CN111914209A - Drainage gas production effect fuzzy comprehensive evaluation method based on entropy method - Google Patents

Abstract

The invention discloses a fuzzy comprehensive evaluation method of drainage gas production effect based on an entropy method. According to the characteristics of foam drainage gas production wells, an index for evaluating foam drainage gas production effect is selected, and a foam is constructed by following the principle of combining qualitative and quantitative. The evaluation index system of drainage gas recovery effect, considering the relationship between the evaluation indicators of gas well drainage gas recovery effect, adopts linear analysis method to establish membership degree matrix, adopts entropy value method to determine the index weight, and calculates the foam drainage recovery rate of gas well with fuzzy comprehensive evaluation method. The comprehensive evaluation index of the gas effect can be obtained by using the method of the present invention to obtain more scientific, accurate and objective evaluation information.

Description

A fuzzy comprehensive evaluation method of drainage gas recovery effect based on entropy method

technical field

The invention relates to the technical field of drainage gas recovery effect evaluation, in particular to a fuzzy comprehensive evaluation method for drainage gas recovery effect based on an entropy method.

Background technique

Drainage and gas recovery is an important measure to improve the production efficiency in the process of gas well production to solve the problem of excessive liquid accumulation or water production near the wellbore and the bottom of the gas well, and to restore the gas well to normal production. Foam drainage gas recovery has been widely used in drainage gas recovery operations around the world because of its simple equipment, easy construction, quick effect, low cost, and no impact on gas well production. especially important.

However, there are many factors that affect the effect of foam drainage gas recovery process, resulting in the absence of a complete and generally industry-recognized evaluation system in the field of foam drainage gas recovery, and it is impossible to compare and evaluate the foam drainage effect of water-producing gas wells in different gas fields. Therefore, based on the needs of production technology management in the field of gas production from gas wells, this paper proposes a comprehensive evaluation method for drainage and gas production based on entropy method and fuzzy comprehensive evaluation.

SUMMARY OF THE INVENTION

The purpose of the present invention is to provide a fuzzy comprehensive evaluation method of drainage gas recovery effect based on entropy method, aiming at the technical defects existing in the prior art.

The technical scheme adopted for realizing the purpose of the present invention is:

A fuzzy comprehensive evaluation method for drainage gas recovery effect based on entropy method, comprising the following steps:

Step 1, select n evaluation indexes Δu _i that affect the effect of drainage and gas recovery, i=1, 2, ..., n;

Step 2: Corresponding to the relationship between the comprehensive evaluation index D of the drainage and gas recovery effect and the evaluation level, the comprehensive evaluation index D is set as m value intervals, v _j is the median value of the value interval, j=1, 2, ... , m, thus determine the judgment set V={v ₁ , v ₂ , v ₃ ,...v _m };

Step 3, use the linear analysis method to establish the membership matrix R:

First, each evaluation index is divided into m evaluation intervals, and the level limit value a _j corresponding to the evaluation interval of each evaluation index is set, j=1, 2, ..., m;

进而可求出隶属度构成的矩阵，也就是模糊关系矩阵R；Then, calculate the membership degree of the evaluation interval of each evaluation index relative to the evaluation set

Then, the matrix composed of membership degrees, that is, the fuzzy relationship matrix R, can be obtained;

Step 4, using the entropy method to determine the weight W of each evaluation index:

转化为相对值，令

然后进行归一化处理，得到t_ij；First, calculate the membership degree obtained in step 3

Converted to relative values, let

Then perform normalization to obtain t _ij ;

Then calculate the proportion of the ith influencing factor _tij under the jth evaluation interval in the evaluation interval, and the entropy value of the jth evaluation interval; then calculate the weight of each evaluation index, and then obtain the weight of each evaluation index W ;

Step 5: Use the (+, *) operator to fuzzy synthesize the weights of each evaluation index obtained in step 4 and the fuzzy relationship matrix R obtained in step 3 to obtain the final evaluation vector S, and then calculate the gas well foam drainage recovery from the final evaluation vector S. The comprehensive evaluation index D of the gas effect.

In the above technical solution, in the step 1, n=4, and the evaluation indicators are the daily gas production change rate Δq _g , the daily water production change rate Δq _w , the oil jacket pressure difference change rate ΔP and the daily foam drainage gas production operation. Cost ΔC.

In the above technical solution, in the step 2, m=5, the evaluation set V={v ₁ , v ₂ , v ₃ , v ₄ , v ₅ }, and the evaluation level is very good, good, good, General sum and difference, v ₁ =90, v ₂ =70, v ₃ =50, v ₄ =30, v ₅ =10.

In the above technical solution, in the step 3,

构成的矩阵得到模糊关系矩阵R。Among them, find

The formed matrix gets the fuzzy relation matrix R.

In the above technical solution, in the step 3, the normalization processing formula is as follows:

Positive indicators:

Negative indicators:

Then r′ _ij or r″ _ij is the value of the j-th evaluation interval of the i-th influencing factor (i=1, 2,...,n; j=1, 2,...,m), the normalized data Denoted as t _ij .

第j项评价区间的熵值

In the above technical solution, in the step 4, _tij accounts for the proportion of the evaluation interval

The entropy value of the jth evaluation interval

计算得出权重，确定权重W：W＝(w₁，w₂，…，w_n)式中权重和为 1。In the above technical solution, in the step 4, the information entropy redundancy is calculated: d _j =le _j , and then the weights of each index are calculated

The weight is obtained by calculation, and the weight W is determined: W=(w ₁ , w ₂ , . . . , _wn ) where the weight sum is 1.

In the above technical solution, in the step 5, S=W·R=(s ₁ , s ₂ , . . . , s _m ).

In the above technical solution, in the step 5, D=S*V=s ₁ *v ₁ +s ₂ *v ₂ +...+s _m *v _m .

Compared with the prior art, the beneficial effects of the present invention are:

1. The entropy method can make up for the insufficiency of using the variance contribution rate as the weight of the principal component when calculating the weight, solve the ambiguity of the actual level boundary, and avoid the interference of human subjective factors. And this method takes into account the discrete degree of data, and can adjust the index weight according to the influence degree of the index on the comprehensive evaluation.

2. Judging from how much the evaluation results reflect the problem, the model combined with the two methods can not only draw new indicators with practical significance, but also reflect the main indicators of each principal component, and can also evaluate the comprehensive situation of each indicator. Sorting can simplify complex problems and obtain more scientific, accurate and objective evaluation information.

Description of drawings

Fig. 1 is the flow chart of the fuzzy comprehensive evaluation method of drainage gas recovery effect based on entropy value method involved in the present invention;

Fig. 2 is the comparison chart of gas production before and after the foam drainage gas production operation involved in the present invention;

Fig. 3 is a comparison diagram of water production before and after the foam drainage gas production operation involved in the present invention;

Fig. 4 is a comparison diagram of oil jacket pressure difference before and after the foam drainage gas production operation involved in the present invention;

FIG. 5 is a graph showing the comprehensive evaluation index of the foam drainage gas recovery operation and the change rate of the oil jacket pressure difference based on the entropy method according to the present invention.

Detailed ways

The present invention will be further described in detail below in conjunction with specific embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention, but not to limit the present invention.

Example 1

As shown in accompanying drawing 1, a kind of fuzzy comprehensive evaluation method of drainage gas recovery effect based on entropy value method, comprises the following steps:

Step 1, according to the characteristics of the foam drainage gas production well, select the evaluation index for evaluating the foam drainage gas production effect;

Step 2, following the principle of combining qualitative and quantitative, construct the evaluation index system of foam drainage gas recovery effect:

Corresponding to the relationship between the comprehensive evaluation index and the evaluation level, set m value intervals v _j , j = 1, 2, ..., m; thus determine the evaluation set V = {v ₁ , v ₂ , v ₃ , ... v _m };

Step 3: Considering the relationship between the evaluation indicators of gas well drainage and gas recovery, a linear analysis method is used to establish a membership matrix, and a fuzzy relationship matrix R is obtained:

3.1. Divide each evaluation index into m evaluation intervals, and set the level limit values a _j , j=1, 2, ..., m corresponding to the evaluation interval of each evaluation index;

进而可求出隶属度构成的矩阵，也就是模糊关系矩阵R；3.2, Calculate the membership degree of the evaluation interval of each evaluation index relative to the evaluation set

Then, the matrix composed of membership degrees, that is, the fuzzy relationship matrix R, can be obtained;

Step 4, using the entropy method to determine the weight of each evaluation index:

转化为相对值，令

然后进行归一化处理，得到t_ij；4.1, the membership degree calculated in step 3

Converted to relative values, let

Then perform normalization to obtain t _ij ;

4.2, calculate the proportion of the i-th influencing factor t _ij under the j-th evaluation interval in the evaluation interval, and the entropy value of the j-th evaluation interval; then calculate the weight of each evaluation index, and then obtain the weight of each evaluation index W;

Step 5: Combine the fuzzy comprehensive evaluation method to calculate the comprehensive evaluation index of the foam drainage effect of the gas well.

Example 2

Referring to the method flow chart shown in Figure 1, the process of the fuzzy comprehensive evaluation method for drainage and gas recovery based on the entropy method is as follows:

Step 1: Determine the evaluation index of drainage and gas recovery. Through the analysis of various factors affecting the effect and benefit of foam drainage and gas recovery, four important indicators affecting the drainage and gas recovery effect are selected: daily gas production change rate (Δq _g ), daily water production The rate of change (Δq _w ), the rate of change of oil jacket pressure difference (ΔP) and the daily foam drainage gas production cost (ΔC) were used as evaluation indicators. These four evaluation indicators are formed into a fuzzy set U, and this fuzzy set is the evaluation target of drainage gas production effect. The expression for U is as follows:

U={u ₁ ,u ₂ ,u ₃ ,u ₄ }={Δq _g ,Δq _w ,ΔP,ΔC}.

Step 2, determine the evaluation set V, in order to correspond to the relationship between the comprehensive evaluation index and the evaluation level, the comprehensive evaluation index D is set to m value intervals, v _j is the median value of the value interval, in this embodiment

V={v ₁ , v ₂ , v ₃ , v ₄ , v ₅ }={very good, good, better, fair, poor}

That is, j=1, 2, 3, 4, 5.

In order to correspond to the relationship between the comprehensive evaluation index and the evaluation effect, the final calculated comprehensive evaluation index is classified into the evaluation set. In this embodiment, the value interval of the comprehensive evaluation index is set as shown in Table 1 below:

Table 1 Value range

v _j is the median value of the corresponding comprehensive evaluation index value interval.

That is, when D is greater than or equal to 80 and less than 100, the evaluation level is very good, when D is greater than or equal to 60 and less than 80, the evaluation level is good, when D is greater than or equal to 40 and less than 60, the evaluation level is good, and when D is greater than or equal to 40 and less than 60, the evaluation level is good. When D is greater than or equal to 20 and less than 40, the evaluation level is general, and when D is greater than or equal to 0 and less than 20, the evaluation level is poor.

Step 3, in order to consider the relationship between the evaluation indexes of the gas well drainage and gas recovery effect evaluation, a linear analysis method is used to establish a membership degree matrix. The specific division forms are shown in Table 2.

Table 2 Evaluation interval divided by evaluation index

For example, in Table 2, when the daily gas production change rate is greater than or equal to 0.5, the evaluation level is very good, when the daily gas production change rate is greater than or equal to 0.2 and less than 0.5, the evaluation level is good, and the daily gas production change rate is greater than or equal to 0.1 and less than 0.2 When the daily gas production change rate is greater than or equal to 0.05 and less than 0.1, the evaluation level is fair, and when the daily gas production change rate is greater than or equal to 0 and less than 0.05, the evaluation level is poor.

Then, the membership degree is calculated by dividing the interval according to the evaluation index. The membership degree is calculated as follows:

If the evaluation index Δu _i is divided into m levels, set a _j (j=1, 2, . . . , m) as the level limit value corresponding to the evaluation index, and the calculation formula of the evaluation index corresponding to the evaluation level (that is, the degree of membership) The calculation formula of ) is as follows:

的值，得出各评价指标相对于各评价区间的隶属度，进而可求出

构成的矩阵，也就是模糊关系矩阵R。According to the relationship between Δu _i and a _i and the corresponding relationship to solve

, the membership degree of each evaluation index relative to each evaluation interval can be obtained, and then the degree of membership of each evaluation index can be obtained.

The matrix formed is the fuzzy relation matrix R.

同理计算u₂(日产水变化率)、u₃(油套压差变化率)、u₄日加注量成本变化率中各隶属度，得到模糊关系矩阵R 如下：In this embodiment, i=1, 2, 3, 4, that is, n=4, and each evaluation index is divided into 5 levels, that is, m=5, then for u ₁ (daily gas production rate of change), a ₁ = 0.5, a ₂ = 0.2, a ₃ = 0.1, a ₄ = 0.05, a ₅ = 0, and then by the calculation formula of the membership degree, we can get

Similarly, calculate the membership degrees in u ₂ (daily water production rate of change), u ₃ (oil jacket pressure difference rate of change), and u ₄ daily injection cost rate of change, and obtain the fuzzy relationship matrix R as follows:

为第i个影响因素的第j个评价区间的数值(i＝1， 2，...,n；j＝1，2，...，m)。Step 4: Determine the weight of the influencing factors, select n influencing factors (four factors are selected in this embodiment, that is, n=4), and m evaluation intervals (m=5 in this embodiment), then

is the value of the j-th evaluation interval of the i-th influencing factor (i=1, 2,...,n; j=1, 2,...,m).

从而解决各项不同质指标值的同质化问题。指标归一化式子如下：Normalization of indicators: Homogenization of heterogeneous indicators. Since the measurement units of various indicators are not uniform, standardization must be carried out first, that is, the absolute value of the indicator is converted into a relative value, that is, the

So as to solve the problem of homogeneity of different index values. The index normalization formula is as follows:

Positive indicators:

Negative indicators:

Then r′ _ij or r″ _ij is the value of the j-th evaluation interval of the i-th influencing factor (i=1, 2,...,n; j=1, 2,...,m), normalized The transformed data is denoted as t _ij .

Calculate the proportion of the i-th influencing factor (t _ij ) under the j-th evaluation interval in the evaluation interval:

where i=1,...,n,j=1,...,m.

Calculate the entropy value of the jth evaluation interval:

Where k=1/ln(n), e _j ≥ 0 is satisfied.

Calculate the information entropy redundancy:

d _j =1-e _j

Calculate the weight of each indicator;

Calculate the weight and determine the weight W:

W=(w ₁ , w ₂ , . . . , _wn )

where the weight sum is 1.

In this example

Step 5: Calculate the comprehensive evaluation index, and use the (+, *) operator fuzzy synthesis weight W and matrix R to obtain the final evaluation vector S:

S=W·R=(s ₁ , s ₂ , ..., s _m )

In this embodiment,

s ₁ =0*0.30403643+0*0.53612817+0.073*0.15329247+0*0.00654293=0.01119035031

s ₂ =0.14*0.30403643+0.14*0.53612817+0.927*0.15329247+0*0.00654293=0.25972516369

s ₃ =0.86*0.30403643+0.86*0.53612817+0*0.15329247+0*0.00654293=0.722541556

s ₄ =0*0.30403643+0*0.1378+0*0.53612817+0*0.15329247+0.47*0.00654293=0.0030751771

s ₅ =0*0.30403643+0*0.1378+0*0.53612817+0*0.15329247+0.53*0.00654293=0.0034677529

S=(s ₁ ,s ₂ ,s ₃ ,s ₄ ,s ₅ )

The calculation formula of the comprehensive evaluation index is: D=S*V

Calculate D=S*V from Table 2

D=S*V=s ₁ *90+s ₂ *70+s ₃ *50+s ₄ *30+s ₅ *10=55.4419036282

Example 3

Utilize the method of embodiment 2 to carry out bubble discharge effect evaluation to a gas well in a certain area of China's southwest oil and gas field, this well starts to carry out foam drainage gas recovery process from April 18, 2012, and the number of days to implement the process as of August 22, 2012 is 126 days, so choose a nearly equal amount of unfoamed row yesterday for comparison, the time is from December 1, 2011 to April 17, 2012. During the implementation of the on-site process, the dosage and cycle of the foaming agent are continuously adjusted according to the on-site data.

The data before and after the foam drainage gas production operation is processed through Python, and the data visualization is realized by the matplotlib tool library, and the comparison chart of the gas production before and after the foam drainage gas production operation in Figure 2, and Figure 3 the comparison chart of the water production volume before and after the foam drainage gas production operation and the attached drawings are made 3. Comparison chart of oil jacket pressure difference before and after foam drainage gas production operation.

Integrate the data and calculate the comprehensive evaluation index based on the entropy method in combination with the calculation formula of the present invention, integrate the data of the oil jacket pressure difference rate of change, and realize data visualization through the Python-based matplotlib tool library, as shown in Figure 5, and The relationship between the comprehensive evaluation index and the change rate of the oil jacket pressure difference is analyzed, so as to better analyze and evaluate the drainage gas recovery effect.

As shown in Figure 2-4, with the continuous addition of the foam discharge agent, the pressure difference of the oil jacket continued to decrease, and the water production and gas production began to increase gradually on May 16, 2012, and then maintained a relatively stable production. From June 25 to July 10, the casing pressure difference decreased to a minimum value of 14.56 and 14.78MPa, and the accumulated fluid in the wellbore was basically discharged. After that, the oil casing pressure difference stabilized within an interval, and the formation The produced water volume is relatively stable, indicating that the foam drainage gas production operation system is more reasonable at this time to achieve the purpose of draining the bottom hole fluid and achieving stable production.

Judging from the production effect of gas wells, the gas production and water production of foam drainage gas production began to increase on May 16, 2012, which achieved the purpose of the construction operation. However, the comprehensive evaluation index of foam drainage gas production based on the entropy method is only 40. It belongs to the stage with general effect, because considering the cost of daily drainage and gas production, it has not achieved good economic benefits. When the change rate of the oil jacket pressure difference reaches 30%, the comprehensive evaluation index of the foam drainage gas recovery operation reaches above 60, the construction operation effect reaches a good stage, and it has relatively good economic benefits.

From the comparison between the comprehensive evaluation index curve of foam drainage and gas production operation and the traditional production parameter curve in Figure 5, the evaluation method proposed in this paper is more comprehensive and has richer performance on the evaluation parameters of foam drainage effect on the basis of the cost of drainage gas production operation. The performance of different operation effect stages is more obvious, which is more conducive to the design of foam drainage and gas recovery and the selection of foaming agent.

The above are only the preferred embodiments of the present invention. It should be noted that, for those skilled in the art, without departing from the principles of the present invention, several improvements and modifications can be made. These improvements and Retouching should also be regarded as the protection scope of the present invention.

Claims (10)

1. A drainage gas production effect fuzzy comprehensive evaluation method based on an entropy method is characterized by comprising the following steps:

step 1, selecting n evaluation indexes delta u influencing the drainage and gas production effects_i，i＝1，2，…，n；

Step 2, corresponding to the relation between the comprehensive evaluation index D of the drainage gas production effect and the evaluation level, setting the comprehensive evaluation index D as m value intervals, v_jThe median of the interval, j is 1, 2, …, m, from which the evaluation set V is determined₁,v₂,v₃,…v_m}；

Step 3, establishing a membership matrix R by adopting a linear analysis method:

first, each evaluation index is divided into m evaluation sections, and a level limit value a corresponding to the evaluation section of each evaluation index is set_j，j＝1，2，…，m；

Then, the membership degree of the evaluation interval of each evaluation index relative to the evaluation set is calculated

Further, a matrix formed by membership degrees, namely a fuzzy relation matrix R can be solved;

step 4, determining the weight W of each evaluation index by adopting an entropy method:

first, the membership degree calculated in step 3 is calculated

Is converted into a relative value, such that

Then normalization processing is carried out to obtain t_ij；

Then, the ith influence factor t under the jth evaluation interval is calculated_ijThe proportion of the evaluation interval and the entropy value of the jth evaluation interval; further calculating the weight of each evaluation index, and then obtaining the weight W of each evaluation index;

and 5, carrying out fuzzy synthesis on each evaluation index weight W obtained in the step 4 and the fuzzy relation matrix R obtained in the step 3 by using (+,) operators to obtain a final evaluation vector S, and calculating a comprehensive evaluation index D of the gas recovery effect of the gas well foam drainage by using the final evaluation vector S.

2. The drainage gas production effect fuzzy comprehensive evaluation method based on the entropy method is characterized in that n is 4 in the step 1, and m is 5 in the step 2.

3. The entropy method-based drainage gas production effect fuzzy comprehensive evaluation method, according to claim 2, wherein the evaluation indexes are daily gas production change rates Δ qg. Rate of change of daily output water Δ q_wThe oil jacket differential pressure change rate delta P and the daily foam drainage gas production operation cost delta C.

4. The drainage gas production effect fuzzy comprehensive evaluation method based on the entropy method as claimed in claim 2, wherein the evaluation set V ═ { V ═ V₁,v₂,v₃,v₄,v₅The evaluation grade is good, general and poor; v. of₁＝90,v₂＝70,v₃＝50,v₄＝30,v₅＝10。

5. The drainage gas production effect fuzzy comprehensive evaluation method based on the entropy method as claimed in claim 1, wherein in the step 3,

wherein, find

The constructed matrix yields a fuzzy relation matrix R.

6. The drainage gas production effect fuzzy comprehensive evaluation method based on the entropy method as claimed in claim 1, wherein in the step 3, the normalization processing formula is as follows:

the forward direction index is as follows:

negative direction index:

then r'_ijOr r ″)_ijIs the ith influence factorThe value of the j-th evaluation interval of the element (i: 1, 2, …, n; j: 1, 2, …, m) is normalized and the normalized data is denoted as t_ij。

7. The drainage gas production effect fuzzy comprehensive evaluation method based on the entropy method as claimed in claim 6, wherein in the step 4, t is_ijThe specific gravity of the evaluation interval

Entropy of j-th evaluation interval

8. The drainage gas production effect fuzzy comprehensive evaluation method based on the entropy method as claimed in claim 7, wherein in the step 4, the information entropy redundancy is calculated: d_j＝1-e_jThen calculating the weight of each index

Calculating to obtain a weight, determining the weight W: w ═ W₁，w₂，…，w_n) Wherein the sum of the weights is 1.

9. The method for fuzzy comprehensive evaluation of drainage gas production effect based on entropy method according to claim 8, wherein in the step 5, S-W-R (S)₁，s₂，...，s_m)。

10. The entropy-method-based fuzzy comprehensive evaluation method for drainage gas production effects, according to claim 9, wherein in the step 5, D ═ S ═ V ═ S₁*v₁+s₂*v₂+…+s_m*v_m。

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