agent formulations to obtain the pressure-bearing experiment results corresponding to each fracture-related leakage plugging agent formulation; and determining the target fracture-related leakage plugging agent formulation from the several fracture-related leakage plugging agent formulations based on the pressure-bearing experiment results to obtain the target plugging agent. In this way, by collecting data such as imaging logging to establish the target fracture exponential function, and combining it with fracture parameters of various scales extracted from logging data, a normal distribution function of the regional fracture aperture is obtained. Based on this, and considering the characteristics of the plugging material, an appropriate ratio design is carried out. By predicting the leakage fracture aperture, a basis is provided for the formulation design of fracture plugging agents, providing drilling plugging technicians and construction personnel with more accurate and effective decision-making basis, thereby improving the efficiency of fracture plugging work, increasing the success rate of plugging operations, and avoiding repeated operations. Attached Figure Description

[0042] To more clearly illustrate the technical solutions 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 embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on the provided drawings without creative effort.

[0043] Figure 1 This is a flowchart of a leak-sealing agent design method disclosed in this application;

[0044] Figure 2 This is a flowchart of a specific leak-sealing agent design method disclosed in this application;

[0045] Figure 3 This is a schematic diagram of a specific well logging curve disclosed in this application;

[0046] Figure 4 This is a data graph generated during a portion of the calculation process disclosed in this application;

[0047] Figure 5 This is a schematic diagram of a normal distribution function disclosed in this application;

[0048] Figure 6This is a schematic diagram of a crack aperture range disclosed in this application;

[0049] Figure 7 This is a schematic diagram of a D90 target curve disclosed in this application;

[0050] Figure 8 This is a schematic diagram of a sealing agent design device disclosed in this application;

[0051] Figure 9 This is a structural diagram of an electronic device disclosed in this application. Detailed Implementation

[0052] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0053] Currently used plugging agent formulations for fractured wells are often based on trial and error, lacking scientific basis and quantitative analysis, remaining at a relatively one-sided, intuitive stage. Furthermore, different construction sites have different formation compositions and fracture types, requiring different plugging agents. For deep fractured well leakage problems under various conditions, relying solely on experience is insufficient to achieve effective plugging. Therefore, this application will specifically introduce a plugging agent design method that can form effective retention in regional fractured leakage channels and has a high pressure-bearing capacity of the sealing layer.

[0054] See Figure 1 As shown in the embodiments, this application discloses a method for designing a sealant, including:

[0055] Step S11: Obtain logging data of drilled wells in the target area, and process the logging data using the fracture indicator parameter method to obtain the target fracture exponential function.

[0056] In this embodiment, acquiring well logging data from drilled wells within the target area and processing the well logging data using the fracture indicator parameter method to obtain the target fracture index function includes: extracting target data from the acquired well logging data from drilled wells within the target area, and determining the comprehensive fracture index and fractal dimension of the well logging curve corresponding to each target data; substituting the comprehensive fracture index and the fractal dimension into a preset fracture index calculation formula to determine the target fracture index function. That is, by collecting well logging data from drilled wells in the area and using the fracture indicator parameter method, the fracture index F (Function) function of the area is obtained. The value range of the F function is 0 to 1, reflecting the probability of fracture development; the closer the value is to 1, the greater the probability of fracture development. Specifically, the step of extracting target data from the logging data of drilled wells within the acquired target area and determining the fracture composite index and fractal dimension of the logging curve corresponding to each target data; and substituting the fracture composite index and the fractal dimension into a preset fracture index calculation formula to determine the target fracture index function includes: extracting target data from the logging data of drilled wells within the acquired target area, and performing data cleaning and normalization operations to obtain the fracture composite index of each logging curve; determining a first weight value based on the fracture response degree corresponding to each logging curve; calculating the fractal dimension corresponding to each target data using rescaled range analysis, and determining a corresponding second weight value based on the fractal dimension; substituting the fracture composite index, the first weight value, the fractal dimension, and the second weight value into a preset fracture index calculation formula to obtain the fracture index function corresponding to each logging curve; and performing integrated processing on the fracture index function based on the preset formula to obtain the target fracture index function. The fracture composite index (I) and fractal dimension (D) are calculated using regional well logging data, and different weights (a, b) are assigned to the fracture composite index and fractal dimension, respectively. The fracture composite index (I) is obtained by selecting well logging data that responds well to fractures, cleaning and normalizing the data, and then obtaining the index I of a certain well logging curve. i Subsequently, based on the degree of fracture response of each logging curve, corresponding weights (a1, a2, ..., a) are assigned to each logging data. x Each logging curve corresponds to a uniform weight value; where a1+a2+...+a x=1). Generally, the logging response characteristics are consistent within a region, meaning the weights of each logging curve remain unchanged. These logging curves include, but are not limited to, AC (acoustic transit time), GR (natural gamma), CAL (well diameter), and DEN (density). The fractal dimension (D) of the logging curve is calculated using Matlab software and the Rescaled Range Analysis (R / S) method (D = 2 - H, where H is the slope of R / S versus N on logarithmic coordinates, and N represents the analysis step size). Typically, D is between 1 and 2; the more developed the fractures, the larger the D value, and the higher its corresponding weight (b) (b1, b2, ..., b...). x Each logging curve corresponds to a uniform weight value; where b1+b2+...+b x =1). The formula for calculating the fracture index using a single logging curve is:

[0057] ;

[0058] Then, by integrating multiple well logging curves, the uncertainty of single-well fracture identification results can be effectively reduced. The fracture interpretation results Fi from different well logging curves are transformed into the F function:

[0059] ;

[0060] in, This represents the fracture factor for each logging curve of the fracture.

[0061] Step S12: Collect fracture parameters of fractures at various scales in the drilled wells within the target area, and determine the normal distribution function corresponding to the fracture aperture in the region based on the fracture parameters and the target fracture exponential function.

[0062] In this embodiment, the step of collecting fracture parameters of fractures at various scales from drilled wells within the target area and determining the normal distribution function corresponding to the fracture aperture in the region based on the fracture parameters and the target fracture exponential function includes: collecting fracture parameters corresponding to fractures at various scales from drilled wells within the target area, constructing a corresponding fractured formation porosity and fracture aperture model based on the fracture parameters and the target fracture exponential function, and determining the corresponding normal distribution function based on the fractured formation porosity and fracture aperture model. Specifically, based on seismic attribute volumes and well logging data, parameters (length and width) of large- to medium-scale fractures can be obtained by extracting attribute volumes such as ant volumes, curvature, and coherence volumes from 3D seismic data. Parameters of small- to micro-scale fractures can be directly obtained from imaging well logging data. Based on the identified and extracted fracture lengths (Li) and widths (Bi) of large (length > 10m), medium (length 1m~10m), small (length 1cm~1m), and micro-scale (length < 1cm) fractures, a model of fractured formation porosity and fracture aperture is established. From this, the normal distribution function W of the regional fracture aperture is obtained. f Specifically, the model formula is:

[0063] ;

[0064] In the formula, F is the fracture exponential function, ψ is the porosity calculated by well logging, Li is the fracture length, Bi is the fracture width, and norm is the normal distribution function.

[0065] Step S13: Obtain the percentage setting instruction, and determine the crack aperture range of the target crack based on the percentage setting instruction and the normal distribution function.

[0066] In this embodiment, the percentage of the crack opening to be sealed needs to be set according to the actual situation. Depending on the actual situation, the percentage of the crack opening to be sealed is 60% to 90%. The determination of this percentage depends on the severity of leakage and the sealing design requirements. If the leakage is small and the pressure resistance requirement for sealing is not high, it can be set to 60%; otherwise, it needs to be set to 90%. Therefore, a percentage setting command needs to be issued, and then the crack opening range of the target crack is determined from the normal distribution function determined in step S12.

[0067] Step S14: Generate several crack-related leakage plugging agent formulations based on the crack opening range and ideal filling theory.

[0068] In this embodiment, several crack-related leakage plugging agent formulations are generated based on the crack aperture range and the ideal filling theory. Specifically, based on the crack aperture range, the particle size range of the plugging agent is optimized using the D90 empirical rule (which assumes that the particle size should be equal to the maximum pore diameter to be plugged when the cumulative particle size distribution is 90%).

[0069] Step S15: Conduct pressure-bearing sealing tests on the several cracked leakage plugging agent formulations to obtain the pressure-bearing test results corresponding to each cracked leakage plugging agent formulation, and determine the target cracked leakage plugging agent formulation from the several cracked leakage plugging agent formulations based on the pressure-bearing test results to obtain the target plugging agent.

[0070] In this embodiment, pressure-bearing sealing tests are conducted on the several crack-related leakage plugging agent formulations to obtain the pressure-bearing test results corresponding to each formulation. Based on the pressure-bearing test results, a target crack-related leakage plugging agent formulation is determined from the several formulations to obtain the target plugging agent. That is, based on the particle size range of the plugging agent, a suitable plugging material is selected, and a crack-related leakage plugging agent formulation suitable for the region is formed according to the proportion. Pressure-bearing sealing tests are conducted on the selected formulation to verify whether it meets the designed pressure-bearing requirements. If it does not meet the requirements, the proportions of each component in the plugging formulation are changed to further form multiple plugging formulations. The plugging formulations are screened until the final optimized formulation meets the designed pressure-bearing requirements.

[0071] As can be seen, in this embodiment, well logging data of drilled wells within the target area are acquired, and the well logging data is processed using the fracture indicator parameter method to obtain the target fracture exponential function; fracture parameters of fractures at various scales of drilled wells within the target area are collected, and the normal distribution function corresponding to the fracture aperture of the region is determined based on the fracture parameters and the target fracture exponential function; a percentage setting instruction is acquired, and the fracture aperture range of the target fracture is determined based on the percentage setting instruction and the normal distribution function; several fracture leakage plugging agent formulations are generated according to the fracture aperture range and the ideal filling theory; pressure-bearing plugging experiments are conducted on the several fracture leakage plugging agent formulations to obtain the pressure-bearing experiment results corresponding to each fracture leakage plugging agent formulation, and the target fracture leakage plugging agent formulation is determined from the several fracture leakage plugging agent formulations based on the pressure-bearing experiment results to obtain the target plugging agent. In this way, by collecting data such as imaging logging to establish the target fracture exponential function, and combining it with fracture parameters of various scales extracted from logging data, a normal distribution function of the regional fracture aperture is obtained. Based on this, and considering the characteristics of the plugging material, an appropriate ratio design is carried out. By predicting the leakage fracture aperture, a basis is provided for the formulation design of fracture plugging agents, providing drilling plugging technicians and construction personnel with more accurate and effective decision-making basis, thereby improving the efficiency of fracture plugging work, increasing the success rate of plugging operations, and avoiding repeated operations.

[0072] The above embodiments specifically introduced the design method of the sealing agent from the perspective of determining the range of crack opening. This application will specifically introduce the design method of the sealing agent from the perspective of determining the proportion of the sealing agent.

[0073] See Figure 2 As shown in the figure, this application discloses a specific method for designing a sealant, including:

[0074] Step S21: Obtain logging data of drilled wells in the target area, and process the logging data using the fracture indicator parameter method to obtain the target fracture exponential function.

[0075] Step S22: Collect fracture parameters of fractures at various scales in the drilled wells within the target area, and determine the normal distribution function corresponding to the fracture aperture in the region based on the fracture parameters and the target fracture exponential function.

[0076] Step S23: Obtain the percentage setting instruction, and determine the crack aperture range of the target crack based on the percentage setting instruction and the normal distribution function.

[0077] Step S24: Determine the empirical rules for the particle size of the plugging agent based on the crack aperture range and the ideal filling theory; then determine the particle size range based on the empirical rules for particle size, and generate several crack-related leakage plugging agent formulations within the particle size range.

[0078] In this embodiment, determining the particle size range based on the empirical rules for particle size and generating several fracture-related leakage plugging agent formulations within the particle size range includes: determining the particle size range based on the empirical rules for particle size, and determining a target plugging material from a preset plugging material within the particle size range; the preset plugging materials include bridging materials, filling materials, fiber materials, and deformable materials; determining the material mixing ratio corresponding to the target plugging material according to the material properties of the target plugging material, and generating several fracture-related leakage plugging agent formulations according to the material mixing ratio. Specifically, based on the "ideal filling theory," when the 'a' value (meaning 90% of the particle size is smaller than this value) of the plugging agent particles on their "cumulative volume percentage - d1 / 2" curve is equal to the maximum pore throat diameter or maximum fracture aperture of the formation, an ideal plugging effect can be achieved. Specifically, the line connecting D90 and the origin on the cumulative volume percentage curve of the plugging agent particles is used as the "plugging baseline" for the reservoir. The closer the cumulative distribution curve of the plugging agent particle size is to the baseline, the higher the particle packing efficiency and the better the plugging effect. It should be noted that the plugging material selection requires a combination of bridging materials, filler materials, fiber materials, and deformable materials. The bridging material is composed of one or two of the following: walnut shells, oyster shells, calcite, polypropylene plastic particles, and PPS (Polyphenylene Sulfide) plastic particles. The filler material is composed of one or two of the following: mica, wood flour, calcium carbonate, and quartz sand. The flexible fiber is composed of one or more of the following: bamboo fiber, sepiolite fiber, and polymer fiber. The deformable material is obtained by crushing asphalt, gel, or a flexible foam with a three-dimensional network structure, such as EPE (Expandable Polyethylene) foam (pearl cotton) or EPS (Expandable Polystyrene).

[0079] Step S25: Configure the target sealing material according to the preset sealing slurry preparation method and the material mixing ratio to prepare the post-sealing agent.

[0080] In this embodiment, the target sealing material is prepared according to the preset sealing slurry preparation method and the material mixing ratio to prepare the post-sealing agent. Specifically, the preset sealing slurry preparation method is as follows: 200g of each embodiment is added to 1L of base slurry and stirred evenly; the base slurry preparation method is: water + 4% sodium bentonite (by weight of water) + 3.5% sodium carbonate (by weight of sodium bentonite) + 0.2% XC (thickening agent) (by weight of water), stirred evenly and allowed to stand for 24 hours for later use. Then, the target sealing material is prepared according to the material mixing ratio obtained in the above steps to prepare the post-sealing agent.

[0081] Step S26: Select a target crack plate based on the crack opening range, and use the target crack plate to conduct a pressure-bearing sealing test on the prepared sealing agent to obtain the pressure-bearing test results corresponding to each cracked leakage layer sealing agent formulation.

[0082] In this embodiment, a target crack plate is selected based on the crack opening range, and a pressure-bearing sealing test is conducted on the prepared sealing agent using the target crack plate to obtain the pressure-bearing test results corresponding to each cracked leakage layer sealing agent formulation. That is, the crack range is selected as the crack plate, and a pressure-bearing sealing test is conducted on the optimized formulation to verify whether it meets the designed pressure-bearing requirements.

[0083] Step S27: Based on the pressure test results, determine the target cracked leakage plugging agent formulation from the several cracked leakage plugging agent formulations to obtain the target plugging agent.

[0084] The specific processes of steps S21 to S23 and step S27 can be found in the relevant content disclosed in the foregoing embodiments, and will not be repeated here.

[0085] As can be seen, in this embodiment, the sealant formulation is composed of soft foam with a spatial network structure, granular bridging material, filler material and fiber material. Through the retention effect of soft foam, the filling and reinforcing effect of flexible fiber and the filling and reinforcement effect of granules, a long sealing layer is formed in cracks or holes of different widths. The test results show that the sealing layer has a significant effect on pressure resistance.

[0086] The following section will introduce the sealing agent design method of this application through specific examples. For example... Figure 3 As shown, logging data from drilled wells in the region were collected, with the logging curve of well X in the region as an example. Using the fracture indicator parameter method, the fracture index F function for the region was obtained. Different F values ​​can be calculated for different wellbore depths and logging data; for example, the F values ​​for well depths of 3556.7m and 3556.8m are 0.36 and 0.23, respectively. Based on the logging data interpretation chart of well X, the length (Li) and width (Bi) of large-, medium-, small-, and micro-scale fractures were identified and extracted. Some data are shown in the appendix. Figure 3 The fracture lengths L at well depths of 3556.7m and 3556.8m are 1.58mm and 2.52mm, respectively, and the fracture widths B are 4.92mm and 1.19mm, respectively. For example... Figure 4 and Figure 5 As shown, based on the porosity and fracture aperture model of fractured formations, the normal distribution function W of the regional fracture aperture is calculated. f Among them, the W corresponding to well depths of 3556.7m and 3556.8m f The values ​​are 0.09 and 0.13. It should be noted here that... Figure 4This shows some of the data generated during the calculation process. Figure 5 This demonstrates the calculated normal distribution function W. f Then, as... Figure 6 As shown, determine the percentage of crack aperture that needs to be sealed. This percentage can be adjusted according to site requirements; here it is set to 60%, combined with the normal distribution function W of the regional crack aperture. f The reference range for the crack aperture that needs to be sealed is calculated to be 0~6.0mm. Based on this range, D... 90 Empirical rules recommend selecting the optimal particle size range for the plugging agent. This range is based on the "cumulative volume percentage - d" of the plugging agent particles. 1 / 2 "Curve D" 90 The line connecting the origin and the reservoir is used as the "plugging baseline". The "plugging curve" in this embodiment is implemented as follows: Based on the fracture aperture range of 0~6.0mm determined in the third step, the maximum pore throat and fracture size of 6.0mm are obtained, which is the D of the plugging agent particles. 90 Value, in "cumulative volume percentage - d" 1 / 2 On the curve, determine the horizontal coordinate as (D). 90 ) ½ The point at 2.45, where the vertical axis represents the 90% mark, connected to the origin, forms the "plugging baseline." The closer the cumulative distribution curve of the plugging agent particle size is to the baseline, the higher the particle packing efficiency and the better the plugging effect. For example... Figure 7 As shown, draw D 90 The target curve is determined by selecting commonly used sealing materials in the field and adjusting the particle size and dosage to achieve a cumulative particle size distribution similar to... Figure 7 The theoretical cumulative particle size distribution is basically consistent, forming a formula for a crack-type leakage plugging agent suitable for the region. The specific implementation formula is shown in Table 1 below:

[0087] Table 1

[0088]

[0089] Then, the crack range was selected as the joint plate, and a pressure-bearing sealing test was conducted on the optimized formula to verify whether it met the design pressure requirements. The sealing slurry was prepared as follows: 200g of each example was added to 1L of base slurry and stirred evenly; the base slurry was prepared as follows: water + 4% sodium bentonite (by weight of water) + 3.5% sodium carbonate (by weight of sodium bentonite) + 0.2% XC (by weight of water), stirred evenly, and allowed to stand for 24 hours before use. The sealing results are shown in Table 2 below.

[0090] Table 2

[0091]

[0092] Experimental results show that the selected composite sealant can effectively remain within the cracks of the determined interval width, forming a long, high-strength sealing layer. Simulation data from crack blocks indicate that the composite sealant easily enters the leakage channel, has a long effective retention length, and exhibits high pressure resistance in the sealing layer, meeting the requirements for on-site operations.

[0093] refer to Figure 8 The present application also discloses a leak-sealing agent design device, comprising:

[0094] The data processing module 11 is used to acquire well logging data of drilled wells in the target area, and process the well logging data using the fracture indicator parameter method to obtain the target fracture exponential function.

[0095] The function generation module 12 is used to collect fracture parameters of fractures of various scales that have been drilled in the target area, and to determine the normal distribution function corresponding to the fracture aperture in the area based on the fracture parameters and the target fracture exponential function.

[0096] The interval determination module 13 is used to obtain the percentage setting instruction and determine the crack aperture interval range of the target crack based on the percentage setting instruction and the normal distribution function;

[0097] Formula production module 14 is used to generate several formulas for crack-related leakage plugging agents based on the crack opening range and ideal filling theory.

[0098] The pressure-bearing leakage sealing test module 15 is used to conduct pressure-bearing leakage sealing tests on the plurality of cracked leakage sealing agent formulations to obtain the pressure-bearing test results corresponding to each cracked leakage sealing agent formulation, and to determine the target cracked leakage sealing agent formulation from the plurality of cracked leakage sealing agent formulations based on the pressure-bearing test results to obtain the target sealing agent.

[0099] It is evident that by collecting data such as imaging logging to establish the target fracture exponential function, and combining it with fracture parameters of various scales extracted from logging data, a normal distribution function of regional fracture aperture can be obtained. Based on this, and considering the characteristics of the plugging material, an appropriate ratio design can be carried out. By predicting the leakage fracture aperture, a basis can be provided for the formulation design of fracture plugging agents. This provides drilling plugging technicians and construction personnel with a more accurate and effective decision-making basis, thereby improving the efficiency of fracture plugging work, increasing the success rate of plugging operations, and avoiding repeated operations.

[0100] In some specific embodiments, the data processing module 11 may specifically include:

[0101] The target data extraction unit is used to extract each target data from the well logging data of the drilled wells in the acquired target area, and to determine the fracture composite index and fractal dimension of the well logging curve corresponding to each target data.

[0102] The data calculation unit is used to substitute the crack comprehensive index and the fractal dimension into the preset crack index calculation formula to determine the target crack index function.

[0103] In some specific embodiments, the data processing module 11 may specifically include:

[0104] The data extraction unit is used to extract target data from the well logging data of the drilled wells in the target area, and to perform data cleaning and data normalization operations to obtain the fracture composite index of each well logging curve.

[0105] The first weight value determination unit is used to determine the first weight value based on the corresponding fracture response degree of each well logging curve;

[0106] The second weight value determination unit is used to calculate the fractal dimension corresponding to each of the target data using the rescaled range analysis method, and determine the corresponding second weight value based on the fractal dimension.

[0107] The function confirmation unit is used to substitute the fracture comprehensive index, the first weight value, the fractal dimension and the second weight value into the preset fracture index calculation formula to obtain the fracture index function corresponding to each logging curve;

[0108] The function integration unit is used to integrate the crack exponential function based on a preset formula to obtain the target crack exponential function.

[0109] In some specific embodiments, the function generation module 12 can be used to collect fracture parameters corresponding to fractures of various scales that have been drilled in the target area, and construct a corresponding fractured formation porosity and fracture aperture model based on the fracture parameters and the target fracture exponential function, and determine the corresponding normal distribution function based on the fractured formation porosity and fracture aperture model.

[0110] In some specific embodiments, the formula production module 14 may specifically include:

[0111] The particle size confirmation unit is used to determine the empirical rules for the particle size of the plugging agent based on the crack opening range and the ideal filling theory.

[0112] The formulation generation submodule is used to determine the particle size range based on the empirical rules of particle size, and generate several crack-related leakage plugging agent formulations within the particle size range.

[0113] In some specific embodiments, the recipe generation submodule may specifically include:

[0114] The material selection unit is used to determine a particle size range based on the empirical rules for particle size, and to select a target sealing material from the preset sealing materials within the particle size range; the preset sealing materials include bridging materials, filler materials, fiber materials and deformable materials;

[0115] The material mixing unit is used to determine the material mixing ratio corresponding to the target sealing material according to the material properties of the target sealing material, and to generate several crack-related leakage plugging agent formulations according to the material mixing ratio.

[0116] In some specific embodiments, the formula production module 14 may specifically include:

[0117] The material preparation unit is used to prepare the target sealing material according to the preset sealing slurry preparation method and the material mixing ratio to prepare the post-sealing agent;

[0118] The formulation experiment unit is used to select a target crack plate based on the crack opening range, and to conduct a pressure-bearing sealing experiment on the configured sealing agent using the target crack plate, so as to obtain the pressure-bearing experiment results corresponding to each cracked leakage layer sealing agent formulation.

[0119] Furthermore, embodiments of this application also disclose an electronic device, Figure 9 This is a structural diagram of an electronic device 20 according to an exemplary embodiment. The content of the diagram should not be construed as limiting the scope of this application.

[0120] Figure 9 This is a schematic diagram of the structure of an electronic device 20 provided in an embodiment of this application. Specifically, the electronic device 20 may include: at least one processor 21, at least one memory 22, a power supply 23, a communication interface 24, an input / output interface 25, and a communication bus 26. The memory 22 stores a computer program, which is loaded and executed by the processor 21 to implement the relevant steps in the sealant design method disclosed in any of the foregoing embodiments. Alternatively, the electronic device 20 in this embodiment may specifically be a computer.

[0121] In this embodiment, the power supply 23 is used to provide operating voltage for each hardware device on the electronic device 20; the communication interface 24 can create a data transmission channel between the electronic device 20 and external devices, and the communication protocol it follows can be any communication protocol applicable to the technical solution of this application, and is not specifically limited here; the input / output interface 25 is used to acquire external input data or output data to the outside world, and its specific interface type can be selected according to specific application needs, and is not specifically limited here.

[0122] In addition, the memory 22, as a carrier for resource storage, can be a read-only memory, random access memory, disk or optical disk, etc. The resources stored thereon can include operating system 221, computer program 222, etc., and the storage method can be temporary storage or permanent storage.

[0123] The operating system 221 is used to manage and control the various hardware devices on the electronic device 20 and the computer program 222, which may be Windows Server, Netware, Unix, Linux, etc. In addition to including a computer program capable of performing the sealant design method executed by the electronic device 20 as disclosed in any of the foregoing embodiments, the computer program 222 may further include a computer program capable of performing other specific tasks.

[0124] Furthermore, this application also discloses a computer-readable storage medium for storing a computer program; wherein, when the computer program is executed by a processor, it implements the aforementioned leak-sealing agent design method. Specific steps of this method can be found in the corresponding content disclosed in the foregoing embodiments, and will not be repeated here.

[0125] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on its differences from other embodiments. Similar or identical parts between embodiments can be referred to interchangeably. For the apparatus disclosed in the embodiments, since it corresponds to the method disclosed in the embodiments, the description is relatively simple; relevant parts can be referred to in the method section.

[0126] Those skilled in the art will further recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of both. To clearly illustrate the interchangeability of hardware and software, the components and steps of the various examples have been generally described in terms of functionality in the foregoing description. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0127] The steps of the methods or algorithms described in conjunction with the embodiments disclosed herein can be implemented directly by hardware, a software module executed by a processor, or a combination of both. The software module can be located in random access memory (RAM), main memory, read-only memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disk, removable disk, CD-ROM, or any other form of storage medium known in the art.

[0128] Finally, it should be noted that in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0129] The technical solutions provided in this application have been described in detail above. Specific examples have been used to illustrate the principles and implementation methods of this application. The descriptions of the above embodiments are only for the purpose of helping to understand the methods and core ideas of this application. At the same time, for those skilled in the art, there will be changes in the specific implementation methods and application scope based on the ideas of this application. Therefore, the content of this specification should not be construed as a limitation of this application.

Claims

1. A method for designing a sealant, characterized in that, include: Obtain logging data from drilled wells within the target area, and process the logging data using the fracture indicator parameter method to obtain the target fracture exponential function; Collect fracture parameters of fractures at various scales in the drilled wells within the target area, and determine the normal distribution function corresponding to the fracture aperture in the area based on the fracture parameters and the target fracture exponential function; Obtain the percentage setting instruction, and determine the crack aperture range of the target crack based on the percentage setting instruction and the normal distribution function; Several formulas for sealing agents to plug cracked layers are generated based on the crack aperture range and the ideal filling theory. Pressure testing was conducted on the several cracked leakage plugging agent formulations to obtain the pressure test results corresponding to each cracked leakage plugging agent formulation. Based on the pressure test results, a target cracked leakage plugging agent formulation was determined from the several cracked leakage plugging agent formulations to obtain the target plugging agent.

2. The sealing agent design method according to claim 1, characterized in that, The process of acquiring logging data from drilled wells within the target area and processing the logging data using the fracture indicator parameter method to obtain the target fracture exponential function includes: Extract each target data from the well logging data of the drilled wells within the target area, and determine the fracture composite index and fractal dimension of the well logging curve corresponding to each target data. The comprehensive crack index and the fractal dimension are substituted into the preset crack index calculation formula to determine the target crack index function.

3. The sealing agent design method according to claim 2, characterized in that, The process involves extracting target data from the well logging data of drilled wells within the target area and determining the fracture composite index and fractal dimension of the well logging curve corresponding to each target data. Substituting the comprehensive crack index and the fractal dimension into a preset crack index calculation formula to determine the target crack index function includes: Target data is extracted from the logging data of drilled wells within the target area, and data cleaning and normalization operations are performed to obtain the fracture composite index of each logging curve. The first weight value is determined based on the degree of fracture response corresponding to each of the aforementioned logging curves; The fractal dimension of each target data is calculated using the rescaled range analysis method, and the corresponding second weight value is determined based on the fractal dimension. Substitute the fracture composite index, the first weight value, the fractal dimension, and the second weight value into the preset fracture index calculation formula to obtain the fracture index function corresponding to each well logging curve; The crack exponential function is integrated based on a preset formula to obtain the target crack exponential function.

4. The sealing agent design method according to claim 1, characterized in that, The process of collecting fracture parameters of various scales from drilled fractures within the target area, and determining the normal distribution function corresponding to the fracture aperture in the region based on the fracture parameters and the target fracture exponential function, includes: Collect fracture parameters corresponding to fractures of various scales that have been drilled in the target area, and construct a corresponding fractured formation porosity and fracture aperture model based on the fracture parameters and the target fracture exponential function, and determine the corresponding normal distribution function based on the fractured formation porosity and fracture aperture model.

5. The method for designing a sealing agent according to any one of claims 1 to 4, characterized in that, The process involves generating several formulations of sealant for cracked leakage layers based on the crack aperture range and ideal filling theory, including: Empirical rules for determining the particle size of the sealing agent are based on the crack aperture range and the ideal filling theory. Based on the empirical rules for particle size, a particle size range is determined, and several crack-forming agent formulations are generated within the particle size range.

6. The method for designing a sealing agent according to claim 5, characterized in that, The process of determining the particle size range based on empirical rules and generating several crack-related leakage plugging agent formulations within the particle size range includes: The particle size range is determined based on the empirical rules for particle size, and a target sealing material is selected from the preset sealing materials within the particle size range; the preset sealing materials include bridging materials, filler materials, fiber materials, and deformable materials; The material mixing ratio corresponding to the target sealing material is determined based on the material properties of the target sealing material, and several crack leakage plugging agent formulations are generated based on the material mixing ratio.

7. The sealing agent design method according to claim 6, characterized in that, The step of conducting pressure-bearing sealing tests on the plurality of cracked leakage plugging agent formulations to obtain the pressure-bearing test results corresponding to each cracked leakage plugging agent formulation includes: The target sealing material is prepared according to the preset sealing grout preparation method and the material mixing ratio to prepare the subsequent sealing agent; Based on the crack opening range, a target crack plate is selected, and a pressure-bearing sealing test is conducted on the prepared sealing agent using the target crack plate to obtain the pressure-bearing test results corresponding to each cracked leakage layer sealing agent formulation.

8. A sealing agent design device, characterized in that, include: The data processing module is used to acquire well logging data of drilled wells in the target area and process the well logging data using the fracture indicator parameter method to obtain the target fracture exponential function. The function generation module is used to collect fracture parameters of fractures at various scales in the drilled wells within the target area, and to determine the normal distribution function corresponding to the fracture aperture in the area based on the fracture parameters and the target fracture exponential function. The interval determination module is used to obtain the percentage setting instruction and determine the crack aperture interval range of the target crack based on the percentage setting instruction and the normal distribution function; The formulation production module is used to generate several formulations of crack-related leakage plugging agents based on the crack opening range and the ideal filling theory. The pressure-bearing leakage sealing test module is used to conduct pressure-bearing leakage sealing tests on the plurality of cracked leakage sealing agent formulations to obtain the pressure-bearing test results corresponding to each cracked leakage sealing agent formulation, and to determine the target cracked leakage sealing agent formulation from the plurality of cracked leakage sealing agent formulations based on the pressure-bearing test results to obtain the target sealing agent.

9. An electronic device, characterized in that, include: Memory, used to store computer programs; A processor for executing the computer program to implement the plugging agent design method as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, Used to store a computer program, which, when executed by a processor, implements the plugging agent design method as described in any one of claims 1 to 7.

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