Evaluation method of transformation effect based on production data of shale gas multi-stage fractured horizontal wells

Abstract

The present invention relates to the technical field of shale gas, and to a method for evaluating the transformation effect based on the drainage data of shale gas multi-stage fracturing horizontal wells, including: 1) collecting the drainage data of the shale gas multi-stage fracturing horizontal wells to be evaluated; 2) calculating the sum of the gas production and liquid production underground of the well to be evaluated; 3) calculating the comprehensive expansion coefficient; 4) deriving the relationship between the sum of the gas production and liquid production underground and the comprehensive expansion coefficient; 5) calculating the sum of the fracture volumes of each fracturing section; 6) using normal distribution to approximate the distribution of the fracture volumes of each fracturing section; 7) randomly extracting samples with the same number as the total number of fracturing sections from the normal distribution, and verifying whether the sum of the sample values ​​and the sum of the fracture volumes of each fracturing section meet the requirements of relative error; 8) combining the sequence numbers of each fracturing section, sorting the fracturing fluid volume in descending order, and sorting the samples in descending order at the same time, and making the two groups of sorting correspond one by one to obtain the fracture volume of each fracturing section. The present invention can better perform differentiated transformation effect evaluation.

Description

Technical Field

[0001] The present invention relates to the technical field of shale gas, and in particular to a method for evaluating differentiated transformation effects based on shale gas multi-stage fracturing horizontal well production data. Background Art

[0002] Shale reservoirs have low porosity, low permeability and low natural production capacity. Therefore, the efficient development of this type of reservoir requires the use of horizontal wells + multi-stage fracturing technology to transform the reservoir. The production of shale gas wells is closely related to the transformation effect. The better the transformation effect, the higher the production. Therefore, quantitative evaluation of the transformation effect of shale gas multi-stage fracturing horizontal wells is of great significance for production prediction and fracturing parameter optimization. However, there is currently no direct method to quantitatively characterize underground fractures, and fracture parameters can only be estimated through some indirect methods. These indirect methods can be roughly divided into five categories: (1) microseismic method; (2) production logging; (3) production data analysis; (4) pump-down pressure drop analysis; (5) drainage data analysis. Among them, the microseismic method can monitor the expansion of underground fractures in real time, but the cost of this method is relatively high. In addition, there is no mature method to interpret microseismic signals, so it is impossible to accurately characterize underground fractures. Production logging generally obtains production data along the horizontal wellbore through special logging instruments, such as gas and liquid production profiles, temperature profiles, etc., and then calculates the gas and liquid production contribution of each perforation cluster through the corresponding interpretation model, so as to evaluate the transformation effect of each fracturing stage. However, production logging also has the problem of high cost. In addition, the interpretation of production logging data is a typical inverse problem, and there are currently problems such as low interpretation efficiency and low accuracy of interpretation results. Production data analysis is mostly based on seepage theory. This method requires the introduction of artificial assumptions, such as the flat plate fracture assumption. There is often a large difference between these assumptions and actual conditions. In addition, production data analysis requires production data. Therefore, production data analysis can only be carried out after the well has been opened for production for a period of time. Pump-off pressure drop analysis requires the pressure drop data after the pump is stopped during fracturing construction. However, the on-site pump-off time is generally less than 15 minutes, and the recorded data points are not enough, so this analysis method is difficult to accurately evaluate the transformation effect. Once the pump-off time is extended, the construction progress will be affected. Drainage data analysis is an analysis method based on post-fracturing drainage data. This method does not require additional data acquisition costs and is an economical analysis method. In addition, the post-hydraulic fracturing data is the first-hand information for evaluating the transformation effect. At present, most of the analysis methods of drainage data are based on material balance theory. These methods can only estimate the total volume of fractures, so they can only evaluate the overall transformation effect of horizontal wells, and cannot achieve differentiated analysis based on the fracturing section. At present, the fracturing design of shale gas horizontal wells is based on the fracturing section as a unit, and targeted fracturing design is carried out for each fracturing section, that is, "one section, one policy". Therefore, after hydraulic fracturing, the fracture volume of each fracturing section of the horizontal well is different. For each fracturing section, the transformation effect analysis is carried out using drainage data, which is expected to achieve a refined and differentiated evaluation of the transformation effect of shale gas multi-stage fracturing horizontal wells. However, there is currently a lack of corresponding drainage data analysis methods. Summary of the invention

[0003] The present invention provides a differentiated transformation effect evaluation method based on shale gas multi-stage fracturing horizontal well production data, which can overcome the shortcomings of existing production data analysis methods.

[0004] The transformation effect evaluation method based on shale gas multi-stage fracturing horizontal well production data according to the present invention comprises the following steps:

[0005] (1) Collect the drainage data of the shale gas multi-stage fractured horizontal wells to be evaluated;

[0006] (2) Based on the collected drainage data, calculate the sum of gas and liquid production Y in the underground of the well to be evaluated;

[0007] (3) further calculating the comprehensive expansion coefficient X based on the collected drainage data;

[0008] (4) Derive the relationship between the sum of underground gas and liquid production Y and the comprehensive expansion coefficient X;

[0009] (5) Drawing a scatter plot of X and Y on Cartesian coordinates, further fitting some points on the scatter plot into a straight line passing through the origin, the slope of the fitted straight line is a; further, using the fitted a, calculating the sum of the fracture volumes of each fracturing stage;

[0010] (6) The normal distribution is used to approximate the distribution of the fracture volume of each fracturing stage. Based on the 3σ principle, the fracture volume of each fracturing stage is distributed in the range of (μ-3σ, μ+3σ), where μ is the average fracture volume of a single fracturing stage (μ=V f ini / n s );σ is the standard deviation of the fracture volume of a single fracturing stage;

[0011] (7) Using the Monte Carlo method, from the normal distribution N(μ, σ 2 ) randomly select n s samples, further convert these n s The values ​​of samples are summed to get V f0 ; Finally, V f0 With V f ini Compare them. If the relative error between the two is greater than 10%, resample until the relative error between the two is less than 10%.

[0012] (8) Based on the collected fracturing data and the serial number of each fracturing stage, the amount of fracturing fluid pumped into each fracturing stage is sorted in descending order to obtain a sorting A; the n samples obtained are sorted into s The samples are sorted in order from large to small to obtain sorting B; finally, sorting A and B are matched one by one to obtain the fracture volume of each fracturing section.

[0013] Preferably, in step (1), specifically:

[0014] Collect geological data, engineering data and production data of multi-stage fracturing horizontal wells; geological data include: reservoir temperature, pressure and burial depth, minimum horizontal principal stress, and fracture gas saturation under initial conditions; initial conditions refer to when the pump is stopped and the fracturing construction is completed; engineering data include: pump stop pressure and number of fracturing stages; production data include: gas production, liquid production and bottom hole flow pressure during the production stage.

[0015] Preferably, in step (2), the sum of gas production and liquid production Y is calculated using the following formula:

[0016] Y=G p B g +W p (11)

[0017] Among them, G p is the gas production of the well to be evaluated under the standard surface condition, m 3 ; W p is the liquid production of the well to be evaluated, m 3 ; B g is the volume coefficient of natural gas.

[0018] Preferably, in step (3), the comprehensive expansion coefficient X is calculated as follows:

[0019]

[0020] in, is the natural gas volume coefficient under initial conditions; C f is the crack compression coefficient, 1 / Pa; is the fluid pressure in the fracture under initial conditions, Pa; P f is the bottom hole flowing pressure, Pa; is the gas saturation of the fracture under initial conditions; the initial condition refers to the time after the pump is stopped and the fracturing operation is completed; therefore, the reservoir pressure under initial conditions is the sum of the pump stop pressure and the static liquid column pressure corresponding to the buried depth in the middle of the reservoir; the fracture compression coefficient C f The calculation formula is:

[0021]

[0022] Among them, σ min is the minimum horizontal principal stress, Pa.

[0023] Preferably, in step (4), specifically:

[0024] The sum of underground gas and liquid production Y and the comprehensive expansion coefficient X have the following relationship:

[0025]

[0026] For a single fracturing stage, during the drainage phase, the supply of gas from the matrix system to the fracture system is very weak, and the fracture is simplified into a two-phase tank model;

[0027] In the drainage stage, the driving force for drainage comes from gas expansion and fracture closure; therefore, the material balance equation corresponding to a single fracturing stage can be expressed as:

[0028]

[0029] Where i is the fracturing stage number; is the volume of gas in the fracture of the fracturing section under the initial conditions under the ground standard state, m 3 ; is the volume of liquid in the fracture of the fracturing section under initial conditions, m 3 ; G pi is the gas production of the fracturing section under the standard ground condition, m 3 ; W pi is the liquid production of the fracturing stage, m 3 ; ΔV fi is the closure amount of the fracture in the fracturing section, m 3 ; ΔV fi It can be expressed as:

[0030]

[0031] in, is the fracture volume under the initial conditions of the fracturing stage, m 3 ; It is expressed as:

[0032]

[0033] Therefore, combining equations (6) and (7), the material balance equation for a single fracturing stage can be expressed as:

[0034]

[0035] If a multi-stage fractured horizontal well is fractured n s segment, this n s The material balance equations corresponding to the segments can be accumulated to obtain:

[0036]

[0037] Among them, n s is the total number of pressure sections; combining equations (1), (2) and (9), we get equation (4).

[0038] Preferably, in step (5), the calculation formula for the sum of the fracture volumes of each fracturing stage is as follows:

[0039]

[0040] The present invention collects geological engineering data and drainage data of multi-stage fracturing horizontal wells, uses the material balance principle, combines normal distribution theory and random sampling method, estimates the fracture volume of each fracturing stage, and realizes differentiated transformation effect evaluation. The present invention has the following beneficial effects: 1) Economic, without adding additional data collection costs; 2) It can realize differentiated transformation effect evaluation for a single fracturing stage; 3) The calculation is simple, the operability is strong, and it has the value of on-site promotion. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] Figure 1 This is a flow chart of a differentiated transformation effect evaluation method based on shale gas multi-stage fracturing horizontal well production data in Example 1;

[0042] Figure 2 This is a schematic diagram of a shale gas multi-stage fracturing horizontal well in Example 1;

[0043] FIG3( a ) is a schematic diagram of the bottom hole flow pressure during the drainage stage in Example 2;

[0044] FIG3( b ) is a schematic diagram of gas production and liquid production during the drainage and production phase in Example 2;

[0045] Figure 4 It is a scatter plot of the sum of gas production and liquid production Y and the comprehensive expansion coefficient X in Example 2. DETAILED DESCRIPTION

[0046] In order to further understand the content of the present invention, the present invention is described in detail in conjunction with the accompanying drawings and embodiments. It should be understood that the embodiments are only for explaining the present invention and are not intended to limit it.

[0047] Example 1

[0048] like Figure 1 As shown, this embodiment provides a differentiated transformation effect evaluation method based on shale gas multi-stage fracturing horizontal well production data, comprising the following steps:

[0049] (1) Collect the drainage data of the shale gas multi-stage fractured horizontal wells to be evaluated;

[0050] Collect geological engineering data and drainage data of multi-stage fracturing horizontal wells. Geological data include: reservoir temperature, pressure and burial depth, minimum horizontal principal stress, and fracture gas saturation under initial conditions. The initial conditions here refer to the time after the pump is stopped and the fracturing construction is completed. Engineering data include: pump stop pressure and number of fracturing stages. Drainage data include: gas production, liquid production and bottom hole flow pressure during the drainage stage.

[0051] (2) Based on the collected production data, calculate the sum of the gas and liquid production Y of the underground well to be evaluated.

[0052] Y=G p B g +W p (twenty one)

[0053] Among them, G p is the gas production of the well to be evaluated under the standard surface condition, m 3 ; W p is the liquid production of the well to be evaluated, m 3 ; B g is the volume coefficient of natural gas.

[0054] (3) Further based on the collected drainage data, the comprehensive expansion coefficient X is calculated.

[0055]

[0056] in, is the natural gas volume coefficient under initial conditions; C f is the crack compression coefficient, 1 / Pa; is the fluid pressure in the fracture under initial conditions, Pa; P f is the bottom hole flowing pressure, Pa; is the gas saturation of the fracture under initial conditions. The initial conditions here refer to the time after the pump is stopped and the fracturing operation is completed. Therefore, the reservoir pressure under initial conditions is the sum of the pump stop pressure and the static liquid column pressure corresponding to the buried depth in the middle of the reservoir. Fracture compression coefficient C f Based on the empirical relationship obtained by Aguilera et al. through indoor experiments, namely:

[0057]

[0058] Among them, σ min is the minimum horizontal principal stress, Pa.

[0059] (4) It is deduced that the sum of underground gas and liquid production Y and the comprehensive expansion coefficient X have the following relationship:

[0060]

[0061] The derivation process of equation (4) is as follows:

[0062] For a single fracturing stage (such as Figure 2 As shown in Figure 2, during the drainage stage, the gas supply from the matrix system to the fracture system is very weak, and the fracture can be simplified into a two-phase storage tank model.

[0063] In this stage, the driving force for drainage comes from gas expansion and fracture closure. Therefore, the material balance equation corresponding to a single fracturing stage can be expressed as:

[0064]

[0065] Where i is the fracturing stage number; is the volume of gas in the fracture of the fracturing section under the initial conditions under the ground standard state, m 3 ; is the volume of liquid in the fracture of the fracturing section under initial conditions, m 3 ; G pi is the gas production of the fracturing section under the standard ground condition, m 3 ; W pi is the liquid production of the fracturing stage, m 3 ; ΔV fi is the closure amount of the fracture in the fracturing section, m 3 . ΔV fi It can be expressed as:

[0066]

[0067] in, is the fracture volume under the initial conditions of the fracturing stage, m 3 ; It can be expressed as:

[0068]

[0069] Therefore, combining equations (6) and (7), the material balance equation for a single fracturing stage can be expressed as:

[0070]

[0071] If a multi-stage fractured horizontal well is fractured n s segment, this n s The material balance equations corresponding to the segments can be accumulated to obtain:

[0072]

[0073] Among them, n s is the total number of pressure stages. Combining equations (1), (22) and (9), we can obtain equation (4).

[0074] (5) Draw a scatter plot of X and Y on Cartesian coordinates, and further fit some points on the scatter plot into a straight line passing through the origin. The slope of the fitted straight line is a. Further, using the fitted a, the sum of the fracture volumes of each fracturing stage can be calculated.

[0075]

[0076] (6) The normal distribution is used to approximate the distribution of the fracture volume of each fracturing section. Based on the "3σ" principle, the fracture volume of each fracturing section is distributed in the range of (μ-3σ, μ+3σ), where μ is the average fracture volume of a single fracturing section. m 3 ; σ is the standard deviation of the fracture volume of a single fracturing stage, m 3 Based on the “3σ” principle, we can obtain σ=μ / 3.

[0077] (7) Using the Monte Carlo method, from the normal distribution N(μ, σ 2 ) randomly select n s samples, further convert these n s The values ​​of samples are summed to get V f0 Finally, V f0 and Compare them, if the relative error between the two is greater than 10%, resample until the relative error between the two is less than 10%.

[0078] (8) Based on the collected fracturing data and the serial number of each fracturing stage, the amount of fracturing fluid pumped into each fracturing stage is sorted in descending order to obtain a sorting A; the n samples obtained are sorted into s The samples are sorted in order from large to small to obtain sorting B. Finally, sorting A and B are matched one by one to obtain the fracture volume of each fracturing section.

[0079] Example 2

[0080] This embodiment provides a specific implementation case.

[0081] (1) A shale gas multi-stage fracturing horizontal well was fractured in 23 stages. After the fracturing operation, the pump stop pressure was 64.44MPa, the reservoir section was buried at a depth of 4236.2m, the reservoir temperature was 405.5K, the minimum horizontal principal stress was 110MPa, and the estimated fracture gas saturation under initial conditions was 0.2. The drainage data of the well are shown in Figures 3(a) and 3(b).

[0082] (2) Based on the collected drainage data, the sum of the gas and liquid production Y of the well to be evaluated is calculated using formulas (1) and (22) in Example 1, and the comprehensive expansion coefficient X is further calculated. The calculated X and Y are plotted on Cartesian coordinates, and some points on the scatter plot are further fitted into a straight line passing through the origin. The fitting result is as follows: Figure 4 shown.

[0083] The slope a of the fitted straight line is 1467.23. Further using equation (10), we can get 7336.14m 3.

[0084] (3) Based on the obtained The average value of the fracture volume of a single fracturing section is μ = 318.96m 3 , and then using the “3σ” principle, the variance σ of the fracture volume of a single fracturing stage is obtained 2 =11304.13m 6 .

[0085] (4) Using the Monte Carlo method, 23 samples are drawn from the normal distribution N (318.96, 11304.13), and these sample values ​​are summed to obtain V f0 . V f0 and If the relative error between the two is greater than 10%, re-sample until the relative error between the two is less than 10%. The final 23 sample values ​​are shown in Table 1.

[0086] Table 1 23 sample values ​​obtained by sampling

[0087]

[0088]

[0089] (5) Combined with the fracturing stage number, the amount of fracturing fluid pumped into each fracturing stage of the well is sorted in descending order to obtain a sorting A, as shown in Table 2. Further, the sample values ​​in Table 1 are sorted in descending order to obtain a sorting B, as shown in Table 2. The sorting A and B are matched one by one, and finally the fracture volume of each fracturing stage is obtained, as shown in Table 2.

[0090] Table 2 Fluid volume pumped into each fracturing stage and fracture volume

[0091]

[0092] The present invention and its embodiments are described schematically above, and the description is not restrictive. The drawings show only one embodiment of the present invention, and the actual structure is not limited thereto. Therefore, if a person skilled in the art is inspired by it and designs a structural method and an embodiment similar to the technical solution without creativity without departing from the purpose of the invention, they shall all fall within the protection scope of the present invention.

Claims

1. A method for evaluating the transformation effect of shale gas multi-stage fracturing horizontal well production data, characterized by: The following steps are involved: (1) Collecting the production data of the shale gas multi-stage fractured horizontal wells to be evaluated; (2) Based on the collected drainage data, calculate the sum of gas and liquid production Y in the underground of the well to be evaluated; (3) further calculating the comprehensive expansion coefficient X based on the collected drainage data; (4) Derive the relationship between the sum of underground gas and liquid production Y and the comprehensive expansion coefficient X; (5) Draw a scatter plot of X and Y on Cartesian coordinates, and further fit some points on the scatter plot into a straight line passing through the origin. The slope of the fitted straight line is a. Further, using the fitted a, calculate the sum of the fracture volumes V of each fracturing stage f ini ; In step (5), the calculation formula for the sum of the fracture volumes of each fracturing stage is as follows: Among them, n s is the total number of fracturing stages; i is the sequence number of the fracturing stage; is the volume of gas in the fracture of the fracturing section under initial conditions under the standard ground state; is the natural gas volume coefficient under initial conditions; is the fracture gas saturation under initial conditions; (6) The normal distribution is used to approximate the distribution of the fracture volume of each fracturing stage. Based on the 3σ principle, the fracture volume of each fracturing stage is distributed in the range of (μ-3σ, μ+3σ), where μ is the average fracture volume of a single fracturing stage, and μ=V f ini / n s ;σ is the standard deviation of the fracture volume of a single fracturing stage; (7) Using the Monte Carlo method, from the normal distribution N(μ, σ 2 ) randomly select n s samples, further convert these n s The values ​​of samples are summed to get V f0 ; Finally, V f0 With V f ini Compare them. If the relative error between the two is greater than 10%, resample until the relative error between the two is less than 10%. (8) Based on the collected fracturing data and the serial number of each fracturing stage, the amount of fracturing fluid pumped into each fracturing stage is sorted in descending order to obtain a sorting A; the n samples obtained are sorted into s The samples are sorted in order from large to small to obtain sorting B; finally, sorting A and B are matched one by one to obtain the fracture volume of each fracturing section.

2. The method for evaluating transformation effect based on shale gas multi-stage fracturing horizontal well production data according to claim 1, characterized in that: In step (1), specifically: Collect geological data, engineering data and production data of multi-stage fracturing horizontal wells; geological data include: reservoir temperature, pressure and burial depth, minimum horizontal principal stress, and fracture gas saturation under initial conditions; initial conditions refer to when the pump is stopped and the fracturing construction is completed; engineering data include: pump stop pressure and number of fracturing stages; production data include: gas production, liquid production and bottom hole flow pressure during the production stage.

3. The method for evaluating transformation effect based on shale gas multi-stage fracturing horizontal well production data according to claim 1, characterized in that: In step (2), the sum of gas production and liquid production Y is calculated as follows: Y=G p B g +W p (1) Among them, G p is the gas production of the well to be evaluated under the standard surface condition, m 3 ; W p is the liquid production of the well to be evaluated, m 3 ; B g is the volume coefficient of natural gas.

4. The method for evaluating transformation effect based on shale gas multi-stage fracturing horizontal well production data according to claim 3, characterized in that: In step (3), the calculation formula of the comprehensive expansion coefficient X is as follows: in, is the natural gas volume coefficient under initial conditions; C f is the crack compression coefficient, 1 / Pa; P f ini is the fluid pressure in the fracture under initial conditions, Pa; P f is the bottom hole flowing pressure, Pa; is the gas saturation of the fracture under initial conditions; the initial condition refers to the time after the pump is stopped and the fracturing operation is completed; therefore, the reservoir pressure under initial conditions is the sum of the pump stop pressure and the static liquid column pressure corresponding to the buried depth in the middle of the reservoir; the fracture compression coefficient C f The calculation formula is: Among them, σ min is the minimum horizontal principal stress, Pa.

5. The method for evaluating transformation effect based on shale gas multi-stage fracturing horizontal well production data according to claim 4, characterized in that: In step (4), specifically: The sum of underground gas and liquid production Y and the comprehensive expansion coefficient X have the following relationship: For a single fracturing stage, during the drainage phase, the supply of gas from the matrix system to the fracture system is very weak, and the fracture is simplified into a two-phase tank model; In the drainage stage, the driving force for drainage comes from gas expansion and fracture closure; therefore, the material balance equation corresponding to a single fracturing stage is expressed as: Where i is the fracturing stage number; is the volume of gas in the fracture of the fracturing section under the initial conditions under the ground standard state, m 3 ; is the volume of liquid in the fracture of the fracturing section under initial conditions, m 3 ; G pi is the gas production of the fracturing section under the standard ground condition, m 3 ; W pi is the liquid production of the fracturing stage, m 3 ; ΔV fi is the closure amount of the fracture in the fracturing section, m 3 ; ΔV fi It is expressed as: in, is the fracture volume under the initial conditions of the fracturing stage, m 3 ; It is expressed as: Therefore, combining equations (6) and (7), the material balance equation for a single fracturing stage is expressed as: If a multi-stage fractured horizontal well is fractured n s segment, this n s The material balance equations corresponding to the segments are summed up to get: Among them, n s is the total number of pressure sections; combining equations (1), (2) and (9), we get equation (4).

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