Low-permeability reservoir same-layer well pattern encryption adjustment effect evaluation method and system

Abstract

The invention relates to a low-permeability reservoir same-layer well pattern encryption adjustment effect evaluation method and system, and belongs to the field of oilfield development. The evaluation method comprises the following steps: determining an evaluation index of a low-permeability reservoir well pattern encryption adjustment effect according to production parameters of an encryption well and surrounding old wells and development characteristic parameters of an encryption block; determining the classification of the evaluation indexes and a classification coefficient; determining a weight coefficient of each evaluation index; and based on the weight coefficient and the classification coefficient of the evaluation index, comprehensive quantitative evaluation of the same-layer well pattern encryption adjustment effect of the low-permeability reservoir is completed. According to the method, accurate evaluation of the effect after oil reservoir encryption is facilitated, and reliable theoretical basis and technical support are provided for timely optimizing and adjusting the oil reservoir with the poor effect, summarizing and popularizing the oil reservoir with the good effect and achieving optimization of the encryption technology and benefits.

Description

Technical Field

[0001] The invention belongs to the field of oilfield development, and in particular relates to a method and system for evaluating the effect of intensification adjustment of well patterns in the same layer of a low permeability oil reservoir. Background Art

[0002] Low permeability oil fields have low single well production, serious water flooding problems, large oil field decline, low oil production rate, and poor development effects of conventional measures. Well density adjustment can effectively reduce water content and improve water drive efficiency. It is an important means to control water and stabilize oil and improve oil recovery in the middle and late stages of low permeability oil reservoir production.

[0003] Clarifying the development effects of low permeability reservoirs under different infill conditions and different infill methods is of great significance for the infill potential evaluation of similar oil fields and the planning and deployment of oil field development. At present, there are relatively few methods for evaluating the effect of well network infill, which are generally divided into empirical methods and numerical simulation methods. The former is mostly qualitative evaluation, without unified standards, difficult to evaluate, and inefficient; although the latter is accurate in prediction, it relies on the overall numerical simulation of the reservoir, resulting in a large amount of calculation and a long time for the entire optimization process. It is often difficult to obtain satisfactory results within a limited amount of calculation and time, and the timeliness of on-site production guidance is not strong. Summary of the invention

[0004] In view of the above problems, the present invention provides a method and system for evaluating the effect of adjustment of well pattern densification in the same layer of a low permeability oil reservoir.

[0005] The first object of the present invention is to provide a method for evaluating the effect of adjusting the well pattern density in the same layer of a low permeability reservoir, the method comprising:

[0006] Determine the evaluation index of the effect of the infill adjustment of the well pattern in low permeability reservoirs based on the production parameters of the infill wells and the surrounding old wells and the development characteristic parameters of the infill blocks;

[0007] Determine the classification and classification coefficient of evaluation indicators;

[0008] Determine the weight coefficient of each evaluation indicator;

[0009] Based on the weight coefficients and classification coefficients of the evaluation indicators, a comprehensive quantitative evaluation of the effect of the intensification adjustment of the well pattern in the same layer of the low permeability reservoir is completed.

[0010] In an embodiment of the present invention, the production parameters include the initial water content of the infilled well, the water content of the surrounding old wells in the same period, the initial single well production capacity of the infilled well, the production capacity of the surrounding old wells in the same period, the average single well cumulative oil production of the infilled wells after two years of production, the single well production capacity of the infilled wells during the stable production period, the production capacity of the surrounding old wells in the same period, the single well production of the old wells before infilling, and the single well production of the old wells after the infilled wells are stabilized.

[0011] In an embodiment of the present invention, the development characteristic parameters include the effectiveness period of the infilled wells, the effectiveness period of the surrounding old wells, the water breakthrough rate of the infilled wells, the water breakthrough rate of the old wells, the pressure maintenance level of the old wells after the infilled wells are stabilized, the pressure maintenance level of the old wells before infilling, the oil production rate improvement value, the dynamically predicted recovery rate improvement value and the internal rate of return.

[0012] In the embodiment of the present invention, the determining of the classification and classification coefficient of the evaluation index includes:

[0013] Combining K-means cluster analysis method and evaluation indexes, determine the classification of evaluation indexes and the corresponding boundary values ​​of each classification;

[0014] Determine the classification coefficient corresponding to the evaluation index classification.

[0015] In the embodiment of the present invention, determining the classification coefficient corresponding to the evaluation index classification includes:

[0016] Determine the classification coefficient corresponding to the evaluation index classification according to the multiple between the expected beneficial change amount and the actual beneficial change amount of each production parameter adjusted by the low permeability reservoir infill;

[0017] and / or,

[0018] Based on the classification of evaluation indicators, evaluation indicator values ​​and the geometric range method, the classification coefficient corresponding to the evaluation indicator classification is determined.

[0019] In the embodiment of the present invention, determining the weight coefficient of each evaluation indicator includes:

[0020] Taking the recovery rate as the target sequence and the evaluation indicators of the encrypted block as the subsequences, the analysis sequence is determined;

[0021] Based on the analysis sequence and Gini index, the weight coefficient of each evaluation indicator is determined.

[0022] In the embodiment of the present invention, the weight coefficient and classification coefficient based on the evaluation index are used to complete the comprehensive quantitative evaluation of the effect of the intensification adjustment of the well pattern in the same layer of the low permeability reservoir, including:

[0023] Determine the comprehensive evaluation index of the encrypted block based on the weight coefficient and classification coefficient of the evaluation index;

[0024] Based on the comprehensive evaluation index of the encrypted block, a comprehensive quantitative evaluation of the effect of the same-layer well pattern encryption adjustment in low-permeability reservoirs is completed.

[0025] In the embodiment of the present invention, the calculation formula of the comprehensive evaluation index is as follows:

[0026]

[0027] Among them, CEI is the comprehensive evaluation index, Wk is the kth evaluation index weight coefficient, N k is the classification coefficient of the kth evaluation index, n is the total number of evaluation indicators, and k is the kth evaluation index.

[0028] The second object of the present invention is to provide a system for evaluating the effect of adjusting the well pattern density in the same layer of a low permeability reservoir, the evaluation system comprising: a determination module, a classification module, a weight module and an evaluation module;

[0029] The determination module is used to determine the evaluation index of the effect of the low permeability reservoir well pattern densification adjustment according to the production parameters of the densified wells and the surrounding old wells and the development characteristic parameters of the densified blocks;

[0030] The classification module is used to determine the classification and classification coefficient of the evaluation index;

[0031] The weight module is used to determine the weight coefficient of each evaluation index;

[0032] The evaluation module is used to complete a comprehensive quantitative evaluation of the effect of the intensification adjustment of the well pattern in the same layer of the low permeability reservoir based on the weight coefficient and the classification coefficient of the evaluation index.

[0033] In an embodiment of the present invention, the classification module includes a classification determination submodule and a classification coefficient calculation submodule;

[0034] The classification determination submodule is used to combine the K-means cluster analysis method and the evaluation index to determine the classification of the evaluation index and the boundary value corresponding to each classification;

[0035] The classification coefficient calculation submodule is used to determine the classification coefficient corresponding to the evaluation index classification.

[0036] Beneficial effects of the present invention:

[0037] The present invention helps to accurately evaluate the effect of reservoir infill, and provides a reliable theoretical basis and technical support for timely optimizing and adjusting reservoirs with poor effects, summarizing and promoting reservoirs with good effects, and optimizing the infill technology and benefits. Other features and advantages of the present invention will be described in the subsequent description, and partly become obvious from the description, or can be understood by practicing the present invention. The objects and other advantages of the present invention can be realized and obtained by the structures indicated in the description, claims and drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0039] Figure 1 A flowchart of a method for evaluating the effect of adjusting the well pattern densification in the same layer of a low permeability reservoir according to an embodiment of the present invention is shown;

[0040] Figure 2 A framework diagram of a system for evaluating the effect of adjusting the well pattern densification in the same layer of a low permeability reservoir according to an embodiment of the present invention is shown;

[0041] In the figure: 1. Determination module; 2. Classification module; 3. Weight module; 4. Evaluation module. DETAILED DESCRIPTION

[0042] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0043] like Figure 1 As shown, a method for evaluating the effect of adjusting the well pattern densification in the same layer of a low permeability reservoir according to an embodiment of the present invention includes:

[0044] Step S1, determining the evaluation index of the effect of the infill adjustment of the low permeability reservoir well pattern according to the production parameters of the infill wells and the surrounding old wells and the development characteristic parameters of the infill block;

[0045] Step S2, determining the classification and classification coefficient of the evaluation index;

[0046] Step S3, determining the weight coefficient of each evaluation index;

[0047] Step S4: Based on the weight coefficients and classification coefficients of the evaluation indicators, a comprehensive quantitative evaluation of the effect of the intensification adjustment of the well pattern in the same layer of the low permeability reservoir is completed.

[0048] In an embodiment of the present invention, the production parameters include the initial water content of the infilled well, the water content of the surrounding old wells in the same period, the initial single well production capacity of the infilled well, the production capacity of the surrounding old wells in the same period, the average single well cumulative oil production of the infilled wells after two years of production, the single well production capacity of the infilled wells during the stable production period, the production capacity of the surrounding old wells in the same period, the single well production of the old wells before infilling, and the single well production of the old wells after the infilled wells are stabilized.

[0049] The development characteristic parameters include the effectiveness period of the infilled wells, the effectiveness period of the surrounding old wells, the water breakthrough rate of the infilled wells, the water breakthrough rate of the old wells, the pressure maintenance level of the old wells after the infilled wells are stabilized, the pressure maintenance level of the old wells before infilling, the increase in oil production rate, the dynamic prediction of the increase in recovery rate and the internal rate of return.

[0050] In the embodiment of the present invention, step S1, determining the evaluation index of the effect of the infill adjustment of the well pattern of the low permeability reservoir according to the production parameters of the infill wells and the surrounding old wells and the development characteristic parameters of the infill block, is specifically performed as follows:

[0051] The above production parameters and development characteristic parameters are calculated and processed to obtain the initial water content of the infilled well / water content of the surrounding old wells in the same period (ratio), initial single well production capacity of the infilled well / production capacity of the surrounding old wells in the same period (ratio), average single well cumulative oil production of the infilled well after 2 years of production (t), single well production capacity of the infilled well during the stable production period / production capacity of the surrounding old wells in the same period (ratio), effective period of the infilled well / effective period of the surrounding old wells (ratio), water breakthrough rate of the infilled well / water breakthrough rate of the old well (ratio), single well production of the old well after the infilled well is stabilized / single well production of the old well before infilling (ratio), pressure maintenance level of the old well after the infilled well is stabilized / pressure maintenance level of the old well before infilling (ratio), oil production rate improvement value (%), dynamic predicted recovery rate improvement value (%), internal rate of return (%) 11 parameters are used as evaluation indicators for the effect of infilling adjustment of low permeability reservoir well pattern. The specific operation is as follows:

[0052] Take a low-permeability reservoir infill block as an example. The average sand body thickness of the reservoir is 13.7m, the average oil layer thickness is 10.5m, the average permeability is 0.57mD, the average porosity is 10.5%, the average oil saturation is 56.5%, the crude oil viscosity is 1.34mPa·s, and the crude oil volume coefficient is 1.32. A batch of infill wells were deployed in the reservoir in 2017, and the infill effect in 2017 was evaluated to find the factors affecting the poor effect. After improving these parameters in 2018-2019, the second batch of infill wells were deployed, and the infill effect was good;

[0053] The production parameters and development characteristic parameters of the encrypted block of the low permeability reservoir are processed to form the above-mentioned 11 indicator data, as shown in Table 1;

[0054] Table 1

[0055]

[0056]

[0057] The embodiments of the present invention only exemplify 11 evaluation indicators that can currently comprehensively and scientifically evaluate the effect of the densification adjustment of the low permeability oil reservoir well network. The data of the evaluation indicators can be flexibly changed according to the actual work of the densification adjustment of the low permeability oil reservoir well network.

[0058] In the embodiment of the present invention, step S2, determining the classification and classification coefficient of the evaluation index, includes:

[0059] Step A1, combining the K-means cluster analysis method and the evaluation index, determining the classification of the evaluation index and the boundary value corresponding to each classification;

[0060] Step A2: determine the classification coefficient corresponding to the evaluation index classification.

[0061] Specifically, in step A1, the K-means cluster analysis method and the evaluation index are combined to determine the classification of the evaluation index and the boundary value corresponding to each classification. The specific operation is as follows:

[0062] K-means cluster analysis was performed on the 11 evaluation index data of 31 blocks in Changqing Oilfield that have been fully infilled. The variables were selected as 11 evaluation indicators, the number of clusters was 3, and after 10 iterations, the data was finally divided into three categories, and the data of the 11 indicators were divided into three categories: A, B, and C. The classification boundaries of each evaluation indicator were determined, as shown in Table 2 (in Table 2, when the initial water content of the infill well / the water content of the surrounding old wells at the same time was used, the classification boundary values ​​of different evaluation indicators should be divided according to the degree of recovery of recoverable reserves in the infill area). At the same time, combined with Table 1, the classification categories of various indicators of a low permeability reservoir in the infill blocks in 2017 and 2018-2019 can be obtained, as shown in Table 3;

[0063] Table 2

[0064]

[0065]

[0066] Table 3

[0067]

[0068] Specifically, in step A2, determining the classification coefficient corresponding to the evaluation index classification includes:

[0069] The classification coefficient corresponding to the evaluation index classification is determined according to the multiple between the expected beneficial change amount and the actual beneficial change amount of each production parameter adjusted by the low permeability reservoir infill. The classification coefficients of the three categories A, B, and C are 1.0, 0.4-1.0, and 0.4, respectively. The specific results are shown in Table 4;

[0070] Table 4

[0071] category Category A Category B Category C Classification coefficient 1 0.4-1.0 0.4

[0072] As can be seen from Table 2, the evaluation index items are divided into three categories, the specific classification coefficients of category A and category C. As for the classification coefficient of category B, it is calculated according to the following steps:

[0073] Based on the classification of evaluation indicators, evaluation indicator values ​​and geometric range method, the classification coefficient corresponding to the evaluation indicator classification is determined, specifically:

[0074]

[0075] In formula (1), N is the classification coefficient; i is the evaluation block number; k is the evaluation index number; X is the value of the evaluation index; maxN is the maximum classification coefficient of the category to which the evaluation block belongs; minN is the minimum classification coefficient of the category to which the evaluation block belongs; maxX is the maximum value of the evaluation index of the category to which the evaluation block belongs; minX is the minimum value of the evaluation index of the category to which the evaluation block belongs;

[0076] Specifically, according to the above-mentioned classification coefficient confirmation steps, the classification coefficients corresponding to various indicators of the encrypted blocks in 2017 and 2018-2019 of a low permeability oil reservoir are obtained, as shown in Table 5.

[0077] Table 5

[0078]

[0079] In the embodiment of the present invention, in step S3, determining the weight coefficient of each evaluation indicator includes:

[0080] Taking the recovery rate as the target sequence and the evaluation indicators of the encrypted block as the subsequence, the analysis sequence is determined. Specifically, see formula (2);

[0081]

[0082] In formula (2), x n (0) is the 0th value of the nth index, x m (0) is the mth value of the nth indicator;

[0083] Based on the analysis sequence and Gini index, the weight coefficient of each evaluation indicator is determined, including:

[0084] The initial sequence data is preprocessed according to formula (3):

[0085]

[0086] In formula (3), x i (k)′ represents the normalized matrix; x i(k) is the kth value of the ith indicator; max x i (k) is the maximum value of the i-th index; min x i (k) is the minimum value of the i-th indicator;

[0087] Calculate the Gini index using the following formula:

[0088]

[0089] In formula (4), GI m represents the Gini coefficient, P mk Represents the proportion of category k in node m;

[0090] The Gini index change is calculated as follows:

[0091] ΔGI=GI m -GI l -GI r (5)

[0092] In formula (5), ΔGI represents the change of Gini index; GI l and GI r Respectively represent the Gini index of the two branches before and after the node m branch;

[0093] Calculate the indicator contribution, the calculation formula is as follows:

[0094]

[0095] In formula (6), r n Contribution to the indicator;

[0096] Determine the weight coefficient of each evaluation index, and the calculation formula is as follows:

[0097]

[0098] In formula (7), W k is the weight coefficient of each evaluation index;

[0099] Based on the above steps, the weight coefficients corresponding to various indicators of a low permeability reservoir encryption block are calculated, as shown in Table 6.

[0100] Table 6

[0101] serial number Evaluation indicators Weight coefficient 1 Initial water content of the infill well / water content of the surrounding old wells at the same time 10 2 Initial single well production capacity of infilled wells / production capacity of surrounding old wells in the same period 10 3 Average cumulative oil production of infill wells after two years of production (t) 10 4 Production capacity of a single well during the stable production period of an infill well / production capacity of surrounding old wells during the same period 10 5 Effective period of infill wells / effective period of surrounding old wells 6 6 Water breakthrough rate of infill wells / water breakthrough rate of old wells 6 7 Single well production of old wells after infill wells are stabilized / single well production of old wells before infill wells 8 8 After the infill wells are stabilized, the pressure of the old wells remains at the same level / before infill wells, the pressure of the old wells remains at the same level 6 9 Increased oil production rate (%) 8 10 Dynamically predicted recovery factor improvement (%) 12 11 Internal rate of return (%) 14

[0102] In the embodiment of the present invention, in step S4, the comprehensive quantitative evaluation of the effect of the intensification adjustment of the well pattern in the same layer of the low permeability reservoir is completed based on the weight coefficient and the classification coefficient of the evaluation index, including:

[0103] Step B1, determining the comprehensive evaluation index of the encrypted block based on the weight coefficient and classification coefficient of the evaluation index;

[0104] Step B2: Based on the comprehensive evaluation index of the encrypted block, complete the comprehensive quantitative evaluation of the effect of the same-layer well pattern encryption adjustment of the low permeability reservoir.

[0105] Specifically, in step B1, the calculation formula of the comprehensive evaluation index is as shown in formula (8):

[0106]

[0107] In formula (8), CEI is the comprehensive evaluation index, W k is the kth evaluation index weight coefficient, N k is the classification coefficient of the kth evaluation index, n is the total number of evaluation indicators, and k is the kth evaluation index;

[0108] Based on the above steps, the comprehensive evaluation index of the encrypted blocks in 2017 and 2018-2019 of a low permeability reservoir was calculated, as shown in Table 7;

[0109] Table 7

[0110] Encrypted Block Comprehensive evaluation index Crypto Blockchain in 2017 65.5 2018-2019 Crypto Blockchain 94

[0111] Specifically, in step B2, the comprehensive evaluation index based on the encrypted block is used to complete the comprehensive quantitative evaluation of the effect of the intensification adjustment of the well pattern in the same layer of the low permeability reservoir, that is:

[0112] The evaluation result level is divided according to the value of the comprehensive evaluation index. For example, in the embodiment of the present invention, the encryption effect evaluation result of the encryption area with a comprehensive evaluation index CEI ≥ 70 is divided into level I, indicating that the encryption effect of the encryption block is good; the encryption effect evaluation result of the encryption block with 50 ≤ CEI ≤ 70 is divided into level II, indicating that the encryption effect of the encryption block is medium; the encryption effect evaluation result of the encryption block with CEI < 50 is divided into level III, indicating that the encryption effect is poor;

[0113] Therefore, it can be obtained that the encryption evaluation result of the encrypted block of the low permeability oil reservoir in 2017 is Level II, and the encryption evaluation result of the encrypted block in 2018-2019 is Level I.

[0114] Specifically, the present invention does not impose any restrictions on the classification of evaluation results, and the classification can be flexibly changed according to the actual encryption evaluation work.

[0115] like Figure 2 As shown, an embodiment of the present invention provides a system for evaluating the effect of adjusting the well pattern density in the same layer of a low permeability reservoir, comprising: a determination module 1, a classification module 2, a weight module 3 and an evaluation module 4;

[0116] The determination module 1 is used to determine the evaluation index of the effect of the low permeability reservoir well pattern densification adjustment according to the production parameters of the densified wells and the surrounding old wells and the development characteristic parameters of the densified blocks;

[0117] The classification module 2 is used to determine the classification and classification coefficient of the evaluation index;

[0118] The weight module 3 is used to determine the weight coefficient of each evaluation index;

[0119] The evaluation module 4 is used to complete a comprehensive quantitative evaluation of the effect of the intensification adjustment of the well pattern in the same layer of the low permeability reservoir based on the weight coefficient and the classification coefficient of the evaluation index.

[0120] Specifically, the classification module 2 includes a classification determination submodule and a classification coefficient calculation submodule;

[0121] The classification determination submodule is used to combine the K-means cluster analysis method and the evaluation index to determine the classification of the evaluation index and the boundary value corresponding to each classification.

[0122] The classification coefficient calculation submodule is used to determine the classification coefficient corresponding to the evaluation index classification.

[0123] Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent substitutions for some of the technical features therein; and these modifications or substitutions do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for evaluating the effect of well pattern densification adjustment in the same layer of a low permeability reservoir, characterized in that: include: Determine the evaluation index of the effect of the infill adjustment of the well pattern in low permeability reservoirs based on the production parameters of the infill wells and the surrounding old wells and the development characteristic parameters of the infill blocks; Determine the classification and classification coefficient of evaluation indicators; Determine the weight coefficient of each evaluation indicator; Based on the weight coefficients and classification coefficients of the evaluation indicators, a comprehensive quantitative evaluation of the effect of the intensification adjustment of the well pattern in the same layer of the low permeability reservoir is completed.

2. The method for evaluating the effect of the well pattern densification adjustment in the same layer of a low permeability reservoir according to claim 1, characterized in that: The production parameters include the initial water content of the infilled wells, the water content of the surrounding old wells during the same period, the initial single well production capacity of the infilled wells, the production capacity of the surrounding old wells during the same period, the average single well cumulative oil production of the infilled wells after two years of production, the single well production capacity of the infilled wells during the stable production period, the production capacity of the surrounding old wells during the same period, the single well production of the old wells before infilling, and the single well production of the old wells after the infilled wells have stabilized.

3. The method for evaluating the effect of the well pattern densification adjustment in the same layer of a low permeability reservoir according to claim 1, characterized in that: The development characteristic parameters include the effectiveness period of the infilled wells, the effectiveness period of the surrounding old wells, the water breakthrough rate of the infilled wells, the water breakthrough rate of the old wells, the pressure maintenance level of the old wells after the infilled wells are stabilized, the pressure maintenance level of the old wells before infilling, the increase in oil production rate, the dynamic prediction of the increase in recovery rate and the internal rate of return.

4. The method for evaluating the effect of the well pattern densification adjustment in the same layer of a low permeability reservoir according to claim 1, characterized in that: The determination of the classification and classification coefficient of the evaluation index includes: Combining K-means cluster analysis method and evaluation indexes, determine the classification of evaluation indexes and the corresponding boundary values ​​of each classification; Determine the classification coefficient corresponding to the evaluation index classification.

5. The method for evaluating the effect of the well pattern densification adjustment in the same layer of a low permeability reservoir according to claim 4, characterized in that: The step of determining the classification coefficient corresponding to the evaluation index classification includes: Determine the classification coefficient corresponding to the evaluation index classification according to the multiple between the expected beneficial change amount and the actual beneficial change amount of each production parameter adjusted by the low permeability reservoir infill; and / or, Based on the classification of evaluation indicators, evaluation indicator values ​​and the geometric range method, the classification coefficient corresponding to the evaluation indicator classification is determined.

6. The method for evaluating the effect of the well pattern densification adjustment in the same layer of a low permeability reservoir according to claim 1, characterized in that: Determining the weight coefficient of each evaluation indicator includes: Taking the recovery rate as the target sequence and the evaluation indicators of the encrypted block as the subsequences, the analysis sequence is determined; Based on the analysis sequence and Gini index, the weight coefficient of each evaluation indicator is determined.

7. The method for evaluating the effect of the well pattern densification adjustment in the same layer of a low permeability reservoir according to claim 1, characterized in that: The weight coefficient and classification coefficient based on the evaluation index are used to complete the comprehensive quantitative evaluation of the effect of the well pattern infill adjustment in the same layer of the low permeability reservoir, including: Determine the comprehensive evaluation index of the encrypted block based on the weight coefficient and classification coefficient of the evaluation index; Based on the comprehensive evaluation index of the encrypted block, a comprehensive quantitative evaluation of the effect of the same-layer well pattern encryption adjustment in low-permeability reservoirs is completed.

8. The method for evaluating the effect of adjusting the well pattern density in the same layer of a low permeability reservoir according to claim 7, characterized in that: The calculation formula of the comprehensive evaluation index is as follows: Among them, CEI is the comprehensive evaluation index, W k is the kth evaluation index weight coefficient, N k is the classification coefficient of the kth evaluation index, n is the total number of evaluation indicators, and k is the kth evaluation index.

9. A system for evaluating the effect of well pattern densification adjustment in the same layer of a low permeability reservoir, characterized in that: include: Determination module, classification module, weight module and evaluation module; The determination module is used to determine the evaluation index of the effect of the low permeability reservoir well pattern densification adjustment according to the production parameters of the densified wells and the surrounding old wells and the development characteristic parameters of the densified blocks; The classification module is used to determine the classification and classification coefficient of the evaluation index; The weight module is used to determine the weight coefficient of each evaluation indicator; The evaluation module is used to complete a comprehensive quantitative evaluation of the effect of the intensification adjustment of the well pattern in the same layer of the low permeability reservoir based on the weight coefficient and the classification coefficient of the evaluation index.

10. The low permeability reservoir same-layer well pattern densification adjustment effect evaluation system according to claim 9, characterized in that: The classification module includes a classification determination submodule and a classification coefficient calculation submodule; The classification determination submodule is used to combine the K-means cluster analysis method and the evaluation index to determine the classification of the evaluation index and the boundary value corresponding to each classification; The classification coefficient calculation submodule is used to determine the classification coefficient corresponding to the evaluation index classification.

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