Method for improving volume fracturing productivity of tight oil reservoir based on imbibition mechanism

Abstract

The invention relates to the technical field of petroleum and natural gas exploration, and discloses a method for improving tight oil reservoir volume fracturing productivity based on an imbibition mechanism, which comprises the following steps of: predicting fracture expansion conditions under different injection strategies by adopting a dynamic simulation technology to perform fracturing; parameter optimization is carried out in combination with machine learning, and imbibition medium injection parameters and fracturing parameters are designed; a nano-particle material is added into the imbibition medium, so that the contact area between the imbibition medium and crude oil is increased; a real-time monitoring system is introduced, and the soaking time is dynamically adjusted by monitoring the formation pressure change through a sensor; and the flow-back rate of the fracturing fluid is regulated and controlled through automatic control. According to the method, the formation pressure change is monitored in real time, and the current soaking state is evaluated by using a machine learning algorithm or an expert system, so that whether the imbibition process is completed or not can be more accurately judged, and the poor effect caused by unnecessary waiting time or too early completion of soaking is avoided.

Description

Technical Field

[0001] The invention relates to the technical field of oil and gas exploration, and in particular to a method for improving the volume fracturing capacity of tight oil reservoirs based on an imbibition mechanism. Background Art

[0002] The exploration and development of conventional medium- and high-permeability oil reservoirs has entered its final stage and is becoming more difficult. In addition, the country's dependence on imported energy is increasing. my country's own energy supply is facing serious challenges. Therefore, the exploration and development of unconventional oil and natural gas such as tight oil has become the direction and breakthrough for improving its own energy supply capabilities.

[0003] The existing patent discloses a method for improving the volume fracturing capacity of tight oil reservoirs based on the imbibition mechanism (publication number CN113417617A). It includes the following steps: fracturing and parameter design; injection of imbibition medium; large-scale fracturing; well shut-in; blow-out and production. In the technology disclosed in the patent, due to the different geological characteristics of different oil reservoirs, the traditional fixed well shut-in time scheme is difficult to meet the needs of all situations, so it is impossible to flexibly adjust the well shut-in strategy according to the actual situation, which will greatly increase the cost of exploration. Summary of the invention

[0004] The main technical problem solved by the present invention is to provide a method for improving the volume fracturing capacity of tight oil reservoirs based on the imbibition mechanism, which solves the problems in the above-mentioned background technology.

[0005] To solve the above technical problems, according to one aspect of the present invention, more specifically, a method for improving the volume fracturing capacity of tight oil reservoirs based on the imbibition mechanism comprises the following steps: S1. Use dynamic simulation technology to predict the crack expansion under different injection strategies to perform fracturing; S2. Combine machine learning to optimize parameters and design the injection parameters of the imbibition medium and the fracturing parameters; S3, adding nanoparticle material to the imbibition medium to increase the contact area between the imbibition medium and the crude oil; S4. Introduce a real-time monitoring system and use sensors to monitor changes in formation pressure to dynamically adjust the soaking time; S5. Use automated control to regulate the fracturing fluid flowback rate.

[0006] Furthermore, in step S1, the geostress field information of the target reservoir is obtained through logging data, and the geostress field information specifically includes elastic modulus, Poisson's ratio, and fracture toughness, and whether to increase the fracturing range is determined based on the geostress field information, as follows: In the formula, Indicates the condition coefficient that needs to increase the fracturing range, Indicates the actual pressure generated by the fracturing equipment. Indicates the minimum pressure required for crack growth.

[0007] Furthermore, the minimum pressure required for the crack to expand can be estimated by the following formula: In the formula, The minimum pressure required for crack expansion. represents the fracture toughness coefficient of the ground in the area, The cracks indicating the ground breaking in the area are half-length, Represents the minimum horizontal principal stress in the initial stress field.

[0008] Furthermore, when When , it means that the prediction of dynamic simulation technology will require the expansion of the fracturing range; when When , it means that the prediction of dynamic simulation technology will not require increasing the fracturing range.

[0009] Furthermore, the nanoparticle material added in step S3 is composed of silicon dioxide nanoparticles, aluminum oxide nanoparticles and carbon nanotubes.

[0010] Furthermore, the mass ratio of the silicon dioxide nanoparticles, the aluminum oxide nanoparticles and the carbon nanotubes is 6:2:0.1.

[0011] Furthermore, the specific steps of dynamically adjusting the soaking time in step 4 are: 1) Based on real-time data, use machine learning algorithms or expert systems to evaluate the current well status; 2) Update the numerical simulation model based on the latest data and re-predict the fracture expansion and production potential; 3) If the data shows that the current well-insulating time is too long or too short, dynamically adjust the well-insulating time: a. If the formation pressure does not reach the expected equilibrium point, it indicates that the imbibition process has not been completed and the soaking time can be appropriately extended; b. If the formation pressure has stabilized and there is no further upward trend, it indicates that the imbibition process has been completed and the soaking stage can be ended early.

[0012] The present invention provides a method for improving the volume fracturing capacity of tight oil reservoirs based on the imbibition mechanism. Compared with the prior art, the method has the following effects: 1. The present invention uses a mixture of silicon dioxide nanoparticles, aluminum oxide nanoparticles and carbon nanotubes in a mass ratio of 6:2:0.1, which can not only introduce additional functional characteristics while ensuring basic performance, but also effectively balance cost and efficiency, and is particularly suitable for oil extraction applications under complex geological conditions.

[0013] 2. The present invention can more accurately determine whether the imbibition process is completed by real-time monitoring of formation pressure changes and using machine learning algorithms or expert systems to evaluate the current soaking status, thereby avoiding unnecessary waiting time or poor results caused by premature termination of soaking.

[0014] 3. The present invention obtains the geostress field information of the target reservoir through logging data. The geostress field information specifically includes elastic modulus, Poisson's ratio, and fracture toughness. Based on the geostress field information, it is possible to quickly and accurately determine whether to increase the fracturing range, which can greatly improve the exploration efficiency of oil and natural gas. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 is a flow chart of the present invention; Figure 2 Schematic diagram of the effect of crack half-length on fracture pressure in the present invention. DETAILED DESCRIPTION

[0016] In order to make the technical solution of the present invention clearer, the present invention is further described in detail below with reference to the accompanying drawings and specific embodiments. Example

[0017] like Figure 1 , 2 As shown, the geostress field information of the target reservoir is obtained through logging data. The geostress field information specifically includes elastic modulus, Poisson's ratio, and fracture toughness. Based on the geostress field information, it is determined whether to increase the fracturing range: In the formula, Indicates the condition coefficient that needs to increase the fracturing range. When , it means that the prediction of dynamic simulation technology will require the expansion of the fracturing range; when When , it means that the prediction of dynamic simulation technology will not require increasing the fracturing range. Indicates the actual pressure generated by the fracturing equipment. Indicates the minimum pressure required for crack growth.

[0018] The minimum pressure required for crack propagation can be estimated by the following formula: In the formula, The minimum pressure required for crack expansion. represents the fracture toughness coefficient of the ground in the area, The cracks indicating the ground breaking in the area are half-length, Represents the minimum horizontal principal stress in the initial stress field.

[0019] Among them, the fracture toughness coefficient of the ground in this area is ( ), the minimum horizontal principal stress in the initial stress field is taken as ( ), the half-length of the cracks in the ground fracture in this area (m), then we have: From the above calculation, we can know that the minimum pressure required for crack expansion is ( ). When the actual pressure generated by the fracturing equipment is ( ), then we have: From the above calculations, it can be seen that the prediction based on dynamic simulation technology will not require an increase in the range of fracturing. Example

[0020] like Figure 1 As shown, the nanoparticle material added in step three is composed of silica nanoparticles, alumina nanoparticles and carbon nanotubes. The mass ratio between silica nanoparticles, alumina nanoparticles and carbon nanotubes is 6:2:0.1. Silica nanoparticles can effectively adjust the viscosity of the solution, which helps to control the flow characteristics of the liquid in the formation and ensure more effective penetration and distribution. Alumina nanoparticles are known for their high hardness, while silica nanoparticles provide good dispersibility and chemical stability. Combining these two materials can improve the mechanical strength of the overall structure without significantly increasing the viscosity of the system. Therefore, silica nanoparticles, alumina nanoparticles and carbon nanotubes are mixed in a mass ratio of 6:2:0.1, which can not only introduce additional functional characteristics while ensuring basic performance, but also effectively balance cost and efficiency, and are particularly suitable for oil extraction applications under complex geological conditions. Example

[0021] like Figure 1 As shown, the specific steps for dynamically adjusting the soaking time in step 4 are: Step 1: Based on real-time data, use machine learning algorithms or expert systems to evaluate the current soaking status. By monitoring the formation pressure changes in real time and using machine learning algorithms or expert systems to evaluate the current soaking status, it is possible to more accurately determine whether the imbibition process is complete, thereby avoiding unnecessary waiting time or premature termination of soaking resulting in poor results.

[0022] Step 2: Update the numerical simulation model based on the latest data and re-predict the fracture expansion and production potential.

[0023] Step 3: If the data shows that the current well-sealing time is too long or too short, dynamically adjust the well-sealing time: If the formation pressure does not reach the expected equilibrium point, it indicates that the imbibition process has not been completed and the soaking time can be appropriately extended.

[0024] If the formation pressure has stabilized and has no further upward trend, it indicates that the imbibition process has been completed and the soaking stage can be ended early.

[0025] And because different reservoirs have different geological characteristics, the traditional fixed well-insertion time plan is difficult to meet the needs of all situations. The dynamic adjustment method can flexibly adjust the well-insertion strategy according to the actual situation and better adapt to various complex geological conditions.

[0026] The above-mentioned embodiments only express several implementation methods of the present invention, and the description thereof is relatively specific and detailed, but it cannot be understood as limiting the scope of the patent of the present invention. It should be pointed out that, for ordinary technicians in this field, several variations and improvements can be made without departing from the concept of the present invention, which all belong to the protection scope of the present invention. Therefore, the protection scope of the patent of the present invention shall be subject to the attached claims.

Claims

1. A method for improving the volume fracturing productivity of tight oil reservoirs based on the imbibition mechanism, characterized in that: The following steps are involved: S1. Use dynamic simulation technology to predict the crack expansion under different injection strategies to perform fracturing; S2. Combine machine learning to optimize parameters and design the injection parameters of the imbibition medium and the fracturing parameters; S3, adding nanoparticle material to the imbibition medium to increase the contact area between the imbibition medium and the crude oil; S4. Introduce a real-time monitoring system and use sensors to monitor changes in formation pressure to dynamically adjust the soaking time; S5. Use automated control to regulate the fracturing fluid flowback rate.

2. The method for improving the volume fracturing productivity of tight oil reservoirs based on the imbibition mechanism according to claim 1, characterized in that: In step S1, the geostress field information of the target reservoir is obtained through logging data, and the geostress field information specifically includes elastic modulus, Poisson's ratio, and fracture toughness. It is determined whether to increase the fracturing range based on the geostress field information, as follows: In the formula, Indicates the condition coefficient that needs to increase the fracturing range, Indicates the actual pressure generated by the fracturing equipment. Indicates the minimum pressure required for crack growth.

3. The method for improving the volume fracturing productivity of tight oil reservoirs based on the imbibition mechanism according to claim 2, characterized in that: The minimum pressure required for the crack to expand can be estimated by the following formula: In the formula, The minimum pressure required for crack expansion. represents the fracture toughness coefficient of the ground in the area, The cracks indicating the ground breaking in the area are half-length, Represents the minimum horizontal principal stress in the initial stress field.

4. The method for improving the volume fracturing productivity of tight oil reservoirs based on the imbibition mechanism according to claim 2, characterized in that: when When , it means that the prediction of dynamic simulation technology will require the expansion of the fracturing range; when When , it means that the prediction of dynamic simulation technology will not require increasing the fracturing range.

5. The method for improving the volume fracturing productivity of tight oil reservoirs based on the imbibition mechanism according to claim 1, characterized in that: The nanoparticle material added in step S3 is composed of silicon dioxide nanoparticles, aluminum oxide nanoparticles and carbon nanotubes.

6. The method for increasing the volume fracturing productivity of tight oil reservoirs based on the imbibition mechanism according to claim 5, characterized in that: The mass ratio of the silicon dioxide nanoparticles, the aluminum oxide nanoparticles and the carbon nanotubes is 6:2:0.

1.

7. The method for increasing the volume fracturing productivity of tight oil reservoirs based on the imbibition mechanism according to claim 1, characterized in that: The specific steps of dynamically adjusting the soaking time in step 4 are as follows: 1) Based on real-time data, use machine learning algorithms or expert systems to evaluate the current well status; 2) Update the numerical simulation model based on the latest data and re-predict the fracture expansion and production potential; 3) If the data shows that the current well-insulating time is too long or too short, dynamically adjust the well-insulating time: a. If the formation pressure does not reach the expected equilibrium point, it indicates that the imbibition process has not been completed and the soaking time can be appropriately extended; b. If the formation pressure has stabilized and there is no further upward trend, it indicates that the imbibition process has been completed and the soaking stage can be ended early.

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