Method, device and equipment for determining sand adding parameters in fracturing operation and medium

Abstract

The embodiment of the invention discloses a sand adding parameter determining method and device for fracturing operation, equipment and a medium. The method comprises the steps that the sand adding concentration, the sand adding amount and the sand adding sequence serve as variables, and according to the target proppant settling velocity and the geometric morphology of a crack, based on at least two candidate sand adding processes, the geometric morphology of a sand bank, the sand paving efficiency and the pressure at a crack inlet are preliminarily simulated; a target sand adding process is selected from the candidate sand adding processes according to the preliminary simulation result, and path information and crack width information of a target propping agent before the target propping agent enters the crack are increased for secondary simulation; and determining different sand adding concentrations, sand adding amounts, sand adding sequences, fracture geometrical shapes, and a function relationship between the target sand paving efficiency and the target effective fracture length, and determining sand adding parameters according to the function relationship. According to the scheme, the distribution and flow characteristics of the propping agent can be effectively controlled, the length of an effective supporting seam is increased, and the overall efficiency of fracturing operation is improved.

Description

Technical Field

[0001] This application relates to the field of petroleum engineering technology, and in particular to a method, apparatus, equipment and medium for determining sand addition parameters in fracturing operations. Background Technology

[0002] In the development of deep and ultra-deep shale gas, fracturing is one of the key technologies for improving oil and gas production. Currently, commonly used proppant design methods in the industry mainly suffer from problems such as uneven proppant deposition, sand blockage, and insufficient fluidity. These problems directly restrict the improvement of fracturing effectiveness. Traditional proppant techniques often cannot adapt to complex geological conditions, resulting in insufficient effective proppant fracture length, which in turn affects oil and gas fluidity and recovery rates. Furthermore, existing design methods lack effective control over proppant distribution and flow characteristics during implementation, leading to low overall fracturing efficiency, prolonged construction time, and increased operational risks and costs. Summary of the Invention

[0003] This application provides a method, apparatus, equipment, and medium for determining proppant addition parameters in fracturing operations, so as to effectively control the distribution and flow characteristics of proppant, increase the length of effective propped fractures, and improve the overall efficiency of fracturing operations.

[0004] According to one aspect of this application, a method for determining sand addition parameters in fracturing operations is provided, the method comprising:

[0005] Using sand concentration, sand amount, and sand addition sequence as variables, preliminary simulations of sandbank geometry, sand spreading efficiency, and pressure at crack inlet were conducted based on at least two candidate sand addition processes, according to the target proppant settling velocity and crack geometry. Among these, at least one of the at least two candidate sand addition processes was a water-binding sand attack process.

[0006] Based on the preliminary simulation results, a target sand addition process is selected from the candidate sand addition processes. The path information of the target proppant before entering the crack and the crack width information are added. The sand addition concentration, sand addition amount and sand addition sequence are used as variables. Based on the target proppant settling velocity, crack geometry and target process, the sand embankment geometry, sand laying efficiency and crack inlet pressure are simulated again.

[0007] Based on the results of the re-simulation, the target sand-laying efficiency and the target effective fracture length are determined. The functional relationship between different sand concentrations, sand amounts, sand-laying sequences, fracture geometries, target sand-laying efficiency, and target effective fracture length is determined. Based on the functional relationship, the sand-laying parameters in the fracturing operation are determined.

[0008] According to one aspect of this application, a device for determining sand addition parameters in fracturing operations is provided, the device comprising:

[0009] The preliminary simulation module is used to simulate the sand embankment geometry, sand laying efficiency, and pressure at the crack inlet based on at least two candidate sand addition processes, taking sand concentration, sand addition amount, and sand addition sequence as variables, and according to the target proppant settling velocity and crack geometry. Among them, at least one of the at least two candidate sand addition processes is the water-binding sand attack process.

[0010] The re-simulation module is used to select the target sand addition process from the candidate sand addition processes based on the preliminary simulation results, add the path information of the target proppant before entering the crack and the crack width information, use the sand addition concentration, sand addition amount and sand addition sequence as variables, and re-simulate the sand dike geometry, sand laying efficiency and crack inlet pressure based on the target proppant settlement velocity, crack geometry and target process.

[0011] The sand addition parameter determination module is used to determine the target sand spreading efficiency and the target effective fracture length based on the results of the re-simulation, determine the functional relationship between different sand addition concentrations, sand addition amounts, sand addition sequences, fracture geometry and the target sand spreading efficiency and target effective fracture length, and determine the sand addition parameters in the fracturing operation based on the functional relationship.

[0012] According to another aspect of this application, an electronic device is provided, the electronic device comprising:

[0013] At least one processor; and

[0014] Memory connected to at least one processor for data processing; wherein,

[0015] The memory stores a computer program that can be executed by at least one processor, such that the at least one processor is able to perform the sand addition parameter determination method in fracturing operations according to any embodiment of this application.

[0016] According to another aspect of this application, a computer-readable storage medium is provided, which stores computer instructions for causing a processor to execute the method for determining sand addition parameters in fracturing operations according to any embodiment of this application.

[0017] The technical solution of this application embodiment uses proppant concentration, proppant quantity, and proppant order as variables. Based on the target proppant settling velocity and fracture geometry, preliminary simulations are performed on the sandbank geometry, proppant spreading efficiency, and fracture inlet pressure using at least two candidate proppant adding processes. Among the at least two candidate proppant adding processes, at least one water-binding sand-attacking process is included. Based on the preliminary simulation results, a target proppant adding process is selected from the candidate processes. The path information of the target proppant before entering the fracture and the fracture width information are added. Propant concentration, proppant quantity, and proppant order are used as variables. Based on the target proppant settling velocity, fracture geometry, and target process, the sandbank geometry, proppant spreading efficiency, and fracture inlet pressure are simulated again. Based on the results of the second simulation, the target proppant spreading efficiency and target effective fracture length are determined. The functional relationships between different proppant concentrations, proppant quantities, proppant orders, fracture geometry, target proppant spreading efficiency, and target effective fracture length are determined. The proppant adding parameters in the fracturing operation are determined based on these functional relationships. The above-mentioned scheme can effectively control the distribution and flow characteristics of proppant, increase the length of effective propped fractures, and improve the overall efficiency of fracturing operations.

[0018] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of this application, nor is it intended to limit the scope of this application. Other features of this application will become readily apparent from the following description. Attached Figure Description

[0019] To more clearly illustrate the technical solutions in the embodiments of this application, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0020] Figure 1 A flowchart illustrating a method for determining proppant addition parameters in fracturing operations, provided as an embodiment of this application;

[0021] Figure 2 A flowchart illustrating a method for determining proppant addition parameters in fracturing operations, provided as another embodiment of this application;

[0022] Figure 3 A flowchart of a method for determining sand addition parameters in fracturing operations is provided as another embodiment of this application;

[0023] Figure 4 This is a schematic diagram of a device for determining sand addition parameters in fracturing operations, provided in an embodiment of this application.

[0024] Figure 5 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Detailed Implementation

[0025] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present application, and not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative effort should fall within the scope of protection of the present application.

[0026] It should be noted that the terms "first," "second," "third," "fourth," "actual," "preset," etc., used in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0027] Figure 1 This application provides a flowchart of a method for determining proppant addition parameters in fracturing operations, applicable to situations where proppant addition parameters are selected and optimized in fracturing operations. This method can be executed by a proppant addition parameter determining device, which can be implemented in hardware and / or software and can be configured in an electronic device. Figure 1 As shown, the method includes:

[0028] S110. Using sand concentration, sand amount, and sand addition sequence as variables, and based on the target proppant settling velocity and crack geometry, conduct preliminary simulations of the sand embankment geometry, sand laying efficiency, and pressure at the crack inlet based on at least two candidate sand addition processes; wherein, at least one of the at least two candidate sand addition processes includes the water-binding sand attack process.

[0029] In the petroleum industry, proppant fracturing refers to a method used in oil extraction where hydraulic fracturing technology is employed to inject a high-viscosity fluid (fracturing fluid) into the well using a high-pressure pump, creating fractures. Propane (sand) is then filled into these fractures to support them, thereby forming a channel for oil and gas flow within the formation. In deep oil and gas well development, after fracturing in high-pressure, low-permeability deposits, the oil-bearing rock formations are fractured, and oil and gas converge through the channels formed by the fractures. At this point, fluid needs to be injected into the rock base layer at pressures exceeding the formation's fracturing strength to create fractures in the surrounding rock layers, forming a channel with high-level flow capacity. To maintain the openness of the fractures and ensure the smooth flow of oil and gas products, proppant is injected into the rock fractures along with the high-pressure solution. This proppant prevents the fractures from closing due to stress release, maintaining high conductivity, ensuring smooth oil and gas flow, and increasing production. In fracturing operations, the target proppant settling velocity and fracture geometry are fixed parameters that can generally be predetermined. Propane concentration, proppant quantity, and proppant addition sequence are variables that can be adjusted. Different proppant concentrations, quantities, and sequences may lead to different fracturing effects. Parameters reflecting fracturing effectiveness include proppant geometry, proppant application efficiency, and pressure at the fracture inlet. Various proppant addition techniques can exist, and different techniques may yield different fracturing results.

[0030] In this embodiment, based on at least two candidate sand-addition processes, and using fixed parameters such as target proppant settling velocity and crack geometry, as well as controlled variables such as sand concentration, sand amount, and sand-addition sequence, simulations can be performed to determine the sandbank geometry, sand-laying efficiency, and pressure at the crack inlet under different candidate sand-addition processes. This approach allows for a clear and intuitive comparison of the effects of different candidate sand-addition processes, enabling the selection of a suitable process.

[0031] S120. Based on the preliminary simulation results, select the target sand addition process from the candidate sand addition processes, add the path information of the target proppant before entering the crack and the crack width information, take the sand addition concentration, sand addition amount and sand addition sequence as variables, and simulate the sand embankment geometry, sand laying efficiency and crack inlet pressure again based on the target proppant settlement velocity, crack geometry and target process.

[0032] For example, a target sand-adding process can be selected from the candidate sand-adding processes based on the preliminary simulation results, and then fine-grained simulation can be continued based on the target sand-adding process.

[0033] Specifically, in the fine-grained re-simulation based on the target sand-addition process, the specific sand-addition process is refined, adding information on the path of the target proppant before entering the crack and the crack width, thereby simulating the entire sand-addition process. Similarly, sand concentration, sand-addition amount, and sand-addition sequence are used as variables, while proppant settling velocity and crack geometry are used as fixed parameters for re-simulation, determining the sandbank geometry, sand-laying efficiency, and pressure at the crack inlet under the target sand-addition process.

[0034] S130. Based on the results of the re-simulation, determine the target sand-laying efficiency and the target effective fracture length. Determine the functional relationship between different sand concentrations, sand amounts, sand-laying sequences, fracture geometries, target sand-laying efficiency, and target effective fracture length. Based on the functional relationship, determine the sand-laying parameters in the fracturing operation.

[0035] For example, the target sand-laying efficiency and target effective fracture length can be calculated based on the re-simulation results. These two parameters most directly reflect the fracturing effect. The sand concentration, sand-laying amount, sand-laying sequence, and fracture geometry corresponding to the re-simulation results are determined. Each re-simulation result yields a set of correspondences between sand concentration, sand-laying amount, sand-laying sequence, fracture geometry, and the target sand-laying efficiency and target effective fracture length. Multiple sets of re-simulation results yield multiple sets of correspondences. Fitting these relationships yields a functional relationship between sand concentration, sand-laying amount, sand-laying sequence, fracture geometry, target sand-laying efficiency, and target effective fracture length. Based on this functional relationship, the sand-laying parameters in fracturing operations can be determined.

[0036] The technical solution of this application embodiment determines a coefficient matrix based on the correlation data of temperature, pressure, and density obtained from experimental testing of the base fluid, and determines the relationship between temperature, pressure, and density of the base fluid based on the coefficient matrix; it then determines a temperature, pressure, and density relationship model of the drilling fluid based on the relationship model, the initial density and initial volume of the base fluid, and the initial density of the drilling fluid; finally, it determines an error term based on the pre-detected actual density of the drilling fluid and the predicted density of the drilling fluid obtained based on the temperature, pressure, and density relationship model, and corrects the model based on the error term. This solution can effectively control the distribution and flow characteristics of the proppant, increase the length of the effective propped fracture, and improve the overall efficiency of fracturing operations.

[0037] Figure 2 This document provides a flowchart of a method for determining proppant addition parameters in fracturing operations, as another embodiment of this application. This embodiment is an optimization based on the above embodiment; solutions not described in detail in this embodiment are found in the above embodiment. Figure 2 As shown, the method in this embodiment of the application specifically includes the following steps:

[0038] S210. Obtain the Reynolds number, dimensionless diameter, drag coefficient, liquid density, proppant diameter, and corresponding settling velocity of the test proppant determined by preliminary tests.

[0039] For example, experiments can be conducted in advance to determine the Reynolds number, dimensionless diameter, drag coefficient, liquid density, proppant diameter, and corresponding experimental proppant settling velocity of the test proppant.

[0040] S220. The Reynolds number, dimensionless diameter, drag coefficient, liquid density, proppant diameter, and corresponding experimental proppant settling velocity of the experimental proppant are used as training and testing samples to train the neural network and obtain the proppant settling velocity determination model.

[0041] A subset of data on the Reynolds number, dimensionless diameter, drag coefficient, liquid density, proppant diameter, and corresponding settling velocity of the experimental proppant were used as training samples to train the neural network model. The same data were then used as test samples to test the trained neural network model. Under the condition that the test conditions were met, a proppant settling velocity determination model was obtained.

[0042] S230. Input the Reynolds number, dimensionless diameter, drag coefficient, liquid density, and proppant diameter of the target proppant into the proppant settling velocity determination model to determine the target proppant settling velocity.

[0043] For the target proppant used in the current simulation, the Reynolds number, dimensionless diameter, drag coefficient, liquid density, and proppant diameter of the target proppant are input into the proppant settling velocity determination model to determine the target proppant settling velocity.

[0044] Specifically, this application conducts a series of experiments to analyze the influence of Reynolds number, dimensionless diameter, drag coefficient, liquid density, and proppant diameter on proppant settling velocity. Based on the above characteristics, machine learning algorithms such as physical neural networks are used to establish an explicit calculation model for proppant settling velocity suitable for transport within a slit, which greatly improves the accuracy of the simulation effect.

[0045] Dimensionless parameter diameter D r There is a linear relationship between the proppant number and the Reynolds number (Re). Therefore, A and B are determined through a series of experiments, and the settling velocity of the proppant is then calculated based on the particle Reynolds number. The specific formula is as follows:

[0046]

[0047] A = 6.9148(n) 2-24.838(n) + 22.642;

[0048] B = -0.5067(n) 2 )+1.3234(n)-0.1744;

[0049]

[0050] In the formula:

[0051] C d — Drag coefficient; Re— Particle Reynolds number;

[0052] d p —Prop diameter, m; v t —Settlement velocity, m / s;

[0053] ρ p —Prop density, kg / m³; ρ f —Liquid density, kg / m3;

[0054] n—flow behavior index; K—consistency index, Pa·Sn;

[0055] A—Parameter A; B—Parameter B.

[0056] S240. Using sand concentration, sand amount, and sand addition sequence as variables, and based on the target proppant settling velocity and crack geometry, conduct preliminary simulations of the sand embankment geometry, sand laying efficiency, and pressure at the crack inlet based on at least two candidate sand addition processes; wherein, at least one of the at least two candidate sand addition processes includes the water-binding sand attack process.

[0057] For example, a numerical model of proppant transport within the crack is established:

[0058] Fluid flow can be described by the Navier-Stokes equations. Considering incompressible fluids, the equations are as follows:

[0059]

[0060] In the formula:

[0061] u: fluid velocity vector; P: fluid pressure; ρ f ν: fluid density; g: fluid dynamic viscosity; g: gravitational acceleration; the motion of particles can be described by Newton's second law.

[0062]

[0063] In the formula: v: particle velocity; F drag : Fluid resistance to particles; F gravity : The gravitational force acting on the particle; F contact: Contact force between particles; m is the mass of a single proppant particle, kg.

[0064] When particles move in a fluid, the resistance of the fluid to the particles is usually calculated using the following formula:

[0065]

[0066] In the formula: d is the diameter of the proppant, in meters.

[0067] The contact force between particles is described by Hooke's Law:

[0068]

[0069] Where: k: contact stiffness; δ: overlap distance between particles; γ: damping coefficient; Contact normal unit vector.

[0070] Based on the above equations, the initial velocity field, pressure field, and initial position and velocity of the particles are defined; appropriate boundary conditions are set according to the geometric characteristics of the crack; different working conditions and parameters are set to simulate the proppant migration process in the crack.

[0071] S250. Calculate the effective seam length based on the preliminary simulation results corresponding to each candidate sand-adding process.

[0072] For example, the effective joint length can be calculated for each preliminary simulation result obtained based on the candidate sand-addition process. Specifically, the bottom diameter of the sandbank geometry in the preliminary simulation results can be used as the effective joint length.

[0073] S260. The candidate sanding process corresponding to the largest effective seam length is taken as the target sanding process.

[0074] The effective fracture length is the most intuitive parameter for evaluating the fracturing effect. The largest effective fracture length can be selected, and the candidate sand addition process corresponding to the largest effective fracture length can be determined as the target sand addition process.

[0075] Candidate sand-addition processes include conventional continuous sand-addition, combined proppant sand-addition, and water-constriction sand-addition. The water-constriction sand-addition process is an optimization of the combined proppant sand-addition process. The combined proppant sand-addition process involves sequentially injecting small-diameter proppant and large-diameter proppant to gradually form a sand embankment. However, according to the proppant migration model, after the small-diameter proppant is injected, its slow settling velocity means that if a sand embankment is not formed before the large-diameter proppant is injected, the large-diameter proppant will be entrained by the large-diameter proppant due to its much higher settling velocity. This results in a loss of conductivity, and the large-diameter proppant migrates a significantly shorter distance than the small-diameter proppant, leading to a shorter effective prop joint length after the crack closes. Therefore, based on the concept of "water-constricted sand attack," a low-displacement, high-concentration, and appropriately sized large-particle-size proppant was first adopted to rapidly form a sand embankment of a certain height at the crack inlet. Pressure changes were monitored in real time to prevent the sand embankment from blocking the entire crack. The sand embankment of a certain height within the crack significantly reduces the flow area. With the same injection displacement, the subsequently injected proppant, due to the reduced flow area, indirectly increases its migration velocity. Furthermore, because the subsequently injected proppant is a small-particle-size proppant, its slow settling velocity results in a sand embankment length far exceeding that of other sand addition processes. Simultaneously, the high-speed flow of the small-particle-size proppant has a cutting effect on the sand embankment formed by the large-particle-size proppant, further increasing its length. Through these two effects, the effective propped crack length formed after crack closure is extended. Based on this, the water-constricted sand attack sand addition process can be considered the target sand addition process.

[0076] S270. Add path information of the target proppant before entering the crack and crack width information, and use sand concentration, sand amount, and sand order as variables. Based on the settlement velocity of the target proppant, crack geometry, and target process, simulate the sand embankment geometry, sand laying efficiency, and pressure at the crack inlet again.

[0077] S280. Based on the results of the re-simulation, determine the target sand-laying efficiency and the target effective fracture length. Determine the functional relationship between different sand concentrations, sand amounts, sand-laying sequences, fracture geometry, target sand-laying efficiency, and target effective fracture length. Based on the functional relationship, determine the sand-laying parameters in the fracturing operation.

[0078] This application provides a method for determining proppant addition parameters in fracturing operations. The method involves acquiring the Reynolds number, dimensionless diameter, drag coefficient, liquid density, proppant diameter, and corresponding settling velocity of a pre-tested proppant. These parameters are then used as training and testing samples to train a neural network, resulting in a proppant settling velocity determination model. Finally, the Reynolds number, dimensionless diameter, drag coefficient, liquid density, and proppant diameter of the target proppant are input into this model to determine the target proppant settling velocity. This method accurately calculates the target proppant settling velocity based on these parameters by training a neural network model to determine the proppant settling velocity. Furthermore, the target proppant addition process is selected from candidate proppant addition processes based on the effective fracture length, which most directly reflects the fracturing effect. This further enables effective control of the proppant distribution and flow characteristics, increases the effective propped fracture length, and improves the overall efficiency of fracturing operations.

[0079] Figure 3 This is a flowchart illustrating a method for determining proppant addition parameters in fracturing operations, provided as another embodiment of this application. This embodiment is an optimization based on the above embodiment; solutions not described in detail in this embodiment are found in the above embodiment. Figure 3 As shown, the method in this embodiment of the application specifically includes the following steps:

[0080] S310. Using sand concentration, sand amount, and sand addition sequence as variables, and based on the target proppant settling velocity and crack geometry, conduct preliminary simulations of the sand embankment geometry, sand laying efficiency, and pressure at the crack inlet using at least two candidate sand addition processes; wherein, at least one of the at least two candidate sand addition processes includes the water-binding sand attack process.

[0081] S320. Based on the preliminary simulation results, select the target sand addition process from the candidate sand addition processes, and add the pipeline information of the target proppant passing through the necking pipe before entering the crack and the crack width information; wherein, passing through the necking pipe includes passing through the casing, passing through the blast hole and the cement ring; the crack width is 3-8 mm.

[0082] For example, after determining the target sand-adding process, during the refined re-simulation based on the target sand-adding process, the simulation conditions can be further refined, adding information on the pipeline through which the target proppant passes before entering the crack, as well as information on the crack width; wherein, passing through the necking pipeline includes via the casing, through the blast hole, and through the cement ring; the crack width is 3-8 mm.

[0083] S330. The geometry of the crack is represented by the ratio of the crack width to its height.

[0084] For example, the crack geometry can be further quantified as the ratio of crack width to height.

[0085] S340. Using sand concentration, sand amount, and sand addition sequence as variables, and based on the target proppant settling velocity, crack geometry, and target process, the sand embankment geometry, sand laying efficiency, and pressure at the crack inlet are simulated again.

[0086] S350, Determine the geometry of the sand embankment and the sand-laying efficiency in the results of the resimulation.

[0087] S360. The bottom diameter of the sand embankment geometry is used as the target effective joint length, and the sand laying efficiency is used as the target sand laying efficiency.

[0088] For example, a sand embankment is generally approximately circular at the bottom, forming a pile shape. The diameter of the bottom can be used as the target effective seam length, and the sand-laying efficiency can be used as the target sand-laying efficiency.

[0089] S370. Using different sand concentrations, sand amounts, sand addition sequences, and crack geometry as independent variables, and the target sand spreading efficiency and target effective crack length as dependent variables, a relationship is fitted to obtain the aforementioned functional relationship.

[0090] For example, sand concentration, sand quantity, sand addition sequence, and crack geometry can be used as independent variables, and target sand spreading efficiency and target effective crack length as dependent variables. A relational analysis can be performed on multiple sets of data to obtain a functional relationship. Cluster analysis, analytic hierarchy process (AHP), and support vector machine (SVM) methods can then be used to fit the functional relationship.

[0091] S380. Solve for the sand addition parameters based on the functional relationship and the constraints on the dependent variable.

[0092] In this embodiment of the application, solving for the sand addition parameter based on the functional relationship and the constraints on the dependent variable includes:

[0093] Set the function relationship to its maximum value, and solve for the values ​​of the independent variables sand concentration, sand amount, and sand order, which are used as sand addition parameters in fracturing operations.

[0094] For example, when the functional relationship reaches its maximum value, that is, when the target effective seam length and the target sand laying efficiency are maximized, the values ​​of the independent variables sand concentration, sand amount, and sand laying order are solved, which is the optimal combination of sand laying parameters.

[0095] This application provides a method for determining proppant addition parameters in fracturing operations. It adds information about the target proppant passing through a necking conduit before entering the fracture, as well as the fracture width. The necking conduit includes passing through a casing, a borehole, and a cement sheath. The fracture width is 3-8 mm. The fracture geometry is represented by the ratio of fracture width to height. Propant concentration, proppant amount, and proppant addition sequence are used as variables. Based on the target proppant settling velocity, fracture geometry, and target process, the proppant geometry, proppant spreading efficiency, and fracture inlet pressure are simulated again. By adding conditions for re-simulation, the fracturing effect under different conditions is determined more accurately. The proppant geometry and proppant spreading efficiency in the re-simulation results are determined. The bottom diameter of the proppant geometry is used as the target effective fracture length, and the proppant spreading efficiency is used as the target proppant spreading efficiency. By using different sand concentrations, sand amounts, sand addition sequences, and crack geometry as independent variables, and the target sand spreading efficiency and target effective crack length as dependent variables, a relationship is fitted to obtain the functional relationship. Based on the functional relationship and the constraints on the dependent variables, the sand adding parameters are solved, thereby establishing an accurate physical model that represents the relationship between each independent variable and the sand spreading efficiency and target effective crack length, so as to obtain the optimized sand adding parameters by solving according to the constraints.

[0096] This application provides a specific implementation and effect of a method for determining proppant addition parameters in fracturing operations. This application's embodiments are based on and optimized from the above embodiments; schemes not described in detail in this application's embodiments are found in the above embodiments. The method of this application's embodiments specifically includes the following steps:

[0097] Example 1: Fracturing operations in deep shale gas wells

[0098] In the fracturing operation of a deep shale gas well (well number: A), the proppant design method described above was tested. The well has complex geological conditions, with multiple natural fractures and formations at different levels. Analysis showed that the effective proppant fracture length of the well was insufficient, resulting in weak production improvement.

[0099] Data Collection and Analysis: Prior to the operation, the team conducted a detailed analysis of the wellbore and surrounding formation using high-resolution geological imaging techniques (such as nuclear magnetic resonance imaging and ultrasonic scanning) to determine the specific location and characteristics of the fractures. Simultaneously, a fluid dynamics model was used to evaluate the impact of different fluid velocities and proppant types on fracture width and flowability.

[0100] Sand Addition Design: Based on the analysis results, a novel proppant delivery device was designed using the concept of water-constriction sand attack. This device can adjust the flow rate and delivery angle to form a uniform sand embankment within the crack, ensuring a large proppant area at the crack. The selected proppant is medium-coarse-grained quartz sand with an optimized particle size distribution to suit the flow characteristics of deep cracks.

[0101] Real-time monitoring and adjustment: During the actual construction process, a real-time monitoring system was used to record the pressure, flow rate, and proppant deposition status. Monitoring data showed that uneven proppant deposition occurred during the initial sand addition stage. The team immediately adjusted the flow rate of the conveying equipment and the proppant dosage to ensure uniform proppant distribution.

[0102] Construction Results: After the operation was completed, the gas production at the wellhead increased by 30%, and the effective support fracture length increased by 20%. Subsequent monitoring showed that the stability of the fractures was significantly improved, and the incidence of sand blockage decreased by 40%. The team concluded that the sand addition parameter determination method and fracturing method in this embodiment demonstrated good adaptability and effectiveness under these complex geological conditions.

[0103] Example 2: Ultra-deep shale gas development project

[0104] In a certain ultra-deep shale gas development project, facing the challenges of high pressure and low permeability, the traditional sand-addition method failed to meet the expected fracturing effect, resulting in project delays and increased costs.

[0105] Preliminary Preparation and Data Analysis: The project team first conducted a series of preliminary geological explorations, using seismic wave reflection and microseismic monitoring technologies to obtain detailed physical characteristics of the strata. Analysis results showed that the permeability of the fracturing section was uneven, and multiple intersecting natural fractures existed, which placed high demands on the effective deposition of proppant.

[0106] Sand Addition Scheme Development: To address the above issues, the team decided to adopt the sand addition parameter determination method described in this embodiment. By constructing a fluid dynamics model, the proppant delivery parameters were optimized. A high-performance proppant was selected, and a sand addition strategy based on multi-dimensional parameters was developed to ensure the stability and uniform distribution of the proppant within the fracture.

[0107] Construction Implementation: In actual construction, an innovative sand feeding and conveying device was adopted, enabling adjustable flow rate and direction control. Multiple simulations were conducted during construction, and combined with real-time data monitoring, the sand feeding strategy was adjusted in real time to ensure the effectiveness of each sand feeding. Finally, 40 / 70 mesh ceramsite was used to ensure its stability under high pressure.

[0108] Construction Results: This operation ultimately achieved a 25% increase in the effective support joint length, while simultaneously increasing wellhead gas production by 35%. Real-time monitoring showed almost no sand blockage, and construction costs were reduced by approximately 15%. The project team stated that the sand-addition design method of this invention is effective in ultra-deep and complex formations.

[0109] Figure 4 This is a schematic diagram of a device for determining proppant addition parameters in fracturing operations, provided in an embodiment of this application. This device can execute the proppant addition parameter determination method for fracturing operations provided in any embodiment of this application, and possesses the corresponding functional modules and beneficial effects of the method. Figure 4 As shown, the device includes:

[0110] The preliminary simulation module 410 is used to take sand concentration, sand amount, and sand order as variables, and perform preliminary simulations of sand embankment geometry, sand laying efficiency, and pressure at crack inlet based on at least two candidate sand addition processes, according to the target proppant settling velocity and crack geometry. Among them, at least one of the at least two candidate sand addition processes is the water-binding sand attack process.

[0111] The re-simulation module 420 is used to select the target sand addition process from the candidate sand addition processes based on the preliminary simulation results, add the path information of the target proppant before entering the crack and the crack width information, use the sand addition concentration, sand addition amount and sand addition sequence as variables, and re-simulate the sand embankment geometry, sand laying efficiency and crack inlet pressure based on the target proppant settlement velocity, crack geometry and target process.

[0112] The sand addition parameter determination module 430 is used to determine the target sand spreading efficiency and the target effective fracture length based on the results of the re-simulation, determine the functional relationship between different sand addition concentrations, sand addition amounts, sand addition sequences, fracture geometry and the target sand spreading efficiency and the target effective fracture length, and determine the sand addition parameters in the fracturing operation based on the functional relationship.

[0113] In this embodiment of the application, the method further includes:

[0114] The settling velocity determination module is used to obtain the Reynolds number, dimensionless diameter, drag coefficient, liquid density, proppant diameter, and corresponding settling velocity of the test proppant determined in the preliminary test.

[0115] The model determination module is used to train the neural network with the Reynolds number, dimensionless diameter, drag coefficient, liquid density, proppant diameter, and corresponding experimental proppant settling velocity as training and test samples to obtain the proppant settling velocity determination model.

[0116] The target proppant settling velocity determination module is used to input the Reynolds number, dimensionless diameter, drag coefficient, liquid density, and proppant diameter of the target proppant into the proppant settling velocity determination model to determine the target proppant settling velocity.

[0117] In the embodiments of this application, the candidate sand-adding processes include conventional continuous sand-adding process, combined proppant sand-adding process, and water-binding sand-adding process.

[0118] The re-simulation module 420 selects the target sand addition process from the candidate sand addition processes based on the preliminary simulation results, including:

[0119] The effective seam length is calculated based on the preliminary simulation results for each candidate sand-addition process.

[0120] The candidate sand-adding process corresponding to the largest effective seam length is taken as the target sand-adding process.

[0121] In this embodiment, the re-simulation module 420 adds path information of the target proppant before entering the crack and crack width information, uses sand concentration, sand amount, and sand addition sequence as variables, and re-simulates the sandbank geometry, sand spreading efficiency, and pressure at the crack inlet based on the target proppant settlement velocity, crack geometry, and target process, including:

[0122] Add information on the target proppant passing through the necked channel before entering the crack, as well as the crack width; where passing through the necked channel includes via the casing, through the blast hole, and through the cement sheath; the crack width is 3-8 mm.

[0123] The geometry of a crack is represented by the ratio of its width to its height.

[0124] Using sand concentration, sand amount, and sand addition sequence as variables, and based on the target proppant settling velocity, crack geometry, and target process, the geometry of the sand embankment, sand laying efficiency, and pressure at the crack inlet are simulated again.

[0125] In this embodiment of the application, the re-simulation module 420 determines the target sand-laying efficiency and the target effective joint length based on the re-simulation results, including:

[0126] Determine the sandbank geometry and sand-laying efficiency in the re-simulation results;

[0127] The target effective joint length is determined by the bottom diameter of the sand embankment geometry, and the sand-laying efficiency is determined by the sand-laying efficiency.

[0128] In this embodiment, the sand addition parameter determination module 430 determines the functional relationship between different sand addition concentrations, sand addition amounts, sand addition sequences, fracture geometry, target sand spreading efficiency, and target effective fracture length, and determines the sand addition parameters in the fracturing operation based on the said functional relationship, including:

[0129] By using different sand concentrations, sand amounts, sand addition sequences, and crack geometry as independent variables, and the target sand spreading efficiency and target effective crack length as dependent variables, the relationship was fitted to obtain the functional relationship.

[0130] The sand addition parameters are solved based on the functional relationship and the constraints on the dependent variable.

[0131] In this embodiment of the application, the sand addition parameter determination module 430 solves for the sand addition parameters based on the functional relationship and the constraints on the dependent variable, including:

[0132] Set the function relationship to its maximum value, and solve for the values ​​of the independent variables sand concentration, sand amount, and sand order, which are used as sand addition parameters in fracturing operations.

[0133] The device for determining sand addition parameters in fracturing operations provided in this application embodiment can execute the method for determining sand addition parameters in fracturing operations provided in any embodiment of this application, and has the corresponding functional modules and beneficial effects of the method.

[0134] Figure 5 A schematic diagram of the structure of an electronic device 10 that can be used to implement embodiments of this application is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices (such as helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the application described and / or claimed herein.

[0135] like Figure 5As shown, the electronic device 10 includes at least one processor 11 and a memory, such as a read-only memory (ROM) 12 or a random access memory (RAM) 13, connected to the at least one processor 11 for data processing. The memory stores computer programs executable by the at least one processor. The processor 11 can perform various appropriate actions and processes based on the computer program stored in the ROM 12 or loaded into the RAM 13 from storage unit 18. The RAM 13 can also store various programs and data required for the operation of the electronic device 10. The processor 11, ROM 12, and RAM 13 are interconnected via a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0136] Multiple components in electronic device 10 are connected to I / O interface 15, including: input unit 16, such as keyboard, mouse, etc.; output unit 17, such as various types of monitors, speakers, etc.; storage unit 18, such as disk, optical disk, etc.; and data processing unit 19, such as network card, modem, wireless data processing transceiver, etc. Data processing unit 19 allows electronic device 10 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0137] Processor 11 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of processor 11 include, but are not limited to, central processing unit (CPU), graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, digital signal processors (DSPs), and any suitable processor, controller, microcontroller, etc. Processor 11 performs the various methods and processes described above, such as the method for determining sand addition parameters in fracturing operations.

[0138] In some embodiments, the method for determining proppant addition parameters in fracturing operations may be implemented as a computer program tangibly contained in a computer-readable storage medium, such as storage unit 18. In some embodiments, part or all of the computer program may be loaded and / or installed on electronic device 10 via ROM 12 and / or data processing unit 19. When the computer program is loaded into RAM 13 and executed by processor 11, one or more steps of the method for determining proppant addition parameters in fracturing operations described above may be performed. Alternatively, in other embodiments, processor 11 may be configured to perform the method for determining proppant addition parameters in fracturing operations by any other suitable means (e.g., by means of firmware).

[0139] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-a-chip (SoCs), payload-programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0140] Computer programs used to implement the methods of this application may be written in any combination of one or more programming languages. These computer programs may be provided to the processor of a general-purpose computer, a special-purpose computer, or other programmable fracturing operation device for determining sand-addition parameters, such that when executed by the processor, the computer programs cause the functions / operations specified in the flowcharts and / or block diagrams to be implemented. The computer programs may be executed entirely on a machine, partially on a machine, or as a standalone software package, partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0141] In the context of this application, a computer-readable storage medium can be a tangible medium that may contain or store a computer program for use by or in conjunction with an instruction execution system, apparatus, or device. A computer-readable storage medium can be, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. Alternatively, a computer-readable storage medium can be a machine-readable signal medium. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, 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 devices, magnetic storage devices, or any suitable combination of the foregoing.

[0142] To provide interaction with a user, the systems and techniques described herein can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the electronic device. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0143] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as data servers), or computing systems that include middleware components (e.g., application servers), or computing systems that include frontend components (e.g., user computers with graphical user interfaces or web browsers through which users can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected through digital data processing (e.g., data processing networks) of any form or medium. Examples of data processing networks include local area networks (LANs), wide area networks (WANs), blockchain networks, and the Internet.

[0144] A computing system can include clients and servers. Clients and servers are generally geographically separated and typically interact via data processing networks. The client-server relationship is created by computer programs running on the respective computers and having a client-server relationship with each other. The server can be a cloud server, also known as a cloud computing server or cloud host, which is a hosting product within the cloud computing service system to address the shortcomings of traditional physical hosts and VPS services, such as high management difficulty and weak business scalability.

[0145] It should be understood that the various forms of processes shown above can be used to rearrange, add, or delete steps. For example, the steps described in this application can be executed in parallel, sequentially, or in different orders, as long as the desired information of the technical solution of this application can be achieved, and this is not limited herein.

[0146] The specific embodiments described above do not constitute a limitation on the scope of protection of this application. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this application should be included within the scope of protection of this application.

Claims

1. A method for determining proppant addition parameters in fracturing operations, characterized in that, The method includes: Using sand concentration, sand amount, and sand addition sequence as variables, preliminary simulations of sandbank geometry, sand spreading efficiency, and pressure at crack inlet were conducted based on at least two candidate sand addition processes, according to the target proppant settling velocity and crack geometry. Among these, at least one of the at least two candidate sand addition processes was a water-binding sand attack process. Based on the preliminary simulation results, a target sand addition process is selected from the candidate sand addition processes. The path information of the target proppant before entering the crack and the crack width information are added. The sand addition concentration, sand addition amount and sand addition sequence are used as variables. Based on the target proppant settling velocity, crack geometry and target process, the sand embankment geometry, sand laying efficiency and crack inlet pressure are simulated again. Based on the results of the re-simulation, the target sand-laying efficiency and the target effective fracture length are determined. The functional relationship between different sand concentrations, sand amounts, sand-laying sequences, fracture geometries, target sand-laying efficiency, and target effective fracture length is determined. Based on the functional relationship, the sand-laying parameters in the fracturing operation are determined.

2. The method according to claim 1, characterized in that, The process of determining the target proppant settling velocity includes: Obtain the Reynolds number, dimensionless diameter, drag coefficient, liquid density, proppant diameter, and corresponding settling velocity of the test proppant through preliminary experiments; The Reynolds number, dimensionless diameter, drag coefficient, liquid density, proppant diameter, and corresponding experimental proppant settling velocity of the experimental proppant were used as training and testing samples to train the neural network and obtain the proppant settling velocity determination model. The Reynolds number, dimensionless diameter, drag coefficient, liquid density, and proppant diameter of the target proppant are input into the proppant settling velocity determination model to determine the target proppant settling velocity.

3. The method according to claim 1, characterized in that, Candidate sand-addition processes include conventional continuous sand-addition process, combined proppant sand-addition process, and water-binding sand-addition process. Based on the preliminary simulation results, a target sand addition process is selected from the candidate sand addition processes, including: The effective seam length is calculated based on the preliminary simulation results for each candidate sand-addition process. The candidate sand-adding process corresponding to the largest effective seam length is taken as the target sand-adding process.

4. The method according to claim 1, characterized in that, The path information of the target proppant before entering the crack and the crack width information are added. Sand concentration, sand quantity, and sand addition sequence are used as variables. Based on the target proppant settlement velocity, crack geometry, and target process, the geometry of the sand embankment, sand spreading efficiency, and pressure at the crack inlet are simulated again, including: Add information on the target proppant passing through the necked channel before entering the crack, as well as the crack width; where passing through the necked channel includes via the casing, through the blast hole, and through the cement sheath; the crack width is 3-8 mm. The geometry of a crack is represented by the ratio of its width to its height. Using sand concentration, sand amount, and sand addition sequence as variables, and based on the target proppant settling velocity, crack geometry, and target process, the geometry of the sand embankment, sand laying efficiency, and pressure at the crack inlet are simulated again.

5. The method according to claim 1, characterized in that, The target sand-laying efficiency and target effective joint length are determined based on the results of the second simulation, including: Determine the sandbank geometry and sand-laying efficiency in the re-simulation results; The target effective joint length is determined by the bottom diameter of the sand embankment geometry, and the sand-laying efficiency is determined by the sand-laying efficiency.

6. The method according to claim 1, characterized in that, Determine the functional relationships between different sand concentrations, sand dosages, sand addition sequences, fracture geometries, target sand spreading efficiency, and target effective fracture length, and determine the sand addition parameters for fracturing operations based on these functional relationships, including: By using different sand concentrations, sand amounts, sand addition sequences, and crack geometry as independent variables, and the target sand spreading efficiency and target effective crack length as dependent variables, the relationship was fitted to obtain the functional relationship. The sand addition parameters are solved based on the functional relationship and the constraints on the dependent variable.

7. The method according to claim 6, characterized in that, Solving for the sand addition parameters based on the stated functional relationship and the constraints on the dependent variable includes: Set the function relationship to its maximum value, and solve for the values ​​of the independent variables sand concentration, sand amount, and sand order, which are used as sand addition parameters in fracturing operations.

8. A device for determining sand addition parameters in fracturing operations, characterized in that, The device includes: The preliminary simulation module is used to simulate the sand embankment geometry, sand laying efficiency, and pressure at the crack inlet based on at least two candidate sand addition processes, taking sand concentration, sand addition amount, and sand addition sequence as variables, and according to the target proppant settling velocity and crack geometry. Among them, at least one of the at least two candidate sand addition processes is the water-binding sand attack process. The re-simulation module is used to select the target sand addition process from the candidate sand addition processes based on the preliminary simulation results, add the path information of the target proppant before entering the crack and the crack width information, use the sand addition concentration, sand addition amount and sand addition sequence as variables, and re-simulate the sand dike geometry, sand laying efficiency and crack inlet pressure based on the target proppant settlement velocity, crack geometry and target process. The sand addition parameter determination module is used to determine the target sand spreading efficiency and the target effective fracture length based on the results of the re-simulation, determine the functional relationship between different sand addition concentrations, sand addition amounts, sand addition sequences, fracture geometry and the target sand spreading efficiency and target effective fracture length, and determine the sand addition parameters in the fracturing operation based on the functional relationship.

9. An electronic device, characterized in that, The electronic device includes: At least one processor; and The memory is connected to the at least one processor for data processing; wherein, The memory stores a computer program that can be executed by the at least one processor, the computer program being executed by the at least one processor to enable the at least one processor to perform the method for determining sand addition parameters in fracturing operations as described in any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions that cause a processor to execute the method for determining sand addition parameters in fracturing operations as described in any one of claims 1-7.

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