A method and system for producing well gas channeling risk discrimination

Abstract

The application discloses a kind of production well gas channeling risk discrimination method and system, by fusing production well three-phase output dynamic data and injection-production connected section static geological parameters, build gas channeling coefficient, channel advantage index and form comprehensive sorting matrix, composite gas channeling risk sequence value is obtained by calculation, then according to well group production well quantity and the quantity of representation quantity statistical derivation theory central value and composite standard deviation, build objective theory risk definition interval, can realize dynamic combination gas channeling risk quantification discrimination, discarded artificial experience subjective setting threshold, improve the stability and accuracy of gas channeling risk discrimination, can provide reliable basis for well group gas channeling risk classification identification.

Description

Technical Field

[0001] This invention relates to the field of gas injection development technology in oil and gas fields, and in particular to a method and system for identifying the risk of gas channeling in production wells. Background Technology

[0002] In the development of gas-driven oil recovery and gas-driven enhanced oil recovery, factors such as reservoir heterogeneity, fracture / dissolution pore development, and permeability differences result in injected gas with low viscosity and high fluidity, which readily migrates along dominant seepage channels. This leads to premature breakthrough at the gas drive front and the gradual establishment of gas channeling pathways. The combined action of multiple injection wells in a production well group further complicates the gas migration path. Once inter-well gas channeling occurs, it not only manifests as an increased proportion of gas phase produced from oil wells and a decrease in oil well productivity, but also exacerbates the injection-production conflict, increasing the difficulty and cost of subsequent plugging and gas control measures.

[0003] In existing technologies, gas channeling identification and early warning often rely on dynamic production indicators as criteria, such as gas-oil ratio, gas production, or gas breakthrough time. However, these dynamic indicators are easily affected by factors such as intermittent injection, injection adjustment, changes in throttling regime, wellhead separation metering errors, and water cut fluctuations, which can lead to short-term or non-stationary fluctuations. This results in an inaccurate correlation between abnormal indicators and actual gas channeling. Furthermore, relying solely on dynamic indicators is insufficient to explain the sources of differences between wells and is not conducive to establishing universally applicable discrimination thresholds across different well groups.

[0004] Furthermore, while methods such as tracers, well testing, and production logging can reflect inter-well connectivity, they are costly in the field and difficult to meet the needs of routine and continuous early warning. If risk inference is based solely on static geological parameters, potential risks may be misjudged as actual occurrences, making it difficult to achieve risk classification under dynamic response constraints.

[0005] Therefore, existing technologies cannot simultaneously integrate static geological information with dynamic production characteristics, making it difficult to solve the problem of accurate identification of gas channeling between wells in gas injection oil recovery development, and failing to meet the field requirements of gas-driven enhanced oil recovery development. Summary of the Invention

[0006] To address or partially address the technical challenges of existing technologies that cannot simultaneously integrate static geological information with dynamic production characteristics, making it difficult to accurately identify gas channeling between wells in gas-driven oil recovery development and failing to meet the field requirements of gas-driven enhanced oil recovery development, this invention provides a method and system for identifying gas channeling risks in production wells.

[0007] To address the aforementioned technical problems, a first aspect of the present invention discloses a method for identifying gas channeling risk in production wells, the method comprising: Within the same statistical time window, three-phase production data of each production well are collected. At the same time, based on the injection-production correspondence, static parameters of the injection-production connected segments between each production well and the injection well are extracted from the geological interpretation and stratified statistical results. The three-phase production data includes: oil production, water production, and gas production. The static parameters include: segment porosity, permeability, and effective thickness. For each production well, a gas channeling coefficient is constructed based on the three-phase production data of each production well; a production well channeling index matrix is ​​constructed based on the gas channeling coefficient and oil production of each production well; wherein, the gas channeling coefficient is used to characterize the degree of abnormality in the gas phase ratio at the production end. For each production well, the channel advantage index of each production well is calculated based on the static parameters of the injection-production connection segment. The channel advantage index of all production wells is combined to construct the channel advantage matrix between injection and production layers of the well group. A comprehensive ranking matrix is ​​constructed based on the production well crossflow index matrix and the well group injection-production interlayer channel advantage matrix; wherein, the comprehensive ranking matrix is ​​with production wells as rows and the ranking values ​​of three types of characterization quantities, namely gas crossflow coefficient, channel advantage index and oil production, as columns; Based on the comprehensive ranking matrix, the ranking values ​​of the three types of characterization quantities corresponding to each production well are summed to obtain the composite gas channeling risk ranking value of each production well. Based on the number of producing wells in the well group and the three types of characterization quantities, the theoretical central value and composite standard deviation of the composite gas channeling risk are calculated. Then, the composite standard deviation is used as the fluctuation range of the theoretical central value to construct the theoretical risk definition interval. Risk assessment is performed on the composite gas channeling risk sequence value of each production well based on the theoretical risk definition range.

[0008] Optionally, the formula for calculating the gas channeling coefficient is as follows:

[0009] in, Indicates the gas channeling coefficient; Indicates oil production; Indicates water production; This indicates the amount of gas produced.

[0010] Optionally, the production well crossflow index matrix is ​​specifically as follows:

[0011] in, 1. 2、…、 n V represents the gas channeling coefficient of each production well. o1 V o2 Von This indicates the oil production of each production well.

[0012] Optionally, the calculation of the channel dominance index for each production well based on the static parameters of the injection-production connectivity zone of each production well specifically includes: For the injection-production interconnection zone of each injection well in each production well, according to Calculations yielded the injection-production well pair ( P k , I i The channel advantage index; in, Indicates the first k Production wells P k With the i injection wells I i Channel dominance coefficients for all connected segments between them; K k，i，j Indicates injection and production well pair The j The permeability of each connected segment; k，i，j Indicates injection and production well pair The j Porosity of each connected segment; H k，i，j Indicates injection and production well pair The j The effective thickness of each connected segment; For the injection-production interconnected zone of each production well, according to the formula The channel dominance index for each production well was calculated; where, ψ k Indicates production well P k Channel advantage index; w k,i Indicates injection and production well pair The connectivity weights, M Indicates relative to production wells P k The total number of connected injection wells.

[0013] Optionally, the specific dominance matrix of the well group injection-production interlayer channel is as follows: ;in, ψ 1. ψ 2、…、 ψ n This represents the channel advantage index for each production well.

[0014] Optionally, the step of constructing a comprehensive ranking matrix based on the production well crossflow index matrix and the well group injection-production interlayer channel advantage matrix specifically includes: Within the well group, the wells are sorted from smallest to largest according to their gas channeling coefficients to obtain the ranking of the gas channeling coefficients for each production well. Within the well group, wells are sorted from smallest to largest according to their channel dominance coefficients to obtain the channel dominance coefficient for each production well. Within the well group, sort the wells according to their oil production from largest to smallest to obtain the oil production corresponding to each production well. The three types of characteristic parameters of each production well are placed in the same row according to the well number, forming the comprehensive sorting matrix.

[0015] Optionally, based on the number of producing wells within the well group and the three types of characterization parameters, the theoretical central value and composite standard deviation of the composite gas channeling risk are calculated. Then, the composite standard deviation is used as the fluctuation range of the theoretical central value to construct a theoretical risk definition interval, specifically including: Based on the number of producing wells in the well group, calculate the expected value and variance of the single list characteristic ranking value; The theoretical center value is calculated based on the expected value of the single-list characteristic ranking value and the three types of characteristic quantities; The composite standard deviation is calculated based on the variance of the single-list characteristic ranking values ​​and the three types of characteristic values; The theoretical risk definition interval is constructed by using the composite standard deviation as the fluctuation range of the theoretical central value.

[0016] Optionally, the formula for calculating the theoretical center value is as follows:

[0017] in, The theoretical center value is represented by m, the number of characterizing quantities is represented by n, and the number of producing wells in the well group is represented by n. μ This represents the expected value of a single list of eigenvalues. The formula for calculating the composite standard deviation is as follows:

[0018] in, Indicates the composite standard deviation. This represents the variance of the sorted values ​​of a single list of eigenvalues.

[0019] Optionally, risk assessment is performed on the composite gas channeling risk sequence value of each production well based on the theoretical risk definition range, specifically including: For each production well, when the first k The composite gas channeling risk sequence value of production wells C kLocated within the theoretical risk definition range It was determined to be of medium risk. When the first k The composite gas channeling risk sequence value of production wells C k Higher than It was determined to be high-risk; When the first k The composite gas channeling risk sequence value of production wells C k Below It was determined to be low risk.

[0020] A second aspect of the present invention discloses a gas channeling risk assessment system for production wells, the system comprising: The data acquisition unit is used to collect three-phase production data of each production well within the same statistical time window. At the same time, based on the injection-production correspondence, it extracts the static parameters of the injection-production connected segments between each production well and the injection well from the geological interpretation and stratified statistical results. The three-phase production data includes: oil production, water production, and gas production. The static parameters include: segment porosity, permeability, and effective thickness. The first construction unit is used to construct the gas channeling coefficient of each production well based on the three-phase production data of each production well; and to construct a production well channeling index matrix based on the gas channeling coefficient and oil production of each production well; wherein, the gas channeling coefficient is used to characterize the degree of abnormality in the gas phase ratio at the production end. The second construction unit is used to calculate the channel advantage index of each production well based on the static parameters of the injection-production interconnection zone of each production well; and to construct the channel advantage matrix between injection and production zones of the well group by combining the channel advantage indices of all production wells. The third construction unit is used to construct a comprehensive ranking matrix based on the production well crossflow index matrix and the well group injection-production interlayer channel advantage matrix; wherein, the comprehensive ranking matrix is ​​with production wells as rows and the ranking values ​​of three types of characterization quantities, namely gas crossflow coefficient, channel advantage index and oil production, as columns; The summation unit is used to sum the ranking values ​​of the three types of characterization quantities corresponding to each production well based on the comprehensive ranking matrix, so as to obtain the composite gas channeling risk ranking value of each production well. The fourth construction unit is used to calculate the theoretical central value and composite standard deviation of the composite gas channeling risk based on the number of production wells in the well group and the three types of characterization quantities, and then use the composite standard deviation as the fluctuation range of the theoretical central value to construct the theoretical risk definition interval. The discrimination unit is used to discriminate the risk sequence value of the composite gas channeling risk of each production well based on the theoretical risk definition interval.

[0021] Through one or more technical solutions of the present invention, the present invention has the following beneficial effects or advantages: The technical solution of this invention integrates dynamic data of three-phase production from production wells with static geological parameters of injection-production interconnected layers to construct a gas channeling coefficient and a channel advantage index, forming a comprehensive ranking matrix. It then calculates a composite gas channeling risk sequence value and, based on the number of production wells and the number of characteristic parameters in the well group, derives a theoretical central value and a composite standard deviation to construct an objective theoretical risk definition interval. This enables a dynamic and static combined quantitative judgment of gas channeling risk, eliminating the subjectivity of manually setting thresholds and improving the stability and accuracy of gas channeling risk judgment. It can provide a reliable basis for the classification and identification of gas channeling risk in well groups.

[0022] The above description is merely an overview of the technical solution of the present invention. In order to better understand the technical means of the present invention and to implement it in accordance with the contents of the specification, and in order to make the above and other objects, features and advantages of the present invention more apparent and understandable, specific embodiments of the present invention are described below. Attached Figure Description

[0023] Various other advantages and benefits will become apparent to those skilled in the art upon reading the following detailed description of preferred embodiments. The accompanying drawings are for illustrative purposes only and are not intended to limit the invention. Furthermore, the same reference numerals denote the same parts throughout the drawings. In the drawings: Figure 1 A flowchart of a method for identifying gas channeling risk in a production well according to an embodiment of the present invention is shown; Figure 2 A schematic diagram of the well location of a well group according to an embodiment of the present invention is shown; Figure 3 A schematic diagram of a production well gas channeling risk assessment system according to an embodiment of the present invention is shown. Detailed Implementation

[0024] Exemplary embodiments of the invention will now be described in more detail with reference to the accompanying drawings. While exemplary embodiments of the invention are shown in the drawings, it should be understood that the invention may be implemented in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this invention will be thorough and complete, and will fully convey the scope of the invention to those skilled in the art.

[0025] In a first aspect, the gas channeling risk identification method for production wells provided in this embodiment of the invention can be packaged as a device or software module and connected to an existing production database to realize automated rolling early warning and management closed loop.

[0026] like Figure 1As shown in the figure, the method for identifying gas channeling risk in production wells provided by this invention includes at least the following steps: S101: Within the same statistical time window, collect the three-phase production data of each production well. At the same time, based on the injection-production correspondence, extract the static parameters of the injection-production connection segments between each production well and the injection well from the geological interpretation and stratified statistical results.

[0027] The three-phase production data include: oil production, water production, and gas production, and the static parameters include: layer porosity, permeability, and effective thickness.

[0028] Specifically, taking the gas injection drive development well group as the basic analysis unit, a unified statistical time window is first determined: a continuous period (such as 3 to 12 months) in which all production wells and injection wells in the well group are in a stable production / injection state is selected. During this period, it is necessary to avoid operating disturbances such as construction work, well shutdown and production stoppage, large-scale adjustment of injection volume, and changes in wellhead throttling system, so as to ensure that the dynamic output data of each production well in the well group are under the same production background and have horizontal comparability, and avoid the distortion of gas channeling response characteristics caused by time window misalignment.

[0029] For three-phase production data acquisition, quantitative data after separation and metering of oil, gas, and water at the wellhead of each production well are obtained, covering oil production. (bbl / d), water production (bbl / d), gas production (scf / d); the data collection frequency can be selected as daily, ten-day, or monthly data according to the needs of on-site production management. Furthermore, the collected raw data undergoes quality control: abnormal extreme values ​​caused by measurement errors or short-term operating condition fluctuations are removed, such as invalid data showing a sudden increase of several times in daily gas production. Missing data is supplemented using linear interpolation with adjacent time windows. Finally, the average three-phase production of each production well within the entire statistical time window is statistically obtained, providing accurate dynamic production data for the subsequent calculation of the gas channeling coefficient.

[0030] For static parameter extraction, firstly, based on the well group injection-production well network deployment and combined with the results of inter-well connectivity analysis, including tracer monitoring, inter-well testing, injection-production dynamic response fitting, and reservoir seismic prediction, the production parameters of each well are determined. Corresponding injection well Establish a precise correspondence between injection and collection.

[0031] For each injection well Based on the reservoir geological interpretation results (such as sublayer correlation, sedimentary facies division, and fracture development characterization) and the statistical results of layer parameters, only the injection-production connected intervals with effective seepage capacity and injection-production pressure response between the injection-production well pairs are extracted. jThe static parameters, including layer porosity, permeability and effective thickness, strictly exclude parameters of non-seepage interlayers and non-connected sublayers that are unrelated to injection-production connectivity, ensuring that the static parameters are completely matched with the injection-production connectivity relationship, and providing accurate geological constraints for the subsequent calculation of channel advantage coefficients.

[0032] S102, for each production well, construct the gas channeling coefficient of each production well based on the three-phase production data of each production well; construct the production well channeling index matrix according to the gas channeling coefficient and oil production of each production well.

[0033] The formula for calculating the gas channeling coefficient is as follows:

[0034] in, Indicates the gas channeling coefficient; Indicates oil production; Indicates water production; This indicates the amount of gas produced.

[0035] Each production well can calculate its own gas channeling coefficient using the formula described above. The gas channeling coefficient characterizes the degree of abnormality in the gas phase ratio at the production end. A higher gas channeling coefficient indicates a larger proportion of gas phase in the produced fluid of the well, a more severe degree of gas channeling along the injection-production connection channel to the production well, a more significant gas channeling response at the production end, and a higher gas channeling risk for the corresponding well. Conversely, a lower gas channeling coefficient indicates that the gas phase production ratio of the production well is at a normal development level, with no obvious gas channeling breakthrough characteristics, and a lower gas channeling risk.

[0036] Furthermore, a production well channeling index matrix is ​​constructed based on the gas channeling coefficient and oil production of each production well, as shown below:

[0037] In the production well crossflow index matrix, the gas crossflow coefficient and oil production are arranged according to the production well number, where n represents the number of production wells in the well group. 1. 2、…、 n V represents the gas channeling coefficient of each production well. o1 V o2 V on This indicates the oil production of each production well.

[0038] S103, For each production well's injection-production interconnection zone, calculate the channel advantage index of each production well based on the static parameters of the injection-production interconnection zone; combine the channel advantage indices of all production wells to construct the channel advantage matrix between injection and production zones of the well group.

[0039] In calculating the channel dominance index for each production well, the injection-production connectivity interval for each injection well of each production well is calculated according to the following formula to obtain the injection-production well pair ( P k , I i Channel advantage index:

[0040] in, Indicates the first k Production wells P k With the i injection wells I i Channel dominance coefficients for all connected segments between them; K k，i，j Indicates injection-production well pair ( P k , I i ) j The permeability of each connected segment; k，i，j Indicates injection-production well pair ( P k , I i ) j Porosity of each connected segment; H k，i，j Indicates injection-production well pair ( P k , I i ) j The effective thickness of each connected segment.

[0041] Furthermore, for the injection-production interconnected sections of each production well, using the first... k Production wells P k For example, the channel dominance index for each production well is calculated using the following formula:

[0042] in, ψ k Indicates the first k Production wells P k Channel advantage index; w k,i Indicates injection-production well pair ( P k , I i The connectivity weights of ) MIndicates relative to production wells P k The total number of connected injection wells. Of course, injection-production well pairs ( P k , I i The sum of the connectivity weights of the filled cells is 1.

[0043] Once the channel dominance index for each production well is obtained, the channel dominance matrix between injection and production layers in the well group can be constructed, as shown in the example below:

[0044] in, ψ 1. ψ 2、…、 ψ n This represents the channel advantage index for each production well.

[0045] S104. Construct a comprehensive ranking matrix based on the production well crossflow index matrix and the well group injection-production interlayer channel advantage matrix.

[0046] The comprehensive ranking matrix is ​​arranged with production wells as rows and ranking values ​​of three types of indicators: gas channeling coefficient, channel dominance index, and oil production as columns.

[0047] Specifically, in constructing the comprehensive ranking matrix, to achieve unified risk direction and scale normalization for the three types of characterization quantities, and to eliminate the interference of differences in dimensions and numerical magnitudes on gas channeling risk assessment, it is necessary to relatively rank the three types of characterization quantities for all producing wells in the well group based on the correlation between each characterization quantity and gas channeling risk: gas channeling coefficient The larger the value, the higher the degree of anomaly in the gas phase ratio at the production end and the stronger the gas channeling response; the channel dominance coefficient ψ The larger the value, the more developed the dominant seepage channels between injection and production wells, and the more sufficient the geological basis for gas channeling; oil production V o It is negatively correlated with the intensity of gas channeling. The lower the oil production, the more significant the inhibitory effect of gas channeling on oil well productivity and the higher the risk of gas channeling.

[0048] Therefore, within the well group, wells are sorted from smallest to largest according to their gas channeling coefficients to obtain the ranking of each production well based on its gas channeling coefficient. For example, each production well is assigned a gas channeling coefficient ranking number from 1 to n. The larger the value, the larger the corresponding sorting number.

[0049] Within the well group, wells are sorted in ascending order of their channel dominance coefficients to obtain the channel dominance coefficient for each production well. For example, each production well is assigned a channel dominance coefficient ranking number from 1 to n, with larger ψ values ​​corresponding to larger ranking numbers.

[0050] Within the well group, wells are sorted from highest to lowest oil production to obtain the oil production corresponding to each production well. For example, each production well can be assigned a reverse-ordered oil production number from 1 to n, V o The smaller the value, the larger the corresponding sorting number.

[0051] Following the well number order, the three types of characterization parameters for each production well are placed in the same row to form the comprehensive ranking matrix. Specifically, following the well number order, the gas channeling coefficient ranking number, channel dominance coefficient ranking number, and oil production reverse ranking number corresponding to each production well are arranged sequentially in the same row. With the production well as the row and the ranking values ​​of the three types of characterization parameters as the column, an n-row, 3-column comprehensive ranking matrix R is constructed to achieve same-scale fusion of multi-source heterogeneous characterization parameters, providing a foundation for the subsequent calculation of composite gas channeling risk ranking values.

[0052] S105. Based on the comprehensive ranking matrix, the ranking values ​​of the three types of characterization quantities corresponding to each production well are summed to obtain the composite gas channeling risk ranking value of each production well.

[0053] The formula for calculating the risk sequence value of complex gas channeling is as follows: C k = k +ψ k +V ok Among them, C k Indicates the first k The composite gas channeling risk sequence value of each production well. k Indicates the first k The channel dominance coefficient ψ, V of each production well ok Indicates the first k Oil production of each production well.

[0054] S106. Based on the number of producing wells in the well group and the three types of characterization quantities, calculate the theoretical central value and composite standard deviation of the composite gas channeling risk, and then use the composite standard deviation as the fluctuation range of the theoretical central value to construct the theoretical risk definition interval.

[0055] In the specific implementation process, to construct a gas channeling risk classification threshold with statistical basis and universal applicability across different well groups, and to address the technical shortcomings of existing technologies that rely on manual experience-based judgments, resulting in strong subjectivity and poor adaptability between well groups, this study considers that when a well group is in an ideal equilibrium state with homogeneous reservoirs and no systematic gas channeling differences, the probability of each well's ranking value is equal, conforming to a discrete uniform distribution. Based on this, and considering the number of producing wells n within the well group and the number m (m=3) of the three types of characterization quantities participating in the fusion, combined with the statistical properties of discrete uniform distribution, the theoretical central value and composite standard deviation for calculating composite gas channeling risk can be calculated. Then, using the theoretical central value as the benchmark and the composite standard deviation as the fluctuation range, a theoretical risk definition interval for gas channeling risk assessment is constructed.

[0056] Specifically, based on the number of producing wells within the well group, the expected value and variance of the single-list characteristic ranking value are first calculated.

[0057] The formula for calculating the expected value of a single eigenvalue ranking is as follows:

[0058] in, represents the expected value of the single-list characteristic ranking value, and n represents the number of producing wells in the well group.

[0059] The formula for calculating the variance of a single metric ranking value is as follows:

[0060] in, This represents the variance of the sorted values ​​of a single list of eigenvalues.

[0061] Furthermore, the theoretical center value is calculated based on the expected value of the single-list characteristic ranking value and the three types of characteristic values.

[0062] The formula for calculating the theoretical central value is as follows:

[0063] in, The theoretical center value is represented by m, the number of characterizing quantities is represented by n, and the number of producing wells in the well group is represented by n. μ This represents the expected value of a single eigenvalue ranking.

[0064] The composite standard deviation is calculated based on the variance of the single-list characteristic ranking values ​​and the three types of characteristic values.

[0065] The formula for calculating the composite standard deviation is as follows:

[0066] in, Indicates the composite standard deviation. This represents the variance of the sorted values ​​of a single list of eigenvalues.

[0067] Using the composite standard deviation as the fluctuation range of the theoretical central value, the theoretical risk delineation interval is constructed, as shown in the example below: .

[0068] S107, Based on the theoretical risk definition range, the risk sequence value of the composite gas channeling risk of each production well is determined.

[0069] For each production well, when the first k The composite gas channeling risk sequence value of production wells C k Located within the theoretical risk definition range It is classified as a medium risk; when the first k The composite gas channeling risk sequence value of production wells C k Higher than It is determined to be high-risk; when the first k The composite gas channeling risk sequence value of production wells C k Below It was determined to be low risk.

[0070] Furthermore, according to C k The production wells are sorted from largest to smallest to form a risk management priority order within the well group. This order guides the selection and implementation sequence of wells for gas control and profile regulation, stratified management, and injection-production system optimization, enabling rolling identification and early warning output of production wells.

[0071] To illustrate and explain this application in detail, specific examples are used below.

[0072] First, a row of wells in a pilot test area of ​​a large, low-permeability carbonate reservoir was selected as the analysis unit. The well group adopted a 4-injection, 4-production production mode: P1~P4, I1~I4. (See attached image) Figure 2 This is a plan view of the well locations of the well group.

[0073] In this well group, the injected gas comes solely from continuous injection from the injection wells, without the influence of external gas sources such as gas caps. The statistical window spans six consecutive months, and dynamic data uses the average monthly production within this window to collect the oil production of each producing well. (bbl / d), water production (bbl / d), gas production (scf / d); simultaneously, using the "connected sections of the injection-production well pair" as the calculation unit, porosity is extracted from the stratified statistical results. Permeability K and effective thickness H. After completing the unified handling of measurement anomalies and missing points, the input dataset is established.

[0074] Furthermore, the gas channeling coefficient at the production end is calculated, and a channeling index matrix for production wells is formed.

[0075] To ensure consistency in the dimensions of the numerator and denominator of the gas channeling coefficient, a unified conversion unit was used, and the gas channeling coefficient for each well was calculated based on monthly production data. At the same time With oil production V o This matrix of production-side crossflow indicators is used for subsequent inter-well comparisons.

[0076] Furthermore, based on connectivity, porosity was read layer by layer within the connected strata of each injection-production well pair. The permeability K and effective thickness H are used, and the well-to-well scale channel dominance coefficient is obtained by calculating layer by layer and accumulating the results. The calculated production well-scale channel dominance matrix is ​​as follows:

[0077] Furthermore, taking the four producing wells within the well group as comparison objects, the three types of characterization quantities are uniformly mapped to the same discrete scale to achieve comparability: for and Assign values ​​in ascending order (1-4), with larger values ​​indicating stronger gas channeling response or channel dominance; for V o Considering its inverse correlation with gas channeling risk, it is ordered from largest to smallest (4-1) to ensure that the three columns of characteristics are consistent in their risk orientation. Based on the calculation results of steps 2 and 3, the sorting results of the three columns are as follows: Sort (from smallest to largest): P4(1), P3(2), P2(3), P1(4); Sort (from smallest to largest): P4(1), P3(2), P2(3), P1(4); V o Sort (from smallest to largest): P4(1), P3(2), P2(3), P1(4).

[0078] Based on this, a comprehensive sorting matrix R is constructed with "production wells as rows and characteristic quantities as columns":

[0079] See Table 1 for a list of various data from the four injection wells.

[0080] Table 1 Production wells β Ψ <![CDATA[V o ]]> <![CDATA[C k ]]> Risk level Disposal sequence <![CDATA[P1]]> 0.24 0.47 1120 12 High risk 1 <![CDATA[P2]]> 0.21 0.41 1180 9 Medium risk 2 <![CDATA[P3]]> 0.09 0.06 1520 6 Medium risk 2 <![CDATA[P4]]> 0.03 0.05 1780 3 Low risk 3 Based on the above data, the ranking of the combined gas channeling risk of each production well is as follows: , , ,

[0081] When ranking, a rolling update of the comprehensive ranking can be used to track the changes in the relative risk ranking of production wells in the well group at different times, thereby reflecting the migration and accumulation characteristics of risks between wells during the gas drive front advancement, flow deviation and channel stabilization process.

[0082] Furthermore, the theoretical center value and risk interval are determined. The number of producing wells in the well group is n=4, and the number of representative quantities participating in the fusion is m=3. For each column of ranking, the set of values ​​within the well group is fixed as {1,2,3,4}. Under the equilibrium assumption, the single-column ranking value can be regarded as a discrete uniform distribution with equal probability on this set. Therefore, the expected value and variance of the single-column ranking value are respectively:

[0083]

[0084] The theoretical central value of the composite sort in equilibrium is:

[0085] By introducing dispersion to characterize the natural fluctuation range of the composite sort under equilibrium conditions:

[0086] By providing a method for deriving the theoretical center value and dispersion of composite sorting, and determining the theoretical risk delineation interval accordingly, the zoning threshold source is clear and highly practical, facilitating horizontal comparison and promotion between different well groups.

[0087] At this point, the logic for determining the theoretical risk definition range is as follows: when At that time, it was identified as a low-risk area; when At that time, it was identified as a medium-risk area; when At that time, it was identified as a high-risk area; Furthermore, the risk level and priority of treatment are output. The above threshold rules are applied to the composite ranking of each well, resulting in P1 falling into the upper tail and being classified as a high-risk well; P2 and P3 falling into the medium-risk range and being classified as medium-risk wells; and P4 falling into the lower tail and being classified as a low-risk well; and then... The priority order for risk management of well groups, from largest to smallest, is P1→P2→P3→P4. This order guides the selection and implementation sequence of wells for gas control and profile control, stratified management, and injection-production system optimization. It can support gas control and profile control, injection-production system optimization, and refined management.

[0088] The above is the complete implementation logic of this technical solution. This invention uses injection-production well groups as evaluation units and simultaneously introduces the dynamic production response of production wells and the static geological characteristics of injection-production interconnected layers within a unified time window to form a dynamic-static synergistic gas channeling risk quantification framework. In practice, the following steps are taken: First, the oil, water, and gas production and capacity indicators of each production well in the well group are statistically analyzed and time-aligned with the same caliber. Simultaneously, the porosity, permeability, and effective thickness parameters of the connected layers that match the injection-production relationship are extracted. Then, dynamic characterization quantities reflecting the strength of gas channeling response at the production end and static characterization quantities describing the development tendency of dominant channeling channels between wells are constructed. Based on this, the dynamic characterization quantities, static characterization quantities, and oil production are relatively ranked and quantified within the well group to reduce the influence of dimensional differences on the discrimination results, forming a comprehensive ranking matrix and obtaining a composite risk sequence value. Furthermore, under the assumption of "well group equilibrium state", the theoretical center level and fluctuation scale of the composite risk sequence value are given, thereby establishing a medium-risk interval and realizing low, medium, and high-risk zoning based on the upper and lower tails. Finally, the risk level and treatment priority order of each production well in the well group are output for gas channeling rolling early warning management.

[0089] In this invention, by introducing gas channeling coefficients and channel dominance coefficients, dynamic response and geological conditions are coupled and validated in the same direction, increasing the interpretability of the results and reducing the risk of misjudgment caused by factors such as system adjustments and metering noise. Furthermore, by combining dynamic and static parameters between injection and production wells, the characteristics of well-specific "dominance channel strength" can be identified at the well group scale, providing a quantitative basis for characterizing inter-well connectivity. Moreover, this invention does not rely on large-sample training; even with limited or small-sample conditions and fluctuations in dynamic data, it can still maintain the stability and reliability of risk assessment.

[0090] Secondly, based on the same inventive concept as the gas channeling risk assessment method for production wells provided in the first aspect of the embodiments described above, this embodiment of the invention also provides a gas channeling risk assessment system for production wells, see below. Figure 3 The system includes: The acquisition unit 301 is used to acquire the three-phase production data of each production well within the same statistical time window, and at the same time, extract the static parameters of the injection-production connected segments between each production well and the injection well from the geological interpretation and stratification statistics results according to the injection-production correspondence. The three-phase production data includes: oil production, water production, and gas production, and the static parameters include: segment porosity, permeability, and effective thickness. The first construction unit 302 is used to construct the gas channeling coefficient of each production well based on the three-phase production data of each production well; and to construct a production well channeling index matrix based on the gas channeling coefficient and oil production of each production well; wherein, the gas channeling coefficient is used to characterize the degree of abnormality in the gas phase ratio at the production end. The second construction unit 303 is used to calculate the channel advantage index of each production well based on the static parameters of the injection-production connection segment of each production well; and to construct the channel advantage matrix between injection and production segments of the well group by combining the channel advantage indices of all production wells. The third construction unit 304 is used to construct a comprehensive ranking matrix based on the production well crossflow index matrix and the well group injection-production interlayer channel advantage matrix; wherein, the comprehensive ranking matrix is ​​with production wells as rows and the ranking values ​​of three types of characterization quantities, namely gas crossflow coefficient, channel advantage index and oil production, as columns; The summation unit 305 is used to sum the ranking values ​​of the three types of characterization quantities corresponding to each production well based on the comprehensive ranking matrix, so as to obtain the composite gas channeling risk ranking value of each production well. The fourth construction unit 306 is used to calculate the theoretical central value and composite standard deviation of the composite gas channeling risk based on the number of production wells in the well group and the three types of characterization quantities, and then use the composite standard deviation as the fluctuation range of the theoretical central value to construct the theoretical risk definition interval. The discrimination unit 307 is used to make risk discrimination based on the composite gas channeling risk sequence value of each production well according to the theoretical risk definition interval.

[0091] It should be noted that the specific methods of operation of each module in the production well gas channeling risk identification system provided in the embodiments of the present invention have been described in detail in the method embodiments provided in the first aspect above. The specific implementation process can be referred to the method embodiments provided in the first aspect above, and will not be described in detail here.

[0092] Although preferred embodiments of the invention have been described, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the appended claims are intended to be interpreted as including both the preferred embodiments and all changes and modifications falling within the scope of the invention.

[0093] Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its spirit and scope. Therefore, if these modifications and variations fall within the scope of the claims of this invention and their equivalents, this invention also intends to include these modifications and variations.

Claims

1. A method for identifying the risk of gas channeling in production wells, characterized in that, The method includes: Within the same statistical time window, three-phase production data of each production well are collected. At the same time, based on the injection-production correspondence, static parameters of the injection-production connected segments between each production well and the injection well are extracted from the geological interpretation and stratified statistical results. The three-phase production data includes: oil production, water production, and gas production. The static parameters include: segment porosity, permeability, and effective thickness. For each production well, a gas channeling coefficient is constructed based on the three-phase production data of each production well; a production well channeling index matrix is ​​constructed based on the gas channeling coefficient and oil production of each production well; wherein, the gas channeling coefficient is used to characterize the degree of abnormality in the gas phase ratio at the production end. For each production well, the channel advantage index of each production well is calculated based on the static parameters of the injection-production connection segment. The channel advantage index of all production wells is combined to construct the channel advantage matrix between injection and production layers of the well group. A comprehensive ranking matrix is ​​constructed based on the production well crossflow index matrix and the well group injection-production interlayer channel advantage matrix; wherein, the comprehensive ranking matrix is ​​with production wells as rows and the ranking values ​​of three types of characterization quantities, namely gas crossflow coefficient, channel advantage index and oil production, as columns; Based on the comprehensive ranking matrix, the ranking values ​​of the three types of characterization quantities corresponding to each production well are summed to obtain the composite gas channeling risk ranking value of each production well. Based on the number of producing wells in the well group and the three types of characterization quantities, the theoretical central value and composite standard deviation of the composite gas channeling risk are calculated. Then, the composite standard deviation is used as the fluctuation range of the theoretical central value to construct the theoretical risk definition interval. Risk assessment is performed on the composite gas channeling risk sequence value of each production well based on the theoretical risk definition range.

2. The method as described in claim 1, characterized in that, The formula for calculating the gas channeling coefficient is as follows: in, Indicates the gas channeling coefficient; Indicates oil production; Indicates water production; This indicates the amount of gas produced.

3. The method as described in claim 1 or 2, characterized in that, The specific matrix of production well crossflow indicators is as follows: in, 1. 2、…、 n V represents the gas channeling coefficient of each production well. o1 V o2 ... V on This indicates the oil production of each production well.

4. The method as described in claim 1, characterized in that, The calculation of the channel dominance index for each production well, based on the static parameters of the injection-production connectivity zone, specifically includes: For the injection-production interconnection zone of each injection well in each production well, according to The injection-production well pair was calculated. P k , I i The channel advantage index; in, Indicates the first k Production wells P k With the i injection wells I i Channel dominance coefficients for all connected segments between them; K k，i，j Indicates injection and production well pair The j The permeability of each connected segment; k，i，j Indicates injection and production well pair The j Porosity of each connected segment; H k，i，j Indicates injection and production well pair The j The effective thickness of each connected segment; For the injection-production interconnected zone of each production well, according to the formula The channel dominance index for each production well was calculated; where, ψ k Indicates production well P k Channel advantage index; w k,i Indicates injection and production well pair The connectivity weights, M Indicates production well P k The total number of connected injection wells.

5. The method as described in claim 1 or 4, characterized in that, The specific dominance matrix of the injection-production interlayer channel in the well group is as follows: ;in, ψ 1. ψ 2、…、 ψ n This represents the channel advantage index for each production well.

6. The method as described in claim 1, characterized in that, The construction of a comprehensive ranking matrix based on the production well crossflow index matrix and the well group injection-production interlayer channel advantage matrix specifically includes: Within the well group, the wells are sorted from smallest to largest according to their gas channeling coefficients to obtain the ranking of the gas channeling coefficients for each production well. Within the well group, wells are sorted from smallest to largest according to their channel dominance coefficients to obtain the channel dominance coefficient for each production well. Within the well group, sort the wells according to their oil production from largest to smallest to obtain the oil production corresponding to each production well. The three types of characteristic parameters of each production well are placed in the same row according to the well number, forming the comprehensive sorting matrix.

7. The method as described in claim 1, characterized in that, Based on the number of producing wells within the well group and the three types of characterization parameters, the theoretical central value and composite standard deviation of the composite gas channeling risk are calculated. Then, the composite standard deviation is used as the fluctuation range of the theoretical central value to construct a theoretical risk definition interval, specifically including: Based on the number of producing wells in the well group, calculate the expected value and variance of the single list characteristic ranking value; The theoretical center value is calculated based on the expected value of the single-list characteristic ranking value and the three types of characteristic quantities; The composite standard deviation is calculated based on the variance of the single-list characteristic ranking values ​​and the three types of characteristic values; The theoretical risk definition interval is constructed by using the composite standard deviation as the fluctuation range of the theoretical central value.

8. The method as described in claim 7, characterized in that, The formula for calculating the theoretical center value is as follows: in, The theoretical center value is represented by m, the number of characterizing quantities is represented by n, and the number of producing wells in the well group is represented by n. μ This represents the expected value of a single list of eigenvalues. The formula for calculating the composite standard deviation is as follows: in, Indicates the composite standard deviation. This represents the variance of the sorted values ​​of a single list of eigenvalues.

9. The method as described in claim 1, characterized in that, Based on the theoretical risk definition range, the risk of composite gas channeling in each production well is assessed using a risk ranking value, specifically including: For each production well, when the first k The composite gas channeling risk sequence value of production wells C k Located within the theoretical risk definition range It was determined to be of medium risk. When the first k The composite gas channeling risk sequence value of production wells C k Higher than It was determined to be high-risk; When the first k The composite gas channeling risk sequence value of production wells C k Below It was determined to be low risk.

10. A gas channeling risk assessment system for production wells, characterized in that, The system includes: The data acquisition unit is used to collect three-phase production data of each production well within the same statistical time window. At the same time, based on the injection-production correspondence, it extracts the static parameters of the injection-production connected segments between each production well and the injection well from the geological interpretation and stratified statistical results. The three-phase production data includes: oil production, water production, and gas production. The static parameters include: segment porosity, permeability, and effective thickness. The first construction unit is used to construct the gas channeling coefficient of each production well based on the three-phase production data of each production well; and to construct a production well channeling index matrix based on the gas channeling coefficient and oil production of each production well; wherein, the gas channeling coefficient is used to characterize the degree of abnormality in the gas phase ratio at the production end. The second construction unit is used to calculate the channel advantage index of each production well based on the static parameters of the injection-production interconnection zone of each production well; and to construct the channel advantage matrix between injection and production zones of the well group by combining the channel advantage indices of all production wells. The third construction unit is used to construct a comprehensive ranking matrix based on the production well crossflow index matrix and the well group injection-production interlayer channel advantage matrix; wherein, the comprehensive ranking matrix is ​​with production wells as rows and the ranking values ​​of three types of characterization quantities, namely gas crossflow coefficient, channel advantage index and oil production, as columns; The summation unit is used to sum the ranking values ​​of the three types of characterization quantities corresponding to each production well based on the comprehensive ranking matrix, so as to obtain the composite gas channeling risk ranking value of each production well. The fourth construction unit is used to calculate the theoretical central value and composite standard deviation of the composite gas channeling risk based on the number of production wells in the well group and the three types of characterization quantities, and then use the composite standard deviation as the fluctuation range of the theoretical central value to construct the theoretical risk definition interval. The discrimination unit is used to discriminate the risk sequence value of the composite gas channeling risk of each production well based on the theoretical risk definition interval.

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