Method for selecting grinding device for polymer injection blowdown treatment

Abstract

The present invention discloses a method for selecting a grinding device for treating polymer injection discharge, which includes the following steps: data collection, investigating and understanding the commonly used tool types, the properties of discharge, and the commonly used discharge flow rate; simulation calculation, using simulation software and tool models to calculate the working conditions of the grinding tools under all working conditions and collect the results; verification and verification, according to actual production requirements and working conditions, determining the type and structure of the grinding tools, selecting multiple groups of grinding tools that can meet the grinding requirements, and conducting on-site tests to select grinding tools that meet the wear rate requirements. This is to solve the current problems of excessive wear and erosion of grinding tools in the discharge treatment process.

Description

Technical Field

[0001] The invention relates to the field of oilfield waste liquid treatment, in particular to a method for selecting a grinding device for treating polymer injection backwash. Background Art

[0002] Currently, polymer flooding has begun to be widely used in the petroleum industry. However, while polymer flooding technology improves crude oil recovery and achieves stable and high crude oil production, a large amount of new oil production wastewater, polymer flooding oil production wastewater (ORWPF), has also been produced.

[0003] Polymer flooding oil production wastewater is a non-Newtonian organic wastewater with high viscosity, high emulsification degree and difficult biodegradation. Therefore, during the filtration process, it is necessary to grind the larger lumps in ORWPF.

[0004] During the grinding process of the backwash, the sand and gravel in the sewage wear and erode the grinding device. As the service life increases, the wear and tear of the grinding device also increases, and the filtration performance of the entire device for sewage is also continuously weakened, resulting in long-term operation in the low-efficiency zone. However, frequent replacement of grinding tools will not only affect work efficiency, but also increase costs, which is not conducive to the entire filtration process.

[0005] After searching, it was found that in the field of oilfield wastewater treatment, there is currently a technical gap in the public method and technical solution for selecting grinding device models based on different oil production wastewater. Summary of the invention

[0006] The purpose of the present invention is to provide a method for selecting a grinding device for polymer injection discharge treatment to solve the current problem of excessive wear and erosion of grinding tools during discharge treatment. The method is simple and reliable, and is more consistent with the actual working conditions of the tool, has a higher availability, and can more reasonably grind the tool during discharge treatment.

[0007] In order to achieve the above object, the present invention adopts the following technical scheme, and the method for selecting a grinding device for treating polymer injection backflow includes the following steps:

[0008] Step 1: simulation calculation step, using the grinding tool model and simulation software to calculate the grinding tool working parameters under all working conditions, the working parameters include the type of grinding tool, the nature of the backwash, the common flow rate of the backwash, the working parameter data of the grinding tool model is tested on site, the simulation data results are collected, and the separation efficiency curves of each grinding tool model are drawn as the parameter basis for selecting the grinding tool;

[0009] Step 2: Verification and calibration steps, determine the type and structure of the grinding tool according to the actual production requirements and working conditions, select multiple types of grinding tools that can meet the grinding rate requirements, conduct on-site tests one by one to obtain their respective measurement results, and compare the measurement results of multiple groups of grinding tools with the simulation results one by one. If the measurement results are consistent with the simulation results, the selection is complete. If it does not meet the performance requirements, it is necessary to re-reference the selection until the type of grinding tool that meets the minimum wear requirements is selected.

[0010] Before the simulation calculation step, the actual production requirements and working conditions are investigated, and on-site tests are performed to obtain the viscosity, sand content, and inlet condition discharge of the effluent. Then, the operating parameters of commonly used grinding tools are investigated and understood. The operating parameters include the type of grinding tool, the nature of the effluent, and the common flow rate of the effluent.

[0011] The functional relationship f(x) between the structural parameters of the grinding tool and the wear rate is fitted by orthogonal test:

[0012]

[0013] The variance analysis of the three-factor regression model of grinding tools shows that the regression sum of squares ss R =0.00029, error sum of squares ss E =0.00014, total sum of squares ss T =ss R +ss E =0.00043;

[0014] The complex coefficient of determination is:

[0015]

[0016] R 2 Calculation formula:

[0017]

[0018] In the formula: n—number of times performed;

[0019] p = k + 1, k is the number of regression variables;

[0020] Through the above fitting formula, combined with the actual needs on site, the grinding tool with the lowest wear rate while meeting the grinding rate is determined.

[0021] The optimal grinding rate under different working parameters obtained by simulation calculation of the grinding tool is compared with the grinding tool with the selected grinding rate during actual operation. If the minimum wear rate of the selected grinding tool is greater than or equal to the maximum value obtained by simulation calculation, the selected tool is selected as the grinding device; otherwise, the tool is selected again to perform step two.

[0022] According to the orthogonal experimental design and results, the functional relationship between the grinding tool structure parameters and the wear rate is fitted, as shown in Table 1;

[0023] Table 1

[0024]

[0025]

[0026]

[0027] Compared with the prior art, the present invention has the following beneficial effects:

[0028] The backwash is a non-Newtonian body with characteristics such as excessive viscosity and difficulty in breaking, which makes it difficult to filter. The present invention utilizes the excellent property of the tool to destroy and grind the colloid in the backwash, and uses Flunet simulation software to calculate the degree of wear of different cutting tools to be selected, and finally statistically analyzes the values ​​obtained by the simulation calculation, and then obtains the separation efficiency of the grinding tool to be selected under different working conditions, thereby providing guidance for the grinding process of the backwash. The method is simple and reliable, and is more consistent with the actual working conditions of the tool, with a relatively high availability, and can more reasonably grind the tool during the backwash processing process. Theory is combined with practice, and finally, through the comparison of orthogonal experiments, a grinding tool fitting function with relatively high credibility is obtained, which provides theoretical guidance for tool selection during on-site use. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] Figure 1 The present invention is a flowchart of a method for selecting a grinding device for treating polymer injection backflow. DETAILED DESCRIPTION

[0030] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0031] See also Figure 1 , the present invention provides a technical solution:

[0032] In this example, the viscosity of the discharge is 12 mPa·s, the sand content is 12%, and the inlet discharge capacity is 20 m 3 / h as an example to explain in detail how to select the grinding tool in the backflow filtration process to obtain the lowest grinding rate.

[0033] like Figure 1 Shown is a flow chart for energy saving in selecting a grinding tool according to the present invention, which includes the following steps.

[0034] Step 1, data collection, investigate the actual production requirements and working conditions, and test the field data to understand the types of grinding tools commonly used, the nature of the effluent, and the commonly used inlet flow rate when filtering the effluent;

[0035] After investigation and testing of field data, we learned the properties of the discharge and the common discharge flow rate. In this case, the discharge viscosity is 12mPa·s, the sand content is 12%, and the inlet condition discharge is 20m 3 / h, which is usually the minimum flow rate in the actual production process.

[0036] The type or structure of the grinding tool specifically refers to the number of upper blades, lower blades, and guide strips of various types of grinding tools, and the common flow rate of the backflow specifically refers to the common inlet flow rate or displacement of the backflow when filtering in the wastewater treatment device;

[0037] Step 2, calculation simulation, using simulation software and grinding tool model to calculate the working conditions of the grinding tool under all working conditions, collect the results, and draw a wear rate curve of the grinding tool as a basis for selecting grinding tool parameters;

[0038] Refer to the selection, according to the collected data, and then determine the type and structure of the grinding tool, and finally establish the model of the grinding tool. Use Flunet simulation software to obtain the grinding rate of the selected grinding tool under this working condition and record it. Finally, integrate all the data to draw a grinding rate curve.

[0039] Step 3, verification and calibration, according to the actual production requirements and working conditions, select multiple groups of grinding tools that can meet the grinding rate requirements, and conduct on-site testing. If the measurement results are consistent with the simulation results, the selection is complete. If it does not meet the performance requirements, it is necessary to re-reference and select until a grinding tool that meets the grinding rate requirements is selected.

[0040] The optimal grinding rate under different working parameters obtained by simulation calculation of the grinding tool is compared with the grinding tool of the candidate grinding rate during actual operation. If the minimum wear rate of the candidate grinding tool is greater than or equal to the maximum value obtained by simulation calculation, the candidate tool is selected as the grinding device. Otherwise, the reason is analyzed and the tool is selected again to proceed to step 2.

[0041] The functional relationship between the structural parameters of the grinding tool and the wear rate was fitted according to the orthogonal experimental design and results. See Table 1.

[0042] Table 1 Orthogonal design and test results under various structural parameters

[0043]

[0044]

[0045] Finally, the functional relationship f(x) between the structural parameters of the grinding tool and the wear rate is fitted through orthogonal experiments:

[0046]

[0047] The variance analysis of the three-factor regression model for grinding tools is shown in the table above. As can be seen from the table, the regression sum of squares ss R =0.00029, error sum of squares ss E =0.00014, total sum of squares ss T =ss R +ss E =0.00043.

[0048] The complex coefficient of determination is:

[0049]

[0050] R 2 Calculation formula:

[0051]

[0052] Where: n is the number of times the operation is performed, in this example n=25.

[0053] p=k+1, k is the number of regression variables, in this example k=9.

[0054] Through the above fitting formula, combined with the actual needs on site, the grinding tool with the lowest wear rate while meeting the grinding rate can be determined.

[0055] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A method for selecting a grinding device for treating polymer injection effluent, characterized in that: The following steps are involved: Step 1: simulation calculation step, using the grinding tool model and simulation software to calculate the grinding tool working parameters under all working conditions, the working parameters include the type of grinding tool, the nature of the backwash, the common flow rate of the backwash, the working parameter data of the grinding tool model is tested on site, the simulation data results are collected, and the separation efficiency curves of each grinding tool model are drawn as the parameter basis for selecting the grinding tool; Step 2: Verification and calibration step, according to the actual production requirements and working conditions, determine the type and structure of the grinding tool, select multiple types of grinding tools that can meet the grinding rate requirements, conduct on-site tests one by one to obtain their respective measurement results, and compare the measurement results of multiple groups of grinding tools with the simulation results one by one. If the measurement results are consistent with the simulation results, the selection is complete. If it does not meet the performance requirements, it is necessary to re-reference the selection until the type of grinding tool that meets the minimum wear requirements is selected; The functional relationship f(x) between the structural parameters of the grinding tool and the wear rate is fitted by orthogonal test: The variance analysis of the three-factor regression model of grinding tools shows that the regression sum of squares ss R =0.00029, error sum of squares ss E =0.00014, total sum of squares ss T =ss R +ss E =0.00043; The complex determination coefficient is: R 2 adj Corrected multiple determination coefficient: Where: n—number of times performed; p = k + 1, k is the number of regression variables; Through the above functional relationship and combined with the actual needs on site, the grinding tool with the lowest wear rate while meeting the grinding rate is determined.

2. The method for selecting a grinding device for treating polymer injection backflow according to claim 1, characterized in that: Before the simulation calculation step, the actual production requirements and working conditions are investigated, and on-site tests are performed to obtain the viscosity, sand content, and inlet condition discharge of the effluent. Then, the operating parameters of commonly used grinding tools are investigated and understood. The operating parameters include the type of grinding tool, the nature of the effluent, and the common flow rate of the effluent.

3. The method for selecting a grinding device for treating polymer injection backflow according to claim 1, characterized in that: The optimal grinding rate under different working parameters obtained by simulation calculation of the grinding tool is compared with the grinding tool of the selected grinding rate during actual operation. If the minimum wear rate of the selected grinding tool is greater than or equal to the maximum value obtained by simulation calculation, the selected tool is selected as the grinding device; Otherwise, reselect the tool and proceed to step 2.

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