Method and device for analyzing water plugging construction shaft integrity risk

Abstract

The invention discloses a method and device for analyzing the integrity risk of a water plugging construction shaft, and the method comprises the steps: determining multi-level factors affecting the integrity of the water plugging shaft of an oil well, collecting the index data of each factor, and determining the weight of each factor in the multi-level factors compared with the previous-level factor, the method comprises the steps of obtaining index data of each factor, then constructing an evaluation model representing the influence degree of a single factor on different risk levels, determining an evaluation matrix of each factor according to the evaluation model and the index data of each factor, and finally determining the current wellbore integrity risk state according to the weight of each factor and the evaluation matrix. According to the method, the integrity state of the shaft can be found in time, accidents caused by the fact that the shaft state is not clear are avoided, optimization operation of water shutoff related factors is carried out based on the current shaft integrity risk state, and therefore the high shaft integrity state is kept.

Description

Technical Field

[0001] The present invention relates to the technical field of oil reservoir water plugging engineering, and in particular to a method and device for analyzing the integrity risk of a water plugging construction wellbore. Background Art

[0002] During the process of oil reservoir water plugging construction, due to various factors related to oil reservoir design, surface pump trucks, wellhead production trees, underground pipe strings, on-site operations, etc., it has the characteristics of complexity, comprehensiveness, and multi-factor nature. Once the wellbore integrity is damaged, it will cause great consequences to the environment, resources, personnel, etc.

[0003] In the prior art, after an oil well enters the high water cut state, water plugging construction operations are often carried out according to past experience. However, due to factors such as equipment, construction, and chemicals, the integrity of oil well water plugging is in an unclear state, which is likely to affect the environment, resources, personnel, etc.

[0004] Therefore, there is an urgent need for a method to evaluate and analyze the integrity of oil well water plugging construction to ensure the integrity of oil well water plugging and thus avoid the occurrence of water plugging construction accidents. Summary of the Invention

[0005] The purpose of the present invention is to provide a method for evaluating and analyzing the integrity of oil well water plugging construction to ensure the integrity of oil well water plugging and thus avoid the occurrence of water plugging construction accidents.

[0006] To solve the above technical problems, an embodiment of the present invention provides a method for analyzing the integrity risk of a water plugging construction wellbore, including: determining multi-level factors affecting the integrity of an oil well water plugging wellbore and collecting index data of each factor; determining the weight of each factor in the multi-level factors compared with the previous-level factor; constructing an evaluation model representing the influence degree of a single factor on different risk levels, and determining the evaluation matrix of each factor according to the evaluation model and the index data of each factor; determining the current wellbore integrity risk status according to the weight and evaluation matrix of each factor.

[0007] Preferably, in the step of determining multi-level factors affecting the integrity of an oil well water plugging wellbore and collecting index data of each factor, it includes: sorting and classifying each factor affecting the integrity of an oil well water plugging wellbore to form multiple primary influencing factors targeted at wellbore integrity risk and several secondary influencing factors respectively belonging to the primary influencing factors; quantifying the data information of the primary influencing factors and the secondary influencing factors to obtain the index data of each factor.

[0008] Preferably, in the step of determining the weight of each factor in the multi-level factors compared with the previous-level factor, it includes: constructing a first type of pairwise comparison matrix of several second-level influencing factors under the same first-level influencing factor; constructing a second type of pairwise comparison matrix of multiple first-level influencing factors under the target; calculating the weight of each factor according to the first type of pairwise comparison matrix and the first type of pairwise comparison matrix.

[0009] Preferably, the method further includes: performing a consistency ratio test on the weight of each factor, and performing subsequent operations when it is determined that the weight of each factor meets the consistency ratio.

[0010] Preferably, the evaluation matrix of the i-th factor is calculated by calculating the membership degrees of the factor compared with different risk levels respectively, where the evaluation matrix of the i-th factor is expressed as:

[0011] R i =(r i1 ,r i2 ,…,r in )

[0012] where Ri represents the evaluation matrix of the i-th factor, and n represents the number of risk levels.

[0013] Preferably, according to the weight and evaluation matrix of each factor, determining the current wellbore integrity risk state includes: calculating the evaluation matrix of each first-level influencing factor by using the weighted average method according to the weights and corresponding evaluation matrices of several second-level influencing factors under the same first-level influencing factor; calculating the evaluation matrix of the target according to the evaluation matrix of each first-level influencing factor and the corresponding weight; and determining the risk level corresponding to the current wellbore integrity based on the evaluation matrix of the target by using the maximum membership degree principle.

[0014] Preferably, the method further includes: judging whether to optimize the influencing factors based on the current wellbore integrity risk state information; when it is determined to optimize the influencing factors, determining the factors to be adjusted based on the weights and evaluation matrices of each factor, and optimizing the factors to be adjusted.

[0015] Preferably, in the step of judging whether to optimize the influencing factors based on the current wellbore integrity risk state information, it includes: when the current wellbore integrity risk is a risk level other than low risk and no risk, determining that the influencing factors need to be optimized currently.

[0016] On the other hand, an embodiment of the present invention also provides a device for analyzing the integrity risk of a water shutoff construction wellbore, including: a data determination module configured to determine multi-level factors affecting the integrity of the oil well water shutoff wellbore and collect index data of each factor; a weight determination module configured to determine the weight of each factor in the multi-level factors compared to the previous-level factor; a matrix determination module configured to construct an evaluation model representing the influence degree of a single factor on different risk levels, and determine the evaluation matrix of each factor according to the evaluation model and the index data of each factor; a state determination module configured to determine the current wellbore integrity risk state according to the weight and evaluation matrix of each factor.

[0017] On the other hand, an embodiment of the present invention provides a computer-readable storage medium containing a series of instructions for executing the method steps as described above.

[0018] Compared with the prior art, one or more embodiments of the above solutions may have the following advantages or beneficial effects:

[0019] The present invention proposes a method and a device for analyzing the integrity risk of a water shutoff construction wellbore. The method and the device determine multi-level factors affecting the integrity of the oil well water shutoff wellbore and collect index data of each factor, then determine the weight of each factor in the multi-level factors compared to the previous-level factor, and further construct an evaluation model representing the influence degree of a single factor on different risk levels. According to the evaluation model and the index data of each factor, the evaluation matrix of each factor is determined. Finally, according to the weight and evaluation matrix of each factor, the current wellbore integrity risk state is determined. The present invention can timely detect the integrity state of the wellbore, avoid accidents caused by unclear wellbore states, and perform optimization operations on water shutoff-related factors based on the current wellbore integrity risk state, so as to maintain a relatively high wellbore integrity state.

[0020] Other features and advantages of the present invention will be described in the following specification, and some of them will become obvious from the specification, or be understood by implementing the present invention. The objectives and other advantages of the present invention can be achieved and obtained through the structures specifically pointed out in the specification, claims, and drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] The drawings are used to provide a further understanding of the present invention, and constitute a part of the specification. They are used together with the embodiments of the present invention to explain the present invention, but do not constitute a limitation to the present invention. In the drawings:

[0022] Figure 1 It is a schematic diagram of the steps of the method for analyzing the integrity risk of a water shutoff construction wellbore according to an embodiment of the present application.

[0023] Figure 2Schematic diagram of the multi-level factor relationship model in the method for analyzing the integrity risk of the wellbore during water plugging construction according to the embodiments of the present application.

[0024] Figure 3 Schematic diagram of the structure of the device for analyzing the integrity risk of the wellbore during water plugging construction according to the embodiments of the present application. Detailed implementation manners

[0025] The following will describe in detail the implementation manners of the present invention in conjunction with the accompanying drawings and embodiments, so as to fully understand how the present invention uses technical means to solve technical problems and achieve the implementation process of technical effects and implement accordingly. It should be noted that as long as there is no conflict, the various embodiments in the present invention and the various features in each embodiment can be combined with each other, and the formed technical solutions are all within the protection scope of the present invention.

[0026] In addition, the steps shown in the flowchart of the accompanying drawings can be executed in a computer device such as a set of computer executable instructions. And although the logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in a different order than here.

[0027] The terms used herein are only for describing specific embodiments and are not intended to limit the exemplary embodiments. Unless the context clearly indicates otherwise, the singular forms "a" and "an" used herein are also intended to include the plural. It should also be understood that the terms "including" and / or "comprising" used herein specify the presence of the stated features, integers, steps, operations, units, and / or components, and do not exclude the presence or addition of one or more other features, integers, steps, operations, units, components, and / or their combinations.

[0028] Currently, the reservoir chemical water plugging technology in Tahe Oilfield is a technology that effectively improves oil recovery after gas injection and water injection. The annual oil increment shows a gradually increasing trend, and it has become a relatively mature technology for increasing production. The water plugging operation during construction involves various aspects such as reservoir design, surface pump trucks, wellhead Christmas trees, downhole strings, and on-site operations, and has the characteristics of complexity, comprehensiveness, and multi-factor. Once the wellbore integrity is damaged, it will have a great impact on the environment, resources, personnel, etc.

[0029] To solve one or more of the technical problems described in the background art, embodiments of the present invention provide a method and a device for analyzing the integrity risk of the wellbore during water plugging construction. The method and device evaluate the integrity of the oil well water plugging construction, collect the factors related to the integrity of the oil well water plugging construction, clarify their weights through the analytic hierarchy process, combine the fuzzy comprehensive evaluation, clarify the state of the oil well water plugging integrity, and correct the weak links therein, so as to ensure the integrity of the oil well water plugging construction.

[0030] See Figure 1 , Figure 1 which is a schematic diagram of the steps of the method for analyzing the wellbore integrity risk of water plugging construction in an embodiment of the present application, specifically including the following steps.

[0031] Step S110: Determine the multi-level factors affecting the wellbore integrity of the oil well water plugging and collect the index data of each factor.

[0032] Specifically, first determine multiple factors that may be relevant during the oil well water plugging construction, and form a multi-level factor relationship model for the multiple factors (see Figure 2 ). Then, collect the data corresponding to these multi-level factors, and further collect and organize the data corresponding to the multi-level factors, so as to determine the weights between the multi-level factors based on the collected and organized data later.

[0033] In one embodiment, when determining the multi-level factors and organizing them based on the determined multi-level factors, it is necessary to establish a multi-level factor relationship model representing the mutual correlation relationship between the multiple factors.

[0034] In step S110, it includes:

[0035] Sort and classify each factor affecting the wellbore integrity of the oil well water plugging to form multiple primary influencing factors targeted at the wellbore integrity risk and several secondary influencing factors belonging to each primary influencing factor respectively;

[0036] Quantify the data information of each secondary influencing factor to obtain the index data of each factor.

[0037] As Figure 2 shown, the primary influencing factors can be understood as the middle layer (i.e., the criterion layer) in the multi-level factor relationship model, and the secondary influencing factors can be understood as the scheme layer belonging to the next level under the criterion layer in the multi-level factor relationship model.

[0038] Specifically, in combination with the current standards of water plugging, referring to the on-site water plugging construction device and the precautions during the construction process, determine each factor affecting the wellbore integrity of the oil well water plugging, collect the data information corresponding to each factor, and then form a multi-level factor relationship model for the collected data information corresponding to each factor in the manner of multiple primary influencing factors targeted at the wellbore integrity risk and several secondary influencing factors belonging to each primary influencing factor respectively; and the data information of each secondary influencing factor can be quantified to obtain the index data of each factor.

[0039] Figure 2 is a schematic diagram of the multi-level factor relationship model in the method for analyzing the wellbore integrity risk of water plugging construction in an embodiment of the present application.

[0040] As Figure 2 shown, the highest level (i.e., the target level): the integrity risk of Well A's water shutoff wellbore; the middle level (i.e., the criterion level) has four major categories of factors, namely: B1 Indoor Design, B2 Wellhead Barrier, B3 Downhole Barrier, B4 On-site Construction; the bottom level (i.e., the solution level) respectively has: C1 Plug Design, C2 Construction Technology, C3 Chemical Dosage belonging to B1 Indoor Design; C4 Christmas Tree, C5 Tubing Head, C6 Casing Head, C7 Surface Pipeline, C8 Sucker Rod Hanger belonging to B2 Wellhead Barrier; C9 Tubing, C10 Rod Pump, C11 Casing, C12 Cement Sheath, C13 Formation belonging to B3 Downhole Barrier; C14 Qualification Certificates, C15 H2S Emergency Disposal, C16 Standard Management, C17 Pressure Control, etc. belonging to B4 On-site Construction. Thus, the secondary influencing factors in the solution level cover the entire process of water shutoff construction, starting from indoor design and implementing to on-site water shutoff construction, with the characteristics of systematicness, comprehensiveness, and integrity.

[0041] After the implementation of step S110, the importance ratio of each factor in the multi-level factors to the previous-level factor, that is, the weight value, can be based on the determined multi-level factors in the subsequent step S120.

[0042] Step S120 determines the weight of each factor in the multi-level factors obtained in step S110 compared to the previous-level factor.

[0043] Specifically, after obtaining the multi-level factors affecting the integrity of the water shutoff wellbore of the oil well in step S110, the weight can be determined based on this multi-level factor and the analytic hierarchy process, that is, calculate the weight value of each factor in the multi-level factors compared to the previous-level factor, and then obtain the importance ratio of each factor to the previous factor.

[0044] In one embodiment, when calculating the weight of each factor in the multi-level factors compared to the previous-level factor, a pairwise comparison matrix of the same level can be constructed, and then the weight of each factor can be calculated based on the constructed pairwise comparison matrix. The specific implementation method is as follows:

[0045] Construct the first type of pairwise comparison matrix of several secondary influencing factors under the same first-level influencing factor, so as to form a corresponding first type of pairwise comparison matrix for each first-level influencing factor;

[0046] Construct the second type of pairwise comparison matrix of multiple first-level influencing factors under the target, so as to form the second type of pairwise comparison matrix for this target;

[0047] Calculate the weight of each factor according to all the first type of pairwise comparison matrices and the second type of pairwise comparison matrices.

[0048] It should be noted that the construction process of the pairwise comparison matrix in the embodiments of the present invention is similar to that in the analytic hierarchy process, so the applicant will not elaborate here. In this way, the present invention determines the importance of each factor at a certain level for the same factor at the upper level through pairwise comparison, so as to obtain the weights of each factor.

[0049] For example, based on the foregoing Figure 2 content, the establishment of the scale comparison criterion is described. Specifically, it is determined that the importance ratios of the intermediate layers B1 indoor design, B2 wellhead barrier, B3 downhole barrier, and B4 on-site construction compared to the top-level target A integrity risk of the plugged water wellbore are a 1n , where n represents the serial numbers of each primary influencing factor. Among them, the scale comparison criteria for the importance of each factor B1 - B4 are shown in Table 1 below.

[0050] Table 1 Scale Comparison Criterion

[0051]

[0052]

[0053] In this way, after obtaining the weight of each factor in the multi-level factors compared to the previous-level factor, based on this and combined with the evaluation matrix obtained in subsequent step S103, the integrity risk status of the wellbore is determined.

[0054] After calculating the weight of each factor, it is necessary to check the coordination between the importance degrees of each element to avoid data conflict problems. The consistency ratio of the weight of each factor is tested, and subsequent operations are performed when it is determined that the weight of each factor meets the consistency ratio.

[0055] Specifically, first, calculate the consistency index CI for the weight of each factor, find the corresponding average random consistency index RI, then calculate the consistency ratio CR based on the consistency CI and the average random consistency index RI, and determine whether the consistency ratio CR is less than 0.1. If it is determined that the consistency ratio CR is less than 0.1, it is determined that the consistency ratio test is passed, and the subsequent step S130 operation is continued.

[0056] Step S130 constructs an evaluation model representing the influence degree of a single factor on different risk levels, and determines the evaluation matrix of each factor according to this evaluation model and the index data of each factor.

[0057] In step S130, first, an evaluation model corresponding to each element needs to be established. Among them, this evaluation model can be a one-dimensional sequence composed of different risk level evaluations. For example, the risk levels can be high risk, medium risk, low risk, no risk, etc.

[0058] In one embodiment, the evaluation matrix of the i-th element is calculated by computing the membership degrees of this factor with respect to different risk levels. Among them, the evaluation matrix of the i-th factor is expressed as:

[0059] R i =(r i1 ,r i2 ,…,r in )

[0060] where R i represents the evaluation matrix of the i-th factor, and n represents the number of risk levels.

[0061] Specifically, calculate the membership degree of the i-th element u i in the factor set U formed by all factors j for the j-th element v ij in the evaluation set as r ij

[0062] ij =f(u i )

[0063] where r ij represents the membership degree of the element u i belonging to v j , and f(u i ) represents the membership degree function of the element v j . After determining the membership degrees of all elements in the factor set, the total membership degree set R (i.e., the set matrix composed of the evaluation matrices corresponding to each factor) can be obtained:

[0064]

[0065] In this way, after obtaining the total membership degree set R, the current wellbore integrity risk status can be determined based on this total membership degree set and the weights in step S120 in the subsequent step S140.

[0066] Step S140 determines the current wellbore integrity risk status according to the weights and evaluation matrices of each factor.

[0067] Specifically, after obtaining the weights and evaluation matrices of each factor based on the foregoing steps, the current wellbore integrity risk status can be determined through fuzzy comprehensive evaluation based on the weights and evaluation matrices.

[0068] In one embodiment, when determining the wellbore integrity risk status based on the weights of each factor and the evaluation matrix, the following steps can be taken: According to the weights of several secondary influencing factors under the same primary influencing factor and the corresponding evaluation matrix, the weighted average method is used to calculate the evaluation matrix of each primary influencing factor; According to the evaluation matrix of each primary influencing factor and the corresponding weight, the evaluation matrix of the target is calculated; Based on the evaluation matrix of the target, using the principle of maximum membership degree, the risk level corresponding to the current wellbore integrity is determined.

[0069] Specifically, the weight matrix formed by the weights of multiple secondary influencing factors under the same primary influencing factor is multiplied by the matrix formed by the evaluation matrices of these secondary influencing factors to obtain the evaluation matrix of the current primary influencing factor, and then the evaluation matrix corresponding to each primary influencing factor is calculated; Then, the matrix formed by the evaluation matrices of each primary influencing factor is multiplied by the weight matrix formed by the weights of all primary evaluation matrices to obtain the evaluation matrix of the target. Furthermore, based on the evaluation matrix of the target, using the principle of maximum membership degree, the risk level with the highest element data in the target evaluation matrix is used as the evaluation result of the current wellbore integrity risk level.

[0070] After determining the current wellbore integrity risk status, in order to further optimize the wellbore integrity and avoid the occurrence of water plugging accidents, it can be determined whether it is necessary to optimize the factors related to water plugging according to the wellbore integrity risk status.

[0071] Specifically, first, based on the current wellbore integrity risk status information, it is judged whether to optimize the influencing factors. Then, in the case of determining to optimize the influencing factors, the factors to be adjusted are determined based on the weights and evaluation matrices of each factor, and the factors to be adjusted are optimized.

[0072] Based on the current wellbore integrity risk status information determined in the foregoing steps, it is judged whether the current wellbore integrity risk status information is in a high-risk state. Furthermore, when it is determined that the current wellbore integrity risk status information is in a high-risk state, based on the weights and evaluation matrices of each influencing factor determined in the foregoing steps, the influencing factors with higher weights and membership degrees are determined as the factors to be adjusted, and the factors to be adjusted are optimized to keep the wellbore in a high-integrity state.

[0073] In one embodiment, in the process of judging whether to optimize the influencing factors of the current wellbore, the corresponding judgment indexes can be determined based on past experience and evaluation factors. The specific implementation steps include: When the current wellbore integrity risk is at a risk level other than low risk and no risk, it is determined that the influencing factors need to be optimized currently.

[0074] For example, based on the foregoing embodiments, different risk levels include, but are not limited to, factors such as high risk, medium risk, low risk, and no risk. Based on past experience and evaluation factors, wellbore states other than low risk and no risk can be determined as wellbore states that require optimization of influencing factors. Then, based on the weights of each factor and the evaluation matrix, the factors to be adjusted are determined, and the factors to be adjusted are optimized.

[0075] Example

[0076] Based on the foregoing embodiments, the following gives a specific application scenario of a method for analyzing the integrity risk of the water shutoff construction wellbore of Well A in Tahe Oilfield.

[0077] Specifically, during the drilling of Well A, there was no blowout and leakage. The seismic profile showed a "beaded" reflection feature. After acid fracturing completion, the communication with the reservoir body was obvious. The water cut was of the explosive water flooding type. In the early stage of production, water was seen sporadically, and then it maintained long-term low water cut production. In the later stage, the bottom water channeled into the well along the wellbore fractures. Therefore, a water shutoff operation was carried out on this well.

[0078] During the water shutoff operation, materials such as temperature-resistant gel and high-temperature gel were used to block the preferential channeling channels, and the remaining oil in the wellbore reservoir body was released. The total designed dosage was about 290m 3 , and its wellhead corresponding parameter was KYS70 / 78-65X. A thousand-type pump truck was used for injection, and the designed injection displacement was ≤0.5m 3 / min. Among them, during the on-site construction process, the qualifications of the operators need to be verified, and the construction personnel need to be familiar with the H2S emergency treatment process. There is a standard inspection route, and it is stipulated that the construction pressure ≤20MPa, so as to ensure the safety of the operation.

[0079] During the water shutoff process, it is necessary to determine the multi-level factors that may affect the integrity of the water shutoff wellbore of Well A, and collect the data information corresponding to the multi-level factors. Based on the data information of the multi-level factors, the weight of each factor in the multi-level factors relative to the previous level factor is determined. Then, after determining the weight of each factor and determining the membership degree of each factor through the membership function, the membership degree set formed by each secondary influencing factor is as shown in Table 2 below.

[0080] Table 2 Membership Degree Set

[0081]

[0082]

[0083] Taking the indoor design of the secondary index B1 as an example, according to the secondary fuzzy comprehensive operation, it can be obtained:

[0084]

[0085] Among them, B1 represents the evaluation matrix of the first-level influencing factor of interior design, which is obtained by weighted average calculation through the above formula. A1 represents the weight matrix corresponding to the slug design of C1, the construction technology of C2, and the dosage of chemical agents of C3. R1 represents the evaluation matrix of the slug design of C1, the construction technology of C2, and the dosage of chemical agents of C3 compared with different risk levels.

[0086] Thus, it can be obtained that:

[0087]

[0088] Among them, B2 represents the evaluation matrix of the first-level influencing factor of wellhead obstacles, which is obtained by weighted average calculation through the above formula. A2 represents the weight matrix corresponding to the Christmas tree of C4, the tubing head of C5, the casing head of C6, the surface pipeline of C7, and the sucker rod hanger of C8. R2 represents the evaluation matrix of the Christmas tree of C4, the tubing head of C5, the casing head of C6, the surface pipeline of C7, and the sucker rod hanger of C8 compared with different risk levels.

[0089]

[0090] Among them, B3 represents the evaluation matrix of the first-level influencing factor of downhole obstacles, which is obtained by weighted average calculation through the above formula. A3 represents the weight matrix corresponding to the tubing of C9, the rod pump of C10, the casing of C11, the cement sheath of C12, and the formation of C13. R3 represents the evaluation matrix of the tubing of C9, the rod pump of C10, the casing of C11, the cement sheath of C12, and the formation of C13 compared with different risk levels.

[0091]

[0092] Among them, B4 represents the evaluation matrix of the first-level influencing factor of on-site construction, which is obtained by weighted average calculation through the above formula. A4 represents the weight matrix corresponding to the qualification certificates of C14, the H2S emergency response of C15, the standard management of C16, and the pressure control of C17. R4 represents the evaluation matrix of the qualification certificates of C14, the H2S emergency response of C15, the standard management of C16, and the pressure control of C17 compared with different risk levels.

[0093] Furthermore, the first-level fuzzy operation is obtained:

[0094]

[0095] Among them, B represents the evaluation matrix of the risk of the integrity of the target plugged wellbore, which is obtained by weighted average calculation through the above formula. A represents the weight matrix corresponding to B1 interior design, B2 wellhead barrier, B3 downhole barrier, and B4 on-site construction. R represents the evaluation matrix obtained by the aforementioned secondary fuzzy operation of B1 interior design, B2 wellhead barrier, B3 downhole barrier, and B4 on-site construction.

[0096] It can be determined by the principle of maximum membership degree that the higher membership degree is 0.6045, and the corresponding evaluation factor is high risk. Then, it can be determined that the risk level corresponding to the current wellbore integrity is in a high-risk state.

[0097] The present invention provides a method and device for analyzing the risk of wellbore integrity in water shutoff construction. The method and device determine multi-level factors affecting the wellbore integrity of oil wells during water shutoff and collect the index data of each factor. Then, the weight of each factor in the multi-level factors compared to the previous level factor is determined. Furthermore, an evaluation model representing the influence degree of a single factor on different risk levels is constructed, and according to the evaluation model and the index data of each factor, the evaluation matrix of each factor is determined. Finally, according to the weight of each factor and the evaluation matrix, the current wellbore integrity risk state is determined. The present invention can timely detect the integrity state of the wellbore, avoid accidents caused by unclear wellbore states, and perform optimization operations on water shutoff-related factors based on the current wellbore integrity risk state, so as to maintain a relatively high wellbore integrity state.

[0098] Based on the above method for analyzing the risk of wellbore integrity in water shutoff construction, the present invention also provides a device for analyzing the risk of wellbore integrity in water shutoff construction. The device for analyzing the risk of wellbore integrity in water shutoff construction is used to implement the above-mentioned method for analyzing the risk of wellbore integrity in water shutoff construction.

[0099] Figure 3 It is a schematic structural diagram of the device for analyzing the risk of wellbore integrity in water shutoff construction according to an embodiment of the present application. As Figure 3 shown, the device for analyzing the risk of wellbore integrity in water shutoff construction described in the embodiment of the present invention includes: a data determination module 301, a weight determination module 302, a matrix determination module 303, and a state determination module 304.

[0100] The data determination module 301 is configured to determine multi-level factors affecting the wellbore integrity of oil wells during water shutoff and collect the index data of each factor; the weight determination module 302 is configured to determine the weight of each factor in the multi-level factors compared to the previous level factor; the matrix determination module 303 is configured to construct an evaluation model representing the influence degree of a single factor on different risk levels and determine the evaluation matrix of each factor according to the evaluation model and the index data of each factor; the state determination module 304 is configured to determine the current wellbore integrity risk state according to the weight of each factor and the evaluation matrix.

[0101] The present invention provides a device for analyzing the integrity risk of a water shutoff construction wellbore. The device determines multi-level factors affecting the integrity of the water shutoff wellbore in an oil well and collects the index data of each factor. Then, it determines the weight of each factor in the multi-level factors compared with the previous-level factor, and further constructs an evaluation model representing the influence degree of a single factor on different risk levels. According to the evaluation model and the index data of each factor, it determines the evaluation matrix of each factor. Finally, according to the weight and evaluation matrix of each factor, it determines the current integrity risk state of the wellbore. The present invention can timely detect the integrity state of the wellbore, avoid accidents caused by unclear wellbore states, and perform optimization operations on water shutoff-related factors based on the current integrity risk state of the wellbore, so as to maintain a high integrity state of the wellbore.

[0102] As mentioned above, the above is only a preferred specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any changes or substitutions that can be easily thought of by those skilled in the art within the technical scope disclosed by the present invention should be covered by the protection scope of the present invention. Therefore, the protection scope of the present invention should be subject to the protection scope of the claims.

[0103] In the description of the present invention, unless otherwise specified, the meaning of "a plurality of" is two or more; the orientation or positional relationship indicated by the terms "upper", "lower", "left", "right", "inner", "outer", "front end", "rear end", "head", "tail", etc. is the orientation or positional relationship based on the orientation or positional relationship shown in the drawings, which is only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and thus cannot be understood as a limitation of the present invention. In addition, the terms "first", "second", "third", etc. are only used for descriptive purposes and cannot be understood as indicating or implying relative importance.

[0104] In the description of the present invention, it should be noted that unless otherwise clearly specified and limited, the terms "connected" and "connected" should be understood in a broad sense. For example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be directly connected or indirectly connected through an intermediate medium. For those of ordinary skill in the art, the specific meanings of the above terms in the present invention can be understood according to specific situations.

[0105] It should be understood that the embodiments disclosed by the present invention are not limited to the specific structures, processing steps or materials disclosed herein, but should extend to equivalent alternatives of these features understood by those of ordinary skill in the relevant fields. It should also be understood that the terms used herein are only for the purpose of describing specific embodiments and do not mean to limit.

[0106] As used herein, the phrase "one embodiment" or "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment is included in at least one embodiment of the present invention. Thus, the appearances of the phrase "one embodiment" or "an embodiment" in various places throughout this specification are not necessarily all referring to the same embodiment.

[0107] Embodiments of the present invention are provided for purposes of illustration and description, and are not intended to be exhaustive or to limit the invention to the disclosed form. Many modifications and variations will be apparent to those of ordinary skill in the art. The embodiments were chosen and described in order to best explain the principles of the invention and its practical application, and to enable others of ordinary skill in the art to understand the invention for various embodiments with various modifications as are suited to a particular use.

[0108] Although the embodiments disclosed herein are as described above, the above description is only for the convenience of understanding the present invention and is not intended to limit the present invention. Any person skilled in the art within the technical field to which the present invention pertains may make any modifications and variations in the form and details of the implementation without departing from the spirit and scope of the present invention as disclosed, but the scope of patent protection of the present invention shall still be subject to the scope defined by the appended claims.

Claims

1. A method for analyzing the integrity risk of a wellbore during water shutoff construction, characterized in that, Including: Determine multi-level factors affecting the wellbore integrity of oil well water shutoff and collect index data of each factor; Determine the weight of each factor in the multi-level factors compared with the previous-level factor; Construct an evaluation model representing the influence degree of single factor on different risk levels, and determine the evaluation matrix of each factor according to the evaluation model and the index data of each factor; Determine the current wellbore integrity risk status according to the weight and evaluation matrix of each factor.

2. The method according to claim 1, characterized in that In the step of determining multi-level factors affecting the wellbore integrity of oil well water shutoff and collecting index data of each factor, it includes: Sort and classify each factor affecting the wellbore integrity of oil well water shutoff to form multiple primary influencing factors targeted at wellbore integrity risk and several secondary influencing factors belonging to the primary influencing factors respectively; Quantify the data information of the secondary influencing factors to obtain the index data of each factor.

3. The method according to claim 2, characterized in that, In the step of determining the weight of each factor in the multi-level factors compared with the previous-level factor, it includes: Construct the first type of pairwise comparison matrix of several secondary influencing factors under the same primary influencing factor; Construct the second type of pairwise comparison matrix of multiple primary influencing factors under the target; Calculate the weight of each factor according to the first type of pairwise comparison matrix and the first type of pairwise comparison matrix.

4. The method according to claim 3, wherein The method further includes: Conduct a consistency ratio test on the weight of each factor, and perform subsequent operations when it is determined that the weight of each factor meets the consistency ratio.

5. The method according to any one of claims 2 to 4, characterized in that, The evaluation matrix of the i-th factor is calculated by calculating the membership degree of the factor compared with different risk levels respectively, where the evaluation matrix of the i-th factor is expressed as: R i ＝(r i1 ,r i2 ,…,r in ) Among them, R i represents the evaluation matrix of the i-th factor, and n represents the number of risk levels.

6. The method according to any one of claims 2 to 5, characterized in that Determine the current wellbore integrity risk status according to the weight and evaluation matrix of each factor, including: Calculate the evaluation matrix of each primary influencing factor by using the weighted average method according to the weights and corresponding evaluation matrices of several secondary influencing factors under the same primary influencing factor; Calculate the evaluation matrix of the target according to the evaluation matrix and corresponding weight of each primary influencing factor; Based on the evaluation matrix of the target, use the maximum membership degree principle to determine the risk level corresponding to the current wellbore integrity.

7. The method according to any one of claims 1 to 6, characterized in that, The method further includes: Based on the current wellbore integrity risk status information, determine whether to optimize the influencing factors; When it is determined to optimize the influencing factors, determine the factors to be adjusted based on the weights and evaluation matrices of each factor, and optimize the factors to be adjusted.

8. The method according to claim 7, wherein In the step of determining whether to optimize the influencing factors based on the current wellbore integrity risk status information, it includes: When the current wellbore integrity risk is a risk level other than low risk and no risk, determine that the influencing factors need to be optimized currently.

9. A device for analyzing the wellbore integrity risk of water shutoff construction, characterized in that, Including: A data determination module configured to determine multi-level factors affecting the wellbore integrity of oil well water shutoff and collect index data of each factor; A weight determination module configured to determine the weight of each factor in the multi-level factors compared with the previous-level factor; A matrix determination module, configured to construct an evaluation model representing the influence degree of a single factor on different risk levels, and determine an evaluation matrix of each factor according to the evaluation model and the index data of each factor; A status determination module, configured to determine the current wellbore integrity risk status according to the weight of each factor and the evaluation matrix.

10. A computer-readable storage medium storing computer-executable instructions, which when executed by a processor implement the steps of the method according to any one of claims 1 to 8.

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