Sleeve transformation risk identification method, system and device, storage medium and program product

Abstract

The invention discloses a casing deformation risk identification method, system and device, a storage medium and a program product, and the method comprises the steps: respectively calculating a crustal stress state value Q of a horizontal well and a maximum and minimum principal stress difference value delta sigma max based on a three-dimensional stress result of horizontal well logging interpretation; obtaining a casing deformation dynamic variation coefficient D of the horizontal well according to the crustal stress state value Q and the maximum and minimum stress difference value delta sigma max; and based on the casing deformation power variation coefficient D, determining a casing deformation risk threshold value delta Da of the horizontal well, and further obtaining a casing deformation risk coefficient R of the horizontal well so as to identify a casing deformation risk point of the horizontal well. According to the invention, accurate identification of the horizontal well casing deformation risk point is realized.

Description

Technical Field

[0001] This invention relates to the field of geological exploration technology, and in particular to methods, systems, equipment, storage media, and program products for identifying risks related to geological variations. Background Technology

[0002] Based on years of exploration and development practices both domestically and internationally, horizontal well multi-stage fracturing technology is a key technology for the effective development of shale gas and coalbed methane resources, and the quality of horizontal well construction is crucial for achieving efficient development.

[0003] Currently, in some areas where the problem of casing deformation in horizontal wells is more serious, a deep integration of scientific research and engineering technology is adopted to reduce the risk of casing deformation by optimizing the casing steel grade and increasing the thickness of the cement sheath. However, in some areas, there are characteristics of large ground stress differences and rapid changes in local ground stress state. In these areas, it is difficult to solve the problem of casing deformation in horizontal wells by increasing the thickness of the cement sheath.

[0004] Therefore, the current identification of casing deformation risk in horizontal wells in this area is mainly qualitative. In particular, during the design of multi-stage fracturing, the risk of post-fracturing casing deformation is mainly determined by identifying fracture development zones and fault zones. However, long-term practice shows that a large number of casing deformations do not occur in fracture development zones or fault zones, and the identification results of whether casing deformation has occurred are poor.

[0005] Therefore, a new method for identifying casing deformation risks in horizontal wells is urgently needed to solve the problem of casing deformation risks and achieve accurate identification of casing deformation risk points in horizontal wells. Summary of the Invention

[0006] The purpose of this invention is to provide a method, system, device, storage medium, and program product for identifying casing deformation risks in horizontal wells, so as to achieve accurate identification of casing deformation risk points.

[0007] To achieve the above objectives, the present invention provides the following technical solution:

[0008] In a first aspect, embodiments of the present invention provide a method for identifying risks associated with arbitrage, including:

[0009] Based on the triaxial stress results interpreted from horizontal well logging, the geostress state value Q and the difference between the maximum and minimum principal stresses Δσ of the horizontal well are calculated. max ;

[0010] Based on the geostress state value Q and the maximum and minimum stress difference Δσ of the horizontal well max The coefficient of variation D of the casing dynamics of the horizontal well is obtained.

[0011] Based on the casing deformation dynamic variation coefficient D, the casing deformation risk threshold ΔD for horizontal wells is determined. aThis allows us to obtain the casing risk coefficient R of the horizontal well, in order to identify the casing risk points of the horizontal well.

[0012] Secondly, embodiments of the present invention provide a risk identification system for asset redistribution, comprising:

[0013] The first calculation unit is used to calculate the geostress state value Q of the horizontal well and the difference between the maximum and minimum principal stresses Δσ, based on the triaxial stress results interpreted from the horizontal well logging. max ;

[0014] The second calculation unit is used to calculate the geostress state value Q of the horizontal well and the maximum and minimum stress difference Δσ. max The coefficient of variation D of the casing dynamics of the horizontal well is obtained.

[0015] The third calculation unit is used to determine the casing deformation risk threshold ΔD of the horizontal well based on the casing deformation dynamic variation coefficient D. a This allows us to obtain the casing risk coefficient R of the horizontal well, in order to identify the casing risk points of the horizontal well.

[0016] Thirdly, embodiments of the present invention also provide an electronic device, including a memory, a processor, and a computer program stored in the memory, wherein the processor executes the computer program or instructions to implement the aforementioned method for identifying risk of asset stripping.

[0017] Fourthly, embodiments of the present invention also provide a computer storage medium storing a computer program or instructions, which, when executed by a processor, implement the aforementioned method for identifying risk of asset stripping.

[0018] Fifthly, embodiments of the present invention also provide a computer program product, including a computer program or instructions, which, when executed by a processor, implement the aforementioned method for identifying risk of asset stripping.

[0019] The technical effects and advantages of this invention are as follows: By accurately analyzing the geostress state that causes horizontal well casing deformation and combining the magnitude of the geostress difference, this invention can accurately predict the risk points of horizontal well casing deformation. By avoiding the risk points and reducing the scale of fracturing operations in adjacent well sections during multi-stage fracturing, the probability of horizontal well casing deformation can be effectively reduced.

[0020] Other features and advantages of the invention will be set forth in the description which follows, and will be apparent in part from the description, or may be learned by practicing the invention. The objects and other advantages of the invention may be realized and obtained by means of the structures pointed out in the description, claims and drawings. Attached Figure Description

[0021] To more clearly illustrate the technical solutions in the embodiments of the present invention, 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 the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0022] Figure 1 This is a flowchart of a method for identifying risks associated with arbitrage according to an embodiment of the present invention;

[0023] Figure 2 This is a schematic diagram illustrating the variation of horizontal geostress values ​​at different depths in well A according to an embodiment of the present invention;

[0024] Figure 3 This is a schematic diagram of the horizontal stress state values ​​of well A at different depths in an embodiment of the present invention;

[0025] Figure 4 This is a schematic diagram showing the difference between the maximum and minimum principal stresses in the horizontal sections of well A at different depths in an embodiment of the present invention;

[0026] Figure 5 This is a schematic diagram of the variation coefficient D of the horizontal section of well A at different depths in an embodiment of the present invention.

[0027] Figure 6 This is a schematic diagram illustrating the variation of the coefficient of variation D of the 6-meter inner casing of the horizontal section at different depths in well A according to an embodiment of the present invention.

[0028] Figure 7 This is a schematic diagram of the horizontal section variation risk coefficient at different depths in well A according to an embodiment of the present invention;

[0029] Figure 8 This is a schematic diagram verifying the risk coefficient and location of the horizontal section casing deformation at different depths in well A according to an embodiment of the present invention.

[0030] Figure 9 This is a schematic diagram of the structure of a risk identification system for asset transfer according to an embodiment of the present invention;

[0031] Figure 10 This is a schematic diagram of the structure of an electronic device according to an embodiment of the present invention. Detailed Implementation

[0032] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0033] To address the shortcomings of existing technologies, embodiments of the present invention disclose a method for identifying risks associated with asset redistribution, such as... Figure 1 As shown, it includes the following steps:

[0034] Step S1: Based on the triaxial stress results interpreted from the horizontal well logging, calculate the geostress state value Q of the horizontal well and the difference between the maximum and minimum principal stresses Δσ. max ;

[0035] Step S2: Based on the geostress state value Q and the maximum and minimum stress difference Δσ max The coefficient of variation D of the casing dynamics of the horizontal well is obtained.

[0036] Step S3: Based on the casing deformation dynamic variation coefficient D, determine the casing deformation risk threshold ΔD for the horizontal well. a This allows us to obtain the casing risk coefficient R of the horizontal well, in order to identify the casing risk points of the horizontal well.

[0037] In some specific embodiments, step S1: Based on the triaxial stress results interpreted from the horizontal well logging, calculate the geostress state value Q of the horizontal well and the difference between the maximum and minimum principal stresses Δσ. max include:

[0038] Step S11: Based on the triaxial stress results interpreted from the horizontal well logging, the geostress state value Q of the horizontal well is calculated according to Anderson stress state analysis; the calculation process is as follows:

[0039] When the geostress state of the horizontal well is σ v >σ Hmax >σ Hmin In the case of a normal fault, the geostress state value Q of the horizontal well is calculated using the following formula:

[0040]

[0041] When the geostress state of the horizontal well is σ Hmax >σ v >σ Hmin In the case of a strike-slip fault, the geostress state parameter Q is calculated using the following formula:

[0042]

[0043] When the geostress state of the horizontal well is σ Hmax >σ Hmin >σ v In the case of (reverse fault type), the geostress state parameter Q is calculated using the following formula:

[0044]

[0045] In the formula, Q represents the value of the geostress state of the horizontal well, which is dimensionless; σv represents the vertical principal stress of the horizontal well, in MPa; σHmax represents the maximum principal stress of the horizontal well, in MPa; and σHmin represents the minimum principal stress of the horizontal well, in MPa.

[0046] Step S12: Based on the triaxial stress results interpreted from the horizontal well logging, calculate the difference between the maximum and minimum principal stresses, Δσ. max The calculation process is as follows:

[0047] When the geostress state of the horizontal well is σ v >σ Hmax >σ Hmin (Normal fault type), the difference between the maximum and minimum principal stresses Δσ in the horizontal well is calculated using the following formula. max for:

[0048] Δσ max =σ v -σ Hmin ;

[0049] When the geostress state of the horizontal well is σ Hmax >σ v >σ Hmin (Strike-slip fault type), the difference between the maximum and minimum principal stresses Δσ in the horizontal well is calculated using the following formula. max for:

[0050] Δσ max =σ Hmax -σ Hmin ;

[0051] When the geostress state of the horizontal well is σ Hmax >σ Hmin >σ v (Reverse fault type), the difference between the maximum and minimum principal stresses Δσ in the horizontal well is calculated using the following formula. max for:

[0052] Δσ max =σ Hmax -σ v ;

[0053] Where, Δσ max σv represents the difference between the maximum and minimum principal stresses of the horizontal well, the maximum driving force for casing deformation caused by the horizontal well, in MPa; σv represents the vertical principal stress of the horizontal well, in MPa; σHmax represents the maximum principal stress of the horizontal well, in MPa; σHmin represents the minimum principal stress of the horizontal well, in MPa.

[0054] Since conventional logging arrays can provide accurate interpretations of triaxial stress in horizontal well sections, this invention uses readily available and accurate triaxial stress interpretations as its data foundation in this step. This approach is highly operable and facilitates the widespread application of this invention.

[0055] In some specific embodiments, step S2: based on the geostress state value Q and the maximum and minimum stress difference Δσ max The coefficient of variation D of the casing dynamics of the horizontal well is obtained as follows:

[0056] The stress state value Q and the maximum and minimum stress difference Δσ of the horizontal well are used to calculate the stress state value Q. max Multiplying the values ​​yields the coefficient of variation D of the casing dynamics in the horizontal well. The specific calculation formula is as follows:

[0057] D=Q·Δσ max ;

[0058] In the formula, D represents the casing dynamic variation coefficient of the horizontal well, and the unit is MPa.

[0059] Since the change in the geostress state around a horizontal well is the intrinsic mechanical cause of casing deformation, and the magnitude of the maximum stress difference in the horizontal well characterizes the main parameter of reservoir strain energy and provides the driving force for casing deformation, in this step, the embodiment of the present invention compares the geostress state value Q characterizing the horizontal well with the parameter Δσ characterizing reservoir strain energy. max Establishing connections to analyze risk of arbitrage is a scientific approach.

[0060] In some specific embodiments, step S3: Based on the casing deformation dynamic variation coefficient D, determine the casing deformation risk threshold ΔD for the horizontal well. a This leads to the acquisition of the casing deformation risk coefficient R for horizontal wells, including:

[0061] Based on the casing deformation dynamic variation coefficient D, combined with the geostress in the area where the horizontal well is located and the construction characteristics of the horizontal well, the casing deformation risk threshold ΔD of the horizontal well is obtained. a That is, based on practice, the aforementioned risk threshold ΔD is clearly defined. a .

[0062] Based on the distance interval of well logging data acquisition (e.g., 0.125m), the degree of change of the casing deformation dynamic variation coefficient D within a predetermined range or a certain range is determined, and the casing deformation risk threshold ΔD is calculated. a The calculation points are taken forward and backward by predetermined step sizes (e.g., L / 2 step size, where L represents the original step size) to obtain the maximum threshold ΔD of casing deformation risk for the corresponding horizontal well. max .

[0063] The casing deformation risk threshold ΔD for horizontal wells aAnd the maximum threshold of risk ΔD max The ratio of the two values ​​is used as the casing deformation risk coefficient R for horizontal wells, and the risk level of casing deformation that may be found in horizontal wells is obtained through the value of the casing deformation risk coefficient R.

[0064] The casing deformation risk coefficient R of the horizontal well is calculated using the following formula:

[0065]

[0066] In the formula, R represents the casing deformation risk coefficient of the horizontal well, and ΔD max ΔD represents the maximum threshold for casing deformation risk in horizontal wells. a This indicates the casing deformation risk threshold for horizontal wells;

[0067] Among them, when R>1, it indicates that the horizontal well has the risk of casing deformation; when R>2, it indicates that the horizontal well has a relatively high risk of casing deformation; and when R>3, it indicates that the horizontal well has a high risk of casing deformation.

[0068] In this step, the present invention establishes a risk coefficient R for housing transformation based on basic mechanical principles, and judges the probability of housing transformation occurring through quantitative results; the quantitative evaluation improves the objectivity of housing transformation evaluation and solves the uncertainty problem of subjective quantitative evaluation.

[0069] This invention primarily addresses the issue of wellbore deformation during horizontal section fracturing in relatively complex regions with large principal stress differences, such as southern Sichuan, which severely impacts oil and gas development. The invention utilizes triaxial stress results from horizontal well logging interpretation to calculate the parameter value Q characterizing the geostress state of the horizontal well using Anderson stress state analysis. Then, based on the triaxial stress results from horizontal well logging interpretation, the maximum and minimum principal stress difference Δσ of the horizontal well is determined. max The product of these two factors yields the coefficient of variation of the dynamics of the set-top box, D = Q·Δσ. max By combining regional geostress and horizontal well construction characteristics, the casing deformation risk threshold of horizontal wells is obtained, and then the casing deformation risk coefficient R is obtained to achieve accurate identification of casing deformation risk points of horizontal wells.

[0070] This invention selects horizontal well logging and casing deformation data from shale gas blocks in Changning, Weiyuan, and Luzhou in the Sichuan Basin to verify the effectiveness of the method. Taking well A in the Sichuan Basin shale gas horizontal wells as an example, the method calculates and obtains the following data: Figures 2 to 8 The results shown are: triaxial geostress at different depths in well A, Q value, difference between maximum and minimum principal stress, coefficient of variation of casing deformation dynamics, change in coefficient of variation D of casing deformation dynamics within 6 meters, and casing deformation risk coefficient R value; based on... Figure 8 As shown, there are 6 locations of casing deformation in the horizontal section of well A, and the casing deformation risk coefficient R value is greater than 1.5. This indicates that the prediction results of the method of the present invention are accurate.

[0071] This invention discloses a risk identification system for arbitrage, such as... Figure 9 As shown, it includes:

[0072] The first calculation unit is used to calculate the geostress state value Q of the horizontal well and the difference between the maximum and minimum principal stresses Δσ, based on the triaxial stress results interpreted from the horizontal well logging. max ;

[0073] The second calculation unit is used to calculate the geostress state value Q of the horizontal well and the maximum and minimum stress difference Δσ. max The coefficient of variation D of the casing dynamics of the horizontal well is obtained.

[0074] The third calculation unit is used to determine the casing deformation risk threshold ΔD of the horizontal well based on the casing deformation dynamic variation coefficient D. a This allows us to obtain the casing risk coefficient R of the horizontal well, in order to identify the casing risk points of the horizontal well.

[0075] Regarding the system in the above embodiments, the specific manner in which each unit module performs operations has been described in detail in the embodiments related to the method, and will not be elaborated here.

[0076] Based on the same inventive concept, embodiments of the present invention also provide an electronic device, the structure of which is as follows: Figure 10 As shown, it includes a memory, a processor, and a computer program stored in the memory. The processor executes the computer program or instructions to implement the aforementioned method for identifying risk of asset tampering.

[0077] Based on the same inventive concept, embodiments of the present invention also provide a computer storage medium storing a computer program or instructions, which, when executed by a processor, implements the aforementioned method for identifying risk of asset stripping.

[0078] Based on the same inventive concept, embodiments of the present invention also provide a computer program product, including a computer program or instructions, which, when executed by a processor, implement the aforementioned method for identifying risk of asset transfer.

[0079] Finally, it should be noted that the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments or make equivalent substitutions for some of the technical features. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for identifying risks associated with arbitrage, characterized in that, include: Based on the triaxial stress results interpreted from horizontal well logging, the geostress state value Q and the difference between the maximum and minimum principal stresses Δσ of the horizontal well are calculated. max ; Based on the geostress state value Q and the maximum and minimum stress difference Δσ max The coefficient of variation D of the casing dynamics of the horizontal well is obtained. Based on the casing deformation dynamic variation coefficient D, the casing deformation risk threshold ΔD for horizontal wells is determined. a This allows us to obtain the casing risk coefficient R of the horizontal well, in order to identify the casing risk points of the horizontal well.

2. The method for identifying risk of arbitrage according to claim 1, characterized in that, Calculate the geostress state value Q and the difference between the maximum and minimum principal stresses Δσ for the horizontal well. max ,include: Based on the triaxial stress results interpreted from the horizontal well logging, the geostress state value Q of the horizontal well is calculated according to Anderson stress state analysis. Based on the triaxial stress results interpreted from the horizontal well logging, the difference between the maximum and minimum principal stresses Δσ in the horizontal well is calculated. max .

3. The method for identifying risk of arbitrage according to claim 1, characterized in that, Based on the triaxial stress results interpreted from horizontal well logging, the geostress state value Q of the horizontal well is calculated according to Anderson stress state analysis, including: When the in-situ stress state of the horizontal well is σv>σHmax>σHmin, the in-situ stress state value Q of the horizontal well is calculated using the following formula: When the in-situ stress state of a horizontal well is σHmax > σv > σHmin, the in-situ stress state value Q of the horizontal well can be calculated using the following formula: When the stress state of a horizontal well is σHmax > σHmin > σv, the stress state value Q of the horizontal well can be calculated using the following formula: In the formula, Q represents the geostress state value of the horizontal well, σv represents the vertical principal stress, σHmax represents the maximum horizontal principal stress, and σHmin represents the minimum horizontal principal stress.

4. A method for identifying risks associated with arbitrage according to claim 2 or 3, characterized in that, Based on the triaxial stress results interpreted from the horizontal well logging, the difference between the maximum and minimum principal stresses Δσ in the horizontal well is calculated. max include: When the stress state of a horizontal well is σv > σHmax > σHmin, the difference between the maximum and minimum principal stresses Δσ in the horizontal well can be calculated using the following formula. max for: Board max =s v -s Hmin ; When the stress state of a horizontal well is σHmax > σv > σHmin, the difference between the maximum and minimum principal stresses Δσ in the horizontal well can be calculated using the following formula. max for: Board max =s Hmax -s Hmin ; When the geostress state of a horizontal well is σHmax > σHmin > σv, the difference between the maximum and minimum principal stresses Δσ in the horizontal well can be calculated using the following formula. max for: Board max =s Hmax -s v ; Where, Δσ max σv represents the difference between the maximum and minimum principal stresses of a horizontal well, σHmax represents the maximum principal stress of a horizontal well, and σHmin represents the minimum principal stress of a horizontal well.

5. The method for identifying risks associated with arbitrage according to claim 1, characterized in that, Based on the geostress state value Q of the horizontal well and the maximum and minimum stress difference Δσ max To obtain the coefficient of variation D of the casing dynamics of a horizontal well, including: The stress state value Q of the horizontal well and the maximum and minimum stress difference Δσ of the horizontal well are used to calculate the stress state value Q of the horizontal well. max Multiplying the results, we obtain the coefficient of variation D of the casing dynamics in the horizontal well: D=Q·Dσ max 。 6. The method for identifying risks associated with arbitrage according to claim 1, characterized in that, Based on the casing deformation dynamic variation coefficient D, the casing deformation risk threshold ΔD for horizontal wells is determined. a This leads to the acquisition of the casing deformation risk coefficient R for horizontal wells, including: Based on the casing deformation dynamic variation coefficient D, combined with the geostress in the area where the horizontal well is located and the construction characteristics of the horizontal well, the casing deformation risk threshold ΔD of the horizontal well is obtained. a ; Based on the distance intervals of well logging data acquisition, the degree of change of the casing deformation dynamic variation coefficient D within a predetermined range is determined, and the casing deformation risk threshold ΔD is calculated. a The calculation points are taken with predetermined step sizes forward and backward to obtain the maximum threshold ΔD of casing deformation risk for the corresponding horizontal well. max ; Based on the casing deformation risk threshold ΔD of horizontal wells a And the maximum threshold of risk ΔD max The casing deformation risk coefficient R of the horizontal well is obtained as follows:

7. A risk identification system for asset redistribution, characterized in that, include: The first calculation unit is used to calculate the geostress state value Q of the horizontal well and the difference between the maximum and minimum principal stresses Δσ, based on the triaxial stress results interpreted from the horizontal well logging. max ; The second calculation unit is used to calculate the geostress state value Q of the horizontal well and the maximum and minimum stress difference Δσ. max The coefficient of variation D of the casing dynamics of the horizontal well is obtained. The third calculation unit is used to determine the casing deformation risk threshold ΔD of the horizontal well based on the casing deformation dynamic variation coefficient D. a This allows us to obtain the casing risk coefficient R of the horizontal well, in order to identify the casing risk points of the horizontal well.

8. An electronic device, characterized in that, The system includes a memory, a processor, and a computer program stored in the memory, wherein the processor executes the computer program or instructions to implement the risk identification method for arbitrage as described in any one of claims 1-6.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program or instructions, which, when executed by a processor, implement the risk identification method for escrow as described in any one of claims 1-6.

10. A computer program product, comprising a computer program or instructions, characterized in that, When the computer program or instructions are executed by the processor, they implement the risk identification method for arbitrage as described in any one of claims 1-6.

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