Acid fracturing parameter design method based on data driving and application and system thereof

Abstract

The invention belongs to the technical field of oil and gas well reservoir transformation, and relates to an acid fracturing parameter design method based on data driving and application and system.The method comprises the steps that a sample database is constructed based on well logging data, well logging data, well drilling data, acid fracturing data and yield data of an acid fracturing well section; optimizing yield influence factors based on the sample database; drawing a box whisker diagram of the yield influence factors and the logging data in the sample database; calculating box whisker graph similarity coefficients of the yield influence factors and the logging data in the sample database to obtain a similarity coefficient sorting result; and acid fracturing parameters are designed according to a similarity coefficient sorting result. The method can realize automation of design, reduces design workload, is suitable for optimization design of segmented acid fracturing parameters of a vertical well, an inclined well and a horizontal well of carbonate rocks, and improves working efficiency.

Description

Technical Field

[0001] The present invention belongs to the technical field of oil and gas well reservoir transformation, and in particular relates to a data-driven acid fracturing parameter design method and an application and system thereof. Background Art

[0002] Acid fracturing is one of the key technologies for increasing the production of carbonate oil and gas reservoirs. Using reasonable acid fracturing parameters for construction is conducive to increasing the production of single wells in carbonate rocks.

[0003] The design of carbonate rock acid fracturing parameters mainly adopts a method combining reservoir numerical simulation and acid fracturing fracture simulation. The geometric dimensions and conductivity of acid erosion fractures are obtained through reservoir numerical simulation optimization. The reservoir numerical simulation adopts general reservoir numerical simulation software such as Eclipse and CMG, and different geometric dimensions and conductivity of acid erosion fractures are set. With the cumulative production or recovery rate or economic benefit as the goal, the length, height and conductivity of acid erosion fractures are optimized. The acid fracturing construction parameters are obtained through acid fracturing fracture simulation optimization, including acid intensity, liquid intensity, construction displacement, alternating injection levels of pre-fluid and acid, etc. The acid fracturing fracture simulation adopts general acid fracturing simulation software such as FracproPT, Gohfer, Stimplan, etc., and different acid fracturing construction parameters are set. With the geometric dimensions and conductivity of acid erosion fractures obtained by reservoir numerical simulation as the goal, the key parameters of acid fracturing construction such as acid intensity, liquid intensity, construction displacement, alternating injection levels of pre-fluid and acid are optimized.

[0004] CN110359900A discloses a method for optimizing the acid fracturing construction parameters of carbonate reservoirs. The method uses oil and gas reservoir capacity simulation software to simulate and calculate the capacity of carbonate reservoirs under different fracture parameters to determine the optimal fracture conductivity required for the production of the reservoir; at the same time, cracks are formed by splitting real rock plates of carbonate reservoirs, and the rough morphology data of the fracture surface is collected through three-dimensional laser scanning. Then, a rock CNC engraving machine is used to engrave on the surface of the real rock sample of the carbonate reservoir to obtain an artificial carbonate rock sample with a real fracture surface morphology; acid etching experiments and acid etching fracture conductivity tests under different construction parameters are carried out using the artificial carbonate rock samples, and the test results are compared and analyzed with the simulation calculation results to obtain the optimal acid fracturing construction parameters that meet the characteristics of the reservoir.

[0005] CN110630240B discloses a method for optimizing the displacement of multi-stage alternating acid fracturing in carbonate reservoirs, comprising the following steps: (a) calculating the surface volume ratio of the reservoir to be acid-fractured, wherein S is the reaction area of ​​the reservoir rock; V is the volume of the acid solution participating in the reaction; (b) calculating the maximum construction displacement that the reservoir can withstand in combination with the surface volume ratio; (c) determining the actual construction displacement according to the pressure bearing capacity of the ground equipment; (d) determining the amount of pre-flushing fluid and acid solution at each stage according to the acid fracturing design plan; and dividing the amount of pre-flushing fluid and acid solution at each stage by the actual construction displacement to obtain the injection time of the pre-flushing fluid and acid solution at each stage.

[0006] However, the above-disclosed multi-stage alternating injection acid fracturing construction parameter optimization method is based on numerical simulation of oil and gas reservoir production capacity, acid-etched fracture conductivity test, acid-rock reaction and surface ratio calculation, and ground equipment performance. It has the problem of incomplete consideration of reservoir factors, and the above-mentioned existing technology cannot realize data-driven automatic design of acid fracturing parameters. Summary of the invention

[0007] The technical solution adopted by the present invention is as follows: a data-driven acid fracturing parameter design method, the method comprising the following steps:

[0008] Construct a sample database based on the well logging data, mud logging data, drilling data, acid fracturing data and production data of the acid fracturing well section;

[0009] Based on the sample database, the factors affecting yield are optimized;

[0010] Draw a box-and-whisker plot of production influencing factors and logging data in the sample database;

[0011] Calculate the similarity coefficient of the box-whisker diagram of the production influencing factors in the sample database and the logging data, and obtain the ranking result of the similarity coefficient;

[0012] The acid fracturing parameters are designed according to the similarity coefficient sorting results.

[0013] Further, the logging data includes one or more of natural gamma, natural potential, well diameter, deep resistivity, shallow resistivity, P-wave time difference, S-wave time difference, sonic time difference, neutron porosity or density;

[0014] The logging data includes the maximum value of total hydrocarbon or C 1-10 One or more of the values;

[0015] The drilling data includes one or more of drilling time, mud density, overflow rate or well leakage rate;

[0016] The production data may be one or more of test production or cumulative production within the same period of time.

[0017] Furthermore, the preferred yield influencing factors based on the sample database include: based on the sample database, the yield influencing factors are preferably selected by a data analysis method; the data analysis method includes one or more of random forest, distributed gradient enhancement library, Pearson correlation coefficient, maximum information coefficient, distance correlation coefficient, grey correlation analysis or multiple regression method.

[0018] Furthermore, the box-and-whisker plot includes five parameters: lower limit, lower quartile, median, upper quartile and upper limit.

[0019] Furthermore, the calculating of similarity coefficients of box-whisker plots of production influencing factors in the sample database and well logging data to obtain similarity coefficient ranking results includes: calculating similarity coefficients of box-whisker plots of production influencing factors in the sample database and well logging data by a similarity measurement analogy method to obtain similarity coefficient ranking results.

[0020] Furthermore, the similarity measurement analogy method includes: obtaining the acid fracturing parameters of the sample well section closest to the target well section through the similarity measurement model, and estimating the target section production range.

[0021] Furthermore, the similarity coefficient is greater than or equal to 0.9.

[0022] Furthermore, the acid fracturing parameters include one or more of construction displacement, acid intensity or liquid intensity.

[0023] The present invention also proposes an application of a data-driven acid fracturing parameter design method, which is applied to the segmented acid fracturing parameter design of carbonate vertical wells, inclined wells and horizontal wells.

[0024] In addition, the present invention also proposes a data-driven acid fracturing parameter design system, which includes a construction module, an optimization module, a drawing module, a calculation module and a design module; wherein:

[0025] The construction module is used to construct a sample database based on the well logging data, mud logging data, drilling data, acid fracturing data and production data of the acid fracturing well section;

[0026] The optimization module is used to optimize the factors affecting the yield based on the sample database;

[0027] The drawing module is used to draw a box-and-whisker diagram of production influencing factors and logging data in a sample database;

[0028] The calculation module is used to calculate the box-whisker plot similarity coefficients of the production influencing factors in the sample database and the well logging data to obtain the similarity coefficient ranking results;

[0029] The design module is used to design acid fracturing parameters according to the similarity coefficient sorting results.

[0030] The present invention proposes a data-driven acid fracturing parameter design method. According to the well logging, mud logging, drilling data of the acid fracturing well section, as well as the acid fracturing construction parameters and production database, a data-driven design method based on similarity analogy is established, and the acid fracturing construction parameters of the new well are automatically designed according to the similarity criterion. The method can realize the automation of design and reduce the design workload. It is suitable for the optimization design of segmented acid fracturing parameters of carbonate vertical wells, inclined wells and horizontal wells, and improves work efficiency.

[0031] Other features and advantages of the present invention will be described in the following description, and part of them will become obvious from the description, or be understood by practicing the present invention. The purpose and other advantages of the present invention can be realized and obtained through the description and the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0033] Figure 1 is a schematic diagram of a data-driven acid fracturing parameter design method in an embodiment of the present invention;

[0034] Figure 2 Schematic diagram of a box-whisker plot of well logging parameters of the third section of Well A among the 110 well sections in an embodiment of the present invention;

[0035] Figure 3 Schematic diagram of a box-whisker diagram of well logging data of six well sections in the A-12H well in an embodiment of the present invention;

[0036] Figure 4 It is a schematic diagram of a data-driven acid fracturing parameter design system in an embodiment of the present invention. DETAILED DESCRIPTION

[0037] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below. Obviously, the described embodiments are 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.

[0038] like Figure 1 As shown, a data-driven acid fracturing parameter design method comprises the following steps:

[0039] S1. Construct a sample database based on the well logging data, mud logging data, drilling data, acid fracturing data and production data of the acid fracturing well section;

[0040] S2. Optimize the factors affecting yield based on the sample database;

[0041] S3, draw a box-and-whisker diagram of production influencing factors and logging data in the sample database;

[0042] S4, calculating the box-whisker plot similarity coefficients of the production influencing factors in the sample database and the well logging data, and obtaining the similarity coefficient ranking results;

[0043] S5. Design acid fracturing parameters based on the similarity coefficient ranking results.

[0044] Specifically, in step S1, the logging data, mud logging data, drilling data and production data are collected by logging, mud logging, drilling and reservoir engineers according to professional methods, and the collection method is implemented by those skilled in the art according to methods well known in the industry; the logging data includes one or more of natural gamma, natural potential, well diameter, deep resistivity, shallow resistivity, longitudinal wave time difference, shear wave time difference, sonic wave time difference, neutron porosity or density and other logging data; the mud logging data includes total hydrocarbon maximum or C 1-10 The sample database includes one or more logging data such as drilling time, mud density, overflow or well leakage; the production data includes one or more of test production or cumulative production in the same period. It should be noted that the sample database must include acid fracturing data and production data; it can also include one or more of logging data, well logging data, logging data, and drilling data.

[0045] Specifically, step S2 includes: based on the sample database, optimizing the factors affecting yield through a data analysis method; the data analysis method includes one or more of a random forest, a distributed gradient enhancement library, a Pearson correlation coefficient, a maximum information coefficient, a distance correlation coefficient, a grey correlation analysis or a multiple regression method.

[0046] Specifically, the box-and-whisker plot in step S3 includes five parameters: a lower limit, a lower quartile, a median, an upper quartile and an upper limit.

[0047] Specifically, step S4 includes: calculating the similarity coefficient of the box-whisker plot of the production influencing factors in the sample database and the logging data through a similarity measurement analogy method, and obtaining a similarity coefficient ranking result. The similarity measurement analogy method includes: obtaining the acid fracturing parameters of the sample well section closest to the target well section through a similarity measurement model, and estimating the target section production interval; the similarity coefficient is greater than or equal to 0.9.

[0048] Specifically, the acid fracturing parameters in step S5 include one or more of construction displacement, acid intensity or liquid intensity.

[0049] The implementation process of the above method is specifically described below through an embodiment. In the embodiment of the present invention, the A-12H horizontal well in the A well area is taken as an example. After the A-12H horizontal well in the A well area is drilled and completed, the method provided by the present invention is used to design acid fracturing parameters. The design steps are as follows:

[0050] The sample database was constructed using the well logging data, mud logging data, drilling data and test production data of each section from 19 horizontal wells in well area A with 110 sections;

[0051] Based on the sample database, the production influencing factors of 110 well sections were selected;

[0052] Draw the box-and-whisker diagram of the production influencing factors of 110 well sections in the sample database. The box-and-whisker diagram of the logging parameters of the third section of Well A is as follows: Figure 2 As shown in Figure 1, the box-whisker diagram of the logging data in this section includes wellbore diameter, natural gamma, natural potential, P-wave time difference, S-wave time difference, neutron porosity and density; the box-whisker diagram of the logging data of the six sections in Well A-12H is shown in Figure 1. Figure 3 As shown, the box-whisker diagram of the logging data of this well section includes total hydrocarbons and C1, and the box-whisker diagram of drilling parameters includes mud density and drilling time.

[0053] Divide A-12H into 6 sections, draw the box-whisker diagram of well logging data, mud logging data and drilling data of the 6 sections in A-12H well, such as the third section of Well A;

[0054] The similarity metric analogy method was used to calculate the similarity coefficients between the five parameters in the box-whisker diagram of each section of the 110 well sections in the sample database and the five parameters in the box-whisker diagram of each section of the six well sections in the A-12 well.

[0055] Sorted by similarity coefficient, the acid fracturing parameters of each section of Well A-12 are designed as follows:

[0056] The first section with the highest similarity is M122-3, and the recommended acid strength is 0.99m 3 / (m·section), displacement 7.0m 3 / min;

[0057] The second section with the highest similarity is M118-3, and the recommended acid strength is 1.28m 3 / (m·section), displacement 8.5m 3 / min;

[0058] The third section with the highest similarity is M118-3, and the recommended acid strength is 1.28m 3 / (m·section), displacement 8.5m 3 / min;

[0059] The fourth section with the highest similarity is M118-2, and the recommended acid strength is 0.67m 3 / (m·section), displacement 7.8m 3 / min;

[0060] The 5th well section with the highest similarity is G01X32-5, and the recommended acid strength is 1.35m 3 / (m·section), displacement 7.5m 3 / min;

[0061] The most similar well section G01X37-2 in the 6th section is recommended to use acid strength 2.09m 3 / (m·section), displacement 7.5m 3 / min;

[0062] The A-12 well uses the method provided by the present invention to optimize acid fracturing parameters, and the daily gas production after acid fracturing is increased by 25% compared with the daily gas production before acid fracturing.

[0063] In addition, the present invention also proposes a data-driven acid fracturing parameter design system, such as Figure 4 As shown, the system includes a construction module, a optimization module, a drawing module, a calculation module and a design module; wherein the construction module is used to construct a sample database based on the well logging data, mud logging data, drilling data, acid fracturing data and production data of the acid fracturing section; the optimization module is used to optimize the production influencing factors based on the sample database; the drawing module is used to draw the box-whisker plot of the production influencing factors in the sample database and the logging data; the calculation module is used to calculate the similarity coefficient of the box-whisker plot of the production influencing factors in the sample database and the logging data, and obtain the similarity coefficient ranking result; the design module is used to design the acid fracturing parameters according to the similarity coefficient ranking result.

[0064] In summary, the data-driven acid fracturing parameter design method proposed in the present invention can realize the automation of design, reduce the design workload, and is suitable for the optimization design of segmented acid fracturing parameters in carbonate vertical wells, inclined wells and horizontal wells, thereby improving work efficiency.

[0065] Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent substitutions for some of the technical features therein; and these modifications or substitutions do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A data-driven acid fracturing parameter design method, characterized in that: The method comprises the following steps: Construct a sample database based on the well logging data, mud logging data, drilling data, acid fracturing data and production data of the acid fracturing well section; Based on the sample database, the factors affecting yield are optimized; Draw a box-and-whisker plot of production influencing factors and logging data in the sample database; Calculate the similarity coefficient of the box-whisker diagram of the production influencing factors in the sample database and the logging data, and obtain the ranking result of the similarity coefficient; The acid fracturing parameters are designed according to the similarity coefficient sorting results.

2. The method according to claim 1, characterized in that The logging data includes one or more of natural gamma, natural potential, well diameter, deep resistivity, shallow resistivity, P-wave time difference, S-wave time difference, sonic time difference, neutron porosity or density; The logging data includes the maximum value of total hydrocarbon or C 1-10 One or more of the values; The drilling data includes one or more of drilling time, mud density, overflow rate or well leakage rate; The production data may be one or more of test production or cumulative production within the same period of time.

3. The method according to claim 2, characterized in that Based on the sample database, the preferred yield influencing factors include: Based on the sample database, the yield influencing factors are optimized by data analysis methods; the data analysis methods include one or more of random forest, distributed gradient enhancement library, Pearson correlation coefficient, maximum information coefficient, distance correlation coefficient, grey correlation analysis or multiple regression method.

4. The method according to claim 2 or 3, characterized in that: The box-and-whisker plot includes five parameters: lower limit, lower quartile, median, upper quartile and upper limit.

5. The method according to claim 4, characterized in that The similarity coefficients of the box-whisker plots of the production influencing factors in the sample database and the well logging data are calculated to obtain the ranking results of the similarity coefficients, including: By using the similarity measurement analogy method, the similarity coefficients of the box-whisker plots of production influencing factors in the sample database and logging data are calculated, and the ranking results of the similarity coefficients are obtained.

6. The method according to claim 5, characterized in that The similarity measurement analogy method comprises: obtaining the acid fracturing parameters of the sample well section closest to the target well section through the similarity measurement model, and estimating the target section production range.

7. The method according to claim 5 or 6, characterized in that: The similarity coefficient is greater than or equal to 0.

9.

8. The method according to claim 7, characterized in that The acid fracturing parameters include one or more of the construction displacement, acid intensity or liquid intensity.

9. The application of a data-driven acid fracturing parameter design method according to any one of claims 1 to 8, characterized in that: The method is applied to the segmented acid fracturing parameter design of carbonate vertical wells, inclined wells and horizontal wells.

10. A data-driven acid fracturing parameter design system, characterized in that: The system includes a construction module, a optimization module, a drawing module, a calculation module and a design module; wherein, The construction module is used to construct a sample database based on the well logging data, mud logging data, drilling data, acid fracturing data and production data of the acid fracturing well section; The optimization module is used to optimize the factors affecting the yield based on the sample database; The drawing module is used to draw a box-and-whisker diagram of production influencing factors and logging data in a sample database; The calculation module is used to calculate the box-whisker plot similarity coefficients of the production influencing factors in the sample database and the well logging data to obtain the similarity coefficient ranking results; The design module is used to design acid fracturing parameters according to the similarity coefficient sorting results.

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